current issues and challenges of supply...

European and Mediterranean Conference on Information Systems 2010 (EMCIS2010)

April 12-13 2009, Abu Dhabi, UAE

Peter Trkman, Ales Groznik

Current issues and challenges of supply chain management

1

CURRENT ISSUES AND CHALLENGES OF SUPPLY CHAIN

MANAGEMENT

Peter Trkman, University of Ljubljana, Faculty of Economics, [email protected]

Aleš Groznik, University of Ljubljana, Faculty of Economics, Slovenia, [email protected]

lj.si

Abstract

Efficient supply chain management is crucial for survival and success in a turbulent world. Current

economic crisis increases its importance even further. This conceptual paper reviews latest findings in

the most relevant areas, namely the importance of a proper supply chain strategy that is a pre-

condition for business process renovation and mitigation of supply chain connected risks.

Performance measurement is also a pre-condition for proper management. Supply chain frameworks

and standards that provide guidelines in facing those challenges are reviewed. Finally, the benefits of

supply chain informatization are shown.

Keywords: Supply chain management, business renovation, IT, supply chain risks, supply chain

frameworks

1 INTRODUCTION

It has often been claimed that in the modern world the competition is no longer between single

companies but between supply chains (Trkman et al., 2007), (Li et al., 2005). Anecdotic evidence also

supports this claim (e.g. the problems in automotive industry due to supplier failures or the infamous

Nokia-Eriksson-Phillips example (Chopra & Sodhi, 2004)). However, most of the papers are focused

on mathematical methods for supply chain optimization instead of an overview of business-related

challenges connected to supply chains

The challenge for firms today is namely not just to take up a supply chain management (SCM)

initiative but to implement it successfully. An informatics perspective is vital since information flow is

an integral part of SCM and material flow is closely dependent on information flow. But SCM

initiative can be a failure unless one is aware of the issues that may arise during its planning or

implementation (Varma et al., 2006).

However, SCM is, at best, still emergent in terms of both theory and practice (Storey et al., 2006),

therefore both further research and classification of previous research efforts is needed. This paper

mainly contributes to the second purpose; namely it presents several important issues in SCM.1

2 CURRENT ISSUES IN SCM

2.1 Strategic insights

Earlier purchasing was wedded to routine in many companies. For the last two decades though, no

company can allow purchasing to lag behind other departments in adjusting to worldwide changes

1 The paper is based on previous conference publication (Groznik & Trkman, 2009)





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(Kraljic, 1983). The recognition of the SCM as a key and vital area, both in the private and public

sectors, has focused attention on its effectiveness. In a number of organizations, cost-effective supply

chain is a matter of survival as purchased goods and services account for up to 80 per cent of sales

revenue (Quayle, 2003), while in the public sector there is an ever-increasing demand for savings in

the procurement process (Groznik et al., 2008).

However, there is (in line with the contingency theory) no single best way of organizing/leading the

supply chain that is effective in all situations and there is no universal set of choices that is optimal for

all SCs (adapted from (Fiedler, 1964), (Gingsberg & Venkatraman, 1985)). In order to optimize the

SC the following five configuration components are critical: operations strategy, outsourcing strategy,

channel strategy, customer service strategy and asset network (Cohen & Roussel, 2005). The four

main approaches towards production are make to stock, make to order (see e.g. (Gunasekaran & Ngai,

2005) for a comprehensive review of make to order SC challenges), configure to order and engineer to

order (Cohen & Roussel, 2005) – they considerably affect the correct strategy.

One of the main consequences of the lack of information exchange/coordination in the chain is the so-

called bullwhip effect, which was first theoretically described in the 60s (Forrester, 1961) and

practically in the 80s with the case of Pampers diapers. The fluctuation of demand namely increases as

we move up the supply chain; small fluctuations at the end of the chain can be propagated to

considerably larger fluctuations for e.g. the original equipment manufacturer. The main reasons for

bullwhip are (Chopra & Meindl, 2007):

• Rewards system

local optimization

employees rewards

• Information processing

lack of information

planning on the base of the orders not final customer demand

• Barriers

lot sizing

long lead-times

• Pricing policy

price fluctuation

quantity discounts

Another important decision is whether push or pull system should be used. The push system schedules

the jobs in advance for a series of work centres, and each work centre pushes its completed jobs to the

succeeding work centres. In a pull system uses a „pull‟ approach, where a work centre finishes its

operations and then requests the next job from the preceding work centre (Özbayrak et al., 2004).

