improving supply chain competitiveness through the
TRANSCRIPT
IMPROVING SUPPLY CHAIN COMPETITIVENESS
THROUGH THE APPLICATION OF TECHNOLOGY.
A CASE STUDY ON A ROUTING AND SCHEDULING
SYSTEM
by
RYAN HOLLANDER
920203095
Thesis submitted in fulfillment of
the requirements for the degree of
MASTER OF COMMERCE
in
LOGISTICS MANGEMENT
in the
FACULTY OF MANAGEMENT
at the
UNIVERSITY OF JOHANNESBURG
Promoter: Prof J Walters
October 2008
i
Acknowledgements
I would like to acknowledge the following people for their contribution to this study:
• Rosy, my wife, for all her support, care and understanding during the
long hours I have spent compiling this dissertation.
• Temima, my daughter, for all the family time she has sacrificed in order
to allow me to complete this dissertation.
• My parents, Marian and Ivan, for their continuous support and
encouragement to persevere throughout my studies.
• Professor J Walters for his guidance, assistance, patience and
encouragement during my dissertation.
ii
Executive summary
In the last hundred years there has been a technological revolution that has forced
people to change the way they live and run their organisations. This technological
revolution has had a major impact on the business world. Coyle, Bardi and Langley
(2003; 57) have suggested that “the rate of change has accelerated with consequent
negative impacts if organisations do not change.”
With today’s emphasis on cutting costs, streamlining expenses while at the same
time trying to offer a competitive edge with regard to customer service, many
organisations are looking to improve their bottom line and financial performance by
implementing new technology into their supply chains. A popular way for
organisations to speedily reap the benefits of having a more competent and
competitive, technology-enabled supply chain, is by outsourcing their supply chain
needs to a third party logistics organisations. The Star newspaper reported that,
according to Brett Bowes, inefficiencies in the supply chain meant that fast-moving
consumer goods manufacturers and retailers were losing R7 billion every year (The
Star, 16 March 2007; 2). Although there are many auxiliary benefits and advantages
of implementing software systems into the supply chain, the two critical benefits
which justify the expense are reduced costs and improved customer service.
Implementing technology is a costly, challenging and sometimes risky endeavor. This
often results in an unwillingness to change until these organisations outgrow their
systems, or the business environment becomes so complex, that they are forced to
implement new technology. This hesitancy to introduce new technology timeously
could hamper the progress and growth of these organisations, and could also affect
their competitiveness in a highly competitive environment. The purpose of this case
study is to compare the benefits achieved from existing older technology to new
technology, based on a routing and scheduling case study in a large 3PL
organisation.
iii
In order to reach a conclusion about the above-mentioned problem statement, an
investigation was carried out into whether the implementation of a state-of-the-art
routing, scheduling and haulier management system into Clover Logistics has
achieved real benefits, improved the bottom line, as well as resulted in improved
customer service. The investigation takes an in-depth look at Magic, Clover Logistics’
previous management support system and compares it to Optima, Clover Logistics’
new dynamic routing, scheduling and financial management system.
In order to be able to fully comprehend the benefits and drawbacks of the
implementation of Optima into Clover Logistics, the dissertation looks at both the
qualitative and quantitative improvements and drawbacks that have occurred as a
result of the implementation of Optima. As a result of the implementation of Optima,
Clover Logistics saved R1 043 850 per month in 2006 through the optimisation of its
routes and scheduling of its vehicles. This equals an annual saving of R12 562 200.
From the qualitative and quantitative discussions and calculations discussed in this
dissertation, it is clear that Clover Logistics has benefited financially, as well as in
many other spheres as a result of the implementation of Optima into their supply
chain. With an improvement in on-time delivery from 85% to 99%, and a reduction in
incorrect invoices from 40% to 1%, Clover’s customer service levels have improved
drastically, resulting in more satisfied clients and a competitive advantage in the
marketplace.
In conclusion, the dissertation clearly establishes how the casting out of old
technology and the implementation of new technology has led to immense benefits
for Clover Logistics and that old technologies were in fact hampering Clover
Logistics’ bottom line and possibly their position in a competitive marketplace. It is
evident from this dissertation that outdated technology could possibly be hampering
the growth of many similar organisations, just as old technology was hampering the
growth and efficacy of Clover Logistics. It is thus in the interest of organisations to be
more aware of new technologies in the marketplace.
iv
Opsomming
Gedurende die afgelope honderd jaar het ‘n tegnologiese rewolusie plaasgevind wat
mense genoodsaak het om hulle lewenswyse en organisasies te verander. Die
tegnologiese rewolusie het ‘n wesenlike impak op die besigheidswêreld gehad.
Coyle, Bardi en Langley (2003; 57) het die mening uitgespreek dat “die tempo
waarteen verandering toegeneem het, negatiewe gevolge het indien organisasies nie
verander nie” (vertaling).
Met die klem vandag op kostebesnoeiing, die beperking van uitgawes
gepaardgaande met die strewe na ‘n mededingende voordeel ten opsigte van
kliëntediens, poog menige organisasie om te verbeter op hulle finansiële prestasies
en winste, deur die implementering van tegnologie in hul toevoerketting.
Organisasies kan vinnig die voordele van ‘n beter en meer kompeterende
tegnologies gedrewe toevoerketting ervaar, deur die behoeftes van hulle
toevoerketting aan ‘n derdeparty logistieke organisasie uit te kontrakteer. The Star
koerant het gerapporteer (volgens Brett Bowes) dat onbevoegdhede in die
toevoerketting ‘n verlies van R7 biljoen per jaar veroorsaak vir die vervaardigers en
verkopers van verbruikersgoedere wat vinnig versprei en afgelewer moet word. (The
Star, 16 Maart 2007; 2). Alhoewel daar menige byvoordele is wanneer
sagtewarestelsels in die toevoerketting geïplementeer word, is die twee kritiese
voordele wat sodanige uitgawe regverdig, beslis verminderde kostes en verbeterde
kliëntediens.
Die implementering van tegnologie is ‘n duur, uitdagende en soms riskante besluit.
Ditt het dikwels tot gevolg dat organisasies onwillig is om hierdie stap te neem, totdat
hulle bestaande stelsels ontoereikend geword het, of die besigheidsomgewing so
kompleks ontwikkel het, dat hulle genoodsaak word om die tegnologie te
implementeer. Die huiwering om nuwe tegnologie betyds te installeer, kan die
vordering van groei van sodanige organisasies erg rem, en daarmeegaande hulle
mededingendheid in ‘n hoogs kompeterende omgewing beïnvloed. Die doel van die
gevallestudie is om die voordele van bestaande tegnologie op te weeg teenoor nuwe
v
tegnologie, gebaseer op ‘n roete- en skeduleringgevallestudie in ‘n groot 3PL
organisasie.
Om tot ‘n gevolgtrekking vir die bogenoemde probleemstelling te kom, is ‘n
ondersoek geloods om te bepaal of the implementering van ‘n tydsrelevante
roeteskedulering- en vervoerbestuurstelsel werklik voordele inhou, winste verbeter
en gevolglik beter kliëntediens vir Clover Logistics teweeggebring het. Die
navorsingstudie het ‘n in-diepte ondersoek gedoen deur Magic, Clover Logistics se
vorige bestuursondersteuningstelsel te vergelyk met Optima, Clover Logistics se
nuwe dinamiese roete-, skedulering- en finansiële bestuurstelsel.
Om werklik die voor- en nadele van die implementering van Optima in Clover
Logistics te begryp, kyk die studie na beide die kwalitatiewe en kwantitatiewe
verbeterings en tekortkominge wat teweeggebring is as gevolg van die
implementering van Optima. Clover Logistics het ‘n besparing van R1 043 850 per
maand in 2006 gewys deurdat roetes en voertuigskedulering optimaal beplan is as
gevolg van die implementering van Optima. Hierdie besparing beloop ‘n jaarlikse
bedrag van R12 562 200.
Vanuit die kwalitatiewe en kwantitatiewe ontledings en berekeninge wat tydens die
studie gedoen is, is dit duidelik dat Clover Logistics finansiëel, sowel as op ander
gebiede gebaat het by die implementering van Optima in hul toevoerketting. Met ‘n
verhoging in die op-tyd lewering van 85% na 99%, en ‘n afname in foutiewe fakture
van 40% na 1%, het Clover se kliëntediensvlakke drasties verbeter. Dit het meer
tevrede kliënte, en aldus ‘n mededingende voordeel in die marksegment tot gevolg
gehad.
Die studie se finale bevinding is dus dat die vervanging van ou tegnologie met nuwe
tegnologie geweldige voordele vir Clover Logistics ingehou het. Ou tegnologie het
Clover se winste benadeel, en daarmee saam hulle posisie in ‘n kompeterende mark
negatief beïnvloed. Daar kan dus uit die studie afgelei word dat verouderde
tegnologie die groei van menige soortgelyke organisasies kan demp, net soos wat in
die geval van Clover se groei en welvaart gebeur het. Dit is dus vir organisasies van
uiterste belang om meer bewus te wees van nuwe tegnologieë in hulle bepaalde
marksektor.
vi
Table of Contents
Page
Acknowledgements ...................................................................................................................................i
Executive summary ..................................................................................................................................ii
Opsomming ...........................................................................................................................................iv
Table of Contents ....................................................................................................................................vi
List of figures ...........................................................................................................................................xi
List of tables ......................................................................................................................................... xiii
List of abbreviations............................................................................................................................... xiv
1 INTRODUCTION............................................................................................................................. 1
1.1 Introduction ......................................................................................................................... 1
1.2 The problem statement ....................................................................................................... 3
1.3 Research aims .................................................................................................................... 5
1.4 Methodology of study.......................................................................................................... 5
1.5 Scope of the study .............................................................................................................. 6
1.6 Exposition of the study........................................................................................................ 7
1.6.1 Chapter 1 ............................................................................................................. 7
1.6.2 Chapter 2 ............................................................................................................. 7
1.6.3 Chapter 3 ............................................................................................................. 8
1.6.4 Chapter 4 ............................................................................................................. 8
1.6.5 Chapter 5 ............................................................................................................. 8
1.6.6 Chapter 6 ............................................................................................................. 8
1.6.7 Chapter 7 ............................................................................................................. 9
2 THE DEVELOPMENT AND GROWTH OF LOGISTICS .............................................................. 10
2.1 Introduction ....................................................................................................................... 10
2.2 The value chain................................................................................................................. 11
2.3 The supply chain ............................................................................................................... 12
2.4 What is logistics? .............................................................................................................. 13
vii
2.4.1 The definition of logistics ................................................................................... 14
2.5 The need for organisations to focus on their core product ............................................... 15
2.6 Supply chain optimisation ................................................................................................. 16
2.7 The advantages and complexities of effective transport optimisation and management . 18
2.8 Why outsource? ................................................................................................................ 20
2.8.1 Examples of where outsourcing makes business sense................................... 20
2.8.2 Advantages of outsourcing ................................................................................ 21
2.8.3 Disadvantages of outsourcing ........................................................................... 26
2.9 The third party logistics provider (3PL) ............................................................................. 28
2.9.1 Outsourcing case studies .................................................................................. 29
2.10 The need for better management and information sharing in the 3PL ............................. 30
2.11 The building of collaborative relationships........................................................................ 32
2.11.1 Evaluating collaborative relationships ............................................................... 35
2.12 The use of technology to enhance relationships and efficacy .......................................... 36
2.13 Summary and conclusion.................................................................................................. 38
3 TECHNOLOGY IN THE SUPPLY CHAIN..................................................................................... 41
3.1 The initial use and growth of technology in the supply chain ........................................... 41
3.2 Technology in the supply chain......................................................................................... 45
3.2.1 Advantages of technology ................................................................................. 45
3.2.2 Disadvantages of technology ............................................................................ 46
3.2.3 Insight into the future of technology from top industry analysts ........................ 47
3.2.4 Challenges when choosing and implementing technology ............................... 49
3.2.5 General benefits of technology.......................................................................... 51
3.2.6 Five Best Practices of World-Class Companies................................................ 53
3.2.7 Guidelines alerting an organisation that the implementation of technology is
overdue.............................................................................................................. 54
3.2.8 Different technologies in the supply chain......................................................... 55
3.3 Vehicle routing and scheduling ......................................................................................... 58
3.3.1 The problem statement...................................................................................... 58
3.3.2 The routing and scheduling problem ................................................................. 61
3.3.3 The importance of time windows ....................................................................... 64
3.3.4 Manual routing and scheduling techniques ....................................................... 66
viii
3.3.5 Benefits of good routing and scheduling ........................................................... 67
3.3.6 Effects of routing and scheduling on the environment ...................................... 68
3.4 Case studies of where technology has been implemented into the supply chain and the
results thereof.................................................................................................................. 69
3.4.1 General case studies......................................................................................... 69
3.4.2 Routing and scheduling case studies................................................................ 72
3.4.3 Case study where routing and scheduling software is combined with other
optimisation software......................................................................................... 77
3.4.4 Summary of routing and scheduling case studies............................................. 81
3.5 Importance of high quality master data............................................................................. 84
3.6 Summary and conclusions................................................................................................ 85
4 CLOVER LOGISTICS’ PAST SYSTEMS AND PROCESSES...................................................... 87
4.1 Introduction into Clover ..................................................................................................... 87
4.1.1 Organisational Overview ................................................................................... 87
4.1.2 Background to Clover Logistics ......................................................................... 88
4.1.3 Background to the primary distribution function in Clover................................. 89
4.1.4 Clover Logistics’ mission statement and objectives .......................................... 91
4.1.5 Clover’s current operational requirements and their predicted growth ............. 92
4.1.6 A look at Clover Logistics’ primary operational and financial complexities ....... 94
4.2 Clover’s previous systems and processes........................................................................ 96
4.2.1 Clover Logistics’ previous system setup ........................................................... 96
4.2.2 General Overview of Clover’s Magic System .................................................... 97
4.3 An in-depth look at Clover’s previous legacy system ....................................................... 99
4.3.1 Capturing a Request For Service (RFS) ........................................................... 99
4.3.2 Allocating a haulier to Request for Service ..................................................... 101
4.3.3 Transport procurement .................................................................................... 102
4.3.4 Confirming delivery of a transport request (Tracking the load) ....................... 103
4.3.5 Financial administration................................................................................... 104
4.3.6 Master Data Management ............................................................................... 106
4.3.7 Reporting ......................................................................................................... 110
4.3.8 Summary of the issues identified within Clover’s Magic system ..................... 112
4.4 A look at Clover’s new business needs and challenges................................................. 114
4.4.1 Clover’s new business needs and challenges................................................. 114
ix
4.4.2 An analysis of what led to the growth of Clover Logistics’ new complexities and
challenges........................................................................................................ 115
4.4.3 Benefits which Clover Logistics management had hoped a new system would
achieve ............................................................................................................ 116
4.5 Summary and conclusion................................................................................................ 117
4.6 Appendix ......................................................................................................................... 119
4.6.1 Capture an RFS............................................................................................... 119
4.6.2 Allocate an RFS to a haulier............................................................................ 120
4.6.3 Link orders to RFS........................................................................................... 120
4.6.4 Generate transport request ............................................................................. 121
4.6.5 Receive confirmation from haulier ................................................................... 122
4.6.6 Confirm haulier transport request .................................................................... 123
4.6.7 Confirm delivery of transport request .............................................................. 124
4.6.8 Generate purchase orders............................................................................... 125
5 CLOVER LOGISTICS’ NEW SYSTEMS AND PROCESSES..................................................... 126
5.1 The vision........................................................................................................................ 126
5.1.1 Introduction ...................................................................................................... 126
5.1.2 The Vision- What Clover Logistics needed ..................................................... 126
5.1.3 The search for a solution ................................................................................. 129
5.1.4 The proposed solution ..................................................................................... 133
5.2 An in-depth look at Clover’s new technology information system .................................. 134
5.2.1 Service Request (SR) Inception ...................................................................... 135
5.2.2 Planning........................................................................................................... 137
5.2.3 Transportation Procurement............................................................................ 141
5.2.4 Track-and-Trace .............................................................................................. 145
5.2.5 Financial Administration .................................................................................. 145
5.2.6 Master data management................................................................................ 146
5.2.7 Reporting ......................................................................................................... 156
5.2.8 General benefits achieved through using Optima ........................................... 157
5.2.9 General concerns resulting from the implementation of Optima..................... 159
5.3 The implementation of Optima........................................................................................ 160
5.3.1 Managing the implementation ......................................................................... 160
5.3.2 Project Plan ..................................................................................................... 161
x
5.3.3 The Implementation and development team................................................... 161
5.3.4 Integration with the Clover ERP system.......................................................... 162
5.3.5 Challenges faced when implementing Optima................................................ 162
5.4 Summary and conclusion................................................................................................ 164
5.5 Appendix ......................................................................................................................... 166
6 AN ANALYSIS OF CLOVER LOGISTICS’ OLD SYSTEMS AND PROCESSES COMPARED TO
THEIR NEW SYSTEMS AND PROCESSES.............................................................................. 167
6.1 A qualitative comparison between old and new processes ............................................ 168
6.1.1 Integration........................................................................................................ 168
6.1.2 Routing and scheduling ................................................................................... 171
6.1.3 Financial .......................................................................................................... 178
6.1.4 Communication................................................................................................ 182
6.1.5 Reporting ......................................................................................................... 184
6.1.6 General ............................................................................................................ 185
6.2 Financial savings achieved through the implementation of Optima ............................... 188
6.2.1 Savings achieved through the optimal routing and scheduling of vehicles..... 188
6.2.2 Analysis of the costs of implementing Optima versus the savings achieved .. 196
6.3 Possible ways for Clover Logistics to achieve additional savings and benefits from
Optima ........................................................................................................................... 199
6.4 Summary and conclusion................................................................................................ 200
7 SUMMARY AND CONCLUSIONS.............................................................................................. 202
7.1 Overview of the chapters ................................................................................................ 202
7.1.1 Chapter 1 ......................................................................................................... 202
7.1.2 Chapter 2 ......................................................................................................... 203
7.1.3 Chapter 3 ......................................................................................................... 205
7.1.4 Chapter 4 ......................................................................................................... 206
7.1.5 Chapter 5 ......................................................................................................... 207
7.1.6 Chapter 6 ......................................................................................................... 208
7.2 Summary and conclusion................................................................................................ 210
References ....................................................................................................................................... 211
xi
List of figures
Figure 2.1 The Value Chain ......................................................................................................... 11
Figure 2.2 The Modern Supply Chain.......................................................................................... 12
Figure 2.3 The Supply Chain Process ......................................................................................... 18
Figure 3.1 Percentage of respondents whose management has requested or received a recommendation to improve transportation performance in 2006 ............................. 44
Figure 3.2 Ordering process ........................................................................................................ 52
Figure 3.3 Transportation management priorities when choosing technology............................ 54
Figure 3.4 Uses of technology in the logistics field...................................................................... 56
Figure 3.5 An example of a vehicle routing problem ................................................................... 62
Figure 3.6 The effects of an advanced routing and scheduling system on CO2 emissions........ 68
Figure 3.7 ABI’s problem: The fixed call cycle............................................................................. 78
Figure 3.8 ABI’s goal: Dynamic demand prediction..................................................................... 79
Figure 3.9 Example of the predicted versus actual refill needs of a vending machine for four months ........................................................................................................................ 80
Figure 4.1 Definition of primary distribution ................................................................................. 90
Figure 4.2 Predicted and historical request for services as in March 2004................................. 93
Figure 4.3 Clover’s primary distribution flows.............................................................................. 94
Figure 4.4 Clover’s Gauteng primary distribution flows............................................................... 95
Figure 4.5 Non-optimal route network ......................................................................................... 96
Figure 4.6 The Magic process flow.............................................................................................. 98
Figure 4.7 Gap created in the accounts receivable process ..................................................... 106
Figure 4.8 Maintaining next generated numbers ....................................................................... 110
Figure 5.1 Clover Logistics’ three steps to an evolving primary distribution ............................. 127
Figure 5.2 The extent of Clover’s required collaboration........................................................... 128
Figure 5.3 The Optima process flow.......................................................................................... 135
Figure 5.4 The Plato Scheduler ................................................................................................. 137
Figure 5.5 The Plato Geo Coding interface ............................................................................... 140
Figure 5.6 Haulier-web interface for tendered transport requests............................................. 142
xii
Figure 5.7 Haulier-web interface showing allocated transport requests ................................... 143
Figure 5.8 Web-based track–and-trace interface ...................................................................... 144
Figure 5.9 How AP and AR vouchers are calculated in Optima................................................ 147
Figure 5.10 Integration with Clover’s ERP system ...................................................................... 162
Figure 6.1 Gap created in the accounts receivable process ..................................................... 170
Figure 6.2 Eastern Cape Magic Route ...................................................................................... 174
Figure 6.3 Eastern Cape Optima Route-Option one ................................................................. 175
Figure 6.4 Eastern Cape Optima Route-Option two.................................................................. 176
Figure 6.5 Maintaining next generated numbers ....................................................................... 187
Figure 6.6 Gauteng-Cape Town-George ................................................................................... 190
Figure 6.7 Gauteng-Eastern Cape: new route versus old route................................................ 193
Figure 6.8 Average fill rate of vehicles per branch (September 2007)...................................... 195
xiii
List of tables
Table 4.1 Information required when adding a new route........................................................ 107
Table 4.2 Information required when adding a new route distance to the distance file........... 107
Table 4.3 Information required when adding a new tariff ......................................................... 108
Table 4.4 Information required when adding a delivery or pick-up point ................................. 108
Table 4.5 Information required when adding a haulier............................................................. 109
Table 4.6 Information required when adding debtor codes...................................................... 109
Table 4.7 Information required when adding reason codes..................................................... 110
Table 5.1 The optimising engines’ parameters ........................................................................ 139
Table 5.2 Information required when adding new hauliers ...................................................... 148
Table 5.3 Information required when adding new clients......................................................... 149
Table 5.4 Information required when adding new sites............................................................ 149
Table 5.5 Information required when adding an area group .................................................... 150
Table 5.6 Information required when adding a new lane ......................................................... 150
Table 5.7 Information required when adding a new tariff ......................................................... 151
Table 5.8 Information required when adding a new charge..................................................... 152
Table 5.9 List of various different charges................................................................................ 153
Table 5.10 Information required when adding a new vehicle..................................................... 154
Table 5.11 Information required when adding a new reason codes .......................................... 155
Table 5.12 Information required when adding new loading bays............................................... 156
Table 6.1 The general feeling of the Optima users towards Optima........................................ 185
Table 6.2 Saving achieved through optimal routing and scheduling of KwaZulu Natal loads 191
Table 6.3 Cost of purchasing and implementing Optima ......................................................... 196
Table 6.4 Saving achieved through optimal routing and scheduling for the last six months of the financial year 2004/2005 .......................................................................................... 197
Table 6.5 Saving achieved through optimal routing and scheduling for the financial year 2005/2006................................................................................................................. 198
xiv
List of abbreviations
• 3PL-Third party logistics (provider)
• AP-Accounts payable
• APS-Advanced Planning System
• AR-Accounts receivable
• BCG- Branded consumer goods
• BPCS-Business Planning and Control System-(Clovers ERP system)
• BR-Branch Replenishment (system)
• CDC-Central distribution centre
• CO2-Carbon dioxide
• CRPS-Customer response planning system
• CRS-Customer response system
• DC-Distribution centre
• DO-Drop-off
• EDI- Electronic data interchange
• ERP-Enterprise Recourse Planning
• ETA-Estimated time of arrival
• FLO-Fleet Logistics Optimiser
• FMCG-Fast moving consumer goods
• GIGO – Garbage-in-garbage-out
• GNP-Gross national product
• GPO-Generation of purchase order
xv
• GPS-Global positioning system
• IDF-Israel Defense Force
• IMS-Inventory management system
• IPS-Inventory planning system
• IS-Information services
• IT-Information technology
• JIT-Just in time
• KM-Kilometre
• KPI- Key performance indicator
• LES-Logistics execution system
• LIS-Logistics information system
• LPS-Logistics planning system
• MRP2 – Materials requirement planning
• NHS-National Health Services
• OVAL- Optimization of Vending and Logistics
• PO – Purchase order
• POD- Proof of delivery
• PU-Pick up
• QR-Quadruple resonance
• RFS - Request for service
• ROI-Return on investment
• SAB-South African Breweries (Ltd)
• SA-South Africa
xvi
• SCES-Supply chain execution systems
• SKU-Stock keeping units
• SMS-Short message service
• SMS-Supply management system
• SPS-Supply planning system
• SR-Service request
• TMS-Transportation management system
• TPS-Transportation planning system
• TR-Transport request
• UOM-Unit of measure
• UPS-United parcel service
• USA-United States of America
• WMS-Warehouse management system
• WPS-Warehouse planning system
1
Chapter 1
1 INTRODUCTION
1.1 Introduction
In the last hundred years there has been a technological revolution that has forced
people to change the way they live and run their organisations. With the rapid rate at
which computer hardware and software has developed, the world of today will only
be a resemblance of the world of tomorrow. This technological age is having a major
impact on the business world. Coyle, Bardi and Langley (2003; 57) have suggested
that “the rate of change has accelerated with consequent negative impacts if
organisations do not change.” All organisations feel the pressure to keep up with the
technological race for fear of falling behind their competitors, or even worse, falling
out of the race.
The first question that needs to be asked is: Is there a need to move to new ways of
doing things? What is wrong with old processes and systems that organisations are
constantly looking to replace them with new ones? These questions can be
answered by understanding how the supply chain has evolved over time and become
more complex, demanding the use of advanced processes in order to control it.
According to Steven Anderson (Anderson, 2005;8 ), the rise in complex supply
chains can be attributed to the fact that transportation options are growing, additional
suppliers have entered the market and the number of products available has
mushroomed. Other factors such as liberated international trade and falling trade
barriers between nations, have also contributed to the rise in the complexity of supply
chains.
Also, with today’s emphasis on cutting costs, streamlining expenses while at the
same time trying to offer a competitive edge with regard to customer service, many
organisations are looking to improve their bottom line and financial performance by
implementing technology into their supply chains. The bottom line includes factors
2
such as reduced costs, improved relationships with supply chain partners and
improved customer service levels amongst other factors. Organisations are
relentlessly searching for technologies that they hope will lead to efficiency,
effectiveness, reduced costs and a competitive edge through differentiation.
Unfortunately, many people involved in an organisation’s decision-making processes
do not fully understand the supply chain process, and often assume that technology
is the ultimate solution in today’s high-tech world. The fact that 53% of midsize
organisations planned to spend more on supply chain technology in 2006 than they
did in 2005 (Enslow, 2006;2), shows that organisations are investing significant
amounts of capital in their supply chains. The question is: Is this money being spent
in the right places, at the right time and with realistic goals in mind?
In order for any technology to be successfully implemented in a supply chain, those
involved need to understand the complexities of the technology that is being
implemented into the supply chain and the function they hope that the technology will
serve in improving that activity. Often, even when there is a proper understanding of
the above, individuals still fail to understand the potential benefits and limitations of
technology which can lead to unnecessary costs and other problems.
Often, the quick turn to technology to solve business problems and improve the
bottom line, has been met with gloomy results. A recent analysis indicated that about
two-thirds of organisations that installed software to improve their supply chains,
realised improved metrics such as inventory turns (it was common to see 100 to 150
percent improvement within two years). The other third experienced unsuccessful
implementations, and actually achieved worse performance than organisations that
did not implement software changes. In other words, poorly conceived software
implementations can hurt organisations more than doing nothing at all (Haggar,
2003; 1).
Supply chain software may often work best in conjunction with older, simpler
systems; and often when investigating and implementing a change of systems,
organisations tend to throw out the old, disregarding its potential value as part of a
new system. Such misinterpretation or misunderstanding of the relationship between
the supply chain and technology often ends up as a disaster.
3
In summary, according to Coyle, Bardi and Langley (2003; 593) the ability to select,
implement and utilise technology can be a key factor in effecting the success or
failure of an organisation. Thus, technology must be viewed as an investment that is
needed to satisfy the information, imperative of the connected economy for velocity,
visibility, rapid decisions and operational flexibility.
1.2 The problem statement
In today’s economy, the speed of information access and delivery is often the
difference between the success and failure of the supply chain. Advertising
campaigns by major software vendors and industry slogans have crept into the
consciousness of the corporate executive looking for a competitive edge (Eckerson,
2006).
The Aberdeen Group (2003;1) reported that “Having exhausted avenues for reducing
headcount and other internal costs, companies are now looking to their supply chain
for cost reduction, innovation and added value.” From here we see that organisations
are constantly looking for ways to improve their bottom line and financial
performance. In the past couple of years, a trend has emerged which shows a
collective focus on exploiting the supply chain in order to reach this goal. This has
been done without attention to the individual organisation’s strengths and
weaknesses which were traditionally seen as the key factors to increasing net profits.
According to a 1999 survey of career patterns conducted for the Council for Logistics
Management, new technologies have become critical in order to compete effectively
(Coyle, Bardi & Langley, 2003; 473). Many software and hardware companies are
selling products that they claim can assist organisations to manage different parts of
their supply chains. These packages each promise to optimise and improve one or
many links in the supply chain - from warehousing to routing. These solutions
promise to dramatically improve business, handle procurement, production,
distribution and even aspects of customer service. The one thing that these different
technology organisations have in common, is that they generally promise to improve
efficiency and ultimately to improve the bottom line. This has created a
misconception shared by many, that by simply implementing technology into the
supply chain is enough to improve profits. However, implementing and actually
4
benefiting from supply chain technology are two different things. In order for the
benefits to show an improvement in profit, many obstacles have to be overcome; for
example, vendor and employee buy-in and clean and accurate master data.
The MCI consumer research lab (Rosen & Weil, 2000) conducted a four year study in
order to understand how people react to new technology. The study identified three
groups of people. The first group being eager adopters, eager adopters are people
who embrace technology as soon as it is released. MCI’s study found 12% of people
to be eager adopters. “Hesitant ‘Prove Its’ form the largest group (59% in MCI's
study). Hesitant ‘Prove Its’ are not anti-technology, nor are they usually technophobic
(although they may be). Rather, they are waiting on the sidelines for someone to
show them how technology can help them. They want to know how technology will
specifically make their life easier. Hesitant ‘Prove Its’ know that technology has
problems and they do not necessarily enjoy dealing with those problems. They would
rather wait on the sidelines until there are no problems”(Ibid). The last group,
resisters, made up 29% of the people involved in the study. Resisters “do not like it,
want it or find it enjoyable” (Ibid). The MCI study concludes that “Across the past five
years, we have seen a strong increase in the use of technology in the workplace by
both Clerical/Support Staff as well as Managers and Executives. Additionally, it
appears that more technological use is being required at home after standard work
hours. In spite of the increased use of technology, rather than being excited and
more accepting of new technology, people in the business world appear to be more
hesitant”(Ibid).
Despite the clear benefits of new technology, hesitancy to adopt new technology is
seen across all fields in the business world. Business Wire (January 2004) reported
that “the reluctance of care providers to adopt new technologies is hampering market
development”.
“When asked why they are hesitant to accept new technologies, Americans largely
claimed that lack of familiarity with the technology (42 percent) and general dislike of
the technology (41 percent) were the main issues. The numbers show hesitancy on
the consumer side mainly resulting from lack of knowledge of the benefits of each
technology, said Miller.” (Trend O.X.Y.G.E.N., 2005)
5
Implementing new technology is a costly, challenging and sometimes risky endeavor.
This often results in an unwillingness to change until organisations outgrow their old,
often in-house-developed systems and processes or the business environment
becomes so complex, that they are forced to implement new technology. This
hesitancy to introduce new technology timeously could hamper the progress and
growth of these organisations, and could also affect their competitiveness in a highly
competitive environment.
1.3 Research aims
The primary objective of this dissertation is to contrast the limitations of older
technology in the supply chain to the benefits achieved from utilising new technology
in the supply chain.
This will be achieved by investigating whether the implementation of a state of the art
routing, scheduling and haulier management system into Clover Logistics, a leading
third party logistics provider in South Africa, has achieved real benefits and improved
the bottom line of the organisation as compared to using their in-house developed
operational systems.
The dissertation seeks to add value to the industry by showing that it is in the interest
of organisations to be aware of the benefits of new technologies in the marketplace.
The results gained from this case study are specific to Clover Logistics; however,
because Clover Logistics is a leading third party logistics organisation, the results of
this case study could be expected in other 3PLs ( it is important to note that Clover
Logistics is both an in-house logistics provider as well as a 3PL for external
companies).
1.4 Methodology of study
This study was based on relevant literature, as well as a case study in which a
specialised state of the art routing, scheduling and haulier management system has
been implemented into the supply chain of Clover Logistics.
6
The literature generally comprised of related publications, as well as articles and
statements which were analysed in the light of the relevant case study. The
dissertation also quotes other case studies where technology has been implemented
into the supply chain, and assesses whether or not benefits were achieved.
The most advantageous way for the author to contrast old technology against new
technology was through a case study. Through the use of a case study where old
technology was replaced with new state of the art technology the author was able to
directly compare the limitations of old technology with the benefits and advantages
of new technology. The case study comprised an evaluation of Clover Logistics
which is at present finalising the implementation of state-of-the-art software to
schedule loads and communicate with its hauliers. The organisation’s procedures,
costs, customer service and relationships with external hauliers, as well as other
important factors were assessed before and after the implementation of the
technology in order to evaluate the benefits and drawbacks of the new technology.
All benefits that could be quantified in numbers were then analysed using statistical
procedures.
The case study initialy involved surveys with personnel involved in all aspects of the
implementation and daily use of the routing, scheduling and haulier management
system, including Clover Logistics personnel, Opsi systems personnel, warehouse
personnel as well as the outsourced hauliers personnel. The surveys, conducted via
e-mail, were carefully analysed along side all relevant documentation that was
generated by Opsi systems and Clover Logistics at the time of the project. Follow up
meetings were then held with the relevant people to clarify and substantiate the
information obtained from the surveys and documentation.
1.5 Scope of the study
This dissertation mainly focuses on the application of technology in supply chain
management. In order to fully understand the application of technology in supply
chain management, a case study of Clover Logistics which is at present finalising the
implementation of state of the art software to schedule loads and communicate with
its hauliers, was looked at and analysed.
7
Clover Logistics provides a number of services including warehousing, secondary
distribution, primary distribution, sales and merchandising, management information
systems, credit control and a large number of other services. This dissertation will
focus on Clover Logistics’ primary distribution as the use of technology has been a
critical element in their growth and has ensured the stability of the organisation as it
continues to grow.
Owing to the fact that only one case study was focused on, principles learnt from this
study only apply directly to Clover Logistics. Reference was also made to studies that
have been conducted in other organisations’ supply chains, adding scope to the
applicability of the research.
1.6 Exposition of the study
This section describes the chapters that the thesis covered.
1.6.1 Chapter 1
The first chapter includes an introduction to the dissertation. This chapter looks at the
problem statement, the objectives and methodology of the dissertation.
1.6.2 Chapter 2
Chapter two begins by defining logistics, and specifically, third party logistics. A large
portion of chapter two is devoted to discussing outsourcing and the benefits and
disadvantages of it. The chapter then goes on to discuss the need for good
management and improved control when outsourcing, specifically to a third party
logistics organisations. This includes the need for better collaboration and
communication with its subcontractors and clients, as well as the need for better
sharing of information with its partners, sharing that is largely an electronic exchange
of business information. Chapter two begins to examine the need and role of
information systems in the supply chain, specifically in third party logistics
organisations. This is discussed in more depth in the following chapter.
8
1.6.3 Chapter 3
The third chapter examines the historical development of how and why technology
became a tool utilised in the logistics industry. Different technological systems
available in the supply chain are briefly discussed. The chapter then takes a more
focused look at routing and scheduling systems and debates their values, problems,
and positive and negative contributions to the supply chain. A few case studies of
where technology has been implemented into the supply chain and the result thereof,
are briefly reviewed. The need and importance of high quality data when
implementing and using technological systems is also discussed in this chapter.
1.6.4 Chapter 4
As a case study, Clover Logistics is examined in some depth in this chapter. The
case study includes the problems and issues in the processes of the organisation,
prior to the implementation of the new technology.
1.6.5 Chapter 5
Chapter five takes a deeper look at the implementation of transport and information
management software into the supply chain of Clover Logistics. An analysis of the
challenges faced when implementing the new software into Clover Logistics’ supply
chain, is investigated. The chapter then takes an in-depth look at the implemented
software and the new processes that have been created at the organisation with the
implementation of the software.
1.6.6 Chapter 6
The sixth chapter consists of a comparison between the old and new systems and
processes at Clover Logistics. The benefits and downfalls obtained from
implementing new technology into the supply chain are quantified. It is important to
note that not all achievements such as customer service can and is quantified in
numbers. The results are then discussed and analysed.
9
1.6.7 Chapter 7
Chapter seven summarises the study on a chapter-by-chapter basis, and draws
overall conclusions in the context of the study.
10
Chapter 2
2 THE DEVELOPMENT AND GROWTH OF LOGISTICS
2.1 Introduction
With the growth of industrialisation, urbanisation, globalisation and mechanisation,
the end of the twentieth century saw a more informed and educated consumer. This
new, informed consumer led to a new competitive environment which meant that
consumers would no longer be satisfied with the standard products and services they
had been provided with in the past, and would demand higher standards and
improved services. Owing to this, organisations began to realise that if they
continued operating with the same processes and strategies, they would no longer
be able to meet the expectations of the new, more demanding consumer, and would
eventually cease to exist.
This more demanding consumer led organisations to begin looking at new ways to
increase their competitive advantages. Once it became clear to organisations that
their core product can only be improved and become more competitive up to a
certain point, organisations started looking elsewhere for ways to improve their
competitive advantage in the marketplace. Two main ways were identified to help
increase competitiveness, those being reduced cost and improved service.
In the endeavour to reduce costs and offer an improved service, organisations began
scrutinising every aspect of their organisation and soon found that their supply chain
was an area than needed lots of attention. This led to organisations successfully
improving their competitive advantage through supply chain optimisation, improved
supply chain management, outsourcing of an organisations’ non-core needs, and the
use of technology to optimise and manage the supply chain.
This chapter will begin by looking at what the supply chain is, and how it fits into the
greater value chain of an organisation. The chapter will then proceed with a definition
of logistics, the birth and growth of the third party logistics organisation and the need
for good management and improved control in third party logistics organisations.
11
Chapter two will then go on to explain the need and role of information systems in the
supply chain, specifically in third party logistics organisations.
2.2 The value chain
In order to gain a greater understanding of logistics, it is necessary to take a look at
the greater framework, that being the value chain and the supply chain of which it is
part.
The value chain is an orderly approach to examining the development of competitive
advantage which was developed by M. E. Porter in 1980. The chain consists of a
series of activities that create and build value which in the end adds up to the total
value delivered by an organisation. As can be seen in the figure below, the
organisation is split into 'primary activities' and 'support activities’ (Marketingteacher,
2007; 1).
