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Business Intelligence Software 1
Running head: BUSINESS INTELLIGENCE SOFTWARE
Business Intelligence Software
Customers’ Understanding, Expectations and Needs
Adis Sabanovic
Thesis for the Master’s degree in Business Administration, Spring 2008
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Executive summary
Modern companies operate in incredibly complex and dynamic environments. This is clearly characterized by constant changes in technology and in various market forces as well as by enormous amounts of data and information that need to be gathered and analyzed every day. Governmental regulations and ongoing competitor pressures, among other external and internal factors, are issues that managers and decision makers in a company must take into a consideration when making decisions. The need for BI systems is growing stronger and businesses in various industries demand such tools that will help them stay on the edge in order to be competitive. Hence the purpose of this paper is to find out what their companies desire when choosing a BI system to work with. What are their needs and what do they expect and understand from this technological system that will hopefully make them work easier and gain their knowledge about the business they operate in.
A web questionnaire is aimed at 67 Swedish companies from various industries and the answers have been summarized and analyzed in different cross tables for comparison reasons. Respondents from the Manufacturing industry were those with the highest response rate. A model called The PET-model of BI implementation was created, as a result of the theoretical findings, and this model is used to finalize the results and the conclusions of this paper.
Key words: BI, Business Intelligence, Business Intelligence Software, Competitive Intelligence, Decision Support Systems
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TABLE OF CONTENTS
1 INTRODUCTION .................................................5
1.1 BACKGROUND ..................................................... 5 1.2 THE DEFINITION OF BUSINESS INTELLIGENCE .............. 6 1.2.1 BI wide‐ranging ............................................ 7 1.2.2 Business Intelligence Software ..................... 8 1.2.3 Why BI software ........................................... 8 1.2.4 Some categories of BI Tools.......................... 9 1.2.5 BI software in organizations....................... 10 1.2.6 Expectations and needs of a BI software.... 11 1.2.7 Common issues regarding BI usage............ 12 1.2.8 Market of BI solutions today ...................... 13 1.3 DEFINITIONS ..................................................... 15 1.4 LIMITATIONS ..................................................... 17
2 METHOD..........................................................18
2.1 CHOICE OF METHODOLOGY .................................. 18 2.2 RESEARCH PHILOSOPHY ....................................... 18 2.3 CHOICE OF THEORY............................................. 19
3 THEORETICAL FRAMEWORK.............................21
3.1 BI SOFTWARE CLASSIFICATION............................... 21 3.1.1 End‐user query, reporting, and analysis ..... 21 3.1.2 Advanced analytics..................................... 22 3.2 ANALYTICAL APPLICATIONS................................... 23 3.2.1 Logical integration...................................... 24 3.2.2 Interactive reports ...................................... 25 3.2.3 Integrated information............................... 25 3.2.4 Addressing of a Business domain ............... 25 3.3 TYPES OF BUSINESS INTELLIGENCE SYSTEMS ............ 26 3.3.1 Model‐driven BI system.............................. 26 3.3.2 Data‐driven system .................................... 26 3.3.3 Communication‐driven system................... 26 3.3.4 Document‐driven system............................ 27 3.3.5 Knowledge‐driven system........................... 27 3.3.6 Web‐based system ..................................... 27 3.4 REAL‐TIME BI SYSTEM......................................... 27 3.5 HOW REAL‐TIME BI SYSTEM WORKS ...................... 28 3.5.1 Time importance when working with BI..... 28 3.6 THE DIFFERENT USER‐GROUPS OF BI ...................... 31 3.7 BI PLACEMENT IN THE ORGANIZATION .................... 32 3.7.1 The special dept. model of intelligence ..... 32
3.7.2 The advisory model of intelligence ............. 32 3.7.3 The professional model of intelligence ....... 33 3.7.4 The top‐down model of intelligence ........... 34 3.7.5 The Integrated Intelligence Model.............. 34 3.7.6 The down‐up model of intelligence ............ 35 3.7.7 The departmental model of intelligence..... 35 3.8 SOME BI TOOLS ON THE MARKET TODAY................. 36 3.9 SUBSOFT – BRIEF PRESENTATION ........................... 39 3.10 THEORY MODEL CREATION ................................... 41
4 EMPIRICAL METHOD ....................................... 45
4.1 RESEARCH STRATEGY .......................................... 45 4.2 TIME HORIZON................................................... 45 4.3 DATA COLLECTION METHOD.................................. 46 4.4 POPULATION ..................................................... 47 4.5 SAMPLE SELECTION ............................................. 48 4.6 RESEARCH CONDUCTION ...................................... 48 4.7 BI RESEARCH PLAN.............................................. 49 4.8 DATA ANALYSIS .................................................. 53 4.9 RESEARCH QUESTIONS......................................... 53 4.10 RELIABILITY AND VALIDITY.................................... 54