Obviously the correct response is contingent on the industry in question. The Figure 1 shows the

percentage of companies in various industries that use different strategies.





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Fig. 1: Operations strategies by industry; Source: (Cohen & Roussel, 2005)

Business renovation in SCM

After successful strategy preparation, companies have to identify areas of possible improvement in

quality of product or service, lead times or operational costs. This step takes an integral view of all

organisations involved into the supply chain in order to renovate their operations towards supply chain

excellence. Business Renovation (BR) or business process renovation and informatisation efforts

integrate the radically strategic method of Business Process Re-engineering (BPR) and more

progressive methods of Continuous Process Improvement (CPI) with appropriate IT infrastructure

strategies. BPR is a thorough re-engineering strategy that critically examines current business policies,

practices and procedures, rethinks them and then redesigns the mission-critical products, processes and

services (Prasad, 1999). BPR seeks improvements by elevating efficiency and effectiveness of the

business process that exist within and across organizations. On the opposite, CPI refers to minor and

specific changes that one makes in an existing business process (Harmon, 2003). CPI relies on

building a fundamental understanding of customers‟ requirements, process capability, and the root

cause of any gaps between them by developing culture of continuous improvement in the areas of

reliability, process cycle times, costs in terms of less total resource consumption, quality, and

productivity. Six Sigma and Total Quality Management (TQM) are examples of approaches to CPI.

BR argues for a balanced approach between radical changes and continuous improvements. Table 1

summarizes comparison of BPR, TQM and Six Sigma on the basis of goal, level of change, scope,

focus and other characteristics.

According to Jacobson (Jacobson, 1995), we view business renovation as an umbrella concept for

strategic IS planning, and both BPR and CPI since thorough and effective renovation should combine

both, radical shifts (BPR) with those that permanently increase business efficiency and effectiveness

(CPI).





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BPR TQM Six Sigma

Level of change Radical Incremental Incremental

Scope Organization Processes Single process

Focus Start from scratch

Redesign current

processes

Improve current

processes

Participation Top-down Bottom-up Bottom-up

Role of IT Essential enabler Key enabler Key enabler

Other Enablers Process owners Statistical tools Statistical tools

Risk High Moderate Moderate

Principle goal Cost reduction Quality improvement Quality improvement

Table 1: Comparison of BPR, TQM and Six Sigma; source: (Simpson et al., 1999; Valentine & Knights, 1998).

Since direct changes can have a detrimental result, companies develop business models (Kovacic et

al., 2001). A business model is an abstraction of a business that shows how business components are

related to each other and how they operate. Its ultimate purpose is to provide a clear picture of the

company‟s current state and to determine its vision for the future. There are several reasons producing

business models (Eriksson & Penker, 2000):

• A business model helps us understand the business: one of the primary goals of business

modelling is to increase understanding of the business and to facilitate communication about the

business.

• A business model is a basis for creating suitable information systems: descriptions of the

business are very useful in identifying the information systems necessary to support the business.

Business models also act as a basis for engineering requirements when a particular information system

is being designed.

• A business model is a basis for improving the current business structure and operation: as it

shows a clear picture of the business current state, a business model can be used to identify the

changes necessary to improve the business.

• A business model provides a polygon for experiments: a business model can be used to

experiment with new business concepts and to study the implications of changes for the business

structure or operation.

• A business model acts as a basis for identifying outsourcing opportunities: using a business

model the core parts of a business system can be identified. Other parts considered less important can

be delegated to external suppliers.

The main purpose of developing and analysing business models is to find revenue and value

generators inside a reversible value chain, or a business model's value network. An example of AS-IS

and TO-BE process models are shown in Figures 2 and 3 (developed on a case of a company in oil

industry).





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gas station

purchasing

department

analytic

department

transport

company

Startmeasurement of

gas level

sending the

results to

purchasing

department

acceptance of

results from

different gas

stations

prediction of

future needs

supply

level high

enough?