Figure 2.1 The Value Chain
Mar
ginInbound
LogisticsOperations
OutboundLogistics
Marketingand Sales
Service
Primary Activities
Technology Development
Procurement
Firm Infrastructure
Human Resource ManagementSupport Activities
Margin
Mar
ginInbound
LogisticsOperations
OutboundLogistics
Marketingand Sales
Service
Primary Activities
Technology Development
Procurement
Firm Infrastructure
Human Resource ManagementSupport Activities
Margin
Source : WMEP, 2007; 1
Included within the primary activities are inbound logistics, operations, outbound
logistics, marketing, and sales and service. Included in the support activities are
procurement, technology development, human resource management and firm
infrastructure. The main objective of Porters’ value chain was to improve overall
efficiency of an organisation in order to obtain a competitive advantage.
12
According to a survey done by IndustryWeek Magazine (HighJump Software,2005),
some of the changes organisations have experienced with Value Chain Management
are listed below:
• Costs Savings 62% Improvement
• Increased Market Share 32% Improvement
• Reduced Inventory 51% Improvement
• Higher Quality 60% Improvement
• Faster Delivery Times 43% Improvement
• Customer Service 66% Improvement
2.3 The supply chain
The primary activities of the value chain make up the supply chain. Beamon defines
the supply chain as an integrated process wherein a number of various business
entities (i.e., suppliers, manufacturers, distributors and retailers) work together in an
effort to: (1) acquire raw materials, (2) convert these raw materials into specified final
products, and (3) deliver these final products to retailers(Beamon, 1998; 281). This
chain is traditionally characterised by a forward flow of materials and a backward flow
of information (Ibid).
Figure 2.2 The Modern Supply Chain
Goods picked
Loads Dispatched
StoreReplenishment
Salesscanned
at checkoutSale updatesthe storeforecast
Store demandgenerated
Purchase ordergenerated
Supplier deliversto depot
Goodsreceived
and unloaded
Supplier Depot
StoreConsumer
Goods picked
Loads Dispatched
StoreReplenishment
Salesscanned
at checkoutSale updatesthe storeforecast
Store demandgenerated
Purchase ordergenerated
Supplier deliversto depot
Goodsreceived
and unloaded
Supplier Depot
StoreConsumer
Source: IGD, 2007; 1
13
The supply chain can be broken down into three distinct flows, namely the product
flow, the information flow and the finance flow. In the traditional supply chain, orders
were the only information exchanged between firms. Now, however, companies are
learning the importance of sharing demand and inventory data, in order to allow
companies down the supply chain to be better prepared for events that occur up the
supply chains. This bi-directional flow of information is critical to supply chain
optimisation and success.
As time goes by and technology continues to improve our lives, customers have
become used to constant improvements, and hence have become more demanding.
“To achieve in today’s customer competitive markets, manufacturers are being forced
to look beyond the essentials of the bare product in order to cope with customer
demands. To achieve this, they need to involve every link in their supply chain and
encourage them to become active participants in the process” (Desbarats, 1999; 4).
No longer is an organisation able to compete on the basis of a product alone.
Instead, complete organisational supply chains have begun competing against one
another (Desbarats, 1999; 3). “Manufacturing needs to accept that unless it creates
value in a form that can be perceived by the consumer, it is easily reduced to low
commodity margins “(Ibid).
“Satisfying the end customer can only take place when the entire supply channel
from materials supplier to retailer are linked closely together in the pursuit of
innovative ways to improve service value, reduce channel costs, and create whole
new regions of competitive space” ( Roethlein, Ackerson ; 2 ).
Optimising an organisations’ supply chain is no longer a choice for organisations, but
has become compulsory if they want to compete as “competence in supply chain
management will be a key determent in gaining a sustainable competitive advantage”
(Spekman, Spar, Kamauff, 2001; 2).
2.4 What is logistics?
The word logistics is derived from the ancient Greek word ‘logos’ (λόγος), which
means “ratio, word, calculation, reason, speech, and oration” (Wikipedia, 2007a). The
14
word logistics was first used in the military service to describe the process of
supplying a war zone with troops, supplies and equipment (Wisegeek).
2.4.1 The definition of logistics
According to the IDF (Israeli Defense Force), this military definition can be broken
down into different components such as:
• the planning, development, acquisition, storage, transportation, supply,
maintenance, evacuation and destruction of equipment (including
weapons, ammunition, etc.);
• force transportation and monitoring;
• evacuation and medical care for casualties (medical services);
• acquisition, construction, maintenance, and operation of buildings and
facilities;
• acquisition and rendering of services.
(Technological and Logistics Directorate, 2007; 1)
Although the term logistics was initially used exclusively in the military field, over time
it has come to refer to a major sector of the business environment.
There are several reasons why logistics has developed into the organisational
environment.
I. Deregulation – “As the economies in North America evolved in the 1970s
and 1980s, transportation deregulation changed the competitive
landscape of business. Carriers were free to charge their customers
(Shippers) a competitive rate for their shipments. Warehousing companies
that typically acted as surplus inventory storage locations, married up with
transportation companies to offer customers full-service solution
capabilities. This formed the beginning of the 3rd party logistics business
and paved the way for outsourcing logistical activities” ( About .com,
2007a ).
15
II. Globalisation – In order to gain a competitive advantage, manufacturing
organisations started moving their manufacturing facilities to countries with
low-cost labour. This resulted in a new logistics network being developed
in order to move the manufactured product from the country of production
to the consumer.
III. Information technology – The growth of computers and software meant
that tasks that were in the past manual and costly, could now be
automated. This change led to concepts being developed like just in time.
According to Coyle, Bardi and Langley (2003,39), logistics has come to be defined in
the business sector as “the process of planning, implementing, and controlling the
efficient, cost effective flow and storage of raw materials, in-process inventory,
finished goods and related information from point of origin to point of consumption for
the purpose of meeting customer requirements”. There is a wide range of definitions
available for the term ‘logistics’ (Webster’s Dictionary, American Heritage Dictionary,
Council of Logistics Management, United States Department of Defence as cited in
Logistics World). Although all different, they share the common idea of delivering the
right product to the right place at the right time in the most effective manner in order
to ensure the lowest costs and optimum level of customer service.
2.5 The need for organisations to focus on their core product
“Traditionally, marketing, distribution, planning, manufacturing, and the purchasing
organisations along the supply chain operated independently” (Ganeshan & Harrison,
22 May 1995; 1). This never only occurred when each organisation was owned and
operated as its own entity, but occurred even when the above were departments of a
single organisation. To make matters worse, these organisations or departments
often had their own objectives which were often conflicting.” Marketing's objective of
high customer service and maximum sales dollars conflicts with manufacturing and
distribution goals. Many manufacturing operations are designed to maximise
throughput and lower costs with little consideration for the impact on inventory levels
and distribution capabilities” (Ganeshan & Harrison, 22 May 95), “The result of these
factors is that there is not a single, integrated plan for the organisation” (Ibid).
16
The constant conflict described above often led to an organisation focusing on its
core product, without paying much attention to the support departments, such as
sourcing and logistics. These departments received little attention with limited focus
on their strategic importance or cost.
According to Ganeshan and Harrison over time organisations have come to realise
that there is a need for a mechanism through which these different functions can be
integrated together, a mechanism through which a competitive advantage can be
achieved due to reduced costs and improved customer service (Ganeshan &
Harrison, 22 May 1995; 1). Supply chain management is a strategy through which
such integration can be achieved.Only once a company realises that its different
departments and organisations are part of a holistic entity, can it begin and attempt to
optimise its supply chain through an integrated approach.
However, even once companies have become aware of this, they often do not see or
understand the possible benefits of working as a link in the expanded supply chain.
Traditionally, every company worked as an individual unit, controlling its own
resources without worrying much about the supplier or customer higher up or lower
down the supply chain. For example, in an effort to keep storage and the associated
costs down, retailers would prefer not to hold stock, but rather force the wholesaler to
hold the stock. This did however not eliminate the expense, but rather pushed it to
another link in the supply chain.
2.6 Supply chain optimisation
In the past few years, certain factors have suggested that focusing on a core service
as well as partnering with other members of the supply chain, can lead to greater
efficiency, reduced cost and hence larger profits. For example, if the retailer,
wholesaler and producer worked together they would find a way to reduce stock
altogether, and would hold stock at the link in the supply chain at which it is cheapest
for everyone.
In an increasingly competitive and globalising business environment, it is not
sufficient for organisations to merely produce high quality products. With
organisations producing similar goods and services, the matter that is commonly
17
raised is, "Where lies the weakest link and the resulting competitive differentiator?"
(Ram Mohan, 21 December 2006). In the past, organisations could compete on the
basis of their products alone, however, with a changing and developing competitive
environment, they are now forced to compete on the basis of the organisations’
supply chain strategies (Ibid).
“A killer product is only successful if it gets to the right customer at the right price at
the right time,” says Levi. “Apple’s supply chain technology is the (sic) really the silent
contributor to the company's success in executing the product innovation”
(Trebilcock, 27 July 2007; 1).
Optimising the entire supply chain as a whole will not only significantly reduce stock-
outs and reduce lead time, but it can also significantly reduce the logistics costs.
According to Martin Bailey, “the total logistics costs make up 15, 2% of South Africa’s
gross domestic product (GDP) a high figure when compared to trading partners such
as the US where logistics costs are 8,6% of the GDP” (Bailey, 2 March 2006; 34). If
South Africa can improve its general optimisation of its supply chain and reach
American standards, products can be up to 6.6% cheaper, giving the consumer more
disposable income and hence the ability to buy more and grow the economy .
Other benefits of managing the supply chain include risk reduction. “It is clear that the
impact upon business can be reduced if the potential risks are proactively managed,
and there is a well-conceived and constructive business plan in place” (Finch; 3).
At its highest level, a supply chain is comprised of two basic integrated processes:
(1) the Production Planning and Inventory Control Process, and (2) the Distribution
and Logistics Process (Beamon, 1998; 282).
However, when these two processes are broken down, many more processes are
involved in the supply chain which can be seen from the next diagram:
18
Figure 2.3 The Supply Chain Process
Suppliers
Manufacturing Facility
Storage Facility
Transport Vehicle
Retailer
Distribution Center
Production Planningand Inventory Control
Distribution and Logistics
Suppliers
Manufacturing Facility
Storage Facility
Transport Vehicle
Retailer
Distribution Center
Production Planningand Inventory Control
Distribution and Logistics
Source: Beamon, 1998; 283
2.7 The advantages and complexities of effective transport optimisation and
management
There are many areas in the supply chain which have room for improvement and
optimisation. Optimising the transport function is only one of the many areas where
the supply chain can be improved.
As can be seen from the following points, transport optimisation is certainly a link that
has much room for improvement. Below are a few of many examples of how,
according to High Jump Software, transportation management systems can rapidly
reduce costs (High Jump Software, 2005).
I. By automating the management of an organisation’s contracts through the
use of a software system to handle all of an organisation’s contacts and
tariffs, a reduction in administrative costs can be achieved by avoiding
mistakes made by manual invoicing.
II. Through optimising an organisation’s routes, schedules and loads, a
reduction in annual transport costs can be achieved.
III. A reduction in annual transport costs can be achieved through least-cost
mode or haulier selection.
19
IV. “By automating the tendering process a company will yield savings greater
than a simple reduction in staff time spent dialing for diesels. Automation
of tendering helps ensure routine conformance to a least-cost carrier
selection program. The automation of a tendering process also means
carriers receive complete, accurate information on tendered shipments the
first time, every time. In the past, automated tendering was limited to large
companies and large carriers where an electronic data interchange
connection was available and cost-effective for both parties. This simple,
reliable methodology can replace a myriad of phone calls attempting to
reach the desired carrier representative. Additionally, the carrier receives a
complete and accurate communication of the shipment detail without a
time-consuming phone conversation” (Ibid).
V. In light of the current extremely competitive transportation environment,
the ability to accurately record and assess performance across the supply
chain has become of great importance and value.
Maintaining a competitive advantage in today's demanding business environment
requires continual process improvement and cost reduction. Previously, in order to
lower costs, many organisations focused on transportation in an effort to control
supply chain costs and help ensure on time delivery.
Recently, however, effective transportation management has become more complex
due to several industry trends:
• the rising cost of fuel, insurance and drivers’ wages;
• the growing shortage of the availability of transportation needed that has
led to an environment in which organisations have to get "service at any
cost";
• consolidation of the transportation provider industry. Many large
corporates are buying up all the smaller transportation organisations;
• progressively more demanding customers;
• increase in transportation regulation.
(High Jump Software. 2005)
20
In South Africa, the new Credit Act (National Credit Act No. 34 of 2005, section 5 of
Schedule 3) that came into effect in 2007, is making it more difficult for hauliers to
borrow capital to increase their fleet as demand grows, which is in turn leading to
higher costs of transportation and increased complexities (Naidoo, 1 October 2007).
The above complexities in transport management along with other new complexities,
have led to the growth of outsourcing an organisation’s transport needs.
2.8 Why outsource?
In general, outsourcing is done in order to allow a firm to focus on its core
competencies. Examples of this can be seen below.
2.8.1 Examples of where outsourcing makes business sense
I. “If an organisation is assembling airplanes, then serving lunch to
employees is not a core competency, doing it internally is a distraction and
hence most companies use catering companies when available”
(Baudin,2004;337).
II. “Intel is turning raw silicon into microprocessors using multi-billion dollar
wafer fabrication plants, and may well consider that inbound and outbound
logistics is not their core competency “(Ibid).
Thomas remarks that although the concept of outsourcing a total department of an
organisation is relatively new, outsourcing to some degree has existed for years
(Thomas, September 2002). Using rented vehicles instead of private fleets, freight
payment plans, freight forwarders and public warehouses, are just a couple of
examples.
There are as many reasons for outsourcing. Many of these reasons are unique to
specific organisations and industries, but in general, there are several identifiable
advantages to subcontracting an organisation’s logistics requirements
(Lynch, 2000, 7).
21
2.8.2 Advantages of outsourcing
I. Return on Assets
Organisations are constantly looking for funds to fund their growth and the
expansion of their core service. Through outsourcing one’s logistics
needs, organisations can reduce investment in logistics-related services
and equipment such as warehouses, vehicles, materials handling and
picking equipment. The saving in capital can in turn be used for core
product expansion (Quelin, October 2003, 647; Lynch, 2000, 7).
II. Personnel Productivity
As discussed above, by outsourcing an organisation’s logistics needs,
capital can be saved for core product expansion, as well as, personnel. As
a result of an organisation’s outsourcing its logistics department, the
internal personnel are freed up and therefore can focus on their core
product without distraction. This especially affects the top management
whose management expertise is often stretched across many departments
(Ketler, Willems, 2000; 2; Lynch, 2000, 7).
III. Flexibility
Outsourcing an organisation’s logistics needs, allows for greater flexibility.
“As new markets and new products are developed, it often is impossible to
predict future logistics needs accurately. Likewise, as existing market and
product characteristics change, logistics needs change as well. New customer
service requirements, ordering methods and competitive offerings all influence
a firm's logistics practices; and the use of a contract provider greatly reduces
the risk of misplaced or outdated facilities and equipment. According to a
study conducted by the European Management Journal the third most
important criteria when choosing to outsource is to gain flexibility”(Lynch,
2000, 7; Slaughter & Soon, July 1996; Quelin, October 2003, 647).
22
IV. Labour Considerations
With the increase in unions and the complexities of labour law,
outsourcing an organisation’s labour can avoid many potential labour
issues. When labour issues arise, the issues can merely be passed
onto the contractor, allowing an organisation to avoid spending time,
money and effort dealing with the issue (Lynch, 2000, 7; Slaughter &
Soon, July 1996; 6; Ketler & Willems, 2000; 2).
V. Cost
A third party service provider that specialises in a particular service,
can often supply the service at a lower price than it would cost an
organisation to provide that service in-house. Other times, although the
costs may be slightly higher, it may still make sense to outsource the
service due to saving on capital. According to a study conducted by the
European Management Journal, the most important criteria when
choosing to outsource is lowering costs. Outsourcing also allows an
organisation to convert fixed costs into variable costs (Ketler & Willems,
2000; 2; Lynch, 2000, 7; Casale, 2007, 1; Quelin, October 2003, 647).
VI. Management and Political Considerations
In today’s constantly developing business environment, workers’ rights are
at the forefront and hence people are becoming more and more difficult to
manage. “It is far easier to manage one or a limited number of providers
than it is to manage the individual functions internally” (Lynch, 2000, 7;
Ketler, Willems, 2000; 2).
VII. Customer Service
Customer service has become a main area of competitiveness in today's
environment. A large specialised organisation will more easily be able to
afford specialised expensive software and equipment to allow it to keep up
with the growing demand of customer service. Keeping up with the
growing levels of customer service is a must in order for an organisation to
survive (Casale, 2007, 1).
23
VIII. Specialised Services
Specialised services are becoming a must, rather than a “nice to have”.
Although some of the larger logistics service providers have the ability to
serve the needs of various different industries efficiently, in general, the smaller
logistics organisations are focusing on proving a specialised service to a specific
niche in the marketplace.
a. Just in Time
The “Just in Time" technique has been utilised in the automotive industry
for many years. As a result of this technique relying on “on time delivery“,
3PL organisations are often used to ensure the high level of service
required for the technique to work efficiently.
b. Order Consolidation
This technique results in smaller, more frequent shipments. Many
manufacturers, particularly grocery manufacturers have decided to rely on
3PL organisations instead of investing the time and money in trying to
provide this service in-house.
c. Packaging
In a high-volume manufacturing plant, the time taken to collect and
package items into the necessary packaging for transport and sales can
be an extremely time-consuming function and can lead to many
inefficiencies. Outsourcing this function to an organisation that has the
volume and afford to automate it can lead to great savings.
d. Order Fulfilment and Electronic Commerce
The Internet and related services have had and continue to have an
enormous impact on logistics service requirements. It is likely that many
manufacturers and distributors, particularly web-based organisations, will
not have the expertise to establish and manage the delivery and
communications systems they require (Lynch, 2000, 7).
24
IX. Information Technologies
Utilising the appropriate information technology is becoming more and
more critical to survive in today’s technology-driven marketplace. The
technologies are often too expensive for many organisations to afford.
Outsourcing to an organisation that has large volumes and hence can
afford to prioritise the required information technology, makes sense for
many smaller organisations (Lynch, 2000, 7; Slaughter & Soon, July 1996;
6).
X. The Logistics Service Provider
The logistics service provider has evolved from a small organisation just
a few years ago, to a large organisation that executes its duties with
precision. “Quite often, it is better qualified than its clients to perform the
product distribution function” (Lynch, 2000, 7).
XI. Global Sourcing and Selling
“Traditional sourcing with local based suppliers has given way to sourcing
based on the best price that meets the product specifications. This has
opened up purchasing to international suppliers. This change, in turn has
added complexity to the supply chain in dealing with suppliers who are
thousands of miles away, not just a phone call away, and where delivery
times for ocean freight can take weeks. Companies must deal with the
impact of a global supply chain and third party logistic companies (3PLs)
can be seen as ways to manage that international logistics need,
especially for companies that are more comfortable with domestic than
with international trade” (Thomas. September 2002).
XII. Supply Chain Management
“Increasing complexity of supply chain operations has driven original
equipment manufacturers to increase outsourcing” (Ram Mohan,
21December, 2006).
By outsourcing supply chain needs, an organisation will be able to keep up
with the supply chain complexity without adding the would-be-needed
25
capital and staff to an organisation’s already limited resources.
Outsourcing one’s logistics needs, also allows an organisation to avoid
any internal organisational politics of where people feel the organisation’s
capital and resources should be invested.
XIII. Outsourcing as part of the business model
In the pursuit for optimisation across one’s organisation, “Outsourcing has
become an acceptable way for a company to implement, develop and
manage its business model and business practice”. Many organisations
have come to realise that the supply chain is a key requirement that needs
to be optimised in the quest for an optimal business model (Thomas,2002;
Ketler & Willems, 2000; 2).
XIV. Product Cost
“An additional benefit is that outsourcing isolates product costs: the cost of
goods sold is known with precision because it is paid by invoice from the
contract manufacturer” (Arena Solutions, 2006; Quelin, October 2003,
647).
XV. Focus on core activity
“Outsourcing allows a company to focus on their core expertise without
having to split their resources with their non-core departments while at the
same time ensuring that their non-core departments get the attention they
need”( Supply and Demand Chain Executive. October 2006; 1). The
logistics department represents a typical department through which
outsourcing can improve its efficiency, while at the same time freeing up
resources to focus on an organisation’s core product. According to a study
conducted by the European Management Journal, the second most
important criterian when choosing to outsource is the ability to free up
resources, and therefore focus on the organisation’s core activities (Ibid;
Slaughter: Soon, July 1996; 6; Quelin, October 2003, 647).
26
XVI. Sharing the Risk
“Problems such as staffing, technology selection or telecommunications
are transferred to or shared with the vendor” (Ketler & Willems, 2000; 2).
Just as there are many advantages to outsourcing, there are many disadvantages.
Below are a few of the disadvantages of outsourcing.
2.8.3 Disadvantages of outsourcing
I. Loss of control
Outsourcing a department can often mean less control over what happens
in that department. Although the logistics department is in general
considered a support department, organisations have come to realise that
good management and control of the logistics department is critical to
success. “In the Dataquest survey (Schwartz, 1992) 31% of the
respondents cite “loss of control” over the quality of information services
(IS) as a disadvantage of outsourcing” (Ketler & Willems, 2000; 2).
II. Difficulty in selecting the right 3PL partner
Selecting the right 3PL partner is critical to success. “If the firms cannot
select reliable 3PL providers, they may suffer from economic losses. It is
not easy for firms to judge the ability of the 3PL provider during the
selection stage, owing to the issue of information asymmetry between the
firm and the 3PL provider” (Nemoto & Tezuka , 2000; 3 ).
III. Higher exit barriers
“It is very difficult to reverse the decision to outsource once your
organization has signed up with a 3PL provider. Contracts are usually 2-5
years in length with penalty clauses for early termination” (About.com,
2007b; 1).
IV. Unexpected fees
Unexpected or hidden fees can often appear after an organisation has
signed a contract with a 3PL. Once the contact has been signed, these
27
fees are difficult to avoid without a resulting impact on the desired level of
service.
V. Outsourcing can be more expensive
Outsourcing can sometimes work out to be more expensive than
producing the required service in-house. Sometimes this expense is
justified due to higher levels of service. However, this expense can not
always be justified.
VI. Outsourcing can be time-consuming to implement
The change from an in-house carrier to using a 3PL can be a very time-
consuming task. Finding and appointing a 3PL is a very complex process.
Because of this, the involvement of higher level management is critical;
however, the extra time of the higher level management is often extremely
limited, and hence they cannot play as active a role in this process as is
required.
VII. The risk of a 3PL providing a poor service
When outsourcing, the risk always exists that the outsourced organisation
may provide a poor service and due to contractual agreements, an
organisation may be tied in using the poor service provider for a lengthy
period of time.
VIII. The risk of dependence on the service provider
This risk includes the risk of not having a safety net if a contracted
provider fails to deliver the right quality product at the right time.”These
concerns clearly manifest the belief that it is difficult to change vendors or
to bring the activity back in-house after the contract has terminated”, due
to lost skills and know-how (Quelin, October 2003, 647).
The drives for greater efficiency, as well as the increasing complexity of the field has
caused organisations to outsource their logistics needs and has spurred major
growth in the third party logistics market. "An increasing number of automotive
companies prefer to focus on core competencies and outsource non-core activities
28
such as logistics to specialized 3PL service providers, to benefit from cost savings
and enhanced efficiency," said Frost and Sullivan Research Associate, Keow Soon
Hiong (Hiong, January 2007).
2.9 The third party logistics provider (3PL)
According to the Supply Chain and Operations Management Glossary, third party
logistics can be defined as “the use of an outside party to perform some part of the
logistics function, typically trucking or warehousing. It is often appropriate if there are
economies of scale in the logistics function” (Supply Chain and Operations
Management Glossary, 13 November 2006).
“The push towards outsourcing logistics has been met with mostly only positive
results. Logistics outsourcing continues to transform companies as they focus on
core competencies to meet corporate objectives." (Hickey, 1 November 2001).
The use of a third party logistics provider stretches far beyond simple cost savings.
As can be seen from the following survey, the benefits of using a third party logistics
provider are rather broad. A study conducted by the Northeastern University in
Boston asked respondents how satisfied they were with their third party logistics
provider’s performance regarding cost savings, service improvements,
communications, overall working relationships and the 3PL managers assigned to
their account. The response was varied with 67% of respondents saying they were
"very satisfied" or "satisfied" with the cost savings achieved, and 90% of respondents
saying they were very satisfied or satisfied with their overall working relationship with
their 3PLs (Gooley, 2002). As can be seen from these results, the introduction of
3PLs into the industry has been beneficial as companies are satisfied with the
performance and their relationship with their 3PL, and would not consider reverting
back to managing their transport themselves.
According to a study conducted by the European Management Journal, logistics is
one of the five most affected departments for outsourcing. The other four
departments that organisations often outsource include office information technology,
industrial maintenance, waste management and telecommunications. “The three
activities most commonly cited as having the greatest outsourcing potential within the
29
next two years are office information technology , waste management and logistics”
(Quelin, October 2003, 647).
In the following case studies the need for outsourcing to a specialist company can be
clearly seen.
2.9.1 Outsourcing case studies
Schiesser AG is Germany’s leading underwear specialist. Due to the short-lived
trends of the fashion industry, fashion organisations have enormous pressure to
ensure “on-time delivery in order to be able to service the demand of end consumers
almost instantly”. This means a no-tolerance for late deliveries or deliveries with
incorrect amounts, as such deliveries can hold up production and lead to the late
delivery of the final product. Due to the large pressures on the fashion industry’s
supply chain, Schiesser decided to outsource its logistics functions. “The outsourcing
of the logistics operations has supported the shortening of process times and the
reduction of process costs”. Schiesser’s outsourcing of logistics activities has allowed
for reduced costs and reduced delivery times. In addition, “the transparency achieved
as a result also has improved process quality by giving Schiesser the possibility to
react quickly to any imminent delays in delivery”( Senger,2002;5-9).
In another example, the outsourcing of warehousing and logistics functions led to
vastly improved customer service in the airline industry.
Jacks Airplane Parts (This is a fictitious name in order to ensure privacy) operates on
the East Coast of America. Due to the nature of the airline business, when a plane
needs a spare part, the spare part needs to be picked, packed, shipped and arrive
within 24 hours of ordering, as every minute an airplane is grounded hundreds of
dollars are lost in missed revenue. With Jacks Airplane Parts’ “entire inventory
housed on the East Coast, it was physically impossible for Jacks to get parts to
airplane mechanics in the Midwest or West Coast in less than one to two days”.
Constraints such as capital and lack of management skills prohibited Jacks from
opening another warehouse on the West Coast. Through outsourcing his West Coast
warehousing and logistics needs to Medallion in Los Angeles, Jacks has been able to
offer his customers a 24-hour delivery, no matter what time they order or where they
30
are located America. By outsourcing his distribution to a 3PL, “Jack was able to
expand his business model, improve product delivery time to his customers, and
significantly increase his sales” (Medallion Fulfilment & Logistics, 2007; 1).
2.10 The need for better management and information sharing in the 3PL
Although the third partly logistics service provider started out by simply distributing an
organisation’s products on its behalf, 3PL organisations have progressed to do far
more. Today’s sophisticated 3PLs literally partner with an organisation and work in
partnership to protect and grow its brand, ensuring that customers receive what they
ordered, when and how they need it. “To achieve this, the 3PL integrates fully with
customers at all the touch points of shipment, including invoicing, inventory
management and reconciliation” (Planeservices.com, 21 July 2005).
With the growth in the use of the third party logistics operator, as well as the growth
in the services offered by the 3PL, the need has arisen for better overall
management within the 3PL, better management of their resources and their
relationships both with the customers, as well as their subcontractors. According to
Slaughter and Soon (Communications of the ACM, June 2001), numerous factors
have contributed to the need for improved management. On the demand side, an
increasingly cost-and value-conscious customer is demanding a more varied, and
often individualised value-added service from the supply chain. On the supply side,
the availability of modern information and communication technologies makes it
possible to obtain an overview of the entire supply chain and to redesign and
manage it in order to meet this demand. Finally, on both the demand and supply
side, the emergence of global markets and global sourcing has stretched these
supply chains over intercontinental distances (Ibid).
Another factor influencing the need for better management and control of third party
logistics enterprises, is the fact that many third party logistics companies have to
allocate a large number of their staff to basic jobs such as communication with their
customers, subcontactors and their drivers.
According to Opsi Systems, a company specialising in logistics software, a logistics
organisation very often allocates a large portion of its resources to various systems
31
controlling individual aspects of the transportation business (Opsi Systems, 2006a).
With proper systems in place, these tasks can be handled by much fewer resources,
thus availing upon manpower for other tasks.
The benefits and need for outsourcing logistics management are clear, however, this
does not mean that outsourcing is always successful. Poor planning and poor
communication are major factors that often cause outsourcing relationships to fail.
Communications on all aspects of the logistics arrangement must be frequent and bi-
directional. If the 3PL is truly integrated into its client’s organisation, it must be kept
fully informed of every aspect of the business that will affect it or influence its
operations. For example, being informed in advance of things such as promotions, or
a possible strike at the factory can be critical to the success of the relationship. The
3PL is often expected to operate as an outside service provider and not a partner,
which paths the way for a suboptimal relationship for both the 3PL and its clients.
Similarly, the 3PL must be encouraged to keep the client fully informed about its
operations and any relevant strategies. Expected transport issues, equipment
shortages or other potential issues must be communicated to the client, forming a
healthy two-way relationship where honest and prompt communication is conductive
to a relationship where both parties benefit. There is no simpler and quicker way to
devastate a relationship than to be presented with unexpected surprises (Lynch,
2000, 183).
Eckerson explains that most organisations deliver reports that summarise past
business activity (Eckerson, 2006). While historical information is critical, it doesn’t
help organisations identify problems or opportunities as they occur, and allows them
to take immediate actions in order to optimise the result. The value of information
changes with the timeliness of its delivery to decision makers, and therefore
companies are increasingly competing regarding the velocity of their information
delivery to business users. Being able to respond quickly to business events can
spell the difference between success and failure (Ibid).
As a result of supply chains relying on current and up to date data, they depend on
information sharing, especially in a global environment, where speed of com-
32
munication is critical and supply chains are continually growing more complex. The
supply chain then makes use of this current and up–to-date data to process, modify
and deliver instantaneous information whenever and wherever it is needed.
“The ability to appraise and use IT packages and electronic communication methods,
has become a key competency for logistics managers, not least because, with the
growing use of the Internet, the supply chain is at the centre of some of the most
exciting developments in telecommunications and electronic commerce - also known
as e-commerce” (The Chartered Institute of Logistics and Transport.2007).
2.11 The building of collaborative relationships
Management of relationships, as well as sharing of information usually leads to a
collaborative relationship of some kind. Self-interest motives are often the overriding
factor when organisations become interested in collaborative relationships, as
organisations have to be motivated to make any changes, especially in the event of
such a major one. However, once the relationship is formed, all parties of the
relationship benefit, although some parties may benefit more than others. The desire
to form a collaborative relationship is typically driven by the party who will receive the
greatest benefit, which is often the biggest and most powerful link in the supply chain.
The collaborative relationship frequently begins by large organisations stating, "If you
want to do business with me, you need to do this at a minimum." Large organisations
need to understand that their partnering organisations will do only the minimum if the
benefits are truly one-sided. However, for collaboration to progress beyond the
operational stage, an organisation must recognise that it also requires mutual sharing
of the risks and rewards (Nickerson &Petersen).
Depending on an organisation’s needs, one of the following types of collaboration
could be chosen as explained by Nickerson and Petersen.
I. Operational: Collaboration consists of a minimum level of coordination and
visibility between organisations. The relationship is best described as
opportunistic, with very limited process and strategy alignment between
companies.
33
II. Tactical: There is a basic level of trust and a desire to create a win-win
relationship where partners work together to create value through shared
processes with an expanded scope.
III. Strategic: This represents the highest level of collaboration where
companies create value through the alignment of their long-term business
strategies. Reporting structures may resemble a matrix, and organisational
boundaries are often blurred with teams working together to achieve the
joint business objectives (Nickerson &Petersen).
While there is an increased emphasis on price and core service, many organisations
would also like to see their partnership with 3PLs becoming more strategic in nature.
The 2005 Third Party Logistics annual study, conducted in Atlanta USA, quotes
Susan Norris, Vice President of Supply Chain for Bacou-Dalloz, as saying, “3PL
providers need to be better at expectation management, executive presence,
education, and cultural change” Rockwell Automation’s, Niek Visarius, notes that his
company started out with a very tactical set of 3PL relationships that are now
migrating to more strategic levels (2005 Third Party Logistics. Results and Findings
of the 10th Annual Study, 2005; 21).
Large organisations as well as 3PLs are striving for greater collaboration in their
relationships, but are having difficulty achieving the desired level of collaboration.
The 2006 annual 3PL report (Langley & Allen; 2006) notes “that clients say they
value highly the ability of a 3PL to identify areas for continuous improvement, but that
few achieve the level of relationship that allows a 3PL to be such a partner when it
may mean a reduction in its revenues as a result”. Supply Chain Digest notes “that in
companies such as Toyota, with deep and long standing 3PL partnerships, this type
of collaboration has been successfully achieved. Hershey, among other companies,
has also realised strong benefits from continual gain sharing programs with 3PL
providers” (Langley, 2005). This means that although difficult, such relationships are
possible.
“As third-party logistics providers demonstrate their ability to bring down conventional
logistics costs, and handle more complex tasks, customers will continue to give their
3PLs more responsibility and input into their business process” (Inbound
34
Logistic.com, 2004; 1).Cost-saving pressures will force many companies to involve
themselves in product lifecycle management in order to ensure their entire operations
run at an optimal. They will increasingly turn to 3PLs to help them optimise their
operations (Ibid).
Today’s 3PLs are forming partner type relationships with their customers as opposed
to merely transactional relationships. “The relationships most likely to succeed, are
partnerships in which the two parties work together to build "value-added" supply
chains”, says Herb Shear, Chairman and CEO of GENCO, a third-party logistics
service provider based in Pittsburgh (Cooke, December 2006). These new
partnerships that are being formed can be described as long-term collaborative
relationships that encourage mutual planning and problem-solving efforts with direct
benefits to all involved.
Partnership types in logistics can be defined as follows:
• Level and degree of information sharing (Mason-Jones, 1997 as quoted
by Chibba 2007),
• Buyer-vendor cost saving initiatives (Thomas, 1996 as quoted by Chibba
2007),
• The entity and stage at which supplier is involved (Toni, 1994 as quoted
by Chibba 2007),
• Extent of mutual co-operation leading to improved quality (Graham ,
1994 as quoted by Chibba 2007),
• Extent of mutual assistance in problem-solving efforts (Krauth, Moonen,
Popova,Schut as quoted by Chibba 2007).
Partnering also has its risks, for example when partnering with the wrong partners, it
may neither be feasible nor profitable to have strong collaboration. In order to
achieve the benefits mentioned previously, 3PL organisations should select key
customers and focus on strengthening their relationships with these customers, as
opposed to trying to build a collaborative relationship with all customers even where it
may not be optimal (Krauth, Moonen, Popova and Schut).
35
2.11.1 Evaluating collaborative relationships
The relationship with an organisation’s partners needs to be constantly evaluated
and assessed. The difficulty when evaluating a partnership is determining with regard
to what key performance indicators an organisation should use to evaluate a
partnership.
The selection of performance indicators is no easy task. No single indicator can give
a complete picture on the performance, as each one presents only a limited view
from a specific viewpoint, and is therefore not enough to serve as the basis for
important management decisions. Historically, organisations concentrated on
financial indicators. “Nowadays it is widely recognised that non-financial and even
non-numerical indicators can give valuable information as well” (Seuring, Müller,.
Goldbach,Schneidewind,2000). Such indicators though are more difficult to measure
and compare.
In order to consider a full set of indicators a large amount of data would be required
which could result in much effort and high costs. An organisation needs to select a
collection of the most important indicators that are relevant to its needs and goals.
“The analysis should be performed with extreme caution so that the resulting set of
indicators covers every relevant point of view. It is not uncommon that the selected
indicators turn out to be conflicting, improving one may worsen another” (Ibid, Krauth,
Moonen, Popova and Schut).
Until now, it seems that collaborating with a 3PL is the optimal way to go to
guarantee efficiency, however the following were some of the concerns of the 2001
Sixth Annual Third-Party Logistics Study (Langley and Allen, 2006;23) :
• Lack of strategic management skills.
• Cost reductions have not been realized.
• Cost “creep” and price increases once relationship has commenced.
• Lack of continuous, ongoing improvements and achievements in
offerings.
36
• Control over the outsourced function(s) diminished.
• Lack of consultative, knowledge-based skills.
• Technology capabilities available, but not delivered to client.
• Time and effort spent on logistics not reduced.
The study explains that 3PL providers should view this list as a starting point for
continuous improvement. Overall, the study suggests the critical importance of 3PLs
meeting their agreed upon service levels and cost objectives, as well as to avoid
unnecessary increases in pricing once the customer relationship has commenced.
Also, it suggests that some 3PLs need to improve their strategic management,
technology and general skills. Furthermore, “several 3PL users felt that the time and
effort spent on logistics have not decreased, and that their control over the
outsourced function may have lessened. In the latter instance, the move to “hybrid”
management of the 3PL provider’s responsibility may be a useful alternative”
(Langley and Allen, 2006; 25).
2.12 The use of technology to enhance relationships and efficacy
The majority of the issues of the Sixth Annual Third-Party Logistics study can be
solved through better management of the 3PL, as well as well as better management
of the partnership relationship between the 3PL and the company. Hence the need
for better systems and control is becoming critical to operate in today’s times. A 3PL
can be successful only if its acts are based on reliable and complete information
about the performance of the company as a whole and all its units. “It is therefore
surprising that such an activity is usually carried out in an ad-hoc manner” (Krauth,
Moonen, Popova and Schut).
In 2006, a study conducted by Lieb, as quoted by Cooke, indicated that 3PLs were
investing in technology to support collaborative relationships and to provide visibility
of items as they move through the supply chain. "Systems with the right functionality
can give you the information to take costs out," says Koerner as quoted by Leib. "It's
becoming a business of data," adds Shear as quoted by Leib. "Customers are
37
expecting us as 3PLs to become more strategic, so we've got to become very good
at managing and analysing data. Give me visibility of data and you make good
management decisions “ (Cooke, December 2006).
“From 1999 to 2002 vendors sold, excluding installation and training costs, more than
$15 billion in supply chain management software. Not withstanding such large
investments, the results have been mixed” (Haggar, R, 2003; 1).
Northeastern University undertook a study focusing on the current usage of
technology in the supply chain. The results showed that “nearly half of its survey
respondents were outsourcing freight payment and transportation planning or
optimisation to their third parties”. This study shows that not only does it make sense
both financially and logically to outsource internal logistics departments, but
companies were taking the big step and putting their money where there mouth is by
partnering with a 3PL and outsourcing their logistics department (Logistics
Management, January 2002).
Georgia Tech also conducted a study in which they asked respondents which
information technology (IT) services their 3PLs now offered, and which of those they
would require from 3PLs in the future. The study found that the greatest demand for
IT systems in the future would be in sophisticated supply chain and supplier-
management information, as well as in electronic markets. These trends indicate a
shift in expectations regarding the role that 3PLs play from functional to strategic
management.