5 ANALYSIS ........................................................ 55
5.1 EMPIRICAL FINDINGS........................................... 55 5.2 CRITIQUE .......................................................... 62 5.3 ANALYSIS CONCLUSIONS ...................................... 63 5.4 SUBSOFT ‐ COMPARED TO THE RESEARCH FINDINGS ... 65
6 THESIS CONCLUSION ....................................... 67
6.1 PRACTICAL RELEVANCE ........................................ 67 6.2 DISCUSSION ...................................................... 67
LIST OF REFERENCES ............................................. 69
APPENDICES ......................................................... 72
APPENDIX 1, EMAIL (SWEDISH) ..................................... 72 APPENDIX 2, EMAIL (ENGLISH)...................................... 73 APPENDIX 3, QUESTIONNAIRE RESULTS........................... 74 APPENDIX 4, QUESTIONNAIRE ....................................... 82 APPENDIX 5, INDUSTRY ‐ ANSWERS ................................ 92
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LIST OF TABLES
TABLE 1 - WORLDWIDE BUSINESS INTELLIGENCE TOOLS REVENUE BY SEGMENT, 2004–2006.......14 TABLE 2 – PET MODEL’S PURCHASE FOUNDATIONS IN THE MANUFACTURING INDUSTRY ..............56 TABLE 3 - PET MODEL’S PURCHASE FOUNDATIONS IN ALL INDUSTRIES COMBINED ........................59 TABLE 4 - PET MODEL’S EMPLOYMENT FOUNDATIONS IN ALL INDUSTRIES COMBINED...................59 TABLE 5 - PET MODEL’S TASK FOUNDATIONS IN ALL INDUSTRIES COMBINED ................................61
LIST OF FIGURES
FIGURE 1 - WORLDWIDE BUSINESS INTELLIGENCE TOOLS REVENUE SHARE BY REGION, 2006.......15 FIGURE 2 – CLASSIFICATIONS OF BI SOFTWARE.................................................................................1 FIGURE 3 - REAL-TIME BI PROCESSING COMPONENTS .......................................................................1 FIGURE 4 – LATENCY IN BUSINESS INTELLIGENCE DECISION MAKING (HACKERTHORN, 2003)..........1 FIGURE 5 – REAL-TIME BI; ACTION TIME VS. IT COSTS (WHITE, 2003) ...........................................30 FIGURE 6 – DIFFERENT BI USER NEEDS IN THE HIERARCHY (SOLBERG SØILEN, 2008) .......................1 FIGURE 7 – THE SPECIAL DEPARTMENT MODEL OF INTELLIGENCE (SOLBERG SØILEN, 2008).............1 FIGURE 8 – THE ADVISORY MODEL OF INTELLIGENCE (SOLBERG SØILEN, 2008)................................1 FIGURE 9 – THE PROFESSIONAL MODEL OF INTELLIGENCE (SOLBERG SØILEN, 2008).........................1 FIGURE 10 – THE TOP-DOWN MODEL OF INTELLIGENCE (SOLBERG SØILEN, 2008).............................1 FIGURE 11 – THE INTEGRATED INTELLIGENCE MODEL (SOLBERG SØILEN, 2008)...............................1 FIGURE 12 – THE DOWN-UP MODEL OF INTELLIGENCE (SOLBERG SØILEN, 2008)...............................1 FIGURE 13 – THE DEPARTMENTAL MODEL OF INTELLIGENCE (SOLBERG SØILEN, 2008) ....................1 FIGURE 14 – SUBSOFT MODEL OF INTERNAL AND EXTERNAL FACTORS (SUBSOFT, 2008)..................1 FIGURE 15 – THE PET MODEL OF BI IMPLEMENTATION .....................................................................1 FIGURE 16 – BI RESEARCH PLAN ......................................................................................................52 FIGURE 17 – SURVEY RESPONDENTS REPRESENTED FROM DIFFERENT INDUSTRIES. .........................55 FIGURE 18 – PET MODEL AFTER THE ANALYSIS ................................................................................1
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1 Introduction
This Chapter describes the definition of Business Intelligence, why we choose to
use it and also anticipated problems when using it as well as the purpose of this
thesis. For the start, a short historical background about the term Business
Intelligence is presented.
1.1 Background
In the modern world of today the access to information is greater than ever before.
In many cases the information flow is overwhelming and it sometimes leads to
valuable information losses. Company leaders and other decision makers are
trying to overcome this problem by investing in various sophisticated
computerized solutions, also known as Business Intelligence Systems. But it is not
only in the modern world that Business Intelligence Systems have been
appreciated for their great capabilities of creating a better understanding of one’s
working environment.
In 1958, the term Business Intelligence is used for the first time in an article called
A business intelligence system by Hans Peter Luhn. Luhn was describing how to
automate the process of collecting and sorting information from documents using
current photo-printing technology. He was saving information on magnetic tapes
and driving it through a process of auto encoding and auto abstracting programs
to later sort it in different pattern storages. Processed information would then be
put into a comparison area and sorted into three main categories: who needs to
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know, who knows what, and what is known (Luhn, 1958). Already in 1958, Luhn
had discovered the importance of information processing and that all greater
information flows contains even greater value for the one who has the ability to
turn it into knowledge. However, in his article Luhn admits that the type of
equipment used for processing information, in late 1950’s, was in early stage of
development and that a great deal of research has yet to be done to perfect the
information processing technique.