End1Yes

aggregation and

optimization of

purchase orders

consultation with

gas station

No

order

confirmationorder OK?

final check of

created order

order correction

Yes

sending the

order to transport

company

acceptance of

order

transport of fuel

to gas station

creation of

purchase orders

acceptance of

delivery

No

consulati

on

needed?

No

Yes

waiting/preparati

tion of delivery

preparation of

orderunloading

End2

Figure 2: AS-IS business process model (Trkman et al., 2007)

transport

company

analytic

department

gas station

Start

identification of

the needs

(automatic)

aggregation of

purchasing

orders

(automatic)

informing the

analytic

departmment

optimization of

transportation

transport of fuel

to the gas station

acceptance of

deliveryEnd

order

confirmation

order

acceptance

waiting/preparati

tion of delivery

unloading

is

confirme

d?

order correction

order

needed?

End1

Yes

No

Yes

No

Figure 3: TO-BE business process model (Trkman et al., 2007)

2.2 Supply chain risks

The risk of disruptions caused by both factors within SC and outside environmental forces is a topic of

increased importance. Supply chain risk management is therefore a field of escalating importance and

is aimed at developing approaches to the identification, assessment, analysis and treatment of areas of

vulnerability and risk in SCs (Neiger et al.). Various trends that enhance exposure to risks, such as the

increased use of outsourcing, globalisation, reduction of the supplier base; reduced buffers, increased

demand for on-time deliveries or shorter product life cycles (Norrman & Jansson, 2004) are increasing





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the importance of SCRM. The sources of risks can be from suppliers‟, customers‟ or internal

environment (also shown in Fig. 4)

Figure 4: Sources of risks (The Supply Chain Council Risk Research Team, 2008)

The recently developed model ((Trkman & McCormack, 2009a) shown in Figure 5) sheds more light

on the prediction of suppliers‟ connected risks. It is based on the premise that different suppliers (and

their second and third tier suppliers) operate in different markets and environments; therefore their

turbulence and the forces influencing a supplier also differ. While a certain supplier strategy (e.g.

ordering large batches to decrease procurement costs or single-source suppliers with long contractual

commitments) may be acceptable in a non-turbulent environment, it may be detrimental in a more

turbulent one (e.g. in the presence of quick technological advances such as microprocessors or large

commodity price swings). Considering all of this, the same supplier attributes, strategy and structure

may pose considerably different risks of disruption. Therefore, a comprehensive approach to SCRM

has to include supplier-associated turbulence as well as various sources of uncertainty due to supplier

attributes such as strategy, structure and performance.

In order to distinguish between the different kinds of risks, the sources of uncertainty were separated

into two different constructs (Trkman & McCormack, 2009a):

- endogenous uncertainty: the source of uncertainty/risk is inside the SC and can lead to

changing relationships between focal firm and suppliers, the most notable kinds are market

and technology turbulence. Market turbulence is likely to arise from the heterogeneity and

rapid changes in the composition of customers in the market and their preferences (Kandemir

et al., 2006). It means continuous changes in customers‟ preferences/demands, in price/cost

structures, and in the composition of competitors (Calantone et al., 2003). Technological

turbulence refers to the degree to which technology changes over time within an industry and

the effects of those changes on the industry (Chatterjee, 2004). Technological turbulence

arises from changes in the underlying technologies of products or services and their rates of

obsolescence (Kandemir et al., 2006). Technical dynamics includes how fast the related

technology is changing, as well as breakthroughs in the manufacturing process, and mass

production techniques (Hsu & Chen, 2004);

- exogenous uncertainty: the source of uncertainty/risk is from outside the SC. These risks are

further divided into the two most notable kinds; namely discrete events (e.g. terrorist attacks,

contagious diseases, workers‟ strikes) and continuous risks (e.g. inflation rate, consumer price

index changes).