Georgia Tech also asked respondents whether they preferred to rely on 3PLs or
software vendors in order to gain access to the appropriate technology. “Sixty-nine
percent preferred to go directly to vendors while only 20 percent turned to 3PLs for
that service, a number also supported by Northeastern's findings” (Logistics
Management, January 2002).
Although some users still want 3PLs to manage the flow and use of information as
well as integration with other technologies, only about 20% of respondents in both
studies said they relied on 3PLs to manage information systems on their behalf,
38
which suggests that organisations do not believe 3PLs are ready and able to take
that task on just yet.
Customers consider a 3PL's information technology capabilities to be crucial to the
relationship, yet less than half are satisfied with their providers' capabilities (Bradley,
November 2005). Simply stated, customer demand is growing for a transportation
solution that combines outsourced technology with managed services (Gonzalez. A,
May 2006b; 4).
As can be seen, in order to compete in a complex and demanding market, that
outsourcing logistics to a 3PL and partnering with them is a must. It also seems that
an “integral part of this outsourced relationship is the effective implementation of
technology in order to access and organise information as quickly and correctly as
possible, as clearly a significant number of the obstacles to effective outsourcing are
primarily related to the simple mechanisms of sharing information and managing
access which a solution that alleviates even a small percentage of the cost and time
burden of outsourcing can deliver a substantial return on investment” (Arena
Solutions, 2006).
2.13 Summary and conclusion
Chapter two began by looking at the changing nature of customers who, because of
a growing level of education and knowledge, have begun to demand a higher level of
service at a reduced cost. In order to meet these demands, organisations are
constantly searching for new ways to improve their product and services; a search
which has led to the development and grown of the value chain.
The value chain encompasses all elements of an organisation that result in the
delivery of their product or service to the customer. In order to satisfy their
customers, organisations have quickly learnt that they can no longer focus solely on
the production of their core product alone: They now need to focus on the entire
value chain in order to provide their customer with a competitive product.
The primary activities of the value chain make up the supply chain and hence the
growth of the value chain led to the growth of the supply chain. The supply chain
consists of a bidirectional flow of product, information and finance between the
39
suppliers and final customer. In order to improve the value chain, it became clear that
a good place to start was by developing a more competent and competitive supply
chain.
In order to meet the demands of this complex business model adequately,
organisations have found that an optimal way of improving their offerings is by
focusing on their core product and outsourcing noncore elements of their
organisations.
The importance of good transport management in general, as well as the advantages
and disadvantages of outsourcing this vital link in the supply chain, is analysed. The
analysis concludes that often the best way to achieve efficient transport management
is to outsource an organisation’s transport needs, as transport is very seldom a core
component of an organisation.
The growth of the third party logistics provider is discussed and analysed. With 3PLs
becoming widely used and a vital element of the value chain, the relationship
between an organisation and a 3PL has become vital.
Chapter two concludes by explaining the need for a good relationship between
organisations and their 3 PL partners and the critical role software plays in achieving
it.
Recently, The Star newspaper reported that inefficiencies in the supply chain meant
fast-moving consumer goods’ manufacturers and retailers were losing R7 billion
every year, according to Brett Bowes. Bowes said investment in the supply chain was
too little too late and service to customers was declining (The Star newspaper, 16
March 2007; 2).
In chapter two, a number of different ways have been focused on as ways to improve
an organisation’s supply chain.
From the above discussion of the advantages and disadvantages of outsourcing, it
would seem that for many organisations operating in today’s competitive
environment, the advantages of outsourcing far outweigh the disadvantages.
Outsourcing certain noncore departments has almost become a must for
40
organisations wishing to stay afloat in today’s fast-paced, customer-driven economy.
In spite of the absolute need for outsourcing, choosing a 3PL to outsource to is a
difficult, time consuming and sometimes risky task. In order to choose the correct
business partner, an organisation must go through extensive research in order to
ensure their partner has the tools, resources and technology to support their part of
the agreement in the most optimal way.
When choosing a 3PL, an organisation needs to remember that in order to have a
successful relationship with the 3PL, the organisation will need to build a relationship
of communication, trust and shared strategising as opposed to having a simple, yet
ineffective transactional relationship with them.
The use of technology can help immensely with the strategic relationship between an
organisation and its 3PL. Chapter three will examine the historical development of
how and why technology became a tool utilised in the logistics industry. The following
chapter will look at technology and technologic systems that one needs to consider
when choosing a 3PL in order to ensure an optimal “logistical” relationship. The
dissertation will then go on to focus on routing and scheduling systems, specifically in
the 3PL environment and a few relevant case studies will be discussed.
In conclusion, it would seem from chapter two that choosing the right 3PL and
building a strong partnership with it through the use of technology is a must in order
to be able to compete in today’s competitive organisational environment.
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Chapter 3
3 TECHNOLOGY IN THE SUPPLY CHAIN
3.1 The initial use and growth of technology in the supply chain
The use of technology began in the logistics industry in the early 1980s (Frazelle, E.
2002; 170) as the rapid adoption of personal computing put supply chain information
and analysis tools in the hands of logistics managers. This meant that organisations
could begin to substitute information for inventory through the use of improved
forecasts, transportation schedules, scheduled receipts etc. Organisations could now
begin to manage information more effectively, and therefore reduce their large
quantities of stock. However, the true breakthrough in logistics technology
performance came when new ways were identified to substitute information for work
content. This was demonstrated in America in the early 1980s. It was during the
1980s that personal computers were slowly rolled out into organisations, enabling
logisticians real-time access to demand, supply, inventory and shipment information.
Access to the relevant information allowed logisticians to take advantage of powerful
optimisation tools which would optimise inventory management, network, routing and
transport optimisation and slotting optimisation in warehouses. Having these different
areas of the supply chain optimised, would allow for lower inventory levels and less
material handling throughout the supply chain (Frazelle, E. 2002; 170,276).
The logistics department was among the last to join the personal computer trend.
The main reason for this is that, in general, the logistics department had the tendency
to be pushed to the corporate back seat, and therefore, it was thought that it had no
need for such high-priced perks. However, as times have changed and the corporate
powers began to realise that the distribution department could save a sizable sum of
money by utilising the power of the computer, these departments have become
equipped with the latest technologies (Stroh, 2001, 101).
42
Below is a list of some of the many past and current organisational issues that can be
improved upon and often solved through the use of technology:
I. Customer satisfaction-Without the use of technology, customer
satisfaction is often very low as manual planning systems fail to meet
customer requirements such at delivery windows, on-time delivery,
delivering the product undamaged, efficient returns, etc.
II. Eroding profit margins-With profit margins becoming smaller, producers
are constantly looking at new ways of reducing costs in other departments
in their organisation in order to increase overall profit and the probability of
the continued existence of the organisation.
III. High cost of logistics-The logistics department was becoming a large
expense instead of being a support service to the organisation. In order to
reduce the costs of this department, technology was needed.
IV. Failure of achieving optimal results-Organisations were starting to realise
that their existing business benefits were not achieving optimally, and only
through streamlining of their business processes and systems would they
be able to maximise their profits and sales.
V. Existing technology could not support growth-Although many
organisations had been using technology in the past, it became evident
that existing technology could not support the desired and needed growth.
VI. Better reporting-The need for better reporting arose in order to allow
management to better understand and respond to what was happening in
their organisations
VII. Continual investment in computer software and hardware-An increase in
technology costs, with decreasing benefits of the technology deployed
became clear.
VIII. Need for transparency-As a result of inefficient and inaccurate reporting,
as well the fact that current systems were extremely complicated, very
technical and often manual, only a handful of selected employees could
fully understand and utilise the relevant systems. This put the organisation
43
at risk as the systems were vulnerable to the manipulation of these
employees.
IX. Globalisation-Globalisation and the development and growth of major
organisations called for systems that could handle more complex and
larger orders.
X. Competition-By utilising technology, an organisation can increase its
competitiveness through the reduction of its costs and improvement of its
service levels.
In general, the constantly increasing awareness of the cost and service impact of
transportation on the overall supply chain performance, has become the main cause
in the need for improved technology.
Although the above list covers some of the past reasons for implementing technology
into an organisation’s logistics department, a constantly changing organisational
environment is leading to a constantly growing list of reasons for the need for
technology.
Recently, logistics became more complex and the outsourcing of the logistics
department has led to the creation of the third party logistics provider (3PL). With the
growth of the 3PL, the need has arisen for systems which would enable clients to
have visibility of their loads, and see into the logistics networks of their 3PL enabling
them to keep track of their product as if they were transporting their products
themselves. This has brought about the need for technology to be developed, which
would allow the clients of a 3PL to see into the 3PL’s logistics networks, and hence
have the ability to deal with any issue that may arise in real time. One way in which
this may be possible is by the client being able to log onto a web page which details
the current status and location of the route along which their product is being
transported . A possible solution to this problem would be a web page, that links with
the 3PL’s planning system, which clients could then log onto to view the current
status of their delivery.
As can be seen from the following, organisations have begun to realise the critical
importance of implementing and upgrading technology and have thus begun doing
44
so. “Most companies are seeking to improve three dimensions: process, technology,
and organizational structure. Fully 91% of companies are concerned that their current
transportation management technology will not meet their future needs” (Aberdeen
Group, September 2006d; 5).
According to a survey done by Aberdeen Group in September 2006 where 173
manufacturers, distribution organisations and retailers were surveyed, 63% of
organisations felt that there was need to enhance their current technologies .This is
depicted in Figure 3.1.
Figure 3.1 Percentage of respondents whose management has r equested or
received a recommendation to improve transportation performance
in 2006
Source: Aberdeen Group, September 2006d; 5
As can be seen from the following quote, organisations are under growing pressure
to lower their costs and are starting to realise the only way this can be done is by
changing the ways they operate. “Supply chain organisations are under constant
intense pressure to meet demands for greater customer intimacy; lower cost of
goods sold, and increased global business processes”. In order to achieve the
desired results, these organisations have identified that they need to “change their
supply chain technology footprints by updating and re-engineering their technology in
the supply chain”(Aberdeen Group, May 2006b; 6).
45
3.2 Technology in the supply chain
As seen above, there is a clear move towards improving the supply chain in an
organisation.
The following are some of the many advantages and disadvantages of using
technology in supply chain operations:
3.2.1 Advantages of technology
I. Technology allows for paperless operations. This reduces the cost of
paper and printing and allows for all transactions to be properly recorded,
archived and reported on (Finn, 25 November 2002; 2).
II. Technology allows for real time communications through devices such as
the global positioning system (GPS), short message service (SMS),
electronic mail as well as the World Wide Web (WWW). This helps
organisations to deal with issues when they occur, not after they have
occurred.
III. Technology allows for system-driven activities as opposed to human-
driven activities. This results in a decrease in human error related
incidents and better keeping of business rules.
IV. Technology allows for more accurate and comprehensive data as data
can be better managed and analysed through the use of the appropriate
systems.
V. Technology allows for the support of value-added services.
VI. Technology allows for more visibility and control over one’s organisation
due to real time information, as well as user accountability. “Some
companies are surprised to discover what they are overlooking due to lack
of visibility into their processes. One Pivotal customer found that it had
shipped a number of orders for which it had not yet invoiced customers,
meaning money was being left on the table. The company only realised
this after automating its order capture, order processing, and order
fulfilment systems” (Pivotal Corporation, 2006; 5).
46
VII. Technology leads to more efficient operations by reducing costs and
allowing for more efficient processes.
VIII. Due to the ability to provide information in real time, technology allows for
improved customer responsiveness.
IX. Technology allows for better compliance of organisations’ rules and costs.
3.2.2 Disadvantages of technology
I. The use of technology often takes away the ability to perform tasks
manually. This means that at times when the technology is not able to be
used due to reasons such as system failure or power cuts, operations
come to a standstill. An organisation is then not able to operate, and
literally has to close its doors until the technology is up and running again.
II. Fewer people are needed to perform a larger number of tasks. With a high
unemployment rate in the world today, doing more with fewer people is not
necessarily the best for the world as a whole.
III. Due to the fact that technology allows for easier access to information, it
also allows for easier changing and modifying of information, which could
be to an organisation's disadvantage.
IV. Technology can often be very costly, which makes it harder for smaller
organisations to break into the marketplace.
V. Buying and implementing the wrong technology could lead to an
organisation’s downfall.
Business management technology gives small and medium enterprises an
advantage by automating the flow of information between departments and reducing
mistakes associated with the double-entry of information across systems, thus
creating a more efficient supply chain. A main objective in creating an efficient supply
chain is to reduce costs; however, another objective of successful supply chain
management is to meet customer requirements and needs. Today's customers
expect the same experience and efficiency, whether they are dealing with a small,
medium or a large organisation. “The Internet has made customers less patient and
47
forgiving about problems with transactions, deliveries, orders and customer service”
(Jani, 2006). It is crucial for small and medium organisations to develop a flowing and
efficient supply chain in order to provide improved quality and improved customer
responsiveness. “Business management software allows small and medium
enterprises to better serve their customers by having instant access to information
regarding their order, status of shipping and payment information. Business
management software provides small and medium enterprises with real-time
information, which reduces response time to customers, and ensures faster order
fulfilment and extended service” (Ibid).
The true value of utilising the power of the computer in the distribution department
can only be properly understood by understanding the large percentage that
transport costs occupy in the supply chain. Transportation is the most expensive
logistics activity, representing over 40% of most organisations’ logistics expense, and
amounts to over $400 billion in annual expenses in America alone. Global
transportation expenditures exceed $two trillion annually (Michigan State
University; 1).
According to Frazelle, transportation expenses are rising disproportionately versus
other logistics costs, as a result of smaller, more frequent orders, increasing
international trade and global logistics, rising fuel charges, labour shortages,
decreased carrier competition due to tier mergers and acquisitions, and increased
union penetration in the labour market. These cost increases can be seen by the
increase in American logistics costs in relation to gross national profit (GNP).
“Reducing transport-costs while maintaining and improving customer service levels
and levering private and third-party transportation systems caused the need for some
serious technology to be developed in the supply chain” (Frazelle , E . 2002; 169).
3.2.3 Insight into the future of technology from top industry analysts
In this section top industry analysts share insight into the future of the technology
which they say has become central to driving down transportation costs, and are
indispensable in establishing global logistics plans (Levans, May 1, 2007). According
to Gonzalez, freight payment is an area where many organisations are focusing on to
reduce cost. “Many companies are looking to implement a self-invoicing process,
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whereby the shipper pays the carrier the rate in the transport management system,
including known surcharges and accessories upon receiving the proof of delivery.
This shifts the audit process to the carrier: a trade-off many carriers are happy to
accept in return for getting paid thirty or more days faster. It improves their cash flow,
and the shipper eliminates all of the overheads involved in auditing and processing
freight invoices” (Adrian Gonzalez as cited in Levans, May 1, 2007).
Enslow is of the opinion that “Rising freight costs are clearly the top pressure driving
companies’ renewed focus on transportation, procurement and payment. In 2007,
with freight rates starting to soften for some transportation modes, the majority of
companies believe this is a great time to review their procurement and freight audit
and payment practices and technology. Companies believe they can save an
average of 8.8 percent on their overall freight budget with more sophistication, and
this is backed up by industry’s Best-in-Class results. Companies are focusing on
reducing manual payment processes and enhancing online collaboration with carriers
for invoice exception handling. The savings comes both from avoiding overpayment
on shipments as well as creating freight spend reports that can be used by
procurement for spend analysis and bid preparation activity. This can help the
company negotiate better rates and more favourable accessorial charges” (Beth
Enslow as cited by Levans, May 1, 2007). As can be seen above, automating one’s
payment procedures can assist in reducing transportation costs.
According to Levans, an aspect many organisations is starting to focus on in order to
reduce costs, is centralising transport procurement and payment. Through the
centralisation of procurement and payment, the right transport modes and hauliers
are chosen, and they are paid the correct amount. “A vital but often overlooked
benefit is that accurate cost allocation information from a freight payment system can
prevent a ripple effect of improper decisions in pricing, product investment strategies,
distribution network design, and sourcing strategies. In transportation the most
important action for companies to take is to centralise transportation procurement.
Companies overwhelmingly cite centralization as having the greatest impact on their
ability to reduce transportation costs. Technology helps arm you with better data and
analysis so you gain that next level of savings. In the next twenty-four months, fully
81 percent of companies with freight spend over $25 million plan to implement new
49
transportation procurement or payment technology, as well as 44 percent of
companies with spend under $25 million. Best-in-Class companies have successfully
reduced their freight rates an average of 8 percent, and they are more likely than
their peers to be using procurement and payment technology already. Expenses
have become a greater percentage of the cost of goods, accurate costing is crucial”
(Levans, May 1, 2007).
3.2.4 Challenges when choosing and implementing technology
Organisations should remember that implementing technology is not the answer to all
their problems. Organisations have to implement the correct technology to achieve
real benefit, and the technology has to be used in the correct way. For example: Due
to the fact that information workers often rely on e-mail to perform their work,
processes can prove frustrating and it can take longer than necessary to finish a task
(Microsoft and SAP White Paper, 2006; 5). As a result of e-mail being so common,
inexpensive and user friendly, it is often used instead of more complex and
organisation-specific systems; this leads to overall inefficiency because optimal
enterprise resource planning (ERP) systems are not being fully utilised, and the re-
entering of data across different formats leads to typing and other errors.
Technology will only help improve an organisation if it has the buy-in of all the
relevant managers and users, as technology is only useful when the correct
information is fed into the system in a timely and accurate manner. Without the flow
of the correct information, it becomes extremely difficult to monitor the supply chain
activities. The bidirectional flow of information is imperative for the success of supply
chain strategies. "There is no advantage in being choosy while exchanging
information. The ability to share information by itself is a competitive differentiator"
(Ram Moham; 21December 2006; 1). Organisations need to fully understand the
value of having and sharing information with the use of technology before any
improvements can be achieved.
According to the Hitachi Data Systems Corporation, choosing technology or a
combination of technologies to support business continuity starts with an assessment
of the potential risks facing an organisation. An operational risk management
approach will clarify business requirements and reduce uncertainty by estimating the
50
likelihood of potential loss that could occur if the wrong technology is implemented, or
if the technology is not implemented correctly and efficiently. By performing an
operational risk analysis for each business-critical application, an organisation will be
able to determine the extent of vulnerability and the impact on business downtime
that the new technology will have. With this information in hand, one can access the
technologies to achieve the optimal balance of recovery speed, data value and cost.
Two key metrics used for organisation continuity planning are recovery-time objective
and recovery-point objective. Recovery-time objective measures how long it takes to
resume essential operations and how long it takes to get back on your feet.
Recovery-point objective is a measure of data currency, how far behind the
organisation can afford to be when resuming operations after a disruption. An
organisation’s recovery-time objective and recovery-point objective determine which
data replication and recovery options the organisations need, and how much the
solution will cost (Hitachi Data Systems Corporation, January 2006).
Implementing technology into an organisation is a large and challenging undertaking.
The following are a number of ideas from the Aberdeen Group which an organisation
can utilise to help ensure a smooth implementation of the desired technology:
• start early; get a jump on your competition
• understand your objectives
• pick the right partners
• don’t “self-integrate” unless you happen to be a data integration
specialist
• your information architecture will make or break the long-term return on
investment(ROI)
• run a pilot. It is easy to miscalculate during the design process or
underestimate the costs. A validation exercise greatly reduces the time
to ROI
• test “what-ifs?”
• look beyond compliance
(Aberdeen Group, 2006c)
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3.2.5 General benefits of technology
According to the Pivotal Corporation, the use of technology allows organisations to
keep a continuous record of the start and end dates of haulier contracts, as well as
income. Using this information, a system can automatically create a new alert for the
organisation a few months before the contract ends, and assigns it to the relevant
personnel to follow-up and re-negotiate if needed (Pivotal Corporation, 2006; 5).
Adrian Gonzaletz expressed that by using technology fewer resources are required,
or they can be assigned to more value-added activities by automating many of the
processes currently performed via telephone or fax, including such activities as order
status confirmation, getting quotes for shipments and appointment booking. Utilising
technology also enables better planning at the receiving warehouse, which minimises
the number of resources required to process deliveries. Poor visibility of the status of
orders and shipments creates uncertainty which organisations typically offset by
carrying safety stock. Knowing exactly when an order will arrive, enables
organisations to plan and respond to changes more efficiently. It also allows them to
reduce safety stock, thus reducing the amount of warehousing space needed
(Gonzalez, 2006a; 8).
Another benefit of utilising technology is speed: Through the use of technology the
time it takes from the time your product or service is sold, till the time the revenue for
the product or service is collected, is reduced. Today organisations need to tighten
their budgets to compete in a constantly developing business environment. Reducing
the time it takes to transfer a customer order into money in the bank, offers strategic
benefits to organisations and creates more rewarding customer service. Using a
manual process to coordinate the “order to cash ” operation, creates the potential for
costly errors, as well as the fact that manual processes are labour intensive and time
consuming, and require valuable resources to manage each part of the process
(Esker document delivery 2006; 3, 2).
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Figure 3.2 Ordering process
Source: Esker document delivery 2006; 3
If an organisation uses manual processes, each invoice must be sorted, evaluated,
sent to the correct department, processed and eventually filed away and stored. It is
this process which is the reason why utilising manual invoices is so time-consuming
and prone to mistakes. When issues arise, the manual invoices need to be retrieved,
and only then can the issue be dealt with.
Conventional invoice processing affects organisations operating efficiency due to:
• limited ability to collect cash quickly
• low staff efficiency rates
• high cost to maintain machines for printing, faxing, folding and posting
• high costs to produce, store, archive and retrieve physical invoices
• high level of errors and issues due to the high volumes of manual
invoices
There is also the potential to cause huge inefficiencies such as invoice disputes.
“This occurs when disputes occur over what service was provided, or what amount
was negotiated for that service. All of this can be avoided through automating the
invoice process” (Esker document delivery 2006; 4). ”For organisations looking to
decrease their budgets, the order to cash process can yield significant savings to the
bottom line of more than 70% of costs accumulating from labour, supplies and errors”
(Ibid; 14).
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3.2.6 Five Best Practices of World-Class Companies
According to Hackett's 2006 Enterprise Book of Numbers, "2006 World-Class
Metrics”, the 5 Best Practices of World-Class Companies are:
I. Strategic Alignment. One typical mistake procurement executives often
make is to operate their organisation in a silo. Departments need to work
as part of the entire business’ units, not just as individual departments.
II. Cross-Functional Partnering: This includes high-quality partnering initiatives
across the supply chain, in both directions.
III. Complexity Reduction: In order to maintain process and systems, things need to
be kept simple, the more complex a process or system is, the more likely it is to
fail.
IV. Technology Enablement: Leverage technologies to increase efficiency and
effectiveness of a business.
V. Business Process Sourcing: Strategic sourcing will bring down costs and improve
product quality.
(Hackett as cited in Supply and Demand Executive, 2 January 2007)
In practice, Hackett addresses the importance of technology in developing a world-
class organisation. Hence without the use of technology in an organisation, it will fall
short when it comes to competing with other world-class organisations. Technology
has become more that a nice thing to have to improve an organisation; it has become
a must to compete.
Different technologies have different aims they can achieve. Organisations must
decide what aims they have when implementing technology. According to a study
done by the Aberdeen Group, two-thirds of organisations looking to improve
transportation management through technology, say that a top goal is to achieve
advanced shipment visibility that includes status, estimated time of arrival, alerts, and
resolution workflow. Another 11% say that basic shipment tracking and tracing is a
priority (AberdeenGroup, May 2006c).
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The following graph shows the results of a survey done by Aberdeen Group in
September 2006 where 173 manufactures, distribution organisations and retailers
were surveyed. As can be seen from the graph, 66% of respondents feel that
improving their advanced shipment visibility is a priority.
Figure 3.3 Transportation management priorities when choosing technology
Source: AberdeenGroup, September 2006c
3.2.7 Guidelines alerting an organisation that the implementation of technology is
overdue
With the need for, and benefits of technology apparent, each organisation needs to
perform an analysis to see whether it is in need of new technology. According to the
Aberdeen Group, the following guidelines will alert an organisation to the fact that the
implementation of new technology is overdue (AberdeenGroup, May 2006a):
• Inefficiencies in the supply chain
• Insufficient systems to handle the growth of the business
• Major change in operating requirements
• Technology infrastructure obsolescence
• Demanding compliance requirements
Organisations “that have yet to prioritise process automation with suppliers or
customers or that do not have a clear game plan for sense and respond capabilities
55
that link real-time visibility with supply chain execution and planning should be put on
notice by the above guidelines” (AberdeenGroup, May 2006a).
3.2.8 Different technologies in the supply chain
It has previously been discussed when and why companies started using technology
in their supply chain. In the following pages, various technologies that have been
developed and implemented into supply chains are going to be discussed.
According to Frazelle, an organisation may need a customer response system
(CRS), an Inventory Management System (IMS), a Supply Management System
(SMS), a Transportation Management System (TMS), and a Warehouse
Management System (WMS) to execute their logistics needs (Frazelle, E. 2002;
278). These modules working in unison are called the execution layer of a Logistics
Information System (LIS) or the Logistics Execution System (LES). The
Transportation Management System (TMS) and Warehouse Management System
(WMS) modules are often referred to as Logistics or Supply Chain Execution
Systems (SCES). To plan customer response, an organisation may need a Customer
Response Planning System (CRPS), an Inventory Planning System (IPS), a Supply
Planning System (SPS), a Transportation Planning System (TPS) and a Warehouse
Planning System (WPS). These planning systems are jointly called a Logistics
Planning System (LPS). An even higher level planning system that may or may not
make use of information from the LPS, is a supply chain or Advanced Planning
System (APS).All the above modules often either form part of the organisation’s
Enterprise Recourse Planning (ERP) system, or integrate in some way with the
organisations ERP system. Below is a visual diagram of the systems discussed
above.
56
Figure 3.4 Uses of technology in the logistics field
Source: Frazelle, E. 2002; 278
A successful organisation will utilise an ERP system that extends outside its own
boundaries and collaborates with its suppliers. It is essential for the ERP system to
posses the agility to support continuous improvement in all areas of the supply chain
relationships (Information Global Solutions, 2005).
It has been discussed previously that real breakthroughs in logistics are achieved
when new ways are found to substitute information for inventory and work content. It
then follows that a tool that enables greater access to logistics information than has
previously been experienced, would receive a speedy implementation, that tool being
the Internet. The Internet is enabling many organisations to manage global logistics
networks and operations through the use of Web-enabled applications (Stock, J. R. &
Lambert, D. S. 2001; 566).
In order to comprehend the speed of adoption of the Internet, the following should be
considered: It took 38 years for radio to reach 50 million users, 13 years for TV, 10
years for cable, and five years for the Internet (Gabay, 2000). “In 1970, 5 percent of
the U.S. economy was agrarian, 10 percent electronic and 85 percent industrial. In
2000, two percent of the U.S. economy was agrarian, 38 percent was electronic, and
60 percent industrial. In 1998, 8 percent of all purchase orders were placed via the
Internet; in 2000, 40 percent of all purchase orders were placed via the Internet.
57
150,000 organisations trading more than $1.8 trillion per year are expected to
participate in Web-based supply chain exchanges in 2001. Transportation bookings
over the Internet are expected to increase by 80 percent per year for next few years”
(Frazelle, E, 2002; 287).
One organisation that has taken advantage of this growth in Internet usage, is
RockPort Trade Systems. The organisation developed a sophisticated client-server
system, called RockWeb that is designed to manage integrated supply chain needs
such as global sourcing, purchasing, financials and logistics.
According to an article in Global Logistics and Supply Chain Strategies (as cited by
Stock, J. R. & Lambert, D. S. 2001; 566), "In far flung and undeveloped nations or in
a company that wants to minimise its outlay on information technology the benefits of
the Internet are many. Vendors can be informed of purchase orders, production
dates can be changed, notices of letters of credit can be sent, receipt of raw
materials can be acknowledged, and forms and invoices can be printed, all without
spending a bundle on technology”.
Federal Express has been one of the most successful organisations in applying
Internet technologies to customer needs. Of the 1.2 billion customer transactions
processed each year by Federal Express, 800 million are handled through their
website. Federal Express estimates that without their Internet enabled customer
service ability, they would require more than 22,000 additional customer service
representatives (Frazelle, E. 2002; 289). The advantage of using the Internet is that
organisations wanting to participate, do not have to invest in the often very expensive
technology to be Electronic Data Interchange (EDI) enabled, and can still benefit
from the latest EDI benefits. An example of such software is OPSI systems software
Plato, where 3PL organisations get notified about loads and accept loads via a
secure web page, and all they need is a basic Internet connection and the ability to
use very basic aspects of the Internet.
In order to benefit from digital and real-time logistics technology, a set of devices is
needed. These devices, which are the basis of the integrated logistics information
systems, are essential for processes from data collection through to communication.
This set of devices is constantly changing and being upgraded as technology
58
progresses. To support paperless logistics, it is important to have a way to
automatically identify a logistics object (eg: a container, crate or box), after the object
is identified the relevant information needs to be communicated to a logistics
operator. This is achieved automatically through the following technologies:
I. Automatic identification technologies, such as bar codes and bar code
scanners, radio frequency tags, smart cards and magnetic strips
II. Automatic communication and presentation technologies such as radio
frequency data communications
(Wikipedia, 2007b; Frazelle, E. 2002; 289)
Up to this point, chapter three has explained the need for different software systems
to be implemented into the supply chain. It has also focused on technology in the
broader supply chain, however, owing to the fact that the supply chain is so vast and
it would be impossible to discuss the entire supply chain in detail, the chapter now
begins to concentrate on a more specific aspect of the supply chain, that being
routing and scheduling and the procurement and payment of the relevant hauliers.
Although there is an abundance of technology in the supply chain, this dissertation is
going to focus on technologies directly involved in transport management. The
objective of this dissertation is to investigate whether the implementation of a state of
the art routing, scheduling and haulier management system into Clover Logistics
have achieved real benefits and improved the bottom line of the organisation. Before
starting to investigate Clover Logistics, it is important to first understand the
underlying principles and benefits of routing and scheduling, including how it works
and from where the savings are achieved.
3.3 Vehicle routing and scheduling
3.3.1 The problem statement
As Frazelle describes, every mother is familiar with the routing and scheduling
problem as a result of needing to plan the most efficient route to do her child’s lift
scheme, or from having to plan her morning shopping route. Many people use some
sort of routing and scheduling in their daily lives, such as the travelling sales or
59
service man, the taxi and bus company and even the ice cream truck. Many people
who have tried to plan efficient routes for holiday trips or running errands, are familiar
with the challenges of planning to avoid known traffic congestion areas, planning in
order to visit the locations in a logical sequence, such as making the grocery store
the last stop so the ice will not melt on the way home, and working all of this against
a deadline getting home in time to cook supper or to watch the day’s sports match on
TV. “The same challenges crop up in industrial settings, where efficient versus
inefficient routing can save millions of dollars in fuel, labour, capital expenditures and
significantly enhance customer service” (Frazelle, E. 2002;198;)(Jacobs-Blecha ,
Goetschalchx , 1998;1 ).
According to Frazelle the objective and constraints of the average commercial
vehicle routing and scheduling case would be the following:
The objectives are to reduce the following:
• total route costs (fuel, labour, equipment, freight, fleet, maintenance,
insurance, loading/unloading, demurrage/detention, taxes/tolls, and
international fees)
• number of routes (to minimise the number of required vehicles and
personnel)
• total distance travelled
• total route time
The constraints of the vehicle routing problem include the following:
• Customer response time requirements and time windows (specified
times at which the vehicle must arrive after and depart before).
• Route balancing (so that not one vehicle or driver has a disproportionate
share of the work).
• Maximum route times (for example, limiting the driving time of a truck
driver or the flight time of a pilot).
• Vehicle capacities (limiting the amount of material assigned to a vehicle
by the vehicle's mass and cubic capacity).
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• Start and stop points (ensuring that the vehicles start and stop at
locations such as a home depot).
• Transportation infrastructure constraints (rates of speed and
transportation volumes along roads may not exceed specified speeds or
volumes).
• Workforce capacities (restrictions on consecutive operating hours or
lifting).
(Desrochers, Jones, Lenstra, Savelsbergh, Stougie, 4 November 1998;
Frazelle, E. 2002; 200)
Considering the significant capital investments in equipment and facilities, along with
operating expenses, 3PLs for numerous years have recognised the importance of
good routing and scheduling in achieving satisfactory levels of customer service and
reducing costs. Due to the complexity of the routing and scheduling process in cases
where many vehicles, customers, and routing combinations exist, technology is often
used to determine optimal routes and schedules.
“Routing problems are computationally some of the most difficult encountered in
mathematics. In fact, they are one of a class of problems that is not solvable to
optimality in a less than infinite time. As a result, programs normally employ one or
more heuristics in solving a routing problem. The heuristics are utilised in the
background of the major routing software packages available on the market”
(Frazelle, E. 2002; 200). “Ideally, the routing solutions should be developed
automatically and manually adjusted for anomalies. In addition, the capability to
dynamically reroute a vehicle should be incorporated in the chosen routing solution”
(Ibid).
In a 3 PL organisation, as well as for organisations operating in-house fleets, through
good routing and scheduling decisions sizable benefits can be achieved. For
example, vehicle load utilisation can be increased while simultaneously reducing the
frequency of deliveries to a specific area .The reduction in the frequency of pick-ups
and deliveries can result in a reduction in the amount of transportation required to
deliver the same amount of goods. This allows for the transportation costs to be
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reduced, while at the same time for productivity to be increased. If customers can
accept deliveries at off-peak hours, the 3PL will have a larger delivery-time window,
and will improve vehicle use and reduce the costs per delivery. In general, the
benefits to a 3PL of improved routing and scheduling include greater vehicle use,
improved customer service, lower transportation costs, less capital investment in
equipment, and better decision-making capability. As an example “Baskin-Robbins,
an ice-cream manufacturer with 2,500 stores in the United States, computerised its
fleet routing and scheduling. The result was a ten percent reduction in truck fleet
miles, equaling an annual cost saving of $180,000” (Stock, J. R. & Lambert, D. S.
2001; 367).
3.3.2 The routing and scheduling problem
In general, the vehicle routing and scheduling problem can be defined as follows: A
fleet of vehicles usually based at a particular depot (as opposed to swapping
between depots), deliver and/or collect (eg: empty beer bottles) products to and from
a customer. Each customer has delivery constraints of which a designated time
window when the vehicle is able to deliver to its store, is often the main constraint.
Although there may be a broad time window (such as 08:00 till17:00), the customer
may want to know what time the delivery is arriving. Other times though, the
customer may be open the entire day, they may only accept deliveries at a particular
time such as between 08:00 and 10:00 and deliveries arriving after 10:00 will not be
accepted. “For example, in the case of collecting goods, vehicles depart from the
depot and visit a subset of customers to pick up goods in sequence and return to the
depot to unload them. A vehicle is allowed to make multiple routes per day. Each
customer must be assigned to exactly one route of a vehicle and all the goods from
each customer must be loaded on the vehicle at the same time. The total weight of
the goods for a route must not exceed the capacity of the vehicle. The problem is to
determine the optimal assignment of vehicles to customers and the departure time as
well as the order of visiting customers for a freight carrier. Vehicle routing and
scheduling problem with time window explicitly incorporates the departure time of
vehicles as a variable to be determined” (Frazelle, E., 2002; 200; Zhong, Cole, 6 May
2004).
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Figure 3.5 An example of a vehicle routing problem
2
3
4
5
6
7
8
Depot
Truck 2
Truck 1
1
2
3
4
5
6
7
8
Depot
Truck 2
Truck 1
1
Source: Taniguchi, Thompson, Yamada, Van Duin, 2001, 138
The diagram above demonstrates a simple example of a vehicle routing and
scheduling problem. In the example in the diagram above, there are 5 trucks
available and they need to make 8 deliveries in a particular day. There are numerous
different options in which the deliveries can be made such as:
• All five vehicles can be used with three vehicles doing two drops and two
vehicles doing one drop each. This is the most expensive due to the fact
that five sets of drivers and crew have to be employed.
• Three vehicles can be used with vehicle one doing stop one, two and
three, vehicle two doing stop four, five and six and vehicle three doing
stop seven and eight.
• Two vehicles can be used with vehicle one doing stop one, two and
three, and vehicle two doing stop four, five, six ,seven and eight.
There are numerous different scenarios of how the five vehicles can make the eight
deliveries. According to Taniguchi, Thompson, Yamada, Van Duin ( 2001, 138), the
optimal solution is for the carrier to use two trucks out of the five trucks available to
visit eight customers in the order shown as seen in figure 3.5.
As mentioned diagram 3.5 is a simple example. In reality an organisation needs to
take into account the additional points that make the vehicle routing and scheduling
problem more realistic.
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• Each customer has a time window in which the delivery has to be made
(this time window may be extremely tight and arriving late may mean the
loss of the order, or the holding up of production).
• There may be multiple depots.
• Travel times vary dynamically (eg. when planning, an organisation needs
to take traffic and road speed and condition into account).
Various different routing and scheduling problems may occur. The following are
some of the factors, constraints and objectives that can create different routing and
scheduling problems:
I. Does the vehicle need to deliver or collect a product or does the vehicle
need to deliver and collect products at the same time, such as in the case
of a brewery where beer is delivered and “empties” are collected at the
same time? If there is a conflict between deliveries and collections, which
one takes preference?
II. Are the vehicles based at a single depot, or are there numerous depots
from which deliveries can be made? If there are numerous depots, can
vehicles depart from one deport and return to another depot at the end of
the day?
III. Is the number of vehicles fixed or variable? Often organisations are able to
hire in extra vehicles if needed on a particular day. Do different vehicles in
the fleet have different operating costs and speeds?
IV. How do the drivers get paid? Do they have a fixed salary or are they paid
per hour? Is driver overtime allowed, and if so, is it cost effective to allow
drivers to work excessive overtime? Are drivers allowed to do multiple trips
on the same day?
V. Are all the orders placed the day before delivery in order to allow for
proper routing, or are orders that need to be delivered the same day
accepted throughout the day? Most organisations stop taking orders 12-24
hours before delivery in order to allow the routes to be scheduled and
products to be packed. However, some organisations take orders and
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deliver them on the same day, making planning of the routes a lot more
complicated.
VI. Do customers have predefined say and/or time in which they have to be
visited on a regular basis, or are customers visited whenever they place
an order?
(Mckinnon, Button, Nijkamp, 2002, 283).
3.3.3 The importance of time windows
As a result of a more demanding customer, it has become a common requirement for
delivery vehicles to arrive at customers within specified time windows for delivery and
collections in the manufacturing and retail sectors. A survey in Osaka and Kobe in
Japan (Traffic Planning Council for Kyoto, Osaka and Kobe Area, 1997), “found that
freight carriers were required to operate with designated arrival times or time
windows for 52% of goods delivered and for 45% of goods collected in terms of
weight”. Such strict time windows have led to smaller loads of goods being
transported more frequently. Using simple logic, it is easy to understand that smaller
loads more frequently are far more optimal for the organisation receiving the product
due to savings in inventory storage costs, insurance and other related costs. Smaller,
more frequent deliveries however have a drastic negative effect on transport costs
and transport planning. As a result of smaller more frequent loads, the reliability of
goods delivery has become critical and has resulted in Just In Time (JIT) transport
systems (Taniguchi, Thompson, Yamada, Van Duin, 2001, 138). According to Keith
Heggie from Haulcon, a 3PL specialising in bulk dry product, delivering cement late
to a dam construction site can cost the construction company millions of rands an
hour as a result of having a large amount of manpower and expensive machinery
sitting idle (Heggie, 3 December 2007).
As discussed above, it is important to deliver products while keeping to customer
constraints. The effects of relaxing the time windows are seen in the following two
case studies.
In the first study, the width of the time windows is set at four levels: one hour wide,
two hours wide, four hours wide and eight hours wide (these widows were arbitrarily
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chosen to illustrate the importance of time windows). A large reduction in total cost,
total travel time and the required number of trucks occurred as a result of the width of
the time windows being increased. As the width of time windows increased the total
cost, total travel time and the required number of trucks decreased. For example,
“when comparing the costs where the width of time window is only one hour with that
of four hours, the total operating costs and total travel time were reduced by 13 %
and 9 % respectively” (Taniguchi, Thompson, Yamada, Van Duin, 2001). This study
also concluded that the “total waiting time at customers decreased from 29.4 to 0
minutes when the width of the time window was extended from one hour to three
hours” (Ibid).
The second study was done for the Plascon Paints, Roodepoort Depot in South
Africa. According to Brian Sher Logistics Executive at Plascon Paints (Sher, 28
February 2008), customers often want their paint delivered before 08:00 in the
morning. This resulted in Plascon using on average 15-20 vehicles a day to meet its
customer constraints. The study concluded that if Plascon could negotiate with its
customers to extend its delivery times till 09:00 in the morning, it would result in a
saving of three to five vehicles a day.
From these studies it can be concluded that the width of time window at customers
considerably affects the performance of vehicle routing and scheduling. Broader
customer constraints do not only reduce the operating costs of the organisation, but
also provide many benefits for society at large due to the reduction in travel time
resulting in a reduction in traffic congestion and pollution. The reduction in waiting
time also has a positive effect on traffic flow, since waiting trucks often disturb traffic
flow by occupying roadside space alongside the customer’s premises. In order for a
route planning system to accommodate the true needs of customers, it needs to be
able to route vehicles according to jobs with small time windows. This is due to the
fact that it is very common in today’s business environment for customers,
particularly large retailling stores to demand on time delivery within a particular time
window. Although there is a growing trend among customers to demand delivery
within a tight time window, it is important to quantify the effects of increasing the
width of time windows on the total delivery costs and the number of trucks required.
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This information may provide logistics providers and customers with an incentive to
relax the tight time windows (Taniguchi, Thompson, Yamada, Van Duin, 2001).
3.3.4 Manual routing and scheduling techniques
In the past, personnel in the logistics department would schedule using the
pigeonhole technique. This technique required the scheduler to take the physical
waybills or invoices to be delivered, and place them in a pigeonhole according to the
area that it needed to be delivered to. The quantities of all the invoices in each
pigeon hole would then be added up to make up a truckload. If they were less that a
truck-load, the truck would be dispatched, though not full. If the quantities added up
to more than a truckload, some of them would be taken out and delivered the next
day. Not only did this method disallow deliveries across area regions, it also often did
not give the driver an indication of which order he should do the drops in, hence,
drivers had to plan their own drop order. Although this method did its job of getting
the product to the customer, it certainly did not do it in the optimal way. Overloading
of the vehicles, late deliveries, not delivering to all of the customers assigned to a
vehicle, etc. were common occurrences. Another issue with the pigeonhole technique
is that it relied on the geographical and customer knowledge of the person dividing
up the orders. This inherent geographical and customer knowledge can take years to
acquire and is very difficult to pass on to another employee.
Another issue with manual scheduling includes the inability to consolidate shipments.
With manual routing and scheduling it is not uncommon for a supplier who has
placed two separate orders, to receive two separate delivers in one day. However in
order to reduce costs, these two orders should have been consolidated into one truck
and delivered simultaneously (Gonzalez,2006a; 8).
It is important to note that for smaller organisations running fleets less than
approximately nine vehicles, routing and scheduling software would not necessarily
improve their efficiency enough to justify the cost of such software, and manual
techniques such as the pigeonhole method would be an appropriate method of
scheduling their vehicles (Lubinsky, D; 26 June 2006).
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Through the use of software, many factors can be taken into account in a matter of
minutes, producing a solution that follows all the business rules and producing the
most cost-effective route. These calculations are done through the use of complex
algorithms that take all the many different factors into account.
3.3.5 Benefits of good routing and scheduling
According to David Lubinsky of Opsi systems, the typical payback calculation of a
routing and scheduling system can be calculated as follows (Lubinsky; 1 February
2007). Consider an average, mid-sized business with 30 vehicles at an average cost
of R18 000 per vehicle per month (including the driver). On average, with the correct
use of routing and scheduling software, it can be assumed that an average cost
savings of 15% will be achieved. This converts to a reduction of 4 vehicles, meaning
a cost savings of R72 000 per month and R864 000 per year. This cost saving is far
more than the costs of implementing the routing and scheduling software, as well as
the relevant annual software license fees.
Although the underlying and desired benefit of efficient routing and scheduling is
financial, there are many other benefits which include the following:
• Improved customer service. Through the use of efficient routing and
scheduling, customer constrains such as delivery windows and vehicles
exclusions can be better adhered to.
• Lower stock levels. Through the use of efficient routing and scheduling,
customers can rely on their supplier to deliver when promised. This
means that customers can keep a lower amount of safety stock.
• Lower personnel requirements. Utilising technology, allows a computer
operated by one person to schedule and monitor tens of vehicles in a
matter of a couple of hours a day, a task that would take numerous
people their entire day to do if done manually.
• Improved stock control. The result of improved reporting on what needs
to be delivered and what has been delivered.
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3.3.6 Effects of routing and scheduling on the environment
However, the effects of efficient routing and scheduling go far beyond financial costs.
This can be seen in a study that was conducted on the effects of an advanced
routing and scheduling system on road traffic. Three cases of differing advanced
routing and scheduling system penetration rates were considered:
• 0% No routing and scheduling was used.
• 50% Vehicles were routed 50% optimally.
• 100% Vehicles were routed 100% optimally.
In the study, five 3PLs introduced advanced routing and scheduling systems. The
demand for freight transport at each customer was increased to one and a half and
two times the base case, as can be seen in figure 3.6. The amount of emitted carbon
dioxide (CO2) was calculated using an estimation of the average travel speed of
vehicles on different road segments and established associated fuel consumption.
Figure 3.6 shows the effects of an advanced routing and scheduling system on CO2
emissions. As can be seen, CO2 emissions are drastically reduced when routing and
scheduling is optimally used (Taniguchi, Thompson, Yamada, Van Duin, 2001; 128).
Figure 3.6 The effects of an advanced routing and schedulin g system on CO 2
emissions
1.6 1.8 2 2.21
400
350
300
250
200
150
100
CO2 emissionsby trucks(kg/day)
Normalised demand for freight transport
1.2 1.4
Penetration rate = 0%Penetration rate = 100%Penetration rate = 50%
1.6 1.8 2 2.21
400
350
300
250
200
150
100
CO2 emissionsby trucks(kg/day)
Normalised demand for freight transport
1.2 1.4 1.6 1.8 2 2.21
400
350
300
250
200
150
100
CO2 emissionsby trucks(kg/day)
Normalised demand for freight transport
1.2 1.4
Penetration rate = 0%Penetration rate = 100%Penetration rate = 50%
Penetration rate = 0%Penetration rate = 100%Penetration rate = 50%
Source: Taniguchi, Thompson, Yamada, Van Duin, 2001;128
As discussed previously, the benefits of efficient routing and scheduling are not just
financial. Below is a short case study on how United Parcel Service (UPS) has been
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able to decrease the amount of CO2 its trucks emit by simply routing their trucks to
avoid making left turns.
“In 2004, United Parcel Service (UPS) announced that its drivers would avoid making
left turns. The time spent idling while waiting to turn against oncoming traffic burns
fuel and costs millions each year” (Sayre, C. 2007). United Parcel Service has
implemented a software programme that designs a customised route for every driver
in order to minimise left turns. By eliminating left turns, United Parcel Service has
reduced CO2 emissions by 1,000 metric tons in metro New York alone since January.
“Today 83% of UPS facilities are heading in the right direction; within two years, the
policy will be adopted nationwide” (Sayre, C, 2007).
3.4 Case studies of where technology has been implemented into the supply
chain and the results thereof
This chapter has gone into great detail explaining the need for technology in the
supply chain and the proposed benefit once it has been implemented. However, one
cannot truly comprehend how great the benefit is without seeing examples of where
technology has been implemented into the supply chain, with the resulting benefit.
Below are numerous case studies from a wide range of different market sectors,
where technology has been implemented into the supply chain and has had an
extremely positive result.
3.4.1 General case studies
I. Case study – Hudson’s Bay Co.
Hudson's Bay Co. operates 102 department stores. In 1991 they decided to
implement Quadrupole Resonance (QR) technology into their supply chain in order to
reduce their costs and improve their service.
According to Peggy Macek, director of merchandise systems at Hudson's Bay Co.,
getting their suppliers to buy into and comply with Hudson's Bay Co’s new
requirements, was a challenging task which involved many months of working in
collaboration with their suppliers in order to better their understanding of the new
processes. Although some suppliers fought what was required of them by Hudson's
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Bay Co. as a result of Hudson's Bay Co. being the largest retailer in Canada,
eventually they had to accept the change and do what we required of them.
With the new process suppliers are required to price all their products and supply all
their products on Hudson’s Bay Co. standardised hangers. This has allowed for
boxes to be moved through the Hudson's Bay Co. warehouse without having to be
opened at all, saving valuable time in getting the latest products to the store.
"We're saving millions of dollars in distribution functions," reports Macek. "We used to
have five distribution centers. Now, because of the technology that's been
implemented and the speed with which we can push goods through the pipeline, we
were able to shut down three distribution centers" (Stores April 1994, p. 42 as cited in
Stock, J. R. & Lambert, D. S. 2001; 41).
II. Case study – Porsche
In today’s time when an executive spends hundreds of thousands of rands buying a
luxury car, he expects far more than just a luxury vehicle. He expects the after-sales-
service to match up to the comfort and high price of the car. Taking a luxury car in for
a service needs to be a quick, pleasant experience, not an experience that takes
weeks due to slow delivery of the required parts. In order to respond to this need of
executives luxury car manufacturer Porsche decided it needed to find a way to speed
up spare parts deliveries in North America.
In the past, Porsche operated one spareparts warehouse in Reno in Nevada in order
to supply the entire North America. The process of ordering the parts from Germany,
the shipping of the parts to the warehouse, and from there the distribution to the
service centre, took an unacceptable period of time.
After investigating possible solutions, Porsche found that the optimal way to reduce
their delivery time was to implement a state-of-the-art warehouse management
system alongside a radio-frequency data collection system. A warehouse
management system would give the distribution centre live accurate information on
what parts are available and where they are stored, eliminating their old paper-based
systems.
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After the implementation of the appropriate technologies, Porsche reduced its
delivery time of spareparts to its customers from 10 days to 3 days, creating satisfied
customers (Cooke, August 1998).
III. Case study – 7-Eleven
7-Eleven operates more than 32 700 convenience stores around the world serving
approximately 6 million customers each day. With an organisation of this magnitude,
utilising the latest technology is the only way to survive.
In order to improve on their customer service levels, 7-Eleven “implemented an
enterprise data warehouse that now improves operational performance and helps 7-
Eleven analyze the profitability of products on a store-by-store basis. This combined
with 7-Eleven’s end-to-end automated ordering system lets the company track each
item of inventory in each store to understand the buying patterns and behaviors of
customers in that specific location”( EDS, 2007a).
Through the combined use of the 7-Eleven newly-implemented automated inventory
tracking software, as well as the relevant weather prediction software, 7-Eleven is
able to ensure that each store always stocks the right product mix for its specific
customers( EDS, 2007).
IV. Case study- Wal-Mart Warner-Lambert
In order to compensate for poor forecasting, organisations keep safety stock. About
$700 billion worth of stock from the $2.3 trillion of retail stock, was in ‘safety stock’ in
1996. This equates to approximately 30% of all stock being safety stock.
In order to reduce this waste and inefficiency, Wal-Mart Warner-Lambert
implemented the Collaborative Forecasting and Replenishment protocol to forecast
their stock more effectively. Through the use of this tool, Wal-Mart Warner-Lambert
have management to reduce their safety stock drastically, as well as take advantage
of volume discounts and reduce their delivery costs (Lewis, 1997 as cited in Stock, J.
R. & Lambert, D. S. 2001; 261).
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3.4.2 Routing and scheduling case studies
After having looked at some general case studies where technology has been
implemented into the supply chain and has led to successful results, this chapter will
now focus on and analyse a few routing and scheduling case studies.
Fast moving consumer goods (FMCG)
I. Willard Batteries(SA)
Willard Batteries, a South African company based in Port Elisabeth, is a producer of
automotive and industrial batteries. Willard Batteries employs in excess of 1000
people countrywide, manufacturing in excess 1.2 million batteries per annum. Willard
Batteries has a well-developed distribution network throughout South Africa to
provide customers with its products and technical service.
Before the implementation of FLO, Willards used an average of 10 vehicles in order
to be able to cope with their daily deliveries. The implementation of FLO into Willards,
resulted in Willards only needing 6 vehicles in order to cope with their daily deliveries;
a saving of approximately 40%. Willard’s vehicle utilisation went up from 50-60% to
over 90% (Opsi Systems,2007a).
II. Pep Hubs(SA)
Pep has 1400 stores across many southern African countries employing more than
14000 people, being the biggest single-brand retailer in Southern Africa. On average,
PEP trucks drive the equivalent of 225 times around the world per year. As PEP is a
low-cost retailer, keeping their logistics costs to a minimum is critical. In order to
lower their logistics costs, PEP decided to implement FLO. The implementation and
use of FLO to plan deliveries from Pep hubs to Pep stores, resulted in vehicle
utilisation close to 100%, as well as vehicle costs reduced by over 15 % (Opsi
Systems,2007a).
III. Meadow Feeds (SA)
Meadow Feeds is regarded as the market leader in the southern African animal feed
industry. Meadow Feeds produces a variety of specialised diets and custom-feed
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mixes for the poultry, dairy, ostrich and swine industries. Despite Meadow Feeds’
very complicated customer restrictions due to chicken and cow feed cross
contamination problems, the implementation of FLO resulted in a saving of
approximately 10% in distribution costs (Opsi Systems,2007a).
IV. Tiger Milling (SA)
Tiger Milling owns and operates one of South Africa's largest capacity plants for the
production of maize and wheat flour and is one of South Africa’s main suppliers of
corn and wheat products to bakers and supermarkets. Despite the many customer
restrictions on when flour can be delivered, the use of FLO has resulted in an
average vehicle savings of 19%, reducing the Tiger Milling fleet from 31 vehicles a
day to 25 vehicles a day (Opsi Systems,2007a).
V. James Oxygen & Supply Company (USA)
James Oxygen & Supply Company based in North Carolina supplies and delivers
compressed gases and propane products.
In the past, James Oxygen & Supply Company would manually plan the routes the
drivers needed to drive. This manual process could take each driver up to 45 minutes
each day. After the implementation of TruckStops routing and scheduling software,
drivers no longer plan their own routes, but are now given system-planned routes
with turn by turn directions. Through utilising the routes planned by TruckStops,
James Oxygen & Supply has reduced their distances travelled by 21%. They have
also decreased their driver overtime by 50%. These savings have allowed James
Oxygen & Supply to reduce the size of their fleet, while at the same time increase
their customer service levels (Micro Analytics, April 6, 2006; 1).
Beverage industry
VI. SAB Miller (SA)
South African Breweries Ltd (SAB) is the South African subsidiary of SABMiller and
is one of the largest breweries by volume in the world. SAB in South Africa has a
fleet of approximately 600 secondary delivery vehicles spread across some 41
depots around South Africa with over 250 independent owner drivers. Different
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depots operate their fleets in slightly different ways due to a different mix of
customers, depending on the specific region. All their depots experience some, if not
all of the typical constraints in routing and scheduling as discussed previously.
Although SAB had been running routing software at some of its bigger depots in
South Africa, real benefits were not being realised due to an inefficient use of the
software. In 2005, SAB decided to search for new routing and scheduling software
which it could roll out to all its 41 depots countrywide. After much research, they
decided to partner with Opsi systems, and to roll out Opsi’s fleet logistics optimiser
(FLO) to all their depots. FLO is a vehicle scheduling system designed to improve
fleet utilisation and reduce delivery costs by finding delivery routes that minimise
costs. Despite an extremely large variety of customers with an even larger variety of
constraints and restrictions, the daily use of FLO has resulted in a 17% increase in
efficiency, which converts to a saving of approximately 4 out of 25 trucks (Opsi
Systems, 2007a).
VII. Gate City Beverage Distributors (USA)
Gate City Beverage Distributors is a beer distributor which is based in San
Bernardino, California. It supplies over 4000 grocery and liquor stores with 400
different stock-keeping units. Gate City Beverage Distributors distributions network
consists of multiple depots and 70 trucks that make the 10 000 deliveries a month.
As with any high-volume distributor, high distribution costs are a constant issue. In
order to try and manage this issue, Gate City Beverage Distributors decided to
implement routing and scheduling software in order to lower distribution cost and
manage customer demands in 1994. Through the implementation of Roadshow’s
scheduling and routing software, Gate City Beverage Distributors has achieved the
following results:
• Improved on-time deliveries by 50%.
• Reduced transportation costs by 5%.
• Increased number of stops delivered per hour by 20%.
• Decreased daily planning time by 75% .
(Avocus Group LLC, 2004)
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VIII. ABI (SA)
In 2001, ABI, one of the Coca-Cola Bottlers in South Africa decided to implement
Roadshow routing and scheduling software throughout all its large depots. Through
utilising Roadshow to plan its routes, ABI was able to reduce its kilometres driven
and hence its delivery costs. The use of Roadshow resulted in a savings of 23.6% for
diesel and 13.9% of petrol (SAB, 31 March 2001; 37).
Travelling Salesman, Representative and Service Technicians
IX. Whirlpool Corp. (USA)
After years of struggling to manage its team of 440 service technicians, Whirlpool
Corp. decided to implement a computerised routing, scheduling and dispatch system.
The system called Resource in Motion Management System helps Whirlpool plan
routes for its 440 technicians around the United States.
Before installing the Resource in Motion Management System, the service
technicians’ routes were planned using the old, laborious and non-optimal "pins and
map” method.
Using the new software, Whirlpool has reduced distances travelled for deliveries by
an average of 10%. The new software has also improved Whirlpool’s customer
service levels, as it allows for last minute changes to routes, and optimises routes
while obeying customer business rules which was not possible with the “pins and
map” method (Routing Software Streamlines Service. 1997 as cited in Stock, J. R. &
Lambert, D. S. 2001; 315).
X. The Missouri lottery routing (USA)
The Missouri lottery generates annual revenues of over $800 million (approximately
six billion rand) through the selling of lottery tickets. The lottery sales representatives
play a key role in increasing sales by providing a high level of customer service to
ticket retailers throughout the state.
The objective of the implementation of routing and scheduling software was to
minimise 39 lottery sales representatives’ total travel distance, while balancing their
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workloads and meeting visitation constraints. If the objectives were met, this would
also lead to the reduction in the number of lottery sales representatives and hence
further reduced costs.
After the successful implementation of the appropriate routing and scheduling
software, the following results were achieved:
• The total driving distance of lottery sales representatives was reduced
from 55 302 kms to 46 998 kms in a two-week period. This is a reduction
of 8304 kms, which is approximately 15% per lottery sales
representative. This improvement is equal to an annual saving of 215
904 kms, which corresponds to a savings of approximately $47 229
(approximately R354217) per year.
• The new routes decrease lottery sales representatives’ working hours
from 921 to 789 for the two-week period.
• The new routes provide other customer service benefits pf which the
financial value is difficult to quantify, for example: The old routes violated
162 time window constraints, and the new schedule only violated 87 time
windows, which is a 46% improvement.
In conclusion, the “newly implemented schedules and routes decreased the lottery
sales representative’s (LSR) travel distance by 15 percent, improved visitation
feasibility by 46 percent, increased the balance of routes by 63 percent, decreased
overtime days by 32 percent, and indirectly increased the sales of lottery tickets by
improving customer service”(Jang, Lim, Crowe, Raskin, Perkins, July 2006, 302).
XI. Röra’s Home Nursing Service (Sweden)
In 2006, Röra’s Home Nursing Service based in Sweden decided to implement
routing and scheduling software to assist with the scheduling of its nurses to home
visits.
According to Paul Palmer, CEO of DPS Internationa, the National Health Services
(NHS) felt they could learn something from the logistics industry and decided to
implement routing and scheduling software.
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The results of utilising a routing and scheduling solution called LogiX from DPS
International have been phenomenal. The software has allowed for nurses to spend
up to 40% more time with their patients, while at the same time reducing their driving
distance by 25%. Röra nurses total actual working time in 2005 was approximately
52%, and after the implementation of LogiX, this figure grew to 73% in 2006 (DPS
LogixSuite, 2006; 1).
Third party logistics providers
XII. Value Logistics (SA)
Value Logistics is one of the largest and most comprehensive third party transport
and logistics companies in South Africa. Value Logistics operates 17 depots,
warehouses and sorting facilities strategically positioned throughout South Africa.
Originally, Value Logistics used fixed routes which were very inefficient. Since Value
Logistics has started to use FLO, a saving of approximately 12% has been achieved
(Opsi Systems,2007a).
Service industry
XIII. First Garment Rental (SA)
First Garment Rental specialises in the laundry and rental of workwear. First
Garment Rental covers the range of workwear needs from food production to
engineering and antistatic garments. On a weekly basis, the soiled garments are
collected and replaced with hygienically-cleansed garments. Before the
implementation of FLO First Garment Rental had 23 fixed delivery routes. By using
FLO route planning, the 23 fixed routes were reduced to 18 routes. This amounts to a
saving of 22% in vehicles and drivers (Opsi Systems, 2007a).
3.4.3 Case study where routing and scheduling software is combined with other
optimisation software
I. ABI Vending, Bedfordview
ABI is the bottler of the Coca-Cola Company brands in southern Africa, and delivers
the popular soft drink brands to customers all over South Africa. ABI’s vending
operation includes 4000 machines in the Gauteng region in South Africa. Previously,
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machines were on a fixed visit frequency, or call cycle, as can be seen in figure 3.7
which shows a machine being visited once a week. Fixed call cycles are problematic
as sometimes a machine is still full upon servicing, which results in a wasted
logistical expense. On the other extreme, stock-outs represent a failure of the
logistics department and results in lost sales. Ideally, machines should be visited
when they need filling to save on transport and avoid lost sales.
After realising the inefficiency of their manual prediction and planning systems, ABI
approached Opsi Systems to come up with a solution to improve their organisation.
Opsi Systems designed and implemented very successful prediction and routing
software together with ABI vending, resulting in fleet utilisation savings of 30-50%,
depending on the season. The systems that were designed and implemented into
ABI are called Optimization of Vending and Logistics (OVAL) and FLO. OVAL is a
demand prediction system that analyses sales data, temperature and holiday
information to predict dynamically when to visit vending machines, which results in
dramatically lowered costs, improved productivity and reduced lost sales and cash
shortages. FLO is a route optimiser with integrated GPS tracking that uses the
dynamically called vendors predicted by 0VAL and creates optimal routing.
In order to properly understand the benefits ABI achieved from the implementation of
OVAL and FLO, their problem first needs to be properly understood.
Figure 3.7 ABI’s problem: The fixed call cycle
Source: Opsi Systems, 2003c; 12
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What ABI needed was a dynamic demand prediction system, which would look at
each vendor individually and predict when to visit, based on predicted consumption.
This would allow for a machine being visited before a stock-out occurred and wasted
trips would be eliminated. Other advantages of a dynamic demand prediction system
would include a significant transport and labour saving, as well as much fewer stock
outs.
Figure 3.8 ABI’s goal: Dynamic demand prediction
Source: Opsi Systems, 2003c; 13
How the ABI dynamic demand prediction system works
OVAL calculates a daily predicted stock level in each machine based on recent
sales, temperature, and holidays. Based on the prediction, OVAL then issues refill
calls dynamically (no fixed call cycles) when machines need to be serviced. OVAL
allows the user to tailor workload per route to allow route combinations and savings.
OVAL also has an integrated space-to-sales system that automatically issues
suggested column changes for machines called, allowing sales to be optimised by
product to suit the customers of each vending machine. The result is an individual
model per machine which predicts response in sales to temperature and holidays for
that specific machine. Vendors with less than one year of data, are assigned the
model of a similar vendor, and OVAL models each vendor individually, not as
averages over trade channels. This result is a tailored response for each machine
based on its individual factors.
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The following example is based on a vending machine with a capacity of 448 units,
as well as a 4-month refill history. Using the OVAL software to predict when to refill
the machine, resulted in an average one-case discrepancy between actual and
predicted.
Figure 3.9 Example of the predicted versus actual refill needs of a vending
machine for four months
Source: Opsi Systems, 2003c; 17
For the month of September 2001, there were 9900 visits to ABI vending machines.
Of these visits 50% of refills were within two cases of prediction, and 67% of refills
within three cases of prediction.
This resulted in a:
• 50% drop in the number of planned and actual calls
• 75% increase in cases per fill: 5.4 to 9.8
• 40% drop in average call frequency: 2.4 to 1.4
• 40% drop in number of drivers
• Customer queries drop by 500%
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Other benefits included:
• Substantial reduction in call frequency, calls per day, trucks used, total
kilometres.
• Cases per machine substantially increased.
• Out of stocks and customer queries went down.
• Vehicles were far less loaded: less wear and tear, more space for a
wider flavour selection.
• Reduced cash shortages with GPS verification.
• More accurate route planning based on actual GPS knowledge.
• Greater control over overtime worked by drivers: route times are
balanced ahead of time.
(Opsi Systems, 2003c)
3.4.4 Summary of routing and scheduling case studies
In conclusion, the following is a summary of statistics grouped according to industry
type of the financial savings achieved through the implementation of routing and
scheduling software:
Fast moving consumer goods (FMCG)
• Willards Batteries............................40% saving
• Pep Stores ......................................15% saving
• Meadow Feeds ...............................10% saving
• Tiger Milling ....................................19% saving
• James Oxygen................................21% saving
Beverage industry
• SAB ................................................17% saving
• Gate City Beverages.......................5% saving
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• ABI Vending....................................50% saving
• ABI..................................................18% saving
Travelling Salesman, Representative and Service Technicians
• Whirlpool Corp ................................10% saving
• Missouri Lottery ..............................15% saving
• Röra’s Home Nursing......................32% saving
Third party logistics providers
• Value Logistics ...............................11% saving
Service industry
• First Garment Rental.......................22% saving
As can be seen, financial savings of between 10% and 50% were achieved through
the implementation of routing and scheduling software in the case studies discussed.
ABI Vending was however able to achieve a saving of 50% on their distribution costs
through the implementation of routing and scheduling software alongside other
logistics prediction software.
The case studies above show that great savings can be achieved through the
implementation of routing and scheduling software, however, even greater savings
can be achieved when routing and scheduling software is combined with other
optimisation software. The importance of and the necessity to combine routing and
scheduling software with other logistical optimisation and management tools, are
discussed in the subsequent paragraphs.
According to a report entitled “What Companies Want in Their Next-Generation
Supply Chain Solution” (AberdeenGroup, May 2006c), the results show that
automating freight payment is a priority for many organisations striving to be leaders
in the marketplace. “In addition, companies that have yet to deploy shipment
optimisation should consider doing so in the short term. With hefty fuel surcharges
and more stringent enforcement of accessorial charges, static route guide or rules-
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based shipment decisions lead to higher-cost decisions in a surprising number of
cases. A move to technology that will be able to do per-shipment optimisation,
especially if one has a mix of parcel and less than truckload shipments or a mix of
less than truckload shipments” (AberdeenGroup, May 2006c; 25). The report
concludes that one should at least do the basics with regard to haulier collaboration,
such as sharing tactical forecasts and moving to electronic tendering with an
organisation’s larger hauliers (AberdeenGroup, May 2006c; 25).
Although forecasting software in collaboration with routing and scheduling software
delivers great savings, there is a real need for other types of software to be used in
the process of managing and handling an organisation’s fleet. “Many manufacturers’
focus on profit management is hampered today because business processes that
impact on revenues are managed manually or are only partially automated, leading
to significant inefficiencies”. “Poor tracking of expired contracts, discount profitability,
and out-of-contract pricing, as well as poor reconciliation of charge-backs, leads to a
great deal of revenue leakage within manufacturing organisations” (Pivotal
Corporation, 2006; 2). According to a report by the Pivotal Corporation titled
Managing Quotes, Contracts and Pricing for Higher Profits, organisations need to
look more closely at the way they quote, contract, and price their products and/or
services and need to implement tools to improve their process efficiency if they wish
to maximise their profit opportunities. Organisations need to start moving away from
using standard spreadsheets and small in-house departmental database applications
as their “ERP” systems, as these applications will not be agile enough to handle the
new needs of a growing economy (Pivotal Corporation, 2006; 2).
The case studies discussed above have shown the importance of utilising technology
in an organisation in order to be able to compete effectively in the marketplace. The
case studies have shown that by implementing technology into only one link in the
supply chain, is not enough to achieve overall efficiency and organisations wishing to
compete in today’s business environment, need to implement a set of
complementary technologies in order to achieve the desired results.
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3.5 Importance of high quality master data
After discussing the need for software in the supply chain and having discussed case
studies to prove the benefits, it is critical to understand the need for and importance
of quality master data.
According to Webopdeia (2007), garbage in garbage out (GIGI) “is a famous
computer axiom meaning that if invalid data is entered into a system, the resulting
output will also be invalid”. Simply stated, the results of any system will only be as
good as the master data that is entered into it.
Only once organisations understand the importance of their master data and start
taking ownership of it, will the outcome of the software systems produce the desired
results.
According to Sean Aspoas (Aspoas; 25 May 2007) of Opsi systems, obtaining master
data from an organisation in order to build the foundations of a database is a
constant challenge. Simple data such as customer addresses is often not available.
This is only the beginning of the challenge as the next challenge arises when an
organisation is required to compile master data on a daily basis, such as a daily list of
customers, or jobs that have to be executed. It can take months to build a simple
database due to the lack of competency of organisations with regard to master data.
A 2006 survey conducted by Business Week Research Services and HP (Hewlett-
Packard Development Company, 2007) found that “52 % of executives surveyed said
there was pervasive recognition of data as a corporate asset throughout their
organisation. Another 37 percent said there was some recognition of data as a
corporate asset within pockets of the organisation” (Hewlett-Packard Development
Company, 2007). The survey concludes that businesses and IT executives are slowly
realising that data is a valuable resource.
Three main issues characterise information quality. First is the availability of the
information required to make the best possible decisions. Second is the accuracy of
the information. Third is the effectiveness of the various means that are available to
communicate needed information. Unfortunately, logistics managers do not always
have the information they need to make effective decisions. Often, the most common
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reason is that many managers are uncertain of their information needs, and thus,
have difficulty understanding and relaying those needs. Another reason for not
having the right information is that staff charged with providing information, give the
logistics manager what they think is needed or what they find convenient or cost-
effective to provide. Often, this is quite different from what the logistics manager truly
needs.
As can be ascertained from the above paragraph, pushing the right, high quality
master data into a software system is critical if organisations would like to reap the
benefits of the software system. However, collecting and maintaining high quality
master data is a continual challenge that requires constant management and
resources from an organisation.
3.6 Summary and conclusions
Chapter three began by looking at the initial use of technology in the supply chain in
the early 1980s. The true breakthrough in logistics technology performance came
when new ways were identified to substitute information for work content. This led to
logisticians taking advantage of powerful optimisation tools which optimised inventory
management, network, routing and transport optimisation, slotting optimisation in
warehouses, and so on. Despite the benefits of utilising technology in the logistics
department, the logistics department was among the last to join the personal
computer bandwagon as organisations did not yet understand the importance of their
logistics network in providing a competitive product.
As organisations began to understand the importance of their logistics network, they
started to outsource this non-core, yet highly critical function of their organisation.
This led to the creation of the 3PL and then the creation of software to manage the
relationship between an organisation and its 3PL.
Utilising technology in the supply chain has many advantages; however along with
the advantages, come the disadvantages. These advantages and disadvantages, as
well as the general benefits of utilising technology have been discussed at length in
this chapter. Although there are many auxiliary benefits and advantages of
implementing software systems into the supply chain, the two main critical benefits
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that have to be achieved in order to justify the expense are reduced costs and
improved customer service. It needs to be remembered though that simply
implementing technology is not necessarily going to reduce costs and improve
customer service, as has been discussed. The appropriate technology needs to be
implemented at the right time in the correct way. Even once the appropriate
technology has been implemented at the right time in the correct way, there is still the
issue of master data, which needs to be of high quality and inputted at the
appropriate time in order to ensure a desired outcome. Organisations need to
remember that the implementation of a software system can make matters even
worse if software is implemented in lieu of correcting a broken distribution process.
When it comes to automating bad processes, software merely enables faster flow of
bad information (Haggar,2003; 1).
This chapter also focused on routing and scheduling software. The constraints when
routing and scheduling vehicles, as well as the benefits of good routing and
scheduling are discussed. Other issues such as the impact of efficient routing and
scheduling on the environment are also discussed.
Chapter three explains why organisations are prepared to spend millions of rands on
software systems which are not their core product in which they specialise, and from
outside the organisation does not appear to directly benefit their core product. By
explaining the absolute necessity of implementing technology into an organisation’s
supply chain, the chapter illustrates the critical importance of technology in the supply
chain of an organisation, and confirms that organisations will not be able to survive in
today’s competitive environment without utilising the appropriate technologies.
Chapter three concludes by looking at numerous case studies where technology has
been implemented into the supply chain, as well as a couple of routing and
scheduling case studies. In conclusion the importance of high quality master-data,
and the negative effect that poor master data can have on an organisation, is
discussed.
The following chapter is going to take an in-depth look at a case study of Clover
Logistics, and will examine the problems and issues in the processes the
organisation used prior to the implementation of the new technology.
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Chapter 4
4 CLOVER LOGISTICS’ PAST SYSTEMS AND PROCESSES
4.1 Introduction into Clover
4.1.1 Organisational Overview
Clover was established in 1900 and is currently the leader in the dairy industry in
South Africa (Clover, 2007b; 1). Its mission is “the superior procurement, production,
marketing, sales and distribution of branded consumer goods (BCG) to customers in
the southern African region at bench marked costs, with margins sufficient to ensure
Clover's long term growth”(Ibid). Clover aims “To reach every southern African
consumer on a daily basis with our most admired branded and trusted products, in
order to create sustainable long term value for all shareholders" (Ibid).
The Clover Group is currently the biggest dairy group in South Africa, with a turnover
in excess of R4,3 billion and a staff complement of approximately 6 300.”Clover
collects some 30% of South Africa's milk and processes it in 13 factories and
distributes its range of well-known dairy and related products through 23 national
distribution depots and seven large agents”(Ibid).
“If you were to knock on the average South African's front door, the chances that
you'll find a Clover product are pretty good. It comes as no surprise, since Clover is
one of the few brands that have earned a place among the world's top two percent of
brands for the emotional bond it has with its consumers” ( Bizcomunity.com, 2008;1).
In order to distribute its products to its customers in a cost effective and efficient way,
Clover established Clover Logistics.
As a result of Clover realising the critical importance of logistics in their organisation,
and the fact that it impacts on four separate departments in Clover’s supply chain
Clover decided to form an organisation to handle all their logistics needs - Clover
Logistics.
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The four departments identified by Clover that have a direct impact on logistics are:
• The commercial department, which is responsible for general product-
related issues including price and brand-related issues.
• The production department which is responsible for operating the
various factories producing Clover’s range of products.
• Clover’s planning department responsible for ensuring that there is
enough stock of the required product at the various DCs (distribution
centres) or the CDC (central distribution centre) at the correct time.
• Clover Logistics’ distribution department ensures the storage and safe
delivery of products from the factory to the customer, as well the
distribution of products.
(Clover Logistics, 2007a; 2)
4.1.2 Background to Clover Logistics
“The wide availability of Clover products, from the local corner cafés to the
hypermarkets, is the result of the Clover Group’s world-class distribution
infrastructure, which has been built up over 100 years and which has culminated in
the formation of a focused distribution operation in 2002, called Clover
Logistics”(Clover, 2007b; 1). Clover Logistics was formed in order to focus on the
increasingly important function of distributing Clover’s products. To ensure the
optimal use of Clover’s in-house and subcontracted fleet, Clover Logistics decided to
procure loads from external sources such as Unilever South Africa, Eskort Processed
Meats, Today’s Foods and Mageu in order to fill up their empty legs. It did not take
long before Clover Logistics evolved from an in-house logistics department to a
specialised third party logistics provider. Today Clover Logistics specialises in the
distribution of products for Clover, Clover Beverages, Danone, as well as a large
number of third party organisations. Clover Logistics is the largest 3PL that focuses
on the chilled and frozen distribution channel in South Africa (Clover, 2007b; 1). It is
responsible for storing and moving a variety of products including milk, margarine,
chicken, chocolate milk, sauces, soups and a variety of other products. The products
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distributed are divided into three temperature ranges namely frozen, chilled and
ambient.
Clover Logistics provides a number of services including warehousing, secondary
distribution, primary distribution, sales and merchandising, management information
systems, credit control and a large number of other services.
This dissertation will focus on Clover Logistics’ primary distribution for the following
reasons:
• Clover Logistics’ primary distribution has grown in only a few years to be
a leader in the distribution industry.
• The use of technology has been a critical element in their growth and
has ensured the stability of the organisation as it continues to grow.
• Clover Logistics’ primary distribution covers a wide range of different
logistical aspects including outsourcing, the transportation of in-house
loads, as well as loads for third party clients and the use of state of the
art technology throughout its organisation.
Of all the services offered by Clover discussed until now, only “primary distribution”
falls under the Clover Logistics’ primary planning division which will be discussed in
the case study further on.
Owing to the fact that Clover Logistics’ operates in the FMCG industry, they have to
deal with the specific characteristics that are typical to the FMCG industry, such as a
high replenishment rate, high frequency of orders, and delivery in all market
segments on a daily basis and within the specified ship-by-period (the period in which
the product has to be delivered to the customer in order that it can be sold before it
expires) for the product.
4.1.3 Background to the primary distribution function in Clover
Primary distribution is the distribution of raw materials and finished products between
the different production facilities and warehouses. Primary distribution very seldom
comes into contact with the final customer. The definition of primary transport is
illustrated in the diagram below.