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Endogenous

uncertainty Risk of Supplier

Non Performance

or Disruption

in a SC

Supplier Attributes

SC Strategy

and Structure

Exogenous

uncertainty

Market Turbulence

New products

Price sensitivity

Level of competition

Demand swings

New customers v. repeat

Continuous

Interest rates

CPI

GDP

Commodity prices

Discrete

Terrorism

Disasters

Strikes

Technology Turbulence

Rapid changes

High tech influenceFinancial Performance

Human Resource Factors

Operational Factors

Culture

Relationship Factors

SC type

lean, agile, hybrid

Suppliers Types

Business Structure

Geographic Location

Endogenous


Non Performance

or Disruption

in a SC

Supplier Attributes

SC Strategy

and Structure

Exogenous

uncertainty

Market Turbulence

New products

Price sensitivity


Demand swings


Continuous

Interest rates

CPI

GDP

Commodity prices

Discrete

Terrorism

Disasters

Strikes


Rapid changes

High tech influence

Endogenous


Non Performance

or Disruption

in a SC

Supplier Attributes

SC Strategy

and Structure

Exogenous

uncertainty

Market Turbulence

New products

Price sensitivity


Demand swings


Continuous

Interest rates

CPI

GDP

Commodity prices

Discrete

Terrorism

Disasters

Strikes


Rapid changes

High tech influenceFinancial Performance

Human Resource Factors

Operational Factors

Culture

Relationship Factors

SC type

lean, agile, hybrid

Suppliers Types

Business Structure

Geographic Location

Figure 5: Conceptual model for suppliers’ connected risks (Trkman & McCormack, 2009a)

The current approaches only offer a limited estimation of the risk of supplier non-performance. The

proposed approach (see (Trkman & McCormack, 2009a) for more details) enables the estimation of

the risks and helps the company to make a more informed decision as to how much risk it is willing to

take and which risks will it mitigate (either with dual/multiple sourcing or with the change of

supplier).

Dual sourcing is namely an important topic – while it may increase the costs due to activities

connected with supplier search and qualification it can considerably decrease the costs of supplier non-

performance or even bankruptcy (see e.g. (Sheffi, 2001), (Wang & Zhao, 2007)).

2.3 Supply chain frameworks and standards

In order to streamline businesses and bridge the supply chain risks, different frameworks and

standards (SCOR, GS1, MMOG/LE, ISO 9001, ISO 14001, BS OHSAS 18001, BS 25999, ISO/IEC

27001, etc) have been developed. The organizations are facing the challenge which one to implement

and to what extent. The adoption of frameworks and standards causes standardization of business

operations that is in contradiction with agile supply chain strategies and lean business models. From

the business model point of view the most relevant is the Supply-Chain Operations Reference (SCOR)

model that was developed by the Supply-Chain Council (SCC) to assist organisations in increasing the

effectiveness of their supply chains, and to provide a process-based approach to SCM (Stewart). The

SCOR model (Figures 6 and 7) provides a common process oriented language for communicating

among supply-chain partners in the following decision areas: PLAN, SOURCE, MAKE, DELIVER

and RETURN.





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Figure 6: SCOR framework (Supply Chain Council, www.supply-chain.org)

SCOR is a top-down analytical method that help organizations break out of the box and see where

they fit into the SC. SCOR provides three-levels of process detail. Each level of detail assists a

company in defining scope (Level 1), configuration or type of supply chain (Level 2), process element

details, including performance attributes (Level 3). Below level 3, companies decompose process

elements and start implementing specific supply chain management practices. It is at this stage that

companies define practices to achieve a competitive advantage, and adapt to changing business

conditions (Figure 7).

As a framework it also facilitates inter and intra supply chain collaboration, horizontal process

integration, by explaining the relationships between processes (i.e., Plan-Source, Plan-Make, etc.). It

also can be used as a data input to completing an analysis of configuration alternatives (e.g., Level 2)

such as: Make-to-Stock or Make-To-Order. SCOR is used to describe, measure, and evaluate supply

chains in support of strategic planning and continuous improvement.





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Figure 7: Detailed SCOR framework; source: Supply Chain Council, www.supply-chain.org

Although SCOR framework is widely used it has limitations that have to be taken into account. Cases

in literature (Wang et al., 2005) show that limitations for applying SCOR in improving current

interfirm processes regarding graphical presentation, „gaps‟ identifying, and none-defined business

activities that are summarized below:

• SCOR can only present business flow in between legal or geographical entities but not any matrix

organisation structure or the concept of „virtual enterprise‟.