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Figure 4.1 Definition of primary distribution
PRODUCTION
DISTRIBUTION CENTRE
CROSS-DOCK
CENTRAL
DISTRIBUTION
CENTRE
DISTRIBUTIONCENTRE
SATELLITE
Secondary Transport
FINISHED GOODS WAREHOUSE AT THE
FACTORY
PRIMARY RECEIVING AT BRANCHES
CUSTOMER
Primary Transport
PRODUCTION
• RAW MAT• PACKAGING
Primary Warehousing Secondary Warehousing
PRODUCTION
DISTRIBUTION CENTRE
CROSS-DOCK
CENTRAL
DISTRIBUTION
CENTRE
DISTRIBUTIONCENTRE
CROSS-DOCK
CENTRAL
DISTRIBUTION
CENTRE
DISTRIBUTIONCENTRE
SATELLITE
Secondary Transport
FINISHED GOODS WAREHOUSE AT THE
FACTORY
PRIMARY RECEIVING AT BRANCHES
CUSTOMER
Primary Transport
PRODUCTION
• RAW MAT• PACKAGING
Primary Warehousing Secondary Warehousing
Source: Clover Logistics, 2007a; 6
As can be seen by the dotted red line in figure 4.1, primary distribution is responsible
for the transportation of the following:
• SKUs (Stock Keeping Unit) from the factories to the CDCs. This includes
all the products manufactured by Clover Dairy, including all Clover SKUs
such as milk, fruit juices and yogurt.
• SKUs from the CDCs to the CDCs. This includes all the products
manufactured by Clover Dairy, as well as products of Clover Logistics’
clients, including Unilever South Africa, Eskort Processed Meats,
Today’s Foods and Mageu.
• SKUs from the CDCs to the DCs. Products are then transported from the
DC to the customer through the use of Clover’s secondary fleet.
• Full SKU loads from the CDCs directly to the Customer. Clover Logistics
found that it would be more efficient to deliver directly from the CDC to
customers who ordered full truck loads. This eliminates storage and
handling at the DC, as well as the need for a secondary vehicle to
deliver the product from the DC to the customer.
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• Factories to factories requirements. Raw material as well as partly
manufactured products needs to be moved between the production
facilities.
• Crates and pallets between relevant locations. All crates and pallets that
are moved from the production facility through the CDCs and DCs need
to be moved back to the production facility in order to be re-used.
• Loads procured from external sources to avoid empty legs. Clover
Logistics initially decided to procure loads from external sources such as
Unilever South Africa, Eskort Processed Meats, Today’s Foods and
Mageu in order to make use of their empty legs. Although these external
loads were initially only procured to fill empty legs, Clover Logistics now
does all types of loads and warehousing for external sources and has
developed into a fully-fledged 3 PL.
(Clover Logistics, 2007a; 8)
As a result of the redesign of Clover’s distribution network over the past few years,
each factory now specialises in the manufacture of certain products and the Central
Distribution Centers (CDC) no longer form part of the factory and operate at their own
sites as a separate entity. This has led to a more complicated distribution process.
Clover Logistics has also experienced a large increase in business from third parties
over the past few years, making the business more complex and difficult to manage.
4.1.4 Clover Logistics’ mission statement and objectives
The mission statement of Clover Logistics primary distribution is to “maximise the
shareholders returns by ensuring that the correct products from Clover, as well as the
primary principles (Clover Logistics’ customers), are delivered from the factory to the
depot in the right time and place and with the necessary retention of quality in order
to create a competitive advantage for Clover and their principles” (Clover Logistics,
2007b; 3).
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Clover Logistics have defined the following objectives as critical in order to be able to
live up to their mission statement:
• Thorough and comprehensive planning of the primary distribution
network in order to optimise service and cost. The plan then needs to be
successfully implemented on a daily basis.
• The minimising of the transport costs without negatively impacting the
overall service level. This includes choosing between own transport
versus contractors, efficient load utilisation and return load utilisation.
• The optimal scheduling of vehicles and loads in order to ensure that the
correct load leaves and arrives within the correct time frame as agreed
upon with the customer.
• The effective management of the Central Distribution Centres and/or
factory stores.
• Ensure that the quality is maintained throughout the supply chain (Cold
chain, damaged, soiled, contaminated).
• The development and marketing of primary distribution service products.
• The efficient management of the distribution division.
4.1.5 Clover’s current operational requirements and their predicted growth
Clover Logistics is constantly growing and as a result of this continuous growth, the
distribution operation is getting more and more complex and difficult to manage. On
20 March 2003 the following statistics applied to Clover Logistics’ primary
distribution.
• Number of dispatch points: ...................................................50
• Number of drop points: .........................................................50
• Number of routes: .............................................................1210
• Number of different SKUs: ................................................1207
• Request for service per peak month: .........An average of 3000
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• Request for service average per month: ....An average of 2400
• Number of trips per peak month: ...............An average of 2300
• Number of trips average per month: ..........An average of 1800
• Lead time for long-life products:..................................48 hours
• Lead time for fresh products: ......................................24 hours
• Number of Clover in-house vehicles: ....................................55
• Number of subcontracted vehicles :.............. An average of 83
• Business outsourced:.........................................................60%
As seen in the above mentioned statistics, Clover Logistics has a large number of
subcontracted vehicles. As a result of the large fluctuations between peak and of-
peak periods, it makes business sense for Clover Logistics to subcontract to external
hauliers during peak periods, rather than purchase in-house vehicles that would sit
idle during off-peak periods. Clover Logistics’ also uses subcontracted vehicles
during off-peak periods in order to benefit from the savings on capital outlay and
other such benefits.
Figure 4.2 Predicted and historical request for services as in March 2004
Source: Clover, 2003a; 1
Figure 4.2 depicts the monthly historical and monthly projected vehicle trips as in
March 2004. All data prior to March 2004 is actual data and all data post-April 2004 is
predicted, based on predicted new business. Analysing the month of August 2004,
Primary Distribution Requests/Trips
500
1000
1500
2000
2500
3000
3500
2003
01
2003
02
2003
03
2003
04
2003
05
2003
06
2003
07
2003
08
2003
09
2003
10
2003
11
2003
12
2004
01
2004
02
2004
03
2004
04
2004
05
2004
06
2004
07
Requests
Trips
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the number of trips executed by Clover Logistics is expected to grow from 2500 trips
in 2003 to over 3100 trips in 2004, which is a growth of over 25%. With an annual
growth rate of approximately 25%, Clover’s operations became more complicated
and challenging.
4.1.6 A look at Clover Logistics’ primary operational and financial complexities
Figure 4.3 represents Clover’s primary distribution flow. The network has over 700
primary legs in and around South Africa with over 4000 different charges which
depend on the length of the leg and are haulier and client specific. Distribution has to
take place to and from 23 Clover factories, as well as a large number of client
factories.
Figure 4.3 Clover’s primary distribution flows
Pretoria
Port ShepstonKokstad
Upington
George
Nelspruit
Kimberley
Queenstown
Bredasdorp
Beaufortwest
Boksburg hub
Slabberts
Ga Rankuwa
Vredendal
Potchefstroom
Welkom
City Deep
Cape Town
East London
Port Elizabet
Merebank
Empangeni
Polokwane
Newcastle
Bloemfontein
Lichtenburg
0 100 200 300
Kilometers
Boksburg Hub Hub dependant CDC dependant
Pretoria
Port ShepstonKokstad
Upington
George
Nelspruit
Kimberley
Queenstown
Bredasdorp
Beaufortwest
Boksburg hub
Slabberts
Ga Rankuwa
Vredendal
Potchefstroom
Welkom
City Deep
Cape Town
East London
Port Elizabet
Merebank
Empangeni
Polokwane
Newcastle
Bloemfontein
Lichtenburg
0 100 200 300
Kilometers
Boksburg Hub Hub dependant CDC dependant
Source: Clover Logistics, 2007a; 9
Although figure 4.2 does not look complicated, an in-depth look at the Gauteng
distribution network better illustrates the complexity.
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Figure 4.4 Clover’s Gauteng primary distribution flows
PALLETS/WEEK
140
175
115 67
30 15
184 84
9 462
45 48 82
1,300 100
564
291 140 141 48
267
11 1,045
716 103
15 21 2,549 97 60
665 84
6,611 60 1,882
GAUTENG - GAUTENG : CHILLED : PRODUCTS : CURRENT
Boksburg
Friesland
Clayville Fresh
Clayville UHT
City Deep
MayfairSprings
Boksburg Hub
Pretoria
Clayville Factory
Unifoods Factory
Gauteng to Ext Ext to Gauteng
Mague
Manhattan
Woolworths
Spar South Rand
Spar North Rand
Fonterra
Cold StorageFresh Connection
Eskort Heildelberg
Source: Clover Logistics, 2007a; 14
Figure 4.4 represents the weekly flow of pallets in Gauteng. The blocks attached to
the arrows represent the number of pallets that need to be moved between the
various CDCs, DCs, production plants, as well as customers who order full truck
loads. Figure 4.4 also includes the pallets that need to be collected from external
clients such as Mague. As can be seen in figure 4.4, with the number of pallets that
need to be transported between the relevant locations on a weekly basis, the need
and potential for an advanced routing and scheduling system is evident.
Figure 4.5 shows one of Clover Logistics’ typical routes. As can be seen in the
illustration, a truck would take a load from the Gauteng region to Port Elizabeth, it
would deliver the load in Port Elizabeth, and would then go and pick up a load in
George from Lancewood (as seen by the black line) and deliver it back to Gauteng.
Although the optimal route would be to go from George directly back to Gauteng (as
can be seen by the red line), Clover’s current scheduling system could not handle
such a “complex” route and the associated charges, and hence the vehicle would be
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forced to go from George back to Port Elizabeth and then return to Gauteng (as seen
by the blue line). The inability of Clover’s current scheduling system to handle
“complex” routes has led to millions of rands being wasted on inefficient routes.
Figure 4.5 Non-optimal route network
Source: Developed by the author for the purpose of the study
In order to efficiently administer an average of 2700 service requests per month, as
well as invoice the correct external clients for their associated loads, and at the same
time remunerate the subcontracted hauliers accurately, (based on 4000 different
types of charges), complex processes and systems are needed. Paragraph 4.2 will
discuss Clover Logistics’ past scheduling and financial processes.
4.2 Clover’s previous systems and processes
4.2.1 Clover Logistics’ previous system setup
In the past, Clover Logistics operated many different stand-alone solutions. These
solutions included the following:
• BPCS-Business Planning and Control System-Clover’s ERP system
• BRs-Branch Replenishment System- Clover’s SKU prediction system
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• Transport Request System known as the “Magic” system
Each system fulfilled its individual task, and most communication between the
systems relied on manual data capturing from one system to the other.
This section will focus on Clover’s previous transport request system known as the
“Magic” system. The Magic system was Clover’s transport planning system and
interacted with Clover’s BR system as well as with Clover’s BPCS system, as will be
described further on.
The Magic system which was positioned on a terminal server located at the Clover
Roodepoort office block, was utilised from Clover’s Primary Distribution Command
Centre located in Boksburg, using terminal services. Magic relied on the DB400, a
database engine which was located at Clover Roodepoort.
4.2.2 General Overview of Clover’s Magic System
The Magic Transport Request System was developed in-house, by Clover’s IT
department in the mid 1990s to assist the Primary Distribution Department to
administer the bookings of transport requests to and from various delivery points.
Magic is the development environment that was used to develop the Transport
Request System, however the Transport Request System soon became known as
the “Magic” system. Clover Logistics has a number of other systems that were
developed using the Magic environment, including their call centre system, their
stock capture system and their branch replenishment (BR) system. Clover’s
Transport Request System will be referred to as the Magic system for the purpose of
this study.
The operational side of the transport request system Magic was run by two users
whose sole responsibility was the Magic system. One user was responsible for
inputting the relevant information and taking the information through the daily Magic
process, and the other user was responsible for following up on the current status of
the loads and capturing the relevant information back into Magic.
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The transport request system (Magic) consisted of a large number of tedious manual
steps, which if not performed, would not produce the required results.
The following is a summary of the process the user would have to follow when
entering a new service request into the system and taking it through the various
steps.
Figure 4.6 The Magic process flow
Step 7- The accounts department picks up that a trip has been done on the BPCS and pays the haulier
- The accounts department manually feeds the accounts receivable information into Pastel based on information in Magic system and invoices the client
Step 1a- BR predicts necessary stock and
generates orders for each DC.- The order is then captured
manually into an e-mail and sent through to Clover’s planning
department for planning
Step 1bOutside clients such as Escort e-mail mail their transport request
though to the to Clovers planning department for planning
Step 6The Magic user generates a purchase order in Magic and
sends it to BPCS.
Step 5The Magic user receives
confirmation via phone that the transport request has been delivered and marks it as
delivered in Magic
Step 4The Magic user receives
confirmation from the haulier or Clover’s internal fleet that they
can and will perform the requested transport request
Step 3- The Magic user then decides
whether to use an internal Clover vehicle or outsource the load to
an external haulier.- The Magic user then allocates
the transport request to the relevant haulier
Step 2The Magic user manually captures
the transport request into the Magic system from the e-mail sent
to him
Step 7- The accounts department picks up that a trip has been done on the BPCS and pays the haulier
- The accounts department manually feeds the accounts receivable information into Pastel based on information in Magic system and invoices the client
Step 1a- BR predicts necessary stock and
generates orders for each DC.- The order is then captured
manually into an e-mail and sent through to Clover’s planning
department for planning
Step 1bOutside clients such as Escort e-mail mail their transport request
though to the to Clovers planning department for planning
Step 6The Magic user generates a purchase order in Magic and
sends it to BPCS.
Step 5The Magic user receives
confirmation via phone that the transport request has been delivered and marks it as
delivered in Magic
Step 4The Magic user receives
confirmation from the haulier or Clover’s internal fleet that they
can and will perform the requested transport request
Step 3- The Magic user then decides
whether to use an internal Clover vehicle or outsource the load to
an external haulier.- The Magic user then allocates
the transport request to the relevant haulier
Step 2The Magic user manually captures
the transport request into the Magic system from the e-mail sent
to him
Source: Developed by the author for the purpose of the study
The user would have to capture a request for service manually, and then link it to a
haulier, and a pre-defined tariff. Order numbers would then have to be linked to the
request for service in order to be able to determine the number of pallets for that
request for service. A transport request would then be generated and sent out to the
haulier via fax or e-mail for confirmation, which the haulier would sign and fax back.
After the haulier has confirmed that it is able to pick-up and deliver the necessary
load, the load is monitored manually until it is delivered. The delivery is captured
manually on the system and a purchase order is then generated for the haulier. From
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the information available on the system, load utilisation and cost allocation can be
determined and calculated for a specified period.
In order to fully understand Magic’s strengths and weaknesses, it is necessary to go
through the main process of capturing an order and the process involved in taking
the order from the beginning stage of its cycle right through to the end.
4.3 An in-depth look at Clover’s previous legacy system
The following is a step-by-step explanation of the Magic process, which will be
discussed in more detail in the following sections of this chapter
I. Capturing a Request for Service(RFS)
II. Allocating a haulier to the RFS
III. Generating a transport request schedule
IV. Receiving confirmation from the haulier
V. Confirming a haulier for a transport request
VI. Confirming delivery of a transport request
VII. Generating purchase orders
4.3.1 Capturing a Request For Service (RFS)
The Magic process begins when the Magic user manually captures a transport order
known as a request for a service. The details that need to be captured into the RFS
are gathered via telephone conversations, e-mails and faxes sent from the
distribution centres, as well as from external clients.
The manual capturing of RFS by the Magic user illustrates the inefficiency of the
Magic system, as the Magic user has to retrieve the e-mail and manually capture the
applicable information into Magic. This manual step creates room for errors and
makes inefficient use of the Magic user’s time.
This request needs to include the following six fields:
• Pick-up and drop-off points
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• Number of pallets
• Type of vehicle
• Pick-up date and time
• Drop-off date and time
• Type of transport - primary, direct, crates, factory-to-factory, returns or
income from the delivery point
Once the above fields have been entered, an order number would then have to be
linked to the RFS in order to be able to determine the number of pallets for that RFS.
The order number is generated by Clover’s business planning and control system
(BPCS). BPCS has all the relevant SKU information associated with it, including the
number of pallets that need to be transported. The user is not forced to link the RFS
to an order number and could manually enter how many pallets needed to be
transported into the RFS. The majority of the time the user would manually enter the
number of pallets, instead of linking the RFS to an order number, which meant that
cost allocation could not be done for the products on the orders.
When multiple loads are entered that need to be delivered on the same vehicle,
either from the same pick-up or same drop-off points, the date and time for that
specific pick-up or drop-off must be exactly the same, so that the correct transport
request can be created. If the date and time of the two RFSs are not exactly correct,
it will not be possible to deliver the two RFSs on the same vehicle. This inability to
easily handle multiple shipments on the same vehicle, is one of the major problems
with the Magic system. Clover needed a transport management system that can
handle multiple shipments on one vehicle with different pick-up and drop-off
locations.
A detailed diagram depicting the process flow of capturing a RFS and linking an
order to an RFS, can be seen in annexure 4.1 and 4.3 respectably.
After following the above procedure, an order for transport known as a “request for
service” is created.
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4.3.2 Allocating a haulier to Request for Service
A transport order (known as a RFS) must exist before it can be allocated to a haulier.
In order to allocate a haulier to the request for service, the following fields need to be
entered:
• A route code must be entered that already exists in the route file. A route
file is a predetermined route linked to the standard kilometres for the
route.
• A hauler code must be entered and must already exist in the haulier file.
• The status of the request for service must be updated to “A” to indicate
that a haulier has been allocated to the request for service.
• The request for service then needs to be manually linked to a predefined
tariff code based on the haulier code, route code and vehicle that was
assigned to it.
The fact that each RFS needs to be linked to a predetermined route that is linked to
the standard kilometres for the route, is another one of the issues with the Magic
system. Having the need for a predefined route takes away Magic’s ability to plan
dynamically and results in sub-optimal routes as discussed above with relation to
figure 4.5.
A detailed diagram depicting the process flow of allocating a haulier to a RFS can be
seen in annexure 4.2.
After following the above procedure, a haulier is then allocated to a transport order
(RFS).
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4.3.3 Transport procurement
I. Generating a transport request schedule
Before a transport request schedule is generated, a transport order (RFS) must exist,
it must be linked to orders (or contain the number of pallets to be transported) and
allocated to a haulier. The following fields must be manually entered into the system
before a transport request schedule can be generated:
• Whether the transport requests must be e-mailed must be specified.
• If two or more transport orders (RFSs) are found with the same tariff
code, the requested date and time for pick-up or drop-off and the
transport request numbers are not allocated yet, the user is prompted if
the requests for service found must be allocated to the same transport
request.
• If the print option was specified, then an e-mail is sent out to the haulier
allocated to the RFS on the transport request, asking the haulier if they
are able to perform the transport request.
A detailed diagram depicting the process flow of generating a transport request can
be seen in annexure 4.4.
After following the above procedure, the RFS is updated and sometimes an e-mail is
sent to the haulier. If an e-mail is not sent to the haulier, the Magic user either
phones or faxes the haulier to inform them of the transport request.
II. Receiving confirmation from the haulier
The haulier will receive the RFS mostly via e-mail, or sometimes by phone. The
haulier will then print the e-mail, write on it whether he is able to fulfil the RFS, sign it
and fax it back to Clover.
Once the haulier has accepted the RFS, the user must enter the applicable transport
request number and update the transport request to ‘Received’.
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The manual capturing of an accepted RFS by the Magic user is another aspect of
inefficiency in the Magic system, as the Magic user has to retrieve the fax and
capture the applicable information into Magic. This manual step creates room for
errors and results in inefficient use of the Magic user’s time.
A detailed diagram depicting the process flow of receiving a confirmation from a
haulier can be seen in annexure 4.5.
After following the above procedure, the RFS is updated to a status of ‘Received’.
III. Confirming a haulier for a transport request
This step involves a confirmation by the haulier for the trip. The following steps must
be followed in order to confirm the hauler for a trip:
• The user must enter the applicable transport request number.
• The user must then check the applicable box indicating whether the
haulier confirmed or rejected the trip.
• The user then has an option for Magic to send an e-mail to the pick-up
and drop-off delivery points as indicated on the RFS.
If the haulier rejects the trip, the user allocates another haulier to the TR, and the TR
starts again from step three.
A detailed diagram depicting the process flow of confirming a haulier to a transport
request can be seen in annexure 4.6.
After following the above procedure, the transport request status is updated to
rejected or confirmed, depending on the haulier’s response, and an e-mail is sent to
the pick-up and drop-off delivery points.
4.3.4 Confirming delivery of a transport request (Tracking the load)
At this stage the delivery of products is confirmed. The user knows when a shipment
has been delivered as the trip is monitored by the Magic user via telephone.
• The user must enter the transport request number.
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• Only transport requests that have a status of ‘Confirmed’ can be marked
as delivered.
• The delivery date and time must be entered and recorded into the
relevant locations.
A detailed diagram depicting the process flow of confirming the delivery of a transport
request can be seen in annexure 4.7.
After following the above procedure, the status of the RFS is changed to “D”, to
indicate that the request for service was carried out.
Ideally, this step should be performed either automatically as a result of integration
with satellite tracking, or should be performed by the receiving warehouse. The fact
that the Magic user has to track the load and manually confirm its delivery, is
inefficient and time consuming.
4.3.5 Financial administration
I. Generating purchase orders
At this stage, the user now needs to generate purchase orders for transport orders
(TRs) that have been delivered.
• The user can select to generate a purchase order for a range of
transport requests or for all the transport requests.
• A purchase order can only be generated for RFS that have been marked
as delivered, and once the delivery date and time has been entered into
the system.
• The user must go and look at the tariff file where all the tariffs are stored,
and retrieve the amount that is applicable to pay the haulier for the trip.
• An amount that was quoted to the haulier must exist, and the amount
quoted must be the same as the amount in the tariff file. If the amount
quoted is not the same as the amount in the tariff file, then the user is
prompted whether or not to accept the quoted amount.
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• The cost centre, branch code, account number and item must exist in
the Company file on BPCS.
• If all the above validations are adhered to, the purchase order is posted
into the BPCS.
• An entry must be made manually in the BPCS to reflect the generation of
purchase orders. It must be marked as ‘GPO’ (generation of purchase
order). This entry is another example of extra manual work that has to be
performed as a result of a non-integrated system.
A detailed diagram depicting the process flow of generating a purchase order can be
seen in annexure 4.8.
After following the above procedure, the status of the transport request is updated to
‘Posted’ and a purchase order is generated for the haulier.
II. Paying the haulier and charging the client
The accounts department picks up that a trip has been done on the BPCS. Once the
accounts department has received an invoice from the haulier, it checks whether the
invoice matches the purchase order on the BPCS and pays the haulier.
Magic does not handle accounts receivable. The accounts department manually
feeds the accounts receivable information into the Pastel accounting system, based
on information in the Magic system, and invoices the client through Pastel. No
checks are done comparing what is entered in Pastel and what was in reality
executed in Magic, leaving a large gap for errors and potential fraud to occur. (Clover
Logistics, 2001)
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Figure 4.7 Gap created in the accounts receivable process
Create Request for Service in Magic- BR sends e-mail to planners- Planners manually create RFS
Create Transport Request in Magic- Source a haulier- Confirm a haulier- Deliver TR
Create a Purchase Order in Magic
Send Purchase Order through to BPCS- Run accounts payable process to pay haulier
Manually Enter Accounts Receivable Information in Pastel- Send invoice to client eg: Escort
Non-integrated process creates a gap for fraud and errorsX
Create Request for Service in Magic- BR sends e-mail to planners- Planners manually create RFS
Create Transport Request in Magic- Source a haulier- Confirm a haulier- Deliver TR
Create a Purchase Order in Magic
Send Purchase Order through to BPCS- Run accounts payable process to pay haulier
Manually Enter Accounts Receivable Information in Pastel- Send invoice to client eg: Escort
Non-integrated process creates a gap for fraud and errorsX
Source: Developed by the author for the purpose of the study
4.3.6 Master Data Management
The following master data has to be entered in Magic in order to allow it to produce
the purchase orders.
• Routes
In order for Magic to calculate the correct tariffs for a haulier, a route has to be
created from every pick-up point to every delivery point. This route has to have a
distance that is entered manually into the system. New routes are entered into the
system by the operations manager.
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Table 4.1 Information required when adding a new route
Information Requirement Description
Route code Unique route code
Pick-up point Pick-up point code
Drop-off point Drop-off point code
Route description Description of the route
Number of kilometres Number of kilometres between pick-up and drop-off point
Comments Any comments concerning this route
Active/Inactive Whether the route is in use or not Source: Developed by the author for the purpose of the study
• Distances
Although the distance between two points has been entered into the route file, a
separate file has to be maintained with the distance between pick-up and delivery
points. This is needed as Magic is not able to access the distance from the route file
when calculating tariffs.
Table 4.2 Information required when adding a new route distance to the
distance file
Information Requirement Description
Pick-up point Pick-up point code
Drop-off point Drop-off point code
Number of kilometres Number of kilometres between pick-up and drop-off point Source: Developed by the author for the purpose of the study
• Tariffs
A tariff has to be created for every specific route and specific haulier, a specific
number of pallets, and a specific vehicle. The tariff is valid for a predefined time
period.
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Table 4.3 Information required when adding a new tariff
Information Requirement Description
Tariff code Unique tariff code.
Route code The code of the route that this tariff applies to
Haulier code The code of the haulier that this tariff applies to
Vehicle code The code of the type of vehicle that this tariff applies to
Number of pallets The number of pallets that this tariff applies to
Tariff description A description of the tariff
Tariff price incl VAT Amount that is to be charged for this route including VAT
Tariff price excl VAT Amount that is to be charged for this route excluding VAT
Must VAT be included Yes/no (whether VAT must be included)
Active/Inactive Whether the tariff is in use or not Source: Developed by the author for the purpose of the study
• Delivery points
The delivery point is entered but not placed in a geographical location on a map.
Magic routes are not calculated through the use of a map, and hence the actual
geographical location of a delivery point is not important.
Table 4.4 Information required when adding a delivery or pick-up point
Information Requirement Description
Delivery/pick-up point code
Unique delivery/pick-up point code
Delivery point description
A description of the delivery point
Delivery point type Depot or customer
Delivery point address The address of the delivery point
E-mail address or phone number
The default contact detail of the delivery point must be entered
Contact person The contact person at the delivery point
Delivery/pick-up point name
Delivery or pick-up point name
Source: Developed by the author for the purpose of the study
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• Hauliers
Table 4.5 Information required when adding a haulier
Information Requirement Description
Haulier code Unique haulier code
Haulier description A description of the haulier
Haulier point type Internal ( Clover)/ external to Clover Logistics
Haulier address The address of the haulier
E-mail address or phone number
The default contact detail of the haulier
Contact person The contact person
External hauliers’ credit number
All external hauliers have to have a credit number linked to them. This credit number is obtained from BPCS
VAT This indicates whether the external haulier must pay VAT to Clover or not
Purchase order generated
Whether or nor a purchase order must be generated on BPCS for this haulier. Purchase orders are not generated for in-house vehicles.
Source: Developed by the author for the purpose of the study
• Debtor code
Table 4.6 Information required when adding debtor codes
Information Requirement Description
Debtor code Unique debtor code
Debtor name The name of the debtor
Internal/External Whether the debtor is internal ( Internal to Clover/external to Clover)
Debtor address The address of the debtor
E-mail address or phone number
The default contact details of the debtor
Contact person The contact person Source: Developed by the author for the purpose of the study
• Reason codes
Reason codes are used when something in Magic does no go according to the plan.
For example if a hauler rejects a trip, a reason is assigned as to why the haulier
rejected the trip.
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Table 4.7 Information required when adding reason codes
Information Requirement Description
Reason code Unique reason code
Reason code description
A description of the reason code
Action/indicator The symbol that represents this reason code Source: Developed by the author for the purpose of the study
• Maintain next generated number
Magic does not have the ability to generate a unique ID for the RFS, TR and Tariff
number. Therefore the user has to generate the next unique number for the RFS, TR
and Tariff. This is done by opening up the “edit numbers file”, and entering in the next
number for the RFS, TR and Tariff.
Figure 4.8 Maintaining next generated numbers
Source: Clover Logistics, 2001; 23
Having to manually generate RFS, TR and Tariff numbers is an example of the
simplicity of the Magic system. Being able to auto generate a unique ID is an obvious
standard function of any modern software package.
4.3.7 Reporting
4.3.7.i Financial and load utilisation reports
Magic has the ability to calculate costs such as load utilisation and cost allocation.
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The following reports need to be generated before Magic is able to calculate costs.
All items showed on the following reports are problems which need to be resolved
before Magic can produce accurate cost calculation reports.
• List of RFS without orders
• List of duplicate orders
• List of orders not valid. This is determined by the order number not being
validated by the warehouse
• List of routes without kilometres
Once the above reports have been produced and all the problems identified have
been solved, the following cost calculation reports can be produced by first triggering
the cost calculation process by clicking on the ‘Prepare Data for Load and Cost
Calculations’ option, followed by the ‘Calculate Load Utilisation’ option and then the
‘Calculate Cost per Item’ option.
The following cost calculation reports can be produced when the cost calculation has
been completed.
• Load utilisation per Transport Request
• Load utilisation shipped per Transport Request
• Load utilisation from / to specific locations
• Cost per client
• Cost from / to delivery points
• Cost from / to, by department
• Cost from / to the manufacturer
4.3.7.ii General reports
The following basic Magic reports can be produced and exported to Microsoft Excel
when required:
• List of requested services
• List of transport requests
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• List of haulier confirmations
• List of transport requests delivered
• List of confirmations received
• Delivery schedules
• List of loads per haulier
• List of loads per route
• List of transport requests statuses
• List of transport requests without price
• List of transport requests without a purchase order
• List load/ haulier for pick-ups per day
4.3.8 Summary of the issues identified within Clover’s Magic system
Clover decided that it was time to replace its Magic software system with a new
scheduling and management system. Clover Logistics’ management felt that the
Magic system had reached capacity, had limits to its functionality, is labour intensive
and does not address their continuously expanding operational needs.
The following issues were identified with the Magic system:
• It is only a transactional system. The Magic system is a basic
transactional system and hence does not have the ability to handle the
following:
a. Complicated calculations such as the ability to calculate and
manage the variable costs of some of Clover’s subcontracted fleets.
b. Optimisation. As a result of Magic being merely a transactional
system, it does not have the ability to plan and optimise loads.
• In order to be able to have a global view of what is happening with
Clovers Logistics’ and their hauliers’ vehicles, the planning system
requires a graphical interface (Ghant chart) to enhance the planning
function which Magic does not have.
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• Magic is a vehicle allocation system and therefore in order to allocate the
costs, many manual steps have to be performed.
• There is no on-line connection to the system, therefore all requirements
are received via e-mail, telephone or fax and then entered manually into
the system, and Magic was only minimally integrated with BR and
BPCS. The result is that the process is labour intensive and error prone.
This situation was expected to worsen with an increase in Clover
business, additional satellite DCs and an increase in utilisation by
external clients such as Escort.
• Magic does not cater for loads undertaken for external parties, the
invoicing thereof, and the allocation of costs if the vehicle is shared
between Clover and external client loads.
• Communication with subcontractors is inefficient as it relies on e-mail,
the telephone and faxes.
• Magic does not adequately cater for multi pick-up and multi drop-off
loads. This is an underlying design flaw of the Magic database structure.
• Magic does not cater for cross-docking of vehicles.
• Magic does not have a view whereby the user can have global visibility
of the status of the request.
• Magic does not interface with satellite tracking systems, and therefore
does not provide a live update on the position of the vehicles in relation
to the planned trip.
• Magic does not allow for planners, dispatchers, warehouse managers
and hauliers to interact with the same job in real-time.
In conclusion, Magic was leading to much frustration as it could not satisfy all
Clover’s business requirements, and was not tightly integrated with any of Clover’s
other systems.
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4.4 A look at Clover’s new business needs and challenges
4.4.1 Clover’s new business needs and challenges
Clover Logistics’ new business needs were formed as a result of Clover Primary
Distributions’ goal to reduce the cost of primary distribution in the Clover Group.
Clover Primary Distribution identified four strategic pillars in which they needed to
excel, in order to reduce their costs and also improve their service offering, those
being:
• The need to take a national view on primary distribution in Clover
incorporating:
a. The transportation of semi-finished goods
b. Regional primary transport
c. An own primary distribution fleet
• The need to bring in collaboration partners that will complement their
existing network and at the same time benefit from it.
• The need to integrate, align and optimise together with reverse logistics,
the network of factories, secondary distribution branches and “direct
customers”.
• The need to administer the business in a complete way, and by
implication, fully integrate with other existing systems in the Clover
framework.
(Clover Logistics, 2003a; 9)
By implication, the above strategic pillars had the following operational
consequences for Clover Logistics:
• Taking a national view on primary distribution in Clover meant that
Clover Logistics had to have the capability to see the connection
between loads in various divisions, and in various regions of South
Africa. They had to be able to schedule their own vehicles in regions and
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between regions and report on their costs, and to be able to measure
and report on all of their primary costs and efficiencies.
• Clover needed to bring in collaboration partners who complimented their
existing network, which meant that they had to have the ability to
undertake collaborative loads, administer multiple charges, take
transport orders from outside Clover, and administer multiple pick-ups
and drop-offs.
• Clover wished to integrate, align and optimise, together with reverse
logistics, the network of factories, secondary distribution branches and
”direct customers”. They needed to schedule other factories and DC
loading and off-loading bays, see the forward and back hauls, select
optimal vehicle type and size and assign priorities to loads.
There was also a need to administer this business in a complete way and hence, fully
integrate it with existing systems, administer multiple tariffs and charge types, and
have immediate route profitability, paperless and email-less confirmation, as well as
needing error-free communication to and from their creditor and debtor systems.
4.4.2 An analysis of what led to the growth of Clover Logistics’ new complexities
and challenges
Before Clover Logistics’ management began to research new systems and
processes that were needed to handle their new business needs, they decided to first
understand what had led to their business needs “outgrowing” their current business
systems and practices.
It was found that the existing Magic system was not able to cope with:
• An increase in order volume. Clover order volumes soared to more than
3000 truck bookings and 7000 transport orders per month. Each truck
often transported goods for more than one principal with multiple pick-
ups and drop-offs. This number is double what Clover Logistics had to
cope with in the previous years.
• A growing fleet to deal with this increased order volume (Clover’s own
vehicles as well as external contractors).
116
• Shrinking time periods for scheduling and planning.
• The logistical and financial aspects of handling third party hauliers.
• The need for planners, dispatchers, warehouse managers and hauliers
to interact with the same job in real-time.
• The provision of accurate and realistic delivery schedules.
• New ways of logistical thinking, collaboration and flexibility.
(Clover Logistics, 2007a; 16)
In general, there was frustration with the Magic system as it could not satisfy all
business requirements, particularly the required tight integration with Clover’s
financial systems. The systems could also not handle multiple pick-ups and drop-offs
efficiently. (Clover Logistics, 2007a; 16)
4.4.3 Benefits which Clover Logistics management had hoped a new system would
achieve
In order for Clover Logistics to know what kind of system to look for and to
implement, Clover Logistics’ management came up with a list of benefits they would
like to achieve with a new system:
• Improved Clover vehicle utilisation
• Improved haulier fleet utilisation
• Improved haulier performance
• Increased revenue
• Reduced costs per kilometre
• Reduced cost per pallet
• Reduced travel time
• Increased planning and control of the Clover fleet
• Effective management (planning, organising, directing and control) of the
various hauliers and contracts
117
• Greater optimisation and scheduling of the vehicles
• Improved load planning
• Improved reporting and Key Performance Indicators (KPI’s) for Clover
and vendors
• Cost allocation of the products transported
• Increased tracking and visibility of the requirement
• Increased reporting functionality
• Audit trail on aspects requiring security
• Reduced error rate, resulting in improved service
• Reduction in communication costs
• Improved utilisation of operational and administrative staff (greater
automation)
• Improved proof of delivery (POD) administration process and invoice
process
(Clover Logistics, 2003a; 17)
In summary, Clover Logistics’ business needed a dedicated, customer-orientated,
haulier-orientated, one-stop operational command centre which is technologically
abled.
4.5 Summary and conclusion
Chapter four provided an overview of the logistics function of the Clover organisation.
The Clover Group is currently the largest dairy group in South Africa and collects and
processes some 30% of South Africa's milk.
As a result of Clover realising the critical importance of logistics in their organisation,
Clover decided to form Clover Logistics to handle all their logistics needs. This is a
division that specialises in the distribution of products for Clover, Clover Beverages,
Danone, as well as a large number of third party organisations. Clover Logistics is
118
the largest 3PL that focuses on the chilled and frozen distribution channel in South
Africa (Clover, 2007a; 5).
As a result of Clover Primary Distributions’ goal to drive down the primary distribution
cost in the Clover Group, Clover Logistics decided it was time to source and
implement a state of the art scheduling, haulier communication and finance system.
Chapter four takes an in-depth look into, including a step-by-step process of Clover
Logistics’ previous Magic system, as well as the reports that could be produced by
the system and data required to drive the system.
The chapter then continues by discussing Clover’s new business needs and
challenges, as well as the complexity of these needs. The chapter concludes by
looking at the benefits Clover Logistics’ management expected from a new, dynamic
system.
In conclusion, after looking at the complexities of Clover’s logistical needs, and after
analysing their old Magic system, it is evident that the Magic system could not
efficiently and effectively handle Clover’s growing business requirements. By utilising
the Magic system, millions of rands were being lost due to inefficient routes, incorrect
billing and payments, as well as inefficient use of manpower.
Chapter five focuses on the scoping, sourcing and implementation of a new software
system in order to allow Clover to better manage their business needs. The chapter
also discusses Clover’s new processes and will detail a step-by-step analysis of the
processes created by the new software.
119
4.6 Appendix
4.6.1 Capture an RFS
Annexure 4.1 Process flow of capturing a RFS
Source: Clover Logistics, 1998; 1
120
4.6.2 Allocate an RFS to a haulier
Annexure 4.2 Process flow of allocating a haulier to an RFS
ALLOCATE RFS TO VENDOR
Select Applicable RFS
1
Enter Route Code
2
Valid Route Code?
3
Enter Vendor No
4
Valid Haulier?
5 Valid Tariff?(Use Route and
Haulier to determine)
6
Update RFS status = 'A', tariff code =
chosen tariff
7RFS allocated to
haulier
8
Yes
YesNo
No
Yes
Re-enter Route and
Vendor
NoRe-enterRe-enter
ALLOCATE RFS TO VENDOR
Select Applicable RFS
1
Enter Route Code
2
Valid Route Code?
3
Enter Vendor No
4
Valid Haulier?
5 Valid Tariff?(Use Route and
Haulier to determine)
6
Update RFS status = 'A', tariff code =
chosen tariff
7RFS allocated to
haulier
8
Yes
YesNo
No
Yes
Re-enter Route and
Vendor
NoRe-enterRe-enter
Source: Clover Logistics, 1998; 2
4.6.3 Link orders to RFS
Annexure 4.3 Process flow of linking an order to an RFS
Select RFS with Requested PU date >= Today
1Zoom on applicable RFS to enter order
number
2Enter Order No and
Warehouse No where order
originated
3
RFS Linked to Orders
5Valid Order
Number Entered?
4
Re-enter
No Yes
Select RFS with Requested PU date >= Today
1Zoom on applicable RFS to enter order
number
2Enter Order No and
Warehouse No where order
originated
3
RFS Linked to Orders
5Valid Order
Number Entered?
4
Re-enter
No Yes
Source: Clover Logistics, 1998; 3
121
4.6.4 Generate transport request
Annexure 4.4 Process flow of generating a transport request
Enter Date From which to search for
RFS records
1Enter Date To
which to search for RFS records
2Enter vendor (Tariff code) or leave blank
for All vendors
3
Vendor > '' and Vendor valid?
4
Specify Print TR
5
Specify EMail TR
6
Choose to Start Process
7
NoRe-enter
Yes
Range on RFS with status = 'A', TR No = '', PU date = Date From
and DO date = Date To
8
Check for Multiple RFS with same
PU details
9
Multiple RFS exist?
10
Display RFS with same Tariff code, PU date >=
Date From and <= Date To and TR No = ''
11
User Must select which RFS's to group by
marking them
12
Check for Multiple RFS with same DO details
15
Display RFS with same Tariff code, DO date = First RFS DO date and DO time = first RFS
DO time and TR No = ''
17
User Input = 'Yes'?
13
Update chosen RFS with TR No = TR No from first RFS, Total No of Pallets =
+ Pallets on RFS
14
User Must select which RFS's to group by
marking them
18
User Input = 'Yes'?
19
Multiple RFS exist?
16
No
Yes
No
Yes
Yes
Yes
TR generated
20
No
No
Enter Date From which to search for
RFS records
1Enter Date To
which to search for RFS records
2Enter vendor (Tariff code) or leave blank
for All vendors
3
Vendor > '' and Vendor valid?
4
Specify Print TR
5
Specify EMail TR
6
Choose to Start Process
7
NoRe-enter
Yes
Range on RFS with status = 'A', TR No = '', PU date = Date From
and DO date = Date To
8
Check for Multiple RFS with same
PU details
9
Multiple RFS exist?
10
Display RFS with same Tariff code, PU date >=
Date From and <= Date To and TR No = ''
11
User Must select which RFS's to group by
marking them
12
Check for Multiple RFS with same DO details
15
Display RFS with same Tariff code, DO date = First RFS DO date and DO time = first RFS
DO time and TR No = ''
17
User Input = 'Yes'?
13
Update chosen RFS with TR No = TR No from first RFS, Total No of Pallets =
+ Pallets on RFS
14
User Must select which RFS's to group by
marking them
18
User Input = 'Yes'?
19
Multiple RFS exist?
16
No
Yes
No
Yes
Yes
Yes
TR generated
20
No
No
Source: Clover Logistics, 1998; 4
122
4.6.5 Receive confirmation from haulier
Annexure 4.5 Process flow of receiving a confirmation from a haulier
Enter TR number
1
TR Exist?
2 TR Status = 'Printed' or 'Allocated'?
3
Send Advanced Notification
5
Update TR status, write Transaction
log
4
Yes
NoNo
Extract Haulierdetail
6Extract Pick Up and Drop Off
detail
7
Mail already sent?
8
Send EMail
9
E-Mail Sent to Haulier
10
Yes
No
Do Not Send MailLeave Procedure
RECEIVE CONFIRMATION FROM VENDOR
Yes
Enter TR number
1
TR Exist?
2 TR Status = 'Printed' or 'Allocated'?
3
Send Advanced Notification
5
Update TR status, write Transaction
log
4
Yes
NoNo
Extract Haulierdetail
6Extract Pick Up and Drop Off
detail
7
Mail already sent?
8
Send EMail
9
E-Mail Sent to Haulier
10
Yes
No
Do Not Send MailLeave Procedure
RECEIVE CONFIRMATION FROM VENDOR
Yes
Source: Clover Logistics, 1998; 6
123
4.6.6 Confirm haulier transport request
Annexure 4.6 Process flow of confirming a haulier to a transport request
Enter TR Number
1
TR exist?
2TR Status = 'Delivered'
3Extract TR Information
4
Select Confirmed or Rejected
5
Confirmed / Rejected?
6Update TR Status
= 'Rejected'
7
Extract Tariff information
8
Get Pallet Conversions
9
Calculate standard tariff
10
Display standard tariff
11
Quote price = standard
tariff?
13
Display warning to user
14
Enter reason for price difference
15
Enter quoted transport price
12
Enter remarks to be printed
16
Update TR Status = 'Confirmed'
17
Yes
No No
Yes
Rejected
Confirmed
No
Yes
Enter TR Number
1
TR exist?
2TR Status = 'Delivered'
3Extract TR Information
4
Select Confirmed or Rejected
5
Confirmed / Rejected?
6Update TR Status
= 'Rejected'
7
Extract Tariff information
8
Get Pallet Conversions
9
Calculate standard tariff
10
Display standard tariff
11
Quote price = standard
tariff?
13
Display warning to user
14
Enter reason for price difference
15
Enter quoted transport price
12
Enter remarks to be printed
16
Update TR Status = 'Confirmed'
17
Yes
No No
Yes
Rejected
Confirmed
No
Yes
Source: Clover Logistics, 1998; 7
124
4.6.7 Confirm delivery of transport request
Annexure 4.7 Process flow of confirming a delivery of a transport request
Enter date to which TR's can be
delivered
1
Enter TR Number
2
TR Exist?
3TR Status = 'Recieved'?
4
Find all RFS for TR Number
6
Enter Date and Time delivered
7Update RFS status = 'D', date and time
= entered values
8
All RFS for TR delivered?
9Update TR status =
'Delivered', date = Last RFS deliver date
10
Yes
No
Yes
No
YesNo
Re-enterRe-enter
Next RFS
Is there an order linked for any RFS
on TR?
5
No
Re-enter
Yes
Enter date to which TR's can be
delivered
1
Enter TR Number
2
TR Exist?
3TR Status = 'Recieved'?
4
Find all RFS for TR Number
6
Enter Date and Time delivered
7Update RFS status = 'D', date and time
= entered values
8
All RFS for TR delivered?
9Update TR status =
'Delivered', date = Last RFS deliver date
10
Yes
No
Yes
No
YesNo
Re-enterRe-enter
Next RFS
Is there an order linked for any RFS
on TR?
5
No
Re-enter
Yes
Source: Clover Logistics, 1998; 8
125
4.6.8 Generate purchase orders
Annexure 4.8 Process flow of generating a purchase order
GENERATE PURCHASE ORDERS
Enter range of request numbers
1Select all TR's in
range with status = 'Confirmed'
2
Order Number exist?
3
Extract Vendor detail
4
Get tariff code
5
Generate PO for Vendor = Yes?
6
Check if PO exist
7
Does PO exist already?
8Yes
Get last delivery date of Request
9
Check tariff / quoted price
10
Authorise Quoted price
12
Calculate Tariff price (Vat?)
15
Update TR status = 'Posted'
16
Tariff / Quote price not equal?
11
No
Quoted price authorised?
13Write
exception entry
14
Yes
No
No
Yes
Get last delivery date
17
Calculate price for vat if vat payable
18
Yes
No
GENERATE PURCHASE ORDERS
Enter range of request numbers
1Select all TR's in
range with status = 'Confirmed'
2
Order Number exist?
3
Extract Vendor detail
4
Get tariff code
5
Generate PO for Vendor = Yes?
6
Check if PO exist
7
Does PO exist already?
8Yes
Get last delivery date of Request
9
Check tariff / quoted price
10
Authorise Quoted price
12
Calculate Tariff price (Vat?)
15
Update TR status = 'Posted'
16
Update TR status = 'Posted'
16
Tariff / Quote price not equal?
11
No
Quoted price authorised?
13Write
exception entry
14
Yes
No
No
Yes
Get last delivery date
17
Calculate price for vat if vat payable
18
Yes
No
Source: Clover Logistics, 1998; 9
126
Chapter 5
5 CLOVER LOGISTICS’ NEW SYSTEMS AND PROCESSES
5.1 The vision
5.1.1 Introduction
Clover Logistics expressed the need to review their routing, scheduling and financial
management transport system as a result of their rapidly growing business and their
need to improve the efficiency and manageability of their organisation. This led to the
introduction of new software systems and procedures to cope with the needs of a this
growing business.
This chapter begins by explaining what the management of Clover Logistics
envisioned in a new system. The chapter then explains the process Clover Logistics
went through in sourcing a new system and then details the new routing, scheduling,
and transport management system.
5.1.2 The Vision- What Clover Logistics needed
Prior to the implementation of the new fleet management system (Optima), Clover
Logistics operated in a linear style. Each department within Clover Logistics operated
within a silo, operating their own systems in which they had to manually feed in
information passed to them from other internal departments. Although Clover
Logistics had its own fleet, it also made use of a large subcontracted fleet which was
handled separately from the in-house fleet. Management and communication with the
external fleet was not handled directly through their internal systems, with all
management and communication taking place via e-mail, phone or fax.
After much investigation, Clover Logistics’ management came to the conclusion that
the key to improving their supply chain was through collaboration, within the Clover
Group itself, (including other departments such as finance and warehousing), as well
as collaboration with their external hauliers and clients. Clover Logistics’
127
management saw the collaborative process as a three-tiered process as can be seen
in figure 5.1.
Figure 5.1 Clover Logistics’ three steps to an evolving primary distribution
Linear• Own network• Own vehicles• Contractor
Collaboration
Collaboration through
aCoordination
Centre
Evolution
Linear• Own network• Own vehicles• Contractor
Collaboration
Collaboration through
aCoordination
Centre
Evolution
Source: Clover Logistics, 2007a; 17
In figure 5.1 three basic steps of the evolutionary process are shown. The first step
shows Clover Logistics’ historic situation, where they operated in a simple linear
framework. The second step shows the next stage of the evolutionary process, the
stage where they begin to collaborate with their hauliers, clients and other
departments within the Clover Group. Clover Logistics realised that only through true
collaboration and the building of long-term relationships with their partners, would
they be able to achieve the efficiencies and cost savings they were striving for. The
third step shows the end of the evolutionary process where they have a coordination
centre to manage their new collaborative business model.
To achieve meaningful collaboration across the supply chain is a constant challenge
which requires continuous attention. This would be achievable through an efficient
coordination centre that would be able to respond to and address these challenges.
Clover Logistics’ management established the following objectives for the co-
ordination centre. It should:
• Be able to “facilitate the exploitation of economies of scale, opposite
imbalances and other synergies in order to eliminate inefficiencies”.
• Interact between the respective supply chain departments.
128
• Interact between clients, hauliers, dispatchers and receivers.
• Deal with hauliers based on their geographical strengths.
• Completely remove duplication throughout Clover’s entire supply chain.
• Allow for more scope to react to the individual clients needs.
• Find partners to reduce imbalances such as found in return loads.
• Arrange transport for inbound raw materials.
• Save on charge-out rates because of network optimisation as a result of
a more global view and better management.
(Clover Logistics, 2007a; 18)
Figure 5.2 The extent of Clover’s required collaboration
Primary Coordination
Centre
Supply Chain Planning
ProductionTransport Contractors
Secondary Distribution
& DC’s
• Regional contracts• Focus on their strengths• Input in business case ( load and off load times)
• Batch sizes• Loading and off loading times• Loading per sku requirements• Send crates to factory in need
direct from secondary DC
• Equalization of trucks throughout the week• Collaborative loads• Truck utilization
• Loading times to suite contractor and for off
loading times• Quicker turn around
times
Principals
• Collaborative loads• Higher frequencies
• Integrate their complete network into ours
• Exploit synergies and opposite imbalances
Primary Coordination
Centre
Supply Chain Planning
ProductionTransport Contractors
Secondary Distribution
& DC’s
• Regional contracts• Focus on their strengths• Input in business case ( load and off load times)
• Batch sizes• Loading and off loading times• Loading per sku requirements• Send crates to factory in need
direct from secondary DC
• Equalization of trucks throughout the week• Collaborative loads• Truck utilization
• Loading times to suite contractor and for off
loading times• Quicker turn around
times
Principals
• Collaborative loads• Higher frequencies
• Integrate their complete network into ours
• Exploit synergies and opposite imbalances
Source: Clover Logistics, 2007a; 22
129
The objective of the control centre (see figure 5.2) is to interact and constantly
manage the relationship with the supply chain planning, production, hauliers, clients,
as well as with Clover’s secondary distribution, and Clover’s distribution centres.
5.1.3 The search for a solution
Following intense debate, Clover Logistics’ management concluded that the only way
they would be able to achieve the desired results of increased collaboration across
all aspects of their supply chain, would be through the use of new technology. New
technology would offer them a fully-integrated solution, incorporating planning and
optimisation, execution of loads, full integration with other systems and real-time load
visibility.
In order to solicit information about potential new technology, Clover Logistics
compiled and sent out a 46-page request for proposals to 13 suppliers whom they felt
would be able to present them with possible solutions. Clover’s in-house IT
department was also asked to put together a proposal on the possibilities and cost of
upgrading the in-house Magic system. Of the 14 suppliers that received the request
for proposal, nine responded with possible solutions. The first step was to narrow
down the list of the respondents. Three of the respondents were immediately
eliminated due to cost, and the remaining five respondents were given the
opportunity to provide Clover with a demonstration of the product they were offering.
The following respondents were eliminated after their demonstrations:
• Company A was eliminated as their transactional system was written in
MS Access which the Clover IT department felt would not be able to
handle the volume of data that would be required. The system was also
not able to integrate with Clover’s other management systems and the
planning system was inadequate.
• Company B was eliminated as they did not offer a planning system and if
FLO (Opsi’s planning and routing system) were added, it would become
too costly.
• Company C was eliminated as they proposed to use Collaborative
Exchange to facilitate their communication, which cannot be purchased.
130
Collaborative Exchange is similar to MQ adaptor, which is Clover’s
standard middle-ware system.
• The Clover in-house Magic system in its present form did not include a
planning system. It was considered too difficult to develop a
sophisticated planning system in-house, especially as there were
appropriate commercially available planning systems. The option of
redeveloping the Clover system and integrating it with FLO was
investigated. After discussions it became apparent that this would not
give the optimal solution, and that a greater degree of integration would
be achieved with the total solution being offered by Opsi Systems.
Further, it is Clover’s policy to purchase software packages rather than
develop solutions in-house, and therefore it was decided not to pursue
this option.
(Clover, 2003b; 8)
After eliminating all but two options, discussions began with Opsi systems and
Company D. After much discussion a list of the advantages and disadvantages was
drawn up on each organisation’s software system.
5.1.3.i Opsi Systems
The proposal from Opsi systems included their optimisation and scheduling tool Flo
II, which formed the core of their proposal and a transactional system called Optima
which still had to be developed.
(a) Advantages of Opsi systems as seen by Clover:
I. Product advantages:
• Flo had developed over eight years to be a market leader and an
outstanding planning and scheduling programme.
• Optima, which still had to be developed, would be developed and
customised in accordance with Clover’s requirements, therefore a 100%
fit to Clover’s business process would be achievable.
131
• Opsi systems proposed seamless integration between Flo, Optima and
Clover’s other systems.
• Opsi systems intended to develop and market Optima with or without
Clover’s participation, as they had three other potential clients.
• Opsi systems would develop any future upgrades to Clover’s
requirements.
• Optima would be fully aligned with Clover’s IT infrastructure.
II. Company advantages as seen by Clover:
• Opsi systems was a professional organisation with high caliber staff.
• Opsi systems was on the leading edge of IT as they had other major
clients with complex logistics systems.
• Opsi systems was a South African concern.
(b) Disadvantages of Opsi systems as seen by Clover:
I. Product disadvantages
• There is always risk associated with developing a new product,
especially as Optima still had to be developed.
• In the development stage there would be a excessive demands on
Clover and CIS (Clover Information Systems) personnel.
• Optima would draw from Clover’s and Opsi experience, but would not
necessarily include the experience gained over time or internationally.
II. Company disadvantages as seen by Clover:
• Opsi systems was still a small company, which comes with the
associated risk of dealing with a small new company.
(Clover, 2003b; 9)
132
5.1.3.ii Company D
Company D’s proposal included their optimisation, scheduling and transactional tool,
as well as their integration tool. The complete solution would be rented on an annual
basis from Company D and hosted at their premises in Sandton.
(a) Advantages of Company D as seen by Clover:
I. Product advantages
• Company D’s scheduling tool was an internationally used programme.
• Utilising Company D’s hosted option, would save on Clover
infrastructure and staff.
• No development was needed to implement, only configuration was
required.
• Visibility and communication to personnel outside Clover already
existed.
• Shorter implementation time due to the fact that no development was
needed.
• Lower risk as a result of the product already being tested in live
environments.
II. Company advantages as seen by Clover:
• Company D was a large company, which comes with the associated
advantage of stability.
(b) Disadvantages of Company D
I. Product disadvantages as seen by Clover:
• Clover’s business processes needed to be changed to fit the software
product.
• The software was inflexible outside programme parameters.
• There was a limited graphical interaction between programme and user.
133
• There were many functionalities that were included in the price that
would not be used.
• The system would never be owned by Clover Logistics.
• There were network, data security and data accessibility issues with the
product being hosted outside Clover’s network and premises.
• The cost of the product would escalate with the expansion of Clover’s
distribution.
II. Company disadvantages
• High costs of renting the software.
After weighing up the advantages and disadvantages of both organisations, Clover
Logistics made the decision to select Opsi systems as the technology provider.
5.1.4 The proposed solution
Optima was designed by Opsi systems to be the intelligent control centre that:
• Collates orders from numerous different integrated forecasting and
replenishment systems.
• Incorporates Opsi's Plato (Opsi’s new routing and scheduling
optimisation tool, which has been developed for primary distribution, as
apposed to FLO which is used for secondary distribution) scheduler to
assemble optimal loads using Plato sophisticated algorithms.
• Integrates with a variety of third party tracking providers allowing for real
time visibility.
• Allocates transportation costs and revenue information to shipments,
through its management of “debtor and creditor contracts and tariff
structures”.
• Easily manages large volumes of data through a user-friendly interface.
(Clover, 2007a; 32)
134
5.2 An in-depth look at Clover’s new technology information system
At present, Clover Logistics has nine Optima planners; each planner is responsible
for planning an order from the time it enters Optima until the time it is delivered.
Clover Logistics currently plans for ten different areas, with each planner being
assigned specific areas. The lead times from when an order enters the system until it
has to be dispatched from the pick-up point, vary between 12 hours and 7 days. As a
result of the varying lead time, it was decided to only plan loads a maximum of 72
hours in advance, and loads that came into the system later, would be planned when
they arrived in the system. This decision meant that only a small number of loads
could be planned on every schedule, which limits the optimisation that can be
performed by Optima. The original idea was to take a few hundred loads and
schedule them together in order to allow for optimisation, however, as a result of the
varying lead time, this was not possible.
There are five main stages an order goes through from the time it is entered into the
system, until the time that it is delivered, these being:
• Service Request Inception
• Planning
• Transportation Procurement
• Track-and-Trace
• Financial Administration
135
Figure 5.3 The Optima process flow
Step 7The Optima user generates accounts receivable and accounts payable vouchers in Optima and sends it electronically to
Clover’s accounting system.
Step 6The haulier delivers the load and
the delivery site marks the load as delivered via the Optima web
page
Step 5The haulier then picks up the load
and the pick-up site dispatches the vehicles via the Optima web
page
Step 4The hauliers confirms, rejects or queries the transport request via
his online web page
Step 3The Optima user then publishes
the transport request to the relevant haulier’s online web
page.
Step 2The Optima user schedules the
transport orders through the use of Optima scheduling and optimisation tool, Plato
Step 1a- BR predicts necessary stock and
generates orders for each DC.- Orders are sent through electronically to Optima
Step 1b- Outside clients such as Escort
e-mail their transport request though to the Clover planning
department for planning. - Order are captured into Optima
Step 7The Optima user generates accounts receivable and accounts payable vouchers in Optima and sends it electronically to
Clover’s accounting system.
Step 6The haulier delivers the load and
the delivery site marks the load as delivered via the Optima web
page
Step 5The haulier then picks up the load
and the pick-up site dispatches the vehicles via the Optima web
page
Step 4The hauliers confirms, rejects or queries the transport request via
his online web page
Step 3The Optima user then publishes
the transport request to the relevant haulier’s online web
page.
Step 2The Optima user schedules the
transport orders through the use of Optima scheduling and optimisation tool, Plato
Step 1a- BR predicts necessary stock and
generates orders for each DC.- Orders are sent through electronically to Optima
Step 1b- Outside clients such as Escort
e-mail their transport request though to the Clover planning
department for planning. - Order are captured into Optima
Source: Developed by the author for the purpose of the study
A detailed diagram depicting the process flow of Optima can be seen in annexure
5.1. The high-level processes in figure 5.3 are described in detail in the following
sections:
5.2.1 Service Request (SR) Inception
The service request screen allows the user to:
• Automatically import orders (service requests) from Clover’s Branch
Replenishment System. Optima polls the middleware constantly for new
SRs. Once a new message has been received from the middleware,
Optima automatically captures the SR information. Only requests
containing factory to DC, and full loads from factory to customers, are
sent automatically from the BR. This automatic importing of orders is one
of Optima’s major advantages. Importing the majority of orders instead
of manually entering them, saves on time and minimises for the
occurrence of error.
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• Manually create a new service request using the Optima service request
wizard. All third party orders, the transportation of raw materials, as well
as the transportation of crates are entered manually.
• Edit imported or manually created service requests
When a new service request is entered, the following information needs to be
captured:
• client
• order number
• loading window
• delivering window
• pick-up point
• delivery point
• quantity of pallets to be transported
The service request screen provides the user with a high-level overview of the status
of all service requests in Optima. From the service request screen, the user has
access to interfaces that allow viewing, addition and removal of service requests from
the system. At all times, the user has the ability to view the complete set of service
request details via a user-friendly grid screen. This global view of all the orders in the
system is an advantage of Optima over Clover’s previous system.
Once a service request has been completed, Optima automatically calculates the
amount that needs to be charged to the client, based on who the client is, the pick-up
and drop-off points, as well as a range of other factors that are described in
paragraph 5.2.5 detailing the different charge types.
A completed service request is then sent to the scheduler to be optimised with a
group of other service requests and placed onto a vehicle.
A complete list of all the service requests can be seen on this screen. Service
requests can also be filtered by many different categories, including: incomplete
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service requests, pending service requests, scheduled service requests, allocated
service requests, confirmed service requests, dispatched service requests and
delivered service requests. The service request screen can also be filtered for a
specific date range.
5.2.2 Planning
A core aspect of Optima is its scheduling and optimising functionality powered by the
Plato engine. Plato is based on Opsi System’s Flo, a multi pick-up and drop-off,
multi-depot and multi-day scheduling and tracking system, designed to improve fleet
utilisation and reduce operating costs.
The Plato scheduler interacts seamlessly with Optima, and the user does not know
that there is a separate piece of scheduling software running in the background. The
user has the ability, if necessary, to interact directly with the Scheduler in order to
manually adjust schedules where necessary.
Figure 5.4 The Plato Scheduler
Source; Opsi Systems, 2008b; 19
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Optimisation in Plato is performed through sophisticated algorithms that analyse data
relating to vehicles, products, drivers, customers and road networks, as well as data
from appointment, tariff and fleet availability tables.
The Plato algorithm is what is known as a ‘hill climber’ which tries to find the minimal
cost solution to the routing problem. This means that it starts with an initial
reasonable solution and then tries to improve on this by improving one small step at
time, where each small step improves on the current solution by decreasing the total
cost. The initial solution is found by clustering the orders geographically into
approximately the right number of routes. This clustering has a random component to
it, so it is necessary to run several iterations with different starting solutions. The
different initial solutions can lead to quite different optimised solutions. In order to
include delivery windows and other constraints into this paradigm, a penalised cost is
used. If any constraint is broken, a high cost is added to the current solution. For
example, if a delivery window is broken, a cost equivalent to twice the cost of that trip
could be added. This means that the cost Plato minimises is the sum of the actual
costs, plus the penalties for broken constraints. This is called the penalised cost.
When Plato creates a schedule, the available resources (trailers, truck tractors, rigids
and loading bays) are always respected. A schedule will never be created with more
than the allocated resources. If fewer resources are needed than are allocated, the
lowest cost solution will also minimise the number of resources used, so that the
Plato solution will often use fewer vehicles than the number that was allocated. (Opsi
systems,2006b; 27)
Plato schedules the vehicle while taking into account the factors in table 5.1.
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Table 5.1 The optimising engines’ parameters
Time constraints The optimiser considers appointments, business hours, customised delivery windows, average road travel times and location load/offload times.
Vehicle capacity Plato is responsible for ensuring that vehicles are not overloaded, but is not responsible for issues regarding warehouse capacity or stock. Plato is thus not responsible for ensuring that the despatch warehouse has the correct stock, or that the receiving warehouses have capacity to receive the stock. Warehouse vehicle constraints are supported in Plato.
Vehicle class Plato’s vehicle classes support multiple product class, i.e. explicit multiple-temperature class products are able to be transported on the same vehicle with Plato multi-compartment functionality.
Vehicle availability
Plato keeps track of the haulier’s fleet, and optimises while ensuring that vehicles that are not available are not double booked.
Distance Distances are based on the Plato road network. Plato is responsible for choosing the most optimal route between locations.
Cross-Dock points
The optimiser imports a list of cross-dock points before the optimisation is run. Cross-dock points are product-class specific.
Loading Bays Bays are classed as loading bays, delivery bays or loading and delivery bays. The optimiser assumes that all bays at a location are dedicated to primary logistics within the specified delivery window.
Source: Developed by the author for the purpose of the study
An often overlooked aspect of optimised schedules is the handling of loading bays.
Should a specific warehouse be equipped with multiple loading bays, Plato has the
ability to balance the collection of loads across these multiple loading bays. Plato
also has the ability to mark certain loading bays as loading, or unloading only, as well
as the option to designate certain loading bays for certain products only, such as
chilled products. When scheduling the vehicles, Plato takes account of loading bay
availability, as well as the constraints and schedules of vehicles to suit loading bay
constraints. Advanced scheduling techniques are supported, including cross-docking,
back hauls and shuttle services, as well as must-go/can-go orders. To avoid vehicles
arriving too late or too early at a site, Plato requires information regarding the
business hours of the pick-up and delivery points. Plato also takes into account
opening and closing times of sties. Plato allows Clover to adjust these opening and
closing times according to changing business requirements. This, coupled with the
loading bay optimisation, allows for more flexible scheduling at the pick-up and
delivery sites.
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When performing multi-day scheduling, information regarding the availability and
location of an organisation’s fleet is essential. Plato books vehicles that are currently
on a schedule as unavailable, and does not allow the new schedule to utilise their
vehicles for the booked time period. When performing optimisation, Plato takes into
account vehicle limitation criteria such as mass and volume, however Plato is not
responsible for packing the vehicles in an optimal manner.
When a new customer is added, it is necessary to physically place the customer in
the correct location on the map in order to allow Plato to know where to schedule the
vehicle to. The scheduler offers an attractive map interface, allowing on-screen Geo-
Coding, and interactive route viewing and editing.
Figure 5.5 The Plato Geo Coding interface
Source: Opsi Systems, 2008b; 22
Clover originally felt that it would be possible to schedule a week’s quantity of loads
at once. This would allow Optima to take a few hundred orders and place them on
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the vehicles in the most optimal way in order to minimise costs and vehicle utilisation.
As a result of extremely short lead times, as well as orders with longer lead times
having to be edited, Clover Logistics was not able to schedule a few hundred orders
at once. Clover now schedules a few loads at once, which reduces Optima’s ability to
optimise the loads. Clover does however, benefit enormously from Optima’s ability to
schedule loading bays, manage Clover’s and their sub-contactors fleets, calculate
travel distances and time, calculate offloading and loading times, as well as the ability
to plan and modify schedules through the Optima graphical interface which can be
seen in figure 5.7.
5.2.3 Transportation Procurement
I. Choosing a haulier
Once a schedule has been finalised by the user, a transport request is automatically
generated and all further handling of the transport request is done in the transport
request screen. In the transport request screen, the transport requests ready for
allocation are displayed. The user can view, edit or remove transport requests, as
well as decide whether to manually allocate a Clover vehicle, or send the transport
request to the haulier. If a Clover vehicle is to be allocated, Optima optimally selects
an available vehicle.
All transport requests that are ready to be allocated to hauliers are listed in the
transport request screen. Clover Logistics’ have dedicated hauliers for specific lanes
and hence depending on the lane, a haulier is allocated.
II. Confirming an offer to the allocated haulier
Once a haulier has been allocated to the transport request, the user then publishes
the request to the haulier’s web page. The transport request will then appear on the
hauler’s web page which can be accessed over the internet through a standard
browser. No special software is needed at the haulier’s site to access the haulier’s
web page.
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Figure 5.6 Haulier-web interface for tendered transport requests
Source: Opsi Systems, 2008b; 25
The haulier has the ability to see on the web page what loads are being offered to
him, including the following information:
• TR number
• Route
• Tariff-amount being offered to do the load
• Loading date and time
• Delivery date and time
• Number of drops
• Pallet quantity
• Vehicle type (ambient / chilled / frozen)
• Recommended vehicle capacity
• Product type
• Value of the goods to be transported (for insurance purposes)
• Related order numbers
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The haulier then has the choice to accept, reject or query the load. The system
allows the haulier to include reasons for rejection, as well as changes to the
proposed tariff.
If accepted by the haulier, the transport request status is changed to ‘allocated’, and
the transport request appears on the relevant warehouse and haulier web-based
interfaces.
Figure 5.7 Haulier-web interface showing allocated transport requests
Source: Opsi Systems, 2008b; 26
If the haulier queries the offer and the proposed changes seem acceptable to the
user, an updated transport request will appear on the hauler’s online system, again to
be either accepted or rejected by the haulier. Should the hauler’s changes be
deemed unacceptable, the user can propose another haulier to offer the service.
Clover’s planners are allowed to accept any proposed tariff within R500 of the
originally proposed tariff. An amount larger than R500 has to be authorised by the
planning manager.
In order to ensure that there is no confusion, the haulier has to be confirmed by the
user. Once the user confirms the haulier, the transport request appears as confirmed
on the haulier web page and the hauliers must now allocate the appropriate
resources to pick-up the load.
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Sometimes hauliers are not able to make use of the web page as either they are out
of the office and cannot access the web, or at other times exterior factors such as
power failures prevent them from accessing the web page. In these situations a
phone call is used to convey the applicable data and to confirm a load.
The haulier web page is another benefit of Optima. This web page minimises errors
that are made when capturing data from a phone conversation or fax as was
previously done with the Magic system. It also reduces the Optima planners’ time as
they are saved from having to capture the data manually.
III. Confirming the dispatch and delivery of a transport request
Confirmation of the dispatch and delivery of goods is entered into the web-based
track-and-trace interface. Once the transport request has left the warehouse, the
relevant authorised warehouse personnel or haulier representatives, log into the site
dispatch web page, update the status of the transport request to “dispatched” or
“delivered”, as well as update other relevant details such as departure date and time.
Figure 5.8 Web-based track–and-trace interface
Source: Opsi Systems, 2008b; 27
For third party clients who do not have access to the web page, the Optima user
phones the dispatch and delivery point to confirm dispatch and delivery, and
manually updates the relevant information in Optima.
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According to Clover’s planning manager, the site web page is extremely useful for
the DC and CDC as they can log on at any time of the day or night, and have full
visibility as to what loads are going to be dispatched or received from their site. This
allows them to plan appropriately (Hoeksma, 2008).
Once the delivery has been confirmed, the status of the transport request and
corresponding service request/s are changed to “delivered”, and the relevant parties
are notified via their online systems. Once delivery of the goods has been confirmed,
the financial process is initiated.
5.2.4 Track-and-Trace
Optima allows the user to monitor TRs while they are in-transit. The provided
information includes:
• Current location
• Expected time of arrival (ETA) at next stop
• Current temperature
• Delay reason code (if applicable)
• Comments
The tracking of an in-transit vehicle is accomplished through Optima integrating with
the haulier’s GPS tracking system, and will update the current location and ETAs
automatically.
Although the GPS integration could save the Optima user much time as it would save
them from calling the drivers to follow up on their current status, it has not been
implemented at Clover Logistics as yet as the management of Clover Logistics views
other Optima modules as priority.
5.2.5 Financial Administration
Once the haulier has picked up a load and the load has been marked as dispatched,
the Optima user can then generate accounts payable (AP) vouchers. Once all the
service requests relating to a transport request have been delivered, the Optima user
can then generate accounts receivable (AR) vouchers.
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The AP and AR vouchers are calculated based on 4000 different charge types.
Optima references the charge type that is applicable to the specific client or haulier,
and then calculates the correct charge based on the relevant variables in the charge
type. The ability to calculate vouchers based on a large variety of charge types for
the haulier, as well as the client, is a competitive advantage that Optima has over
Clover’s old Magic system. Clover is in the process of going live with the AR process.
The AR and AP vouchers are then exported to BPCS and MRP2 (Clover Logistics’
financial system) for use by Clover’s financial department. Optima initiates the
creation of a purchase order in BPCS and receives a confirmation order number back
from BPCS. Optima initiates the creation of a client invoice in MRP2 and receives a
confirmation invoice number back from MRP2.
It is important to note that Optima is not responsible for the actual creation of the
invoice and debit note, but merely transfers the applicable information required by the
financial system to generate these documents.
5.2.6 Master data management
Managing and maintaining master data is a critical element in ensuring that Optima
runs optimally and produces the correct results. Master data does not need to be
handled on a daily basis, and only needs to be managed when something changes
or new data needs to be added. All master data management at Clover is handled by
the planning manager, as normal users do not have access to modify master data.
In order to fully understand the importance of master data, a brief explanation of how
Optima works is set out in the following paragraphs.
The blue circles in figure 5.9 represent an example of pick-up and delivery points
(called sites). These sites are physically placed in the correct location on the map
through a process called Geo-Coding described previously. Sites are then grouped
into areas (called area groups), as can be seen by the red circles circling the sites.
The red circles are then linked to one another by the purple line called a lane. Each
lane has a tariff associated with it as can be seen by the box. A tariff is a collection of
charges. Each haulier and each client have thier own tariffs for the lanes. Each tariff
has a collection of charges associated with it.
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Figure 5.9 How AP and AR vouchers are calculated in Optima
Source: Developed by the author for the purpose of the study
When Optima produces accounts payable and accounts relievable vouchers, it looks
at which area groups the pick-up and drop-off site are located in, then it looks at
which lanes link the pick-up and drop-off area group, and what tariff and charges are
associated with that lanes for that specific client or haulier. Based on this specific
information, a voucher is then created.
A detailed description of the master data is presented below.
• Haulier Information
Hauliers need to be added to Optima’s database whenever a new haulier is used to
render transport services. BPCS is responsible for the initial capture of haulier
information, after which an electronic update automatically creates the haulier within
Optima.
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Table 5.2 Information required when adding new hauliers
Information Requirement Description
Haulier ID Unique Identifier for haulier
Description Haulier description
Physical address Physical address for haulier
Postal address Postal address for haulier
Telephone number Telephone number
Contact person Contact person at the hauliers
Insurance cover The financial amount of the goods transported
Internal / external Haulier
Flag indicating whether the haulier is an internal service provider or an external service provider
ERP supplier code Code used for haulier in the ERP system
Billing type Determines whether a purchase order will be generated over multiple transactions or per transaction or not at all
Active/inactive Flag to indicate whether haulier is still being used or not
Source: Opsi systems, 2004; 39
Optima does not own haulier data and relies on regular synchronisations with the
ERP system to maintain its database. If a haulier is made inactive, no new TRs can
be allocated to that specific haulier. A haulier can not be deleted while there are still
open transactions pending against the haulier.
• Client Information
Clients need to be added to Optima’s database whenever a client is acquired for
whom a transport service is performed. BPCS is responsible for the initial capturing
of a certain client’s information, after which an electronic update automatically
creates the client within Optima. Other clients information, such as third party clients
are captured directly into Optima.
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Table 5.3 Information required when adding new clients
Information Requirement Description
Client code Unique client code
Client name Full client name
Physical address Physical address of client
Billing address Billing address of client
Tel number Contact numbers for the client
Contact person Contact person at the client
Active/inactive Flag signifying whether the client is still active or not
Source: Opsi systems, 2004; 39
Optima does not own all its client data and relies on regular synchronisations with the
ERP system to maintain its database. If a client is made inactive, no new SRs can be
accepted from that client.
• Sites
Site-related information is stored in Optima. The location can be accurately Geo-
Coded (placed in the correct location on the map) using the Plato Geo-Coding
interface as can be seen in figure 5.5.
Table 5.4 Information required when adding new sites
Information Requirement Description
Location type Depot or delivery point
Address Physical address of site
Contact details Contact details of site
Loading and offloading times
Loading and offloading time of the site
Operating hours Operating hours of the site
Vehicle exclusions Vehicles that are not able to enter the site due to size constraints
Source: Opsi systems, 2004; 45
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• Areas Groups
An area is defined by a collection of geographical areas. Optima provides the ability
to define areas. Optima owns area group data and hence the Optima users are free
to add, remove and modify areas and locations via the map interfaces.
Table 5.5 Information required when adding an area group
Information Requirement Description
Area group ID Unique identifier for area group
Area group name Unique name for area group
List of area in area group List of geographical areas in Area group
Source: Opsi systems, 2004; 45
• Lanes
A lane is defined by an origin area group and destination area group. The lane
essentially links two area groups with an associated tariff. All lane data is stored in
Optima, and therefore the Optima user is able to add, remove and modify lanes.
Table 5.6 Information required when adding a new lane
Information Requirement Description
Lane ID Unique identifier for lane
Lane name Unique name for lane
Route description Long description for lane
Origin area Geographical area where the lane originates
Destination area Geographical area where the lane terminates
ERP route code The lane code used in the ERP system
ERP route reference An additional lane reference
Active/inactive Flag for activating or de-activating Routes
Haulier performance The performance of the haulier on this route
Source: Opsi systems, 2004; 43
Lanes are not bidirectional, and hence a different rate has to be entered for the
reverse haul of a specific route.
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• Tariffs
A tariff is defined as “a collection of charges per route, per haulier/client, per vehicle
type” (Opsi Systems, 2003a; 7). Optima owns the tariff data, and therefore allows the
Optima user to add, remove and modify tariffs.
Table 5.7 Information required when adding a new tariff
Information Requirement Description
Unique ID System generated ID
Name Unique name for tariff
Description Description of tariff
Haulier ID or client ID The haulier to whom the tariff applies
Effective date Date the tariff becomes effective and available for use
Expiry date Date the tariff expires and is not available for use
Route ID The route associated with the tariff
Charge information The list of charges associated with the tariff
TL / LTL Truck load or less than truck load
Vehicle class ID The vehicle class associated with this tariff
Source: Opsi systems, 2004; 40
Tariffs may be marked to take priority over older tariffs. When priority tariffs are
created, the effective date remains unchanged and the current tariff’s expiry date is
changed accordingly. For non-priority tariffs, the current tariff’s expiry date remains
unchanged, and the new tariff’s effective date is changed accordingly. The effective
period for a tariff cannot overlap for a specific haulier. Only one tariff may be valid for
a specific haulier at a specific time.