• SCOR is limited to the presentation of one single supply chain while most of the enterprises may be

associated with multiple channels of markets and products.

• The KPI of SCOR is not always available in the target firm, particular when it involves with cross-

sites information.

• Problems sometimes can not be identified by KPI gaps such as information systems readiness.

Some essential activities are not defined in SCOR standard, for example,

• Demand up-size and down-size from order changes, e.g., emergent orders or order cancelling.

• The activities of collaborative design and customer relationships management are not defined in

SCOR.

Researching the link between frameworks or standards and supply chain performance is scarce.

Lockamy & McCormack (Lockamy & McCormack, 2004) have studied the link between SCOR

planning practices and supply chain performance and shown that the supply chain planning practices

related to process integration, collaboration, teaming, process measurement, process documentation

and process ownership have been shown to be important to supply chain performance, but lack broad

implementation by supply chain partners. This suggests that integrated supply chain management may

be more difficult to operationalize in practice than the popular supply chain press or consultants would

have one to believe.





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This study also suggests is that some of the best practices proposed as mechanisms for improving

overall supply chain management performance may not have the degree of impact often presented in

the literature. Some best practices help to improve supply chain performance only in specific decision

areas.

2.4 Performance measurement in SCM

A well known-saying is that: „You Can‟t Manage What You Can‟t Measure‟. Therefore all

frameworks and research efforts emphasize the importance of performance measurement. Before

investigating different performance measures it is important to note that performance measures have to

be closely connected with strategy, business model and also the objectives of a company/SC. This

connection is also shown in Figure 8.

Figure 8: Connection between strategy and measurement system(Santos & Gomes, 2006)

The starting point for performance measurement is that the metrics should:

• be directly related to the manufacturing strategy,

• primarily use non-financial measures,

• vary between locations,

• change over time, as needs change,

• be simple and easy to use,

• provide fast feedback to operators and managers,

• be intended to foster improvement rather than just monitor (Persson & Olhager, 2002).

Performance measurement focuses on two connected but still separable areas, namely the

measurement of performance of each supplier and the measurement of supply chain as a whole. The

classic metrics for supplier performance measurement are replenishment lead time, on-time

performance, supply flexibility, delivery frequency, quality, viability, information coordination

capability etc. (Chopra & Meindl, 2007). According to the recent survey the most important measures

are quality of delivered goods, on time delivery and flexibility of supply (Gunasekaran et al., 2004).

Since balanced scorecard (Kaplan & Norton, 1996) is in general one of the most widely used models

for performance measurement its application to supply chain area has also been proposed. Such an

example is presented in (Park et al., 2005) who derived the objectives for SCM from financial,





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customer, business process (both internal and external) and learning and growth perspective. As

shown performance measurement is closely connected with process renovation outlined in the

previous section (see e.g. (Theeranuphattana & Tang, 2008) as an example of performance metrics for

each of the supply chain processes.

Different performance measures can also be used at various decision areas of the SCOR model; for

example supplier delivery performance and purchase order time are suitable metric for “SOURCE”

while utilization of resources or percentage of defects are more relevant for “MAKE” phase (see e.g.

(Gunasekaran et al., 2004) for more details). The review of customer and internal facing metrics is

also shown in Figure 9.

One of the increasingly popular approaches for both measurement of effectiveness and prediction of

changes due to renovation of supply processes is the use of simulations. They enable the preparation

of the models of current and desired state (Caridi et al., 2004) and can be used to estimate the risks of

different events (Cho & Eppinger, 2005). In connection with business process modeling (see chapter

2.2. of this paper) they can be used to compare different configurations of business processes (Roeder

& Tibken, 2006). Figure 10 shows the analysis of different scenarios (with the increasing use of e-

procurement) and the consequent changes in lead times.