Tariff changes range from global changes such as percentage increases in the fuel
charge, to structural changes such as a rate per pallet charge being replaced with a
fixed charge. Optima allows the user to capture the new charges or apply changes to
existing ones. Optima also allows for the global updating of tariffs. When selecting
the tariffs to update, the system allows the user to filter on haulier, route or charge
type. In addition, the Optima user is able to specify a value change or a percentage
change.
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Optima also supports the global updating of fuel costs. Explicit fuel charges are
simply separate charges linked to a tariff and are modified as discussed here. Implicit
fuel charges are not separate charges. Often, hauliers agree that a percentage of
their fixed charge will be for fuel. Recognising this difference, Optima performs global
updates accordingly.
• Charges
Charges are the price components of a tariff. Multiple charges can be linked to a
tariff. Charges include: (1) fixed charges, for example a toll fee or admin fee, or/and
(2) variable charges, for example a cost per pallet or cost per kilometre (3) discounts
(a negative charge).
Table 5.8 Information required when adding a new charge
Information Requirement Description
Charge ID User defined charge ID
Charge description Description of charge
Charge type Fixed, per pallet, per kilometre, per stop, etc.
Charge validity period The specific time period when the charge is valid from and until
Source: Opsi systems, 2004; 41
Optima has a large number of different charge types. A number of different charges
can be used concurrently for one tariff for one lane. For example, a flat rate of
R 3 000, as well as a per unit of measure (UOM) of R 100 per ton could be used for a
particular tariff. Optima will then add the flat rate and the per UOM rate to provide the
total chargeable amount.
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Table 5.9 List of various different charges
NAME DESCRIPTION
Trip flat rate Single amount for the trip (haulier)
Labour Single amount for labour
Fuel flat rate Single amount for fuel
Shipment flat rate Single amount for the shipment (client)
Per UOM (actual) Amount per unit (pallet), based on the actual quantity
Per trip kilometre Amount per kilometre travelled in total by the vehicle
Per trip hour Amount per hour travelled in total by the vehicle
Per kilogram (actual) Amount per kilogram, based on the actual quantity
Per UOM (planned) Amount per unit (pallet), based on the planned quantity
Per kilogram (planned) Amount per kilogram, based on the planned quantity
Flat rate for UOM Single amount based on the unit type
Per UOM (actual) by majority
Amount per unit (pallet), based on the actual quantity of unit that is in the majority on the trip
Per UOM (planned) by majority
Amount per unit (pallet), based on the planned quantity of unit that is in the majority on the trip
Flat rate for UOM by majority
Single amount, based on the actual quantity of unit that is in the majority on the trip
Spot flat rate Variable amount, entered before despatch
Per pick-up
Amount per pick-up (can be specified to activate after a number of pick-ups, e.g. charge R100 00 per pick-up only after the first 2 pick-ups)
Per drop Amount per drop (can be specified as above)
Per stop Amount per stop, i.e. pick-up or drop-off (can be specified as above)
For any pick-ups
Single amount, based on the number of pick-ups after a specified amount (e.g. charge a flat rate R1000.00 if there are more than 3 pick-ups)
For any drops Single amount, based on the number of drops (specified as above)
For any stops Single amount, based on the number of pick-ups and drops
Source: Developed by the author for the purpose of the study
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• User Types , permissions and log
Optima provides the ability to create user-defined user types and their associated
permissions. Permissions are customised per user type, per screen and per function.
For financial, operational and legal reasons, the use and functioning of Optima is
transparent, with each transaction and event logged by the system. The Optima log
itself consists of a set of tables in Optima’s database, containing the following
information for each event:
I. Timestamp
II. User
III. Event type
IV. Field changed
V. Field value before change
VI. Field value after change
VII. TR/SR reference
VIII. Reason code
• Vehicle Details
Optima owns the vehicle class and vehicle data since it maintains the information
regarding each haulier’s fleet for purposes of accurate optimisation and vehicle
tracking.
Table 5.10 Information required when adding a new vehicle
Information Requirement Description
Name Description of vehicle class
Dimensions Length, width, height
Capacities Unit, volume and mass
Operating hours Operating hours of the vehicle class
Product class exclusions Which product/s may not be transported on the particular vehicle
Source: Opsi systems, 2004; 46
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• Reason Codes
The use of reason codes is strictly limited to events that require specific authorisation
for example, accepting a load on behalf of a haulier.
Table 5.11 Information required when adding a new reason codes
Information Requirement Description
Code Reason code
Category To what Optima module does this reason code refer
Description Comments
Source: Opsi systems, 2004; 47
• Products
In Clover’s case, Optima has three products, chilled pallets, ambient pallets and a
normal pallets. Optima is not concerned with what SKU is on each pallet. All SKU
information is stored in BPCS and is linked to the pallets in Optima through an order
number.
• Loading bays
Optima requires the user to enter in the number of loading bays at each site, as well
as other loading bay specific information that can be seen in table 5.12.
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Table 5.12 Information required when adding new loading bays
Information Requirement Description
Name Loading bay name
Number of loading bays The amount of loading bays at the site
Product exclusions Eg: a product that needs to be refrigerated is excluded from a non-refrigerated loading bay
Vehicle exclusions Eg: a refrigerated vehicle is excluded from a non-refrigerated loading bay
Loading/offloading Does the loading bay facilitate loading or offloading , or loading and offloading
Loading and offloading times
The amount of time it takes to offload an item/volume at that loading bay
Loading bay open time What days of the week and what times are the loading bay open to receive and dispatch loads?
Source: Developed by the author for the purpose of the study
5.2.7 Reporting
Optima’s reporting capability provides intuitive access to information contained within
the system. Through the use of Microsoft SQL server reporting services, Optima
reports are accessible from either a screen display, a printout, a PDF file or from a
Microsoft Excel file.
The following Optima reports are available:
• PLANNING
o Transport requests per planner
o Daily haulier schedule
• TRACK AND TRACE
o Early /late transport requests
o Track-and-trace information for a specific transport requests
• ADMIN/FINANCE
o Tariffs per haulier
o Transport requests costs per haulier
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o Payment status of haulier invoices
o Costs per service request type
o Total cost for routes
o Cost comparisons (per pallet/per route/per kilometre/per client/per
haulier)
o Invoiced income per client
o Unit costs (rand per pallet per route per client per km, etc.)
o Unit cost per haulier
o Profit per haulier per route
• ANALYSIS
o Service request / transport request history
o Haulier per route and vehicle type
o Trips per route
o Service requests / transport requests per status
o Status for service requests / transport requests
o Transport requests per client per route
o Transport requests with/without referenced POs
o Reason codes for cancelled transport requests
o Vehicle utilisation
o Haulier performance
o Hours per trip per route
• DATA MANAGEMENT
o Client details
o Haulier details
o Master route details
o Routes with/without segment codes
5.2.8 General benefits achieved through using Optima
In general, Optima is a fully-integrated software system that caters better for Clover
Logistics’ business needs.
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The following benefits are achieved through the use of Optima:
• Optima is an integrated solution that integrates with all Clover existing
systems allowing for error-free communication between the relevant
systems.
• Much time is saved as a result of the majority of manual data capturing
having been eliminated through the use of Optima.
• Optima has the ability to perform complicated calculations, and calculate
the relevant amount needed for each AP and AR voucher by referencing
over 4000 charge types.
• Optima allows for a global view of the current status of all relevant
transport orders.
• Through Optima’s integration with Plato, Optima is able to manage
Clover’s internal and external fleets, while at the same time optimising
vehicle usage and scheduling vehicles around loading bay availability.
• Optima is able to comfortably handle Clover’s growing order volume.
• In contrast to Magic, Optima is able to produce accounts receivable
vouchers allowing for accurate invoicing of Clover Logistics’ clients.
• Communication with subcontractors is efficient as it relies on a web
page, ensuring no errors are made while capturing data from a phone
call and faxes.
• Optima is able to optimise and schedule multi pick-up and multi drop-off
loads.
• Optima caters for the cross-docking of vehicles.
• Although not yet activated, Optima interfaces with satellite tracking
systems and provides a live update on the position of the vehicles in
relation to the planned trip.
• Optima allows for planners, dispatchers, warehouse managers and
hauliers to interact with the same job in real-time.
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• Improved reporting enables Clover Logistics’ management to make
better business decisions.
In conclusion, Optima allows Clover Logistics to better manage their organisation and
hence improve on their profits. A detailed analysis of the benefits both financial and
other will be presented in the following chapter.
5.2.9 General concerns resulting from the implementation of Optima
As a result of Optima being custom developed to suite Clover Logistics business
needs there were no direct drawbacks of Optima that were not already present in
Clover’s previous Magic system. A few concerns around the implementation of
Optima are listed below:
• The financial administration of the Optima system is very complicated.
This complex structure is however necessary in order to allow for proper
financial visibility.
• When Clover Logistics began implementing Optima’s tracking module, it
became evident that hauliers were not happy to share their GPS
information with Clover. This challenge resulted in Clover Logistics
postponing the implementation of the tracking module indefinitely.
• At the beginning of the Optima implementation, one additional Opsi
employee was dedicated to the Clover implementation. However, after a
year Clover realised that having a dedicated person managing Optima
was a critical aspect of its success. This resulted in an additional annual
expense that was not budgeted for at the outset of the project.
• Presently a large percentage of the information in Optima has to be
extracted by Clover’s in-house IT department, as Optima does not have
the necessary reports to produce the needed information. As a result of
Clover Logistics initially relying on their in-house IT department to extract
the data required from Optima, reports in Optima have not yet been
developed as necessary (Fourie, 31 July 2008).
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5.3 The implementation of Optima
5.3.1 Managing the implementation
In order to ensure optimal project management, Opsi systems decided to bring in a
third-party project management specialist, namely REDINK Solutions.
The objective of bringing in a third-party project management specialist was to:
• Enhance the quality of the implementation with their extensive
experience in the implementation of primary distribution solutions.
• Ensure that all stakeholders (both Opsi Systems and Clover) are
delivering on project objectives and deliverables in a timely manner.
In order to ensure that the project runs according to plan, REDINK Solutions provided
a dedicated project manager to coordinate all project management related activities.
The following functionaries attended a weekly meeting where the status of the project
was discussed and any issues that had arisen during the previous week were
discussed and resolved. The project team consisted of operational and IT personnel
from Clover, development and implementation personnel from Opsi systems, as well
as an external project manager from REDINK Solutions.
• Project Manager at REDINK Solutions
• Leading developer from Opsi systems
• Systems manager at Clover
• Project manager from Clover IT perspective
• Management of Clover infrastructure and interfaces
• Business analyst
• Systems analyst
• Project sponsor from Clover Logistics
• IT process architecture at Clover
• Head implementer from Opsi systems
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A progress report was produced on a weekly and monthly basis, and discussed at
the weekly project meetings and monthly steering committee meetings.
5.3.2 Project Plan
A project plan was drawn up to ensure the smooth running of the project. The Project
started on the first of December 2003, and the estimated go-live for the first business
function was scheduled for 8 August 2004.
During the design stage of the project, an extremely detailed specification document
was written including process flows, screenshots and mock-ups. Opsi systems then
worked closely with Clover’s ERP consultants and developers to specify all the
interfaces. Once the specification was finalised, it was signed off by Clover Logistics
and Opsi systems. As soon as the development was completed, configuration of
Optima began and the database was populated by defining all drop points,
distributions centres, hauliers, tariffs, and other relevant master data.
Although the individual system components were tested by Opsi systems at their
offices, on-site end-to-end testing ensured that the integration with Clover’s other
systems worked as planned, thus ensuring that an order could be processed
efficiently, and that the system was able to handle the transaction volumes.
5.3.3 The Implementation and development team.
The Optima implementation and development team comprised of the following:
Opsi systems Personnel
• One web developer
• One middleware developer
• One Plato developer
• One Optima developer
• One GPS tracking integration developer
Clover Personnel
• One project manager
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• One Optima system administrator
• Two staff members from Clover’s IT department
• Three operational personnel
• Various operational and financial consultants
5.3.4 Integration with the Clover ERP system
A key aspect of Optima was the integration with Clover’s existing systems. Optima
integrates with a number of Clover back-end systems, including Clover’s existing
ERP and financial system via IBM WebSphere MQ.
Figure 5.10 Integration with Clover’s ERP system
OPTIMA MIDDLEWARE
IDS / BPCS
BR
WM
QW
MQ
WM
Q
Source: Opsi systems, 2004; 13
BR (branch replenishment) is Clover’s branch replenishment system which does
forecasting based on past sales. BR creates the orders and sends them to BPCS
(business planning and control system) which is Clover’s ERP system. At the same
time, when BR sends the orders to BPCS, it simultaneously sends the orders to
Optima (Opsi Systems, 2003b; 7).
5.3.5 Challenges faced when implementing Optima
Many challenges were faced when developing and implementing Optima, some large
and some small. A few of the challenges are discussed below:
• Although order lead-time varied from a week down to 12 hours, orders
that were received a week in advance often changed. The challenge was
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how to change orders once they had already been scheduled, and
hauliers procured. The decision was made to plan orders 72 hours in
advance in order to allow orders that changed to be changed outside of
Optima, and planned correctly once in Optima. This however had a
negative impact on the optimisation of loads and vehicles.
• Multiple service requests would often be planned on one vehicle and
often even from different clients. The complication arose as how to
produce financial vouchers for all these different shipments that were
being delivered on the same vehicle. A decision was made to produce a
voucher per SR or shipment as opposed to per trip. This meant that
multiple shipments could be delivered on one vehicle and each shipment
could be charged to its respective client.
• A constant challenge was the integration of Optima with the relevant
Clover systems, as there were many different messages that need to be
passed continually between Optima and the relevant Clover systems.
Each different message had to be carefully discussed with the relevant
parties, and only after much testing was the integration finalised.
• Another constant challenge was the gathering of master data in order to
input it into the Optima database. Data such as the addresses of all
delivery points was required in order to plot them on a map. This was
extremely difficult to gather. Eventually, 70 delivery points had to be
phoned in order to obtain their physical addresses. To gather up loading
bay data, and loading and offloading times at the relevant Clover depots,
the Clover planning manager had to travel to all the Clover depots and
physically count how many loading bays there were. She also had to
calculate, based on the number of staff and equipment available, how
long loading and offloading took.
• Training all the relevant parties in the new system was also a large
challenge. Many different parties had to be trained, including the
planners, hauliers, clients, as well as other Clover personnel such as
those involved from the finance department. Coordinating and providing
the training was a time consuming, challenging task.
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• The methodology used to calculate haulier tariffs had to be interrogated
and captured into the system.
• Overcoming the resistance for change from the users and hauliers was a
large challenge. The users and hauliers were used to the old way of
doing things, and were concerned about the change(
Holtzhausen,2008).
As can be seem from the challenges described above, some of the challenges were
trivial, such as collecting address information, and others were more complicated
such as deciding on the best way to send every message to and from Optima. These
challenges took time and resources to resolve.
5.4 Summary and conclusion
Clover Logistics felt it was time to begin sourcing a new dynamic routing scheduling
and financial management transport system as a result of their speedily growing
business, and their need to improve the efficiency and manageability of their
organisation.
After much investigation, Clover Logistics’ management came to the conclusion that
the key to improving their supply chain was through collaboration with their internal
departments, as well as collaboration with their hauliers, clients and warehouses.
Clover Logistics realised that collaboration on this scale required new technology to
facilitate the necessary communication.
A request for proposal was sent out to 13 suppliers who Clover Logistics felt would
be able to present them with a possible solution. After much deliberation over the
proposed solutions, Clover Logistics decided to appoint Opsi Systems as their
technology provider.
Chapter five explained how Optima was developed and implemented, including some
of the challenges that were faced when implementing the new software.
There are five main stages an order goes through from the time it is entered into the
Optima, until the time it is delivered. Each stage was explained in detail, including
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how Optima calculates the relevant financial vouchers and the master data needed
for the system to operate smoothly.
Chapter five concluded with an explanation of how the Optima reporting function
works, as well as a list of reports that can be run from Optima.
In conclusion, Optima was developed to suit Clover Logistics’ business needs. It
tightly integrates with Clover’s other departments, and through the web portal allows
seamless communication with external hauliers and Clover warehouses. Optima also
allows for seamless integration with Clover’s financial systems, ensuring that no data
needs to be entered manually in order to invoice customers and pay hauliers.
Chapter six will begin with a comparison between the old and new systems at Clover
Logistics. The advantages and disadvantages obtained from implementing new
technology into the supply chain will be discussed. Clover Logistics’ costs, as well as
other important factors such customer service and their relationships with external
hauliers will be analysed.
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5.5 Appendix
Appendix 5.1 Summary of the Optima Process
Source: Opsi Systems, 2003b; 12
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Chapter 6
6 AN ANALYSIS OF CLOVER LOGISTICS’ OLD SYSTEMS
AND PROCESSES COMPARED TO THEIR NEW
SYSTEMS AND PROCESSES
To be able to fully comprehend the advantages and drawbacks of the implementation
of Optima into Clover Logistics, it is necessary to look at both the qualitative and
quantitative improvements and drawbacks that have occurred as a result of the
implementation of Optima. Chapter six will begin by explaining the qualitative
improvements and drawbacks that arose from the implementation of Optima. The
qualitative improvements and drawbacks that resulted through the implementation of
Optima will be looked at from a number of different angles, including:
• The integration of Optima into Clover’s various ERP, financial and
tracking systems.
• Optimal routing and scheduling of Clover’s and their hauler’s vehicles.
• The financial capabilities provided by Optima.
• The communication capabilities provided by Optima.
• Numerous different improvements provided by Optima.
Chapter six will continue by quantifying the improvements that arose from the
implementation of Optima. Although financial savings can be indirectly attributed to
many of the qualitative benefits, the only financial savings that can be directly
accredited to the implementation of Optima are those savings achieved through
improved vehicle utilisation as a result of improved routing and scheduling.
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Clover Logistics was extremely helpful in providing all of the information gathered in
this study; their records, however, lacked in certain areas. For the limitations of this
study, see the footnote*.
6.1 A qualitative comparison between old and new processes
Four main qualitative aspects were improved upon as a result of the implementation
of Optima, those being integration into Clover’s ERP, financial and vehicle tracking
systems, improved routing and scheduling, generation of financial vouchers, and
improved communication between hauliers, clients, warehouses and Clover’s
management. The following section will take an in-depth look at the qualitative
improvements and drawbacks that arose from the implementation of Optima.
6.1.1 Integration
Integration is a major advantage of using technology. Section 3.2.1 in the discussion
of the advantages of technology, points to how technology allows for system-driven
activities as opposed to human-driven activities, resulting in a decrease in human
error-related incidents. Elsewhere in chapter three it mentions how business
management technology gives small and medium enterprises an advantage by
automating the flow of information between departments, and reducing mistakes
associated with the double-entry of information across systems, thus creating a more
efficient supply chain. This section takes a closer look at the different aspects of
integration between the systems in Clover Logistics and how the organisation
benefited from it.
*Firstly, when calculating Clover Logistics’ total savings, indirect benefits such as savings
in communication costs and benefits resulting from on-time payment were not included.
This is a result of some of these indirect savings being complex and difficult to calculate,
as well as other factors not being considered of strategic importance (for example
indirect saving achieved through improved communication) and finally, certain savings
could not be publicly disclosed. Secondly, certain records contained figures which were
based on calculations that were lost.
Because of the competent nature of Clover Logistics, these savings can be deemed as
reliable and accurate. In certain cases theoretical explanations of these missing
computations have been given. *
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I. Integration with Clover’s ERP system
When using the Magic system, all orders were sent to the Magic users via e-mail and
were then manually captured into the Magic system. This manual process consisted
of someone capturing the orders from BR into an e-mail, and then the Magic user
capturing the orders from the e-mail they received into the Magic system. The
manual capturing of these orders was as inefficient as it was time consuming, and
created room for errors. Transport orders from outside clients were also e-mailed to
the planners and manually captured into the Magic system.
As a result of the integration between Optima and Clover’s BR system, all manual
capturing of orders from the BR system have been eliminated, as orders from BR are
now automatically imported into Optima. Transport orders from outside clients do not
reside in any internal Clover system, and hence still have to be e-mailed to the
Optima planner and manually captured into Optima.
The elimination of the manual capturing of orders from BR has reduced errors in
Clover’s transport system and freed up many hours of the planners’ time.
II. Integration with Clover’s financial system
The Magic system was only able to generate financial information for accounts
payable. Once the accounts department had received an invoice from the haulier, it
checked whether the invoice matched the purchase order generated by Magic on
BPCS, and paid the haulier. This process took a long time as the invoice from the
hauler often did not match the information generated by Magic. It then took the
accounts department weeks to investigate and find the reason the invoices did not
match up, and correct the problem.
Magic did not handle accounts receivable data. The accounts department had to
manually feed the accounts receivable information into the Pastel accounting system,
based on trip information in the Magic system, and then invoiced the client through
Pastel. No checks were done comparing what was entered into Pastel and what in
reality was executed in Magic, leaving a large gap for errors and fraud to occur, as
can be seen in figure 6.1.
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Figure 6.1 Gap created in the accounts receivable process
Create Request for Service in Magic- BR sends e-mail to planners- Planners manually create RFS
Create Transport Request in Magic- Source a haulier- Confirm a haulier- Deliver TR
Create a Purchase Order in Magic
Send Purchase Order through to BPCS- Run accounts payable process to pay haulier
Manually Enter Accounts Receivable Information in Pastel- Send invoice to client eg: Escort
Non-integrated process creates a gap for fraud and errorsX
Create Request for Service in Magic- BR sends e-mail to planners- Planners manually create RFS
Create Transport Request in Magic- Source a haulier- Confirm a haulier- Deliver TR
Create a Purchase Order in Magic
Send Purchase Order through to BPCS- Run accounts payable process to pay haulier
Manually Enter Accounts Receivable Information in Pastel- Send invoice to client eg: Escort
Non-integrated process creates a gap for fraud and errorsX
Source: Developed by the author for the purpose of the study
Optima is able to generate both accounts payable and accounts receivable vouchers.
Once these vouchers are generated, they are exported in to BPCS and MRP2. The
accounts payable purchase orders and accounts receivable invoices can then be
generated. The financial information is posted to the general ledger on a daily basis
in order to give Clover Logistics’ management a daily update on the financial stability
of the business.
As a result of the previous Magic system not being able to produce accounts
receivable vouchers, the integration on the accounts receivable side of Optima was
not seen as a priority. The accounts receivable process in Optima is currently being
fully tested and will be implemented shortly. Currently, Clover Logistics is in the
process of comparing the accounts receivable information that Optima produces to
the information in their accounting software, and are finding that there are significant
discrepancies. This points to problems that resulted from the non-integrated process
described above. In the near future, the information generated from the accounts
receivable vouchers in Optima will be used to invoice clients.
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III. Integration with Clover’s vehicle tracking system
In section 3.2.1, when discussing the advantages of technology, the section mentions
how technology allows for real-time communications through devices such as the
global positioning system, which helps organisations deal with issues in real time, not
after they have already occurred.
Magic did not integrate with a live tracking system. This meant that the Magic users
would have to monitor the vehicle using the tracking provider’s software, and then
manually enter the departure and dispatch information, as well as any delays into
Magic.
Optima integrates with Clover’s tracking service providers Fleet Manager. The
integration allows Optima to update load status using real-time information. “By
combining the schedule with GPS tracking data, tracks the progress of each trip,
each task on each trip and the progress of each shipment. Once tasks can be
identified as complete, the latest remaining scheduled task estimates can be
recalculated by taking full advantage of the scheduler engine”(Opsi Systems, 2008a;
11). For example, if a vehicle is delayed as a result of an accident on the road,
Optima will pick up this delay in real time and adjust the arrival time and any further
trip times of the vehicle accordingly.
Clover Logistics began implementing Optima’s tracking module, however hauliers
were not happy to share their GPS information with Clover as they did not want
Clover to track their vehicles while they were not in use by Clover Logistics. This
challenge, together with the fact that the previous Magic system was not able to
integrate with a tracking system, resulted in Clover Logistics postponing the
implementation of the tracking implementation indefinitely.
6.1.2 Routing and scheduling
Chapter three discusses how in 3PLs, as well as organisations operating in-house
fleets, good routing and scheduling decisions can lead to sizable benefits being
achieved. For example, vehicle load utilisation can be increased while simultaneously
reducing the frequency of deliveries to a specific area .The reduction in the frequency
of pick-ups and deliveries can result in a reduction of the amount of transportation
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required to deliver the same quantity of goods. This allows for the transportation
costs to be reduced, while at the same time for productivity to be increased. Despite
the fact that “Routing problems are computationally some of the most difficult
encountered in mathematics” (Frazelle, 2002; 200), sizable benefits such as
improved customer service, lower stock levels, lower personnel requirements,
improved stock control, as well as positive effects on the environment can be
achieved when efficiently routing and scheduling vehicles.
The Magic system did not have a vehicle scheduler, and hence vehicles were not
scheduled. All loads were rather manually placed on vehicles.
“In order to provide cutting edge scheduling functionality, Optima is tightly integrated
into the Plato-Scheduler, Opsi's sophisticated optimiser and scheduler. Using
advanced algorithms to honour physical and operational constraints, the scheduler
builds optimal, cost-effective loads, called trips. Plato schedules the vehicles by
making use of:
• Extensive road network data,
• Stop-time learning;
• Loading bay information;
• Drop shunting; and
• Cross-docking”.
(Opsi Systems, 2008a; 4)
I. Utilisation of empty legs
Empty legs add large costs to deliveries. Included in the delivery cost has to be the
cost of the vehicle returning empty from the delivery. This cost often doubles the cost
of deliveries. If a route can be planned in such a way that on the return leg the
vehicle picks up products on the way back from the drop-off site, and then delivers
this product on the way back to its site of origin, then this first delivery doesn’t have to
bear the cost of the return leg. By using the return empty leg to do a delivery, the cost
of deliveries can be halved. Section 2.7 discussed a few examples of how, according
to High Jump Software, transportation management systems can rapidly reduce
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costs. One of the ways discussed is how, through optimising an organisation’s
routes, schedules and loads, a reduction in annual transport costs can be achieved.
The utilisation of empty legs is a key aspect in optimising an organisation’s routes.
Empty legs are often a challenging aspect to optimise in 3PL businesses, as 3PLs
first need to be aware of the empty legs they generate, and then they need to find
contracts to fill these empty legs. In order to utilise empty legs 3PL organisations also
need to use one vehicle across different contracts, which is difficult to coordinate and
administrate.
Although Clover Logistics’ understood the importance of utilising the empty leg, the
previous Magic system was not able to plan and administer the utilisation of the
empty leg. This resulted in almost all vehicles returning empty from their deliveries.
An example of how the utilisation of empty legs saved Clover Logistics’ two empty
leg trips, is discussed below.
For the purposes of this dissertation, the Eastern Cape route will be used in the
example.
In figure 6.2 the different vehicle routes that were planned in Magic for part of the
Eastern Cape region can be seen. Two vehicles were used to pick up products from
the Unifoods warehouse in Boksburg for deliveries to the DCs in Port Elizabeth and
East London. Both vehicles retuned empty to the Unifoods warehouse in Boksburg.
Another vehicle was based at the dairy in Grahamstown. It would wait until 15:00
when the milk was ready to be transported, and would then deliver the milk to the DC
in Port Elizabeth. It would then return with a few empty crates on the vehicle.
Other vehicles that were based at the dairy in Grahamstown would make deliveries
to the DC in Queenstown and the DC in East London, and would then return empty
to the dairy in Grahamstown.
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Figure 6.2 Eastern Cape Magic Route
Source: Clover, 2005a; 4
Figure 6.3 shows how Clover was able to restructure their routes with the help of
Optima. Two vehicles are still used to pick up products from the Unifoods Warehouse
in Boksburg and deliver to the DCs in Port Elisabeth and East London, with both
vehicles retuning empty to the Unifoods warehouse in Boksburg.
Vehicles were however no longer based at the dairy, but were based at the DCs. The
vehicle based at the Port Elizabeth DC was used for secondary distribution in the
morning instead of just waiting at the dairy. In the afternoon it was used for primary
transport to pick up the milk from the dairy and deliver it to the DC in Port Elizabeth.
Instead of two partly empty vehicles being used to deliver from the dairy to East
London and Queenstown, one vehicle was used. The vehicle was based at the East
London DC. In the morning it would travel to the dairy in Grahamstown with some
empty pallets on it. It would then pick up a full load of milk and deliver it firstly to
Queenstown, and then to East London. This new routing resulted in one vehicle
being used instead of two. This represents a 100% saving in vehicle costs.
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Figure 6.3 Eastern Cape Optima Route-Option one
Dairy
DC
Satellite
CDC
Unifoods/Clayville/Springs
Boksburg
Dairy
DC
Satellite
CDC
Dairy
DC
Satellite
CDC
Unifoods/Clayville/Springs
Boksburg
Unifoods/Clayville/Springs
Boksburg
Source: Clover, 2005a; 5
Figure 6.4 shows another option of how Clover could handle the Eastern Cape routes
with the help of Optima.
The vehicle that was used to deliver products from Boksburg to Port Elizabeth, no
longer returned empty to Boksburg. It rather picked up empty crates in Port Elizabeth
and delivered them to the dairy in Grahamstown. It then picks up milk from the dairy
in Grahamstown and delivers it first to the DC in East London and then to the DC in
Queenstown, and finally returns with some empty pallets to the Unifoods warehouse
in Boksburg. The vehicle that delivers from Boksburg to East London, no longer
returns empty. It rather picks up empty crates from east London, delivers them to the
dairy in Grahamstown, picks up milk from the dairy in Grahamstown and delivers it to
the DC in Port Elizabeth. Finally it returns empty to the Unifoods Boksburg
warehouse.
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Figure 6.4 Eastern Cape Optima Route-Option two
Source: Clover, 2005a; 6
Through the use of the new routes, Clover Logistics was able to “Facilitate the
exploitation of economies of scale, opposite imbalances and other synergies in order
to eliminate inefficiencies” (Clover logistics, 2007a; 18).
As seen above, the implementation of Optima has allowed for improved routing and
scheduling resulting in fewer trips being scheduled to deliver the same amount of
products, resulting in an improvement in the vehicle fill rate. Section 6.2 will quantify
the benefits achieved from improved routing and scheduling.
II. Multiple pick-up and drop-off
In order to schedule multiple shipments on a vehicle, information for the two
shipments had to be identical in order for Magic to be able to allocate two shipments
to one trip. This manual system was prone to mistakes as it relied on Magic
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identifying two or more transport orders with identical information. The Magic system
also did not handle shipments with large numbers of pick-up and drop-off locations.
Optima is able to take a large amount of different orders, with as many different pick-
up and drop-off locations as required, and automatically group and schedule them on
a vehicle in an optimal way, thereby ensuring that minimal kilometres are driven and
the vehicle is filled to the most optimal capacity possible .
III. Cross-docking of vehicles
As a result of Magic not scheduling vehicles, it was not able to cater for the cross-
docking of vehicles. This meant that delivery vehicles regularly had to travel long
distances, often with low space utilisation, to make a delivery.
Optima caters for the cross-docking of vehicles, which ensures that minimal
kilometres are driven and vehicle space utilisation is kept to a maximum. Cross-
docking allows vehicles from different production facilities to meet at a central
warehouse, merge their loads, and then deliver full loads of assorted products to the
various DCs.
IV. Loading bays
In order to achieve realistic delivery schedules, it is necessary to take into account as
many constraints (eg: delivery times, travel times, loading bays’ availability, traffic
times, vehicle constraints, loading bay constraints) as possible that would affect the
schedule. A major constraint affecting vehicle scheduling is the availability of loading
bays. Vehicles can often wait for hours while waiting for loading bays to become
available, delaying future trips the vehicles are assigned to. Optima not only
schedules vehicles, but it also books loading bays at the different sites allowing for
realistic schedules to be produced. The scheduling of vehicles around loading bay
availability has drastically minimised Clover’s vehicle idle time, especially in the
inner-Gauteng region. The savings achieved are quantified in section 6.2.1.
V. On-time delivery
Improved customer service, of which on-time delivery is a key element, is one of the
many reasons why organisations decide to outsource their distribution to a 3PL
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provider (section 2.8.2 VII). More importantly, the high costs of holding stock have led
to the growth of JIT (explained in section 2.8.2 VIII), which is dependent on on-time
deliveries. The impact of late deliveries has become of more importance with the
growth in JIT deliveries, as when using JIT, deliveries that are not on-time impact on
stock outs and often result in loss of sales.
An example of the critical importance of on-time delivery is seen in the case study
discussed in section 2.9.1 where no tolerance is shown for late deliveries; as such
deliveries can hold up production and lead to the late delivery of the final product.
Through the use of advanced routing and scheduling, Optima’s routes are more
realistic, which has resulted in an increase in on-time deliveries of 99%, compared to
85% when scheduling deliveries manually. (De Lange, 18 July 2008). The
improvement in on-time delivery has resulted in more satisfied customers and has
given Clover Logistics’ a competitive edge in the marketplace.
6.1.3 Financial
In section 3.2.3 top industry analysts shared their insight into the future use of
technology in the supply chain. They were of the opinion that technology has become
central to driving down transportation costs, and is in fact indispensable in
establishing global logistics plans. According to Gonzalez, freight payment is an area
where many organisations are focusing on to reduce cost. “Many companies are
looking to implement a self-invoicing process, whereby the shipper pays the carrier
the rate in the transport management system including known surcharges and
accessories upon receiving the proof of delivery. This shifts the audit process to the
carrier, a trade-off many carriers are happy to accept in return for getting paid thirty
or more days faster. It improves their cash flow, and the shipper eliminates all of the
overheads involved in auditing and processing freight invoices” (Adrian Gonzalez as
cited in Levans, May 1, 2007).
The following section will discuss how Clover Logistics has automated their accounts
receivable and payable processes.
I. Handling of multiple shipments per vehicle
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As mentioned above, in order to utilise empty legs, 3PL organisations need to use
one vehicle across different contracts, which is difficult to coordinate and administer.
Although the Magic system was able to handle two shipments on one particular
vehicle, it was not able to allocate the costs of the vehicle to the different shipments.
Magic was also not able to generate accounts receivable vouchers, and only
generated accounts payable vouchers. All accounts receivable information had to be
manually entered into Pastel, with the associated issues described in section 6.11.
Optima generates accounts receivable and accounts payable vouchers, and passes
theses vouchers on seamlessly to Clover’s relevant financial systems. If multiple
shipments are placed onto one vehicle, Optima will produce one accounts receivable
voucher per shipment allowing for accurate invoicing of clients. Optima also divides
proportionally the accounts payable vouchers to each shipment. This enables Clover
Logistics to accurately calculate profitability on a shipment.
II. Administering of multiple tariffs
Clover Logistics found that although the Magic system could allocate fixed costs to
routes, it could not adequately handle the variable cost of the leased Imperial fleet
(Clover, 2003b; 3). As a result of this, Clover Logistics needed a system that could
handle both fixed and variable charges and administer multiple charge types.
Optima caters for this complicated need and can handle multiple charges, both fixed
and variable per shipment. This has allowed management to instantly know the
profitability of a route and has hence allowed Clover’s management to better manage
their organisation.
III. Accuracy of invoices resulting is fewer disputes
Section 3.2.5 mentions the importance of the “order to cash” cycle. The section
explains that one of the benefits of utilising technology is speed: By using technology,
the time it takes from the time an organisation’s product or service is sold, until the
time the revenue for the product or service is collected, is reduced.
In the past clients would often dispute invoices. With the Magic system it would take
months to reconcile the client’s invoice and explain to the clients in detail what they
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were being invoiced for. This resulted in cash flow issues for Clover Logistics as a
result of the account not being paid until the dispute was resolved. It was also often
found that a client’s dispute was justified.
After the implementation of Optima, when a client disputes an invoice, an itemised
invoice can be generated within hours. This means that the client’s query can be
addressed within hours. It has also been found that the majority of client queries are
found to be incorrect, and as a result, after a few years of using Optima, client
disputes have reduced as trust in the system has increased.
As mentioned in chapter five, Clover has a collaborative and transparent relationship
with their clients. This means, amongst other benefits, that clients are able to
question the tariffs Clover Logistics charges. With Optima, Clover is now able to
show clients exactly what a certain trips costs them, and can thus justify their tariff
structure.
After a few years of fine-tuning Optima and the master data it relies on, Optima now
produces less then 1% of accounts receivable vouchers that are incorrect (Fourie, 31
July 2008).
IV. Increased accuracy of invoices provided by hauliers
Companies are focusing on reducing manual payment processes and are beginning
to enhance online collaboration with hauliers in order to improve invoicing (section
3.2.3).
When using Magic, hauliers would have to keep a record of what trips they
performed for Clover Logistics, and what amount was agreed upon for each trip.
They would then submit their invoice to Clover at the end of every month, at which
time Clover’s financial department would tie up the hauliers’ invoice with Clover’s
records of trips performed. This was a difficult, time consuming task which resulted in
many disputes between Clover and their hauliers.
The accuracy of invoices has improved as a result of the Optima haulier web page.
At the end of the month, when hauliers invoice Clover for the loads they executed,
they are able to log onto their companies’ web page and see exactly which loads
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they’d performed for Clover, as well as the amount that was agreed upon for each
load. This has allowed the hauliers to invoice Clover with a 99.5% accurate invoice,
resulting in minimal disputes and immediate payment.
After a few years of fine-tuning Optima and the master data it relies on, Optima
produces less then 0.5% of accounts payable vouchers that are incorrect (Fourie, 31
July 2008).
V. Ability to determine the additional transport costs generated by a
product promotion
In order to move the additional stock needed for the promotion of a product,
additional hauliers often have to be procured (seldom one of Clover’s standard
hauliers), often at a higher cost, as it is usually a last-minute decision. In utilising
Optima, Clover can now see the additional transport cost that is incurred as a result
of a particular promotion. This enables Clover to compare the profit generated from
the promotion with what the promotion costs, in additional transport costs. Since the
implementation of Optima, Clover has discovered that certain promotions are not
cost effective, as the additional transport costs outweigh the profit generated by the
promotion.
VI. Real-time visibility of Clover Logistics’ financial status
Wayne Eckerson (section 2.10) explains that while historical information is critical, it
doesn’t help organisations identify problems or opportunities as they occur, and allow
them to take immediate actions in order to optimise the result.
When utilising the Magic system, all invoices were processed in batches, which
meant that only at the end of the month Clovers Logistics’ management would be
informed if it had been a profitable, or an unprofitable month. At this stage it was too
late to make any modification to the non-profitable operations for the month.
With Optima, accounts payable vouchers are produced immediately when a trip is
dispatched, and accounts receivable vouchers are produced immediately when a trip
is completed. Each day at 17:00 the vouchers are posted to the general ledger. This
allows Clover Logistics’ management to have a daily real-time view of what is
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happening in their organization, and to deal with any issues that may have arisen on
a daily basis.
A drawback of Optima is that the financial administration of the system is very
complicated. This is the result of an extremely complex development specification
when Optima was developed. Although it is complicated to administer the various
tariffs, the complex structure is necessary in order to allow for proper financial
visibility. Another one of the benefits of this complex structure is the ability to monitor
the start and end dates of contracts. The Pivotal Corporation explains (section 3.2.5)
that the use of technology allows organisations to keep a continuous record of the
start and end dates of haulier contracts, as well as income.
According to Clover Logistics’ planning manager, although the complex structure
makes it challenging to manage, the detailed information that can be produced as a
result of the complex structure, more than justifies the additional time needed to
manage the tariffs (Fourie, 31 July 2008).
6.1.4 Communication
In section 2.10 it mentions how many third party logistics companies have to allocate
a large number of their staff to basic functions such as communication with their
customers, subcontractors and their drivers. With proper systems in place, these
tasks can be handled by much fewer resources, thus availing up manpower for other
tasks. Section 3.2.8 discusses how the internet allows organisations to communicate
without “spending a bundle on technology”. The following section explains how
Optima harnesses the internet to optimise communication between the 3PL and its
hauliers, clients and warehouses.
When using the Magic system, communication was done via phone, fax or e-mail.
This meant that every phone conversation, e-mail or fax had to be manually
captured. Manual capturing created room for error and was extremely time
consuming.
Optima allows for planners, dispatchers, warehouse managers and hauliers to
interact with the same job in real-time through a web-based portal, eliminating the
many phone calls, faxes and e-mails .
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I. Communication with hauliers
When a haulier needed to be notified of a potential trip, an e-mail would be sent to
him from the Magic system with all the trip details. The haulier would then either
phone and confirm he was able to execute the trip, or would fax written confirmation
that he was able to execute the trip. The phone call or fax would then have to be
manually captured into Magic.
With Optima, the haulier receives all trip information via a personalised web page,
and the haulier confirms that he is able to execute the trip via the web page. This
eliminates any mistakes as a result of manual capturing of the relevant information. It
also eliminates any confusion or miscommunication, as everything is clearly stated
on the web page. According to the head planner, (Hoeksma, 20 May 2008) the
hauliers have on numerous occasions expressed their satisfaction with the Optima
haulier web page.
One drawback of relying on a web page for communication is that sometimes the
hauliers are not able to access their computer as they are not in their office, or as a
result of a power outage. In these cases, Clover has to revert back to their previous
method of using the phone to communicate the relevant information.
II. Communication with clients
With both Magic and Optima, clients e-mail their orders to Clover and the orders are
manually captured into Magic or Optima.
Optima has a web page whereby the client can log in and see the status of the trip,
that their products are being transported, including live updates via the integration
with a GPS tracking provider. Clover has not yet implemented the use of this web
page and currently does not have plans to implement it in the near future.
III. Warehouses
When using the Magic system, the departure and delivery of a trip were confirmed
via phone and manually captured into Magic.
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Using Optima, confirmation of the dispatch and delivery of loads is entered by the
warehouse into the web-based ‘track-and-trace’ interface. When a load leaves or
arrives at a warehouse, the relevant authorised warehouse personnel or haulier
representatives log onto the dispatch site web page and update the status of the
transport request to “dispatched” or “delivered”, as well as updating other relevant
details such as departure date and time.
According to a study done by the Aberdeen Group, two-thirds of organisations
looking to improve transportation management through technology, say that a top
goal is to achieve advanced shipment visibility that includes status, estimated time of
arrival, alerts, and resolution workflow (section 3.2.6). According to Jenny Hoeksma
the warehouse web page is a major advantage of Optima, as warehouse users can
log onto the web page 24 hours a day, 7 days a week, and have visibility into what
loads are arriving or departing in the upcoming days (Hoeksma, 20 May 2008).
6.1.5 Reporting
Chapter three lists some of the issues that can be solved through technology. The
chapter then continues and lists the advantages of technology. Improved reporting is
considered an advantage of technology.
Although Magic had a large number of reports it could generate, a large amount of
data was not captured into Magic, and hence Magic could not report on it.
As a result of the large amount of daily operational and financial information that
flows through Optima, Optima is able to produce numerous reports.
According to Corne Fourie, information from Optima has been a critical element in
assisting Clover Logistics’ management to improve the management of their
organisation. This is achieved by promptly knowing what is happening in their
organization, and by making changes when necessarily (Fourie, 30 June 2008).
However, at the moment most of the information in Optima has to be extracted by
Clover’s in-house IT department, as Optima does not have the necessary reports to
produce the needed information. As a result of Clover Logistics initially relying on
their in-house IT department to extract the data required from Optima, reports in
Optima have not yet been developed as necessary (Fourie, 31 July 2008).
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Although Optima has some management reports which have become of critical value
to the management of Clover Logistics, Optima is lacking some basic operational
reports, such as a schedule report (Hoeksma, 20 May 2008 ). Instead of simply
printing a schedule report, the Optima users manually write the schedule details onto
a sheet of paper, which is time consuming and inefficient. Optima does not yet
provide a fully paperless environment as envisioned originally, however, as more
reports are developed, Optima will move towards a more paperless environment.
As discussed above, although Optima has all the required information stored in its
database , the number and variety of reports produced by Optima are limited and
more time and development need to be focused on the reports in order to ensure
they produce the information required.
6.1.6 General
I. How users view Optima
The following table shows the general feeling of the Optima users towards Optima,
based on a survey conducted by the author. The survey was conducted via e-mail
and involved all the Optima planners at Clover Logistics. 66% percent of the planners
responded to the survey, all with the same result seen in table 6.1.
Table 6.1 The general feeling of the Optima users towards Optima
Very productive
Slightly
productive Neutral
Slightly
destructive Very destructive
Rate OPTIMA’s effect on Clover
Logistics as a whole. 100%
Easier, less
complicated
Easier, more
complicated No effect
More difficult, less
complicated
More difficult,
more
complicated Did OPTIMA make your daily job…? 100%
Very satisfied Slightly satisfied Neutral
Slightly
dissatisfied Very dissatisfied
Rate your overall
satisfaction with OPTIMA. 100%
Very user-friendly
Slightly user-
friendly
Slightly non-user-
friendly
Very non-user-
friendly Rate the user-friendliness of
OPTIMA. 100%
Source: Developed by the author for the purpose of the study
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Optima users at Clover Logistics feel that Optima is a user-friendly, easy and
effective planning tool. Although none of the current users worked on the previous
Magic system, most of them have experience on other planning systems. According
to one of the Optima users at Clover Logistics, who has experience of a number of
other planning systems, the process a trip has to go through in Optima takes longer
than the process trips have to go through in other systems, however the process is
much easier and is more efficient (Hoeksma, 20 May 2008).
II. Improved security
The warehouse web page has led to increased security as explained by means of the
following scenario: Every trip on the web page has a TR number associated with it.
Hauliers are informed of the TR number via the haulier web page. Only hauliers that
know what the TR number of the load they have come to collect is are allowed to
collect it. In the past, illegitimate hauliers would arrive to collect loads, and once
loaded, the haulier would steal the load. The matching up of the haulier TR number
to the warehouse TR number has eliminated this issue (Hoeksma, 20 May 2008).
III. Load visibility
According to a study conducted by the Aberdeen Group, two-thirds of organisations
looking to improve transportation management through technology, say that a top
goal is to achieve advanced shipment visibility that includes status, estimated time of
arrival, alerts, and resolution workflow (section 3.2.6).
A large issue with the Magic system was that it did not provide easy visibility about
the status of the loads. To find the status of a load, a number of reports had to be
printed.
The status of a load can be seen in numerous different screens in Optima. In the trip
management screen, the colour coded status off all loads can be seen. This screen
can be filtered and adjusted to suit the user’s requirements providing global visibly of
the load status.
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IV. Maintain next generated number
Section 3.5 explains the importance of master data as follows: If garbage is fed into
the system, garbage will be produced from the system (GIGO). Magic’s inability to
auto generate certain critical information resulted in another entry point for bad data
to enter the system.
Magic did not have the ability to generate a unique ID for the RFS, TR and tariff
number. Therefore the user had to generate the next unique number for the RFS, TR
and tariff every time a new RFS, TR or tariff was added. This was done by opening
up the “edit numbers file”, and entering in the next number for the RFS, TR and tariff,
as can be seen in figure 6.5
Figure 6.5 Maintaining next generated numbers
Source: Clover Logistics, 2001; 23
Having to manually generate an RFS, TR and tariff number, is an example of the
simplicity of the Magic system. The ability of Optima to auto generate a unique ID,
has saved the users much time and frustration and has ensured that the process
runs more smoothly.
V. Time management
Section 3.2.5 discusses how the conventional invoicing process results in low staff
efficiency rates.
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Due to the decrease in manual data captured in Optima, “the average time required
by an Optima user to complete a trip schedule was decreased significantly to four
minutes” (The Logistics News, 2008; 71).
6.2 Financial savings achieved through the implementation of Optima
Although financial savings can be indirectly attributed to many of the qualitative
benefits mentioned in section 6.1, the only financial savings that can be directly
accredited to the implementation of Optima, are those savings achieved through
improved vehicle utilisation as a result of improved routing and scheduling.
6.2.1 Savings achieved through the optimal routing and scheduling of vehicles
Clovers Logistics’ previous Magic system was not an integrated vehicle routing and
scheduling system, and could only schedule vehicles from point A to point B and
back, based on predetermined traveling times. Optima is a complete routing and
scheduling optimisation tool which has allowed Clover Logistics to determine optimal
routes for its vehicles through the calculation of accurate and realistic drive times,
scheduling of loading bays, and most importantly, the scheduling of return loads on
vehicles’ return legs.
Clover Logistics analysed the improved routes produced by Optima and the resultant
saving after the first complete financial year after the implementation of Optima.
6.2.1.i Change in the way crates are returned to the factories
When using the Magic system, empty crates from the fourteen Clover depots around
the country were all collected at a central point in Boksburg and then redistributed to
the seven Clover factories. Vehicles returning from the various depots to
Johannesburg, would transport the empty crates with them on their return leg and
offload them at a central warehouse in Boksburg. The empty crates were then
transported from the central warehouse in Boksburg to the various factories. This
method resulted in the empty crates being transported and handled twice before
returning to the factories for re-use.
The Optima schedule allows and plans for the empty crates to be delivered directly
from the various depots back to the factories. This approach resulted in less handling
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of the empty crates, less warehousing of the empty crates and fewer kilometres
being driven to return the empty crates to the factories. The monthly savings
achieved from this new initiative was R108 300 from July 2005 to June 2006.
6.2.1.ii Utilising the empty leg from Nelspruit to Gauteng
When using the Magic system, a vehicle carrying Clover products travelled from
Gauteng to Nelspruit to make its delivery. The vehicle would then return from
Nelspruit to Gauteng with a few empty crates on it. A vehicle based in Nelspruit
would deliver boxes of bananas from Nelspruit to Gauteng and return empty to
Nelspruit. With Optima’s ability to plan loads on the empty legs, the route was
changed to deliver Clover’s products on a vehicle travelling from Gauteng to
Nelspruit. In order to make optimal use of the empty crates returning to Gauteng, the
empty crates were used to pack bananas, instead of the bananas being packed into
boxes. The vehicles that delivered Clover products to Nelspruit would then return
with a load of bananas to Gauteng. The bananas were then boxed at Clover’s
warehouse in Gauteng.
This new route not only ensured that the empty leg of a route was filled, but it also
enabled the empty crates to be returned to Gauteng while being used.
The savings achieved from this new route amounted to R17 000 a month from July
2005 to June 2006. This savings can be explained in the following theoretical
explanation. The distance between Gauteng and Nelspruit is 303 kilometres. With the
elimination of two empty legs per trip, 606 kilometres were saved per trip. At an
assumed cost of R7.01 per kilometre (for the specific vehicle used for that route), a
total of R2 124.03 was saved per leg, equivalent to R4 248.06 per trip. Four of these
trips were saved per month, totaling a savings of R16 992.24 (rounded up to
R17 000) per month.
6.2.1.iii Gauteng and factories (Western Cape)
In the past, vehicles loaded with Clover’s products would depart from Cape Town
and deliver to George as depicted in figure 6.6. The vehicle would then return with a
few empty pallets on it. On another trip these pallets would then be delivered from
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Cape Town to Gauteng, and the vehicle would return from Gauteng to Cape Town
loaded with Clover products.
With Optima’s ability to efficiently plan and manage triangulation, the route was
changed. Vehicles now deliver products from Cape Town to George and then take
the empty crates directly to Gauteng. The vehicles then return from Gauteng with
products to Cape Town. This new method cuts out one leg from the trip, enabling the
same amount of products and empty number of pallets to be moved with fewer
kilometres being driven.
Figure 6.6 Gauteng-Cape Town-George
Source: Developed by the author for the purpose of the study
The savings achieved from this new route amounted to R200 000 a month from July
2005 to June 2006. This savings can be explained in the following theoretical
explanation. The distance between Gauteng and Cape Town is 1275 kilometres,
between Cape Town and George 382 kilometres, and between George and Gauteng
1044 kilometres. The substitution of two partly empty legs (from Gauteng to Cape
Town and from George to Cape Town) with one nearly full load (from George to
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Gauteng), resulted in a saving of 613 kilometres (1275 kilometres + 382 kilometres -
1044 kilometres) per trip. At an assumed cost of R11.25 per kilometre (for the
specific vehicle used for that route), a total of R6896.25 was saved per trip.
Assuming one of these trips was done per day (in a 29-day month), a savings
totalling R199 991.25 (rounded up to R200 000) per month was achieved.
6.2.1.iv Gauteng-KwaZulu Natal-Northern Free State-Gauteng
The total amount of primary transport flowing in and out of KwaZulu Natal amounted
to 30 million rand for the financial year 2005/2006, resulting in it being Clover’s
second largest region after Gauteng.
Table 6.2 Saving achieved through optimal routing and scheduling of
KwaZulu Natal loads
Source: Source: Clover, 2005b; 10
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As seen in table 6.2, the optimisation of the routing and scheduling of the KwaZulu
Natal loads resulted in numerous loads such as the Queensburgh to Gauteng,
Queensburgh to Ladysmith and Ladysmith to Queensburgh to be totally eliminated.
The adjustment of other loads led to a savings of up to as much 68% in routes such
as the Queensburgh to Pinetown route. Smaller savings were achieved across other
routes, such as a saving of 49% across the Merebank to Queensburgh route, and a
saving of 20% across the Estcourt to Merebank route. With the elimination of certain
loads, and well and the reduction and adjustment of other loads, a total savings of R
24 001was achieved per week in 2006. With a weekly saving of
R 24 001, coupled with the savings achieved from the optimisation of KwaZulu Natal
loads, a total monthly saving of R 169 950 was achieved in 2006.
6.2.1.v Gauteng-Eastern Cape (Includes intra-Eastern Cape routes)
In the past, Clover vehicles would deliver products from Port Elizabeth to Cape Town
and return empty. Another Clover vehicle would then deliver products from Gauteng
to Port Elizabeth and return empty as depicted in figure 6.7.
With Optima’s ability to efficiently plan and manage triangulation, the route was
changed. Clover Logistics also decided to outsource the route to a haulier to ensure
an optimal route cost. The new route requires the haulier to deliver a load from Port
Elizabeth to Cape Town. It then delivers Cadburys chocolate (The Cadburys
chocolate contract is a contract that the haulier sourced and executes independently)
from Cape Town to Gauteng. In Gauteng, the haulier then picks up a load of Clover
products and delivers it to Port Elizabeth.
The savings achieved from this new route amounted to R113 300 a month from
October 2005 to June 2006. This savings can be explained in the following
theoretical explanation. The distance between Cape Town and Port Elizabeth is 645
kilometres and between Port Elizabeth and Gauteng 930 kilometres. The elimination
of two empty legs (from Cape Town to Port Elizabeth and from Port Elizabeth to
Gauteng), resulted in a saving of 1575 kilometres (645 kilometres + 930 kilometres)
per trip. At an assumed cost of R11.98 per kilometre (for the specific vehicle used for
that route), a total of R18 868.50 was saved per trip. Assuming six of these trips were
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done per month, a monthly saving totaling R113 211 (rounded up to R113 300) was
achieved.
Figure 6.7 Gauteng-Eastern Cape: new route versus old route
Source: Developed by the author for the purpose of the study
“The creation of a coordinated rescheduling of operations between the Eastern Cape
and Gauteng with a collaboration partner has resulted in an immediate saving of R1,
5 million per year” (The Logistics News, 2008; 67)
6.2.1.vi Gauteng- Polokwane (Pietersburg)
According to the Pivotal Corporation (section 3.2.1) “Some companies are surprised
to discover what they are overlooking due to lack of visibility into their processes“.
In the past, Clover used 22 pallet vehicles to service the Gauteng to Polokwane
route. Utilising the information generated by Optima, Clover Logistics’ management
was able to establish that this is not the optimal size vehicle for the route. By
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analysing the historical information in Optima, Clover Logistics changed the vehicle
used for this route to a 28 pallet vehicle. In 2006, R20 600 was saved monthly as a
result of fewer trips being needed to transport the necessary products.
Prior to the implementation of Optima, Clover Logistics’ management was blind to
what was happening in their supply chain. Without being able to see what was
happening in their supply chain, they were not able to analyse it and improve on any
inefficiencies.
6.2.1.vii Gauteng region
Clover’s intra-Gauteng transport (see figure 4.4) is without doubt the most
complicated of all Clover regions, with the total amount of primary transport flowing
within the Gauteng region amounting to R36 million in the 2005/2006 financial year.
Large volumes of product have to be moved between depots and factories, with a
limited number of loading bays, as well as resources that have to be shared between
the inner-Gauteng vehicles and Clover’s long distance fleet.
Through the use of Optima, Clover was able to accurately determine the driving time
between the various factories and warehouses, whilst taking into account reduced
vehicle speeds during peak traffic. This allowed Optima to determine when the
vehicles would be arriving at the relevant depots and factories, and to efficiently
schedule the loading bays at the various depots and factories. The determination of
drive time and scheduling of loading bays allowed Clover to drastically increase their
vehicles’ working time as a result of reduced waiting time at the loading bays.
Through the improvement resulting from optimising the routing and scheduling of
their vehicles and loading bays, Clover was able to increase their daily loads per
vehicle from 2.6 to 3.7, which allowed the company to reduce the size of their
Gauteng fleet by 30%. According to David Lubinsky (section 3.3.5), the average cost
savings achieved from routing and scheduling is 15%, hence Clover’s savings of
30% is extremely high when compared to the industry standards.
“Subsequent to Optima, Clover used 18 refrigerated trucks to service the Gauteng
region. Double truck scheduling and bay scheduling enabled Clover to reduce the
fleet to 11 vehicles in the Gauteng region” (The Logistics News, 2008; 71).
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The total financial savings achieved in the Gauteng region as a result of optimisation
of Clover Logistics’ routes and booking of loading bays, resulted in a saving of
R231 750 per month from March 2006 to June 2006. This saving can be explained in
the following theoretical explanation. Assuming a daily cost of running an intra-
Gauteng vehicle being R1 655.30 per day, the saving achieved from eliminating a
vehicle in the region totalled R 33 106 (R1655 * 20 days) per month. As mentioned
above, 7 vehicles were eliminated from the Gauteng region, which amount to savings
of R231 742 (R33 106 * 7 vehicles) (rounded up to 231 750) per month.
6.2.1.viii Improvement in average fill rate of vehicles
Through better routing and scheduling of its vehicles, Clover Logistics has improved
the average fill rate of its vehicles. Before the implementation of Optima, the average
fill rate of Clover primary vehicles in September 2004 was 56.7 % (Clover, 2005a;
19). As can be seen in figure 6.8, the average vehicle utilisation for September 2007
is between 80% and 85%, which is an increase of 32%.
Figure 6.8 Average fill rate of vehicles per branch (September 2007)
Source: Clover, 2008a; 2
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6.2.2 Analysis of the costs of implementing Optima versus the savings achieved
Table 6.3 details the cost involved with purchasing and implementing Optima. As can
be seen, the cost is broken down into three categories; the purchase cost of Optima;
the annual license fee; and the cost of additional personel needed to implement
Optima. At the beginning of system implementation, one Opsi employee was
dedicated to the Clover implementation. Clover paid for this cost for the year it took to
get Optima operational. However, after a year Clover realised that having a
dedicated person managing Optima, was a critical aspect of its success and
employed the Opsi implementer on a full-time basis. Hence, this once-off cost
became a monthly expense.
Table 6.3 Cost of purchasing and implementing Optima
Cost of Purchasing and Implementing Optima
Purchase cost of Optima R 1,307 225.00
Annual license fee R 140,000.00 increased yearly at CPIX
Full time implementer for a year R 300,000.00
TOTAL R 1,747,225.00 Source: Opsi Systems, 2003d
Tables 6.4 and 6.5 show the savings achieved from the various routes over the first
18 months of the use of Optima. As can be seen in tables 6.4 and 6.5, in order to
reduce risk, the new routes were not all rolled out at once, but introduced gradually
throughout the first 18 months. The tables show the total savings achieved on a
monthly basis. Their savings have increased as new routes are rolled out. Clover
Logistics continues to save on these routes, with the resulting savings increasing as
a result of inflation and the rising cost of diesel.
In table 6.5, in the month of March 2006, after all the new routes had been
implemented, the total savings achieved from optimising the routing and scheduling
in Clover Logistics amounted to R1 043 850 per month, which equals R 12 526 200
per annum
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Table 6.4 Saving achieved through optimal routing and scheduling for the
last six months of the financial year 2004/2005
Source: Clover Logistics, 2006; 1
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Table 6.5 Saving achieved through optimal routing and scheduling for the financial year 2005/2006
Source: Clover Logistics, 2006; 1
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With a once-off fixed cost of R 1 307 225 and an annual variable cost of R 440 000
(license fee of R140 000 and cost of additional staff member of R 300 000), the
savings achieved totally outweigh the expense of purchasing and maintaining
Optima.
In summary, the results of using Optima can be seen in the following calculation as
seen in Clover’s presentation at the Logistics Achievers Awards on 2007( Clover
Logistics 2007a; 28) .
From the financial year 2004/2005 to 2005/2006 there was an increase in vehicle
operating costs of 4.7%. The increase in volume transported by Clover logistics
amounted to a 0.8% increase. This means that there should have been a total
increase of 5.5% (4.7% +0.8%) on Clover’s primary distribution costs. With the
implementation of Optima, Clover Logistics’ primary distribution costs only increased
by 3%, which meant that a saving of 2.5% was achieved (Clover Logistics, 2007a;
27). Although 2.5% may seem like a nominal figure, when multiplied by Clover
Logistics’ primary distribution’s annual transport budget of a few hundred million
rand, the cost of implementing Optima can immediately be justified.
6.3 Possible ways for Clover Logistics to achieve additional savings and
benefits from Optima
Clover Logistics may achieve additional saving through the following actions:
I. Hauliers are sometimes not able to access their computer for numerous reasons.
In these cases, Clover has to revert back to their previous method of using the
phone to communicate the relevant information, which detracts from the benefits
the haulier web page provides. An effective way of managing this communication
during times when the haulier is not able to access the internet, may be through
the use of a short message service (sms) system. The hauliers could receive and
respond to all the relevant trip information via an sms sent to their cell, which
would automatically update Optima just as the web page does. This would reduce
all manual communication between the Optima users and the hauliers, saving time
and any problems that are caused as a result of miscommunication.
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II. At present, Clover Logistics’ clients do not have real-time visibility about the
current status of their product. Optima has the functionality whereby clients can log
onto a personalised web page and see the status of the trip on which their
products are being transported, including live updates via the integration with a
GPS tracking provider. Utilising this functionality could raise Clover Logistics’
customer service to an even higher level, and increase their competitive position in
the marketplace.
III. The manual task of capturing orders from outside clients could be eliminated by an
online order capturing system. Clients could log onto their personal web page, and
capture their orders directly into Optima via this web page. The elimination of the
manual capturing of orders from clients could reduce errors of incorrect
information entered into Clover’s transport system, and avail many hours of the
planners’ time.
IV. Clover Logistics should investigate the implementation of the Optima GPS module.
If sharing of haulier GPS data is an issue, they could implement Optima’s GPS
module across their in-house fleet, allowing them to benefit partially from this
efficient and time-saving module. The GPS integration could save much time and
money, as it could minimise communication time and expense between the
Optima user and the drivers.
6.4 Summary and conclusion
To be able to fully understand the benefit and drawbacks of the implementation of
Optima into Clover Logistics, it was necessary to look at both the qualitative and
quantitative improvements and drawbacks that have occurred as a result of the
implementation of Optima.
The qualitative improvements and drawbacks that resulted through the
implementation of Optima, were looked at from a number of different perspectives,
including benefits and drawbacks achieved from:
• The integration of Optima into Clover’s various ERP, financial and
tracking systems;
• Optimal routing and scheduling of Clover’s and their haulers’ vehicles;
201
• The financial capabilities provided by Optima;
• The communication capabilities provided by Optima;
• Numerous different improvements provided by Optima.
Although the financial saving can be attributed indirectly to many of the qualitative
benefits mentioned in section 6.1, the only financial savings that can be directly
attributed to the implementation of Optima, are those savings achieved through
improved vehicle utilisation as a result of improved routing and scheduling.
Chapter six detailed the financial savings of R1 043 850 per month that was achieved
through improved routing and scheduling. The chapter also analysed a few examples
of how the savings were achieved. Clover Logistics has benefited largely both
qualitatively and quantitatively from the implementation of new technologies into their
supply chain.
202
Chapter 7
7 SUMMARY AND CONCLUSIONS
This dissertation has taken an in-depth look at whether the application of technology
results in improved performance with specific reference to a case study conducted at
Clover Logistics. In order to arrive at a conclusion, an analysis of the processes at
Clover Logistics was conducted before and after the implementation of new software.
This allowed the author to compare and analyse whether the new software did
indeed result in improved performance. This final chapter briefly reviews the various
chapters followed by conclusions in the context of the study.
7.1 Overview of the chapters
7.1.1 Chapter 1
Chapter one began by explaining how in the last hundred years there has been a
technological revolution that has forced people to change the way they live and run
their organisations. This technological age is having a major impact on the business
world. Coyle, Bardi and Langley (2003; 57) have suggested that “the rate of change
has accelerated with consequent negative impacts if organisations do not change.”
Over the years, supply chains have developed and become so complex that it is no
longer possible to effectively manage them without the assistance modern
technology provides. According to Steven Anderson (Anderson, 2005;8 ), the rise in
complex supply chains can be attributed to the fact that transportation options are
growing, additional suppliers have entered the market and the number of products
available has mushroomed. Other factors such as liberated international trade and
falling trade barriers between nations, have also contributed to the rise in the
complexity of supply chains.
The dissertation’s problem statement was then posed: Implementing technology is a
costly, challenging and sometimes risky endeavor. This often results in an
unwillingness to change until these organisations outgrow their systems or the
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business environment becomes so complex, that they are forced to implement new
technology. This hesitancy to introduce new technology timeously could hamper the
progress and growth of these organisations, and could also affect their
competitiveness in a highly competitive environment.
According to a 1999 survey of career patterns conducted for the Council for Logistics
Management, new technologies have become critical in order to compete effectively
(Coyle, Bardi & Langley, 2003; 473). Despite this, there is still a hesitancy to move to
new technologies.
In order to fully comprehend the critical importance of using new technology in an
organisation’s supply chain, the objective of this dissertation was to contrast the
limitations of older technology in the supply chain to the benefits achieved from
utilising new technology in the supply chain. This was achieved by investigating
whether the implementation of a state-of-the-art routing, scheduling and haulier
management system into Clover Logistics has achieved real benefits and improved
the bottom line of the organisation, as compared to using their in-house developed
operational systems.
7.1.2 Chapter 2
Chapter two analysed the changing nature of customers who, because of a growing
level of education and knowledge, and as a result of a more complex and global
marketplace, have begun to demand higher levels of service at reduced costs. In
order to meet these demands, organisations are constantly searching for new ways
to improve their products and services; a search which has led to the development
and growth of the value chain.
In order to satisfy their customers, organisations have quickly learnt that they can no
longer focus solely on the production of their core product, and they now need to
focus on the entire value chain in order to provide their customer with a competitive
product.
After looking at different ways to improve their value chain, it soon became clear to
organisations that a good place to start was the development of a more competent
and competitive supply chain. The Star newspaper reported that according to Brett
204
Bowes, inefficiencies in the supply chain meant fast moving consumer goods
manufacturers and retailers were losing R7 billion every year (The Star, 16 March
2007; 2) .
A popular way for organisations to speedily reap the benefits of having a more
competent and competitive supply chain is by outsourcing their supply chain needs to
specialised logistics organisations.
Chapter two discusses and analyses the importance of good transport management
in general, as well as the advantages and disadvantages of outsourcing this vital link
in the supply chain. The analysis concludes by reporting that an optimal way to
achieve efficient transport management is often to outsource, as transport is very
seldom a core component of an organisation.
After concluding that an excellent way for an organisation to improve its efficiency is
to outsource its logistics needs, chapter two looks at the growth of the third party
logistics provider.
With 3PLs becoming a widely used and vital element of the value chain, the
relationship between an organisation and a 3PL has become significantly important.
This has led to the development of specialised software in order to ensure that this
relationship runs smoothly and efficiently.
From the discussions in chapter two, it would seem that for many organisations
operating in today’s competitive environment, the advantages of outsourcing far
outweigh the disadvantages. Outsourcing certain non-core departments has almost
become a must for organisations wishing to stay afloat in today’s fast-paced,
customer driven economy.
In spite of the clear need for outsourcing, choosing a 3PL is a difficult, time-
consuming and potentially risky task. In order to ensure that the correct 3PL partner
is chosen as a business partner, an organisation must conduct extensive research.
Chapter two concludes by explaining the need for a good relationship between
organisations and their 3PL partners, and the critical role software serves in
achieving it. Choosing the right 3PL and building a strong partnership with them
205
through the use of technology, is a necessity in order to be able to compete in
today’s competitive organisational environment.
7.1.3 Chapter 3
The initial use of technology in the supply chain began in the early 1980s, however;
the real breakthrough in logistics technology came when new ways were identified to
substitute information for work content. This led to logisticians taking advantage of
powerful optimisation tools which optimised inventory management, network, routing
and transport optimisation and slotting optimisation in warehouses. Despite the
benefits of utilising technology in the logistics department, it was among the last to
join the personal computer bandwagon as organisations did not yet understand the
importance of their logistics network in providing a competitive product.
As organisations began to understand the importance of their logistics network, they
began to outsource this non-core, yet highly critical function of their organisation.
This led to the creation of the 3PL and then the creation of software to manage the
relationship between an organisation and its 3PL.
Despite the many advantages of utilising technology in the supply chain, it still has
some disadvantages. These advantages and disadvantages, as well as the general
benefits of utilising technology are discussed at length in chapter three. Although
there are many auxiliary benefits and advantages of implementing software systems
into the supply chain, the two critical benefits which justify the expense are reduced
costs and improved customer service. It needs to be remembered that these benefits
will not be achieved merely by implementing technology. The appropriate technology
rather needs to be implemented at the right time in the correct way. Even once the
appropriate technology has been implemented at the right time in the correct way,
there is still the issue of master data, which needs to be of high quality and inputted
at the correct time in order to ensure the desired outcome. Organisations need to be
aware that the implementation of a software system can make matters even worse if
software is implemented in lieu of correcting a broken distribution process. When it
comes to automating bad processes, software merely enables a faster flow of bad
information (Hagger, 2003; 1).
206
Chapter three then focuses on routing and scheduling software. The constraints
when routing and scheduling vehicles, as well as the benefits of good routing and
scheduling, are discussed. Other issues, such as the impact of efficient routing and
scheduling on the environment, are also investigated.
By explaining the necessity of implementing technology into an organisation’s supply
chain, chapter three illustrates the critical importance of technology in the supply
chain, and how an organisation would not be able to survive in today’s competitive
environment without the aid of technology.
Chapter three concludes by looking at numerous case studies in which technology
was implemented into the supply chain, as well as of routing and scheduling case
studies.
7.1.4 Chapter 4
Chapter four begins by providing an overview of the logistics function in the Clover
organisation. The Clover Group is currently the largest dairy group in South Africa
and collects and processes some 30% of South Africa's milk.
As a result of Clover realising the critical importance of logistics in its organisation,
Clover decided to form Clover Logistics to handle all of their logistics needs. This is a
division that specialises in the distribution of products for Clover, Clover Beverages,
Danone, as well as a large number of third party organisations. Clover Logistics is
the largest 3PL that focuses on the chilled and frozen distribution channel in South
Africa (Clover, 2007a; 5).
Chapter four takes an in-depth look at Magic, Clover Logistics’ previous management
support system. The analysis includes a step-by-step guide to the processes of the
magic system.
After looking at the complexities of Clover’s logistical needs and after analysing their
previous system, it is evident that the Magic system could not efficiently and
effectively handle Clover’s growing business requirements. By utilising the Magic
system, millions of rands were being lost due to inefficient routes, incorrect billing and
payments, as well as an inefficient use of manpower.
207
From chapter four it can be seen that Clover Logistics decided that it was time to
implement new technology into their supply chain as a result of their current
technology not being able to handle their growing complicated business needs. This
is clearly stated in the document drafted by Clover Logistics entitled “PD software
evaluation” (Clover Logistics, 2003b; 6). Numerous critical business needs were not
being catered for by the Magic system, including the need to remove duplication from
the Clover group, the need to improve vehicle utilisation through optimal routing and
scheduling, the need to produce accurate financial vouchers, as well as the need to
improve communication between all relevant parties. These needs were carefully
documented and assessed.
When publishing an RFP for a new system, Clover Logistics asked their in-house IT
department to respond to the RFP, as their first choice was to modify their in-house
Magic system to meet their needs. However, after much analysis it was clear that
upgrading their in-house Magic system would be more expensive and result in a less-
optimal product, than if they purchased a totally new system.
7.1.5 Chapter 5
Clover Logistics felt it was time to begin sourcing a new dynamic routing, scheduling
and financial management system as a result of their speedily growing business,
growing complexities and the need to improve the efficiency, competitiveness and
manageability of their organisation.
After much investigation, Clover Logistics’ management concluded that the key to
improving their supply chain was through collaboration with their internal
departments, as well as with their hauliers, clients and warehouses. Clover Logistics
realised that collaboration on this scale required cutting edge technology to facilitate
the necessary communication.
A request for proposal was sent out to 13 suppliers who Clover Logistics felt would
be able to present them with a possible solution. After much deliberation over the
proposed solutions, Clover Logistics decided to appoint Opsi Systems as their
technology provider.
208
Chapter five explains how Optima was developed and implemented, including some
of the challenges that were faced when implementing the new software.
There are five main stages an order goes through from the time it is entered into
Optima, until the time the order is delivered. Each stage is explained in detail,
including how Optima calculates the relevant financial vouchers and the master data
needed for the system to operate smoothly.
An explanation of how the Optima reporting function works, as well as a list of reports
that can be generated from Optima, is then detailed.
Chapter five concludes by explaining how Optima was developed to suit Clover
Logistics’ business needs. It tightly integrates with Clover’s other departments, and
through the web portal allows seamless communication with external hauliers and
Clover warehouses. Optima also allows for seamless integration with Clover’s
financial systems, ensuring that no data needs to be entered manually in order to
invoice customers and pay hauliers.
7.1.6 Chapter 6
In order to be able to fully comprehend the benefits and drawbacks of the
implementation of Optima into Clover Logistics, it was necessary to look at both the
qualitative and quantitative improvements and drawbacks that have occurred as a
result of the implementation of Optima.
The qualitative improvements and drawbacks that resulted through the
implementation of Optima were analysed from a number of different perspectives
including:
• The integration of Optima into Clover’s various ERP, financial and
tracking systems,
• Optimal routing and scheduling of Clover’s and their hauliers vehicles,
• The financial capabilities provided by Optima,
• The communication capabilities provided by Optima,
• Numerous different improvements provided by Optima.
209
Although financial savings can be indirectly attributed to many of the qualitative
benefits mentioned in section 6.1, the only financial savings that can be directly
accredited to the implementation of Optima are those savings achieved through
improved vehicle utilisation.
Chapter six details the financial savings achieved through improved routing and
scheduling as a result of Optima, and discusses how many of these savings were
achieved.
From the qualitative and quantitative discussions and calculations mentioned in
chapter six, it is clear that Clover Logistics have benefited financially, as well as in
many other spheres following the implementation of Optima into their supply chain.
As a result of the implementation of Optima, Clover Logistics saved
R1 043 850 per month in 2006 through the optimisation of its routes and scheduling
of its vehicles. This equals an annual saving of R12 562 200. This saving of
R12 562 200 per annum excludes indirect savings such as reduced communication
costs, and an improvement in cash flow as a result of a reduced order to cash cycle
time, improved customer service and other indirect savings.
With an improvement in on-time delivery from 85% to 99%, and a reduction in
incorrect invoices from 40% to 1%, Clover’s customer service levels have improved
drastically resulting in more satisfied clients and a competitive advantage in the
marketplace. Hauliers have benefited largely from Optima as a result of improved
communication and live visibility into all the loads assigned to them. Internally, Clover
Logistics have also benefited from the implementation of Optima as a result of a
reduction in duplicated tasks, reduced manual data entry, a reduction in errors as
result of miscommunication between internal Clover departments, and improved
communication with hauliers (Fourie, 31 July 2008).
Chapter six clearly establishes how the discarding of old technology and the
implementation of new technology has led to immense benefits for Clover Logistics.
Chapter one poses the dissertation’s study objective, being: implementing new
technology is a costly, challenging and sometimes risky task. This often leads
organisations to continue using their old, often in-house developed, systems and
210
processes until they outgrow them, or the business environment becomes so
complex, that they are forced to implement new technology. This hesitancy to
introduce new technology timeously could hamper the progress and growth of these
organisations and could also affect their competitiveness in a highly competitive
environment.
As it was the objective of this study to show that switching from old technology
systems to new technology systems could benefit organisations, it has been shown
that new technology systems have led to reduced costs and improved customer
service at Clover Logistics. This study clearly establishes how the replacement of
older technology systems has led to immense benefits for Clover Logistics. This
allows the researcher to conclude that the benefits of new technology systems have
advantaged Clover Logistics significantly when compared to the outdated and limited
capabilities of the old technology systems at Clover Logistics.
7.2 Summary and conclusion
Chapter 7 provides an overview of the entire dissertation. This was achieved through
an overview of each chapter.
Organisations often retain old, outdated technology as a result of new technology
being expensive, possibly difficult to implement, as well as the fact that organisations
often do not understand all of the benefits that new technology could provide. This
dissertation has shown through the example of Clover Logistics, that it is in the
interest of organisations to be aware of the benefits of new technologies in the
marketplace. Many old technologies only enable organisations to function at a basic
level which hampers their growth and efficiency. It is evident from this dissertation
that outdated technology could possibly be hampering the growth of many similar
organisations, just as old technology was hampering the growth and efficacy of
Clover Logistics. In order to obtain the maximum benefits from technology,
organisations need to regularly reassess whether they are utilising the best possible
systems and processes to allow them to function optimally in a competitive
environment. Although the results gained from this case study are specific to Clover
Logistics, the results of this case study could probably be replicated in 3PLs that find
themselves in similar situations.
211
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