Figure 9: Main metrics for supply chain performance measurement (Lai et al., 2002)





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0

200

400

600

800

1000

1200

1400

1600

1800

2000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

no. of days

no

. o

f tr

an

sa

cti

on

s

scen1

scen2

scen3

scen4

Figure 10: Distribution of lead times in various scenarios (Trkman & McCormack, 2009b)

2.5 Supply chain informatization

Final issue in SCM is supply chain informatization which is by far an easy task. Information

technology is an important enabler of effective supply chain management. Much of the current interest

in SCM is motivated by the possibilities that are introduced by the abundance of data and the savings

inherent in sophisticated analysis of these data (see e.g. (Davenport, 2006) for several successful case

studies). SC must move from mere cooperation and coordination to true collaboration which requires a

foundation of trust and commitment. According to Ruppel (Ruppel, 2004) core issues of SC

informatization are:

- ability to secure since trust is important from relationship point of view. From technological

point of view a company can attempt to protect itself from exploitation while maintaining an

open collaborative system by its ability to secure SCM systems.

- return on investment (ROI) which is a panacea oversold by vendors (Krizner, 2002).

According to Nickles (Nickles, 1999), ROI may not be the correct indicator when technology

whose purpose is to facilitate relationships is applied. ROI could be applied in case of

technology that reduce internal costs. The recent slowing down of the economy has led to a

renewed emphasis on the use of ROI assessment.

- cost/affordability relative to budget is related to but not the same as ROI. Even if a tool has the

potential for a high rate of return, if an organization cannot afford the costs involved in

purchasing and implementing the tool they cannot gain the potential benefits.

- fit with business user needs is key to successful technology introduction. It has often been

suggested that technology should not be implemented merely for technology‟s sake, but rather

to meet specific business need. SCM informatization should meet the needs of business users,

while still being compatible with existing systems. Matching or aligning of users‟ business





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needs with technology should be a threshold criterion to ensure appropriate technology

choices.

The innovative opportunities coming to the fore with e-business have increased the interest in IT.

From technological perspective SCM spans over internal as well as external systems, which facilitates

information transfer between various organizations. In addition, SCM typically includes many

functional areas within an organization and is affected by the way the various groups communicate

and interact.

According to Simchi-Levi (Simchi-Levi et al., 2000) ultimate goals (Figure 11) of IT are to collect,

access and analyze information. In practice that SCM systems have to:

- collect information on each product from production to delivery or purchase point and provide

complete visibility for all parties involved,

- access any data in the system from single-point-of-contact,

- analyze, plan activities, and make trade-offs based on information from the entire supply

chain.

In order to achieve these goals, major issues (Figure 11) in informatization are standardization,

infrastructure e-business, supply chain components and integration. Standardization is vital for IT

since it allows systems to work together and is a key feasibility factor of SCM implementation.

Infrastructure is a basic component of system capabilities without which some of the goals cannot be

achieved. E-business is an emerging area of business conduct that provides cost-effective way of

SCM. Supply chain components are various systems that are involved directly in supply chain

planning. These are typically systems that combine short-term and long-term decision support system

elements.

Figure 11: Goals and means of SCM – an IT view(Simchi-Levi et al., 2000)

The goal of SCM software is to increase flows through collaboration. However, increasing

collaboration is not merely a matter of making a tool available. Participants must be encouraged to use

the tool share information to make its use effective. Ruppel (Ruppel, 2004) compared adoption of

three information technologies (i.e. group decision support systems, EDI and e-business) that can be

used to improve information flows and the factors that affect their adoption and use. Comparison

indicates that the decision to adopt one of these technologies does not guarantee its effective use.

Those who wish to champion the use of tools have a complex task to perform not just to foster

adoption, but also to encourage successful implementation.





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The real challenge of implementation is bridging the gap between IT, process and performance view

(Figure 12). According to Gun Kim (Byoung et al., 2008) business processes are key integrator

providing performance-process-IT relation to elicit the actual impacts. To connect the performance

with IT, business processes are acted as mediators between them. Linkage could be explained via

reliance level of a business process that corresponds to the allied IT system.

Figure 12: Goals and means of SCM – an IT view (Byoung et al., 2008)

3 CONCLUSION

The paper has tackled a vital challenge to provide a comprehensive review of several inter-connected

challenges in supply chain management. Only continuous efforts in each of the mentioned areas assure

efficiency and success. Nevertheless, optimal decision making is not possible since the choice set is

too complex and generally unknown, due to the large number of possibilities and uncertainties.

Therefore SCM »optimization« involves a small number of choices at each step of exploration (Lee &

Ahn, 2008). We hope that our paper is a small but significant contribution in this quest

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