Ever since Luhn introduced us to Business Intelligence terminology, the
importance of knowing how to turn information into knowledge has grown
tremendously, especially among today’s modern business leaders and other
decision makers around the world.
1.2 The definition of Business Intelligence
Today, after many facelifts and makeovers of BI there are quite many definitions.
In many cases the same definition will be used for other terms such as;
Competitive Intelligence (CI) or Decision Support Systems (DSS).
A more recent definition of the term was coined by The Data Warehousing
Institute (TDWI), a provider of education and training in the data warehousing
and BI industry; and is as follows(Loshin, 2003, p. 6):
The process, technologies, and tools needed to turn data into information, information into knowledge, and knowledge into plans that drive profitable business action. Business intelligence encompasses data warehousing, business analytic tools, and content/knowledge management.
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The characterization of the term Business Intelligence or BI, as it will be referred
to throughout this paper, is basically still the same as in the early 1960’s but the
significance and understanding of BI has changed as technology has improved,
organizations have decentralized and the complexity levels of new information
have increased.
1.2.1 BI wide-ranging
The popularity of the term “Business Intelligence” has grown rapidly in the last
decade. As mentioned earlier the definition of a BI software is yet somewhat
open-ended and may differ from author to author. BI gives the impression of being
a multifaceted term that can refer to processes, techniques or tools to support the
making of faster and better decisions (Pirttimäki & Hannula, 2003). Expectations of
what a BI software is supposed to perform, or accomplish, is even more
differently understood by the users. In many cases, corporations are already using
some kind of BI tools or solutions but have chosen to call them differently, e.g.
Management Information Systems (MIS), Decision Support Systems (DSS),
Executive Information Systems (EIS), et cetera. (Pagels-Fick, 2000) It is also
common that companies, unknowingly, use small parts of a complete BI system,
e.g. CRM- Customer Relation Management (CRM) and Knowledge Management
which focuses exclusively on customers and knowledge while a complete BI
system primarily deals with information (Solberg Søilen, 2005).
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1.2.2 Business Intelligence Software
Business Intelligence (BI) software is used as an effective reporting and analyzing
tool to better understand a company’s organizational surrounding and
environment and it gives managers basic data for decision. There are some main
and very basic objectives that a BI tool must accomplish. These are to generate
better information than your rivals do, to analyze that information and make
sound choices, to make those choices quickly and to convert strategic choices into
decisive actions (Vine, 2000).
1.2.3 Why BI software
There are many reasons for why a company should use business intelligence or
decision support systems. Eckerson (2004) has, in his research, found that BI
systems do not only help decision makers to make better and more efficient
decision but that BI also helps the entire organization to improve Return on
Investment (ROI) profitability, gain customer/supplier, as well as employee,
satisfaction, et cetera. He also points out that if one BI system is implemented
throughout the entire company, there is a single version of truth which helps the
company to avoid misunderstandings and gets everyone going in the same
direction (Eckerson, 2004).
Loshin (2003) points out how Customer Relationship Management is improved
and how certain risks are decreased by analyzing supplier/consumer activity and
reliability, providing insight into how to rationalize the supply chain. BI can also
help the companies to evaluate organizational costs and to improve logistics
management, lowering the operational costs and decreasing the investments
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required to make sales. Another areas of usage for BI is evaluation of customer
lifetime value, short term-profitability expectations and using this knowledge to
distinguish between profitable and non-profitable customers to increase
profitability (Loshin, 2003).
1.2.4 Some categories of BI Tools
Most companies today use a set of different BI tools, instead of focusing on only
one. The reason for that may be simple; different users prefer different types of
BI tools. The tools may differ in reporting, ad hoc queries, OLAP, et cetera. BI
tool vendors are doing their best to meet all those requirements allowing
organizations to standardize on using one single tool and on one single vendor
(DM Review and SourceMedia, Inc., 2005). Below, a list of some major
categories of BI tools is presented:
• Production Reporting Tools: Used by professional developers to create
standard reports for groups, departments or the enterprise.
• End-User Query and Reporting Tools: Used by end users to create reports
for themselves or others and require no programming.
• OLAP Tools: Enable end users to "slice and dice" data dimensionally to
explore data from different perspectives and time periods.
• Dashboard/Scorecard Tools: Enable end users to view critical
performance data at a glance using graphical icons and drill down to
analyze detailed data and reports if desired.
• Data Mining Tools: Enable statisticians or business analysts to create
statistical models of business activity.
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• Planning and Modeling Tools: Enable analysts and end-users to create
business plans and simulations against BI data. Planning tools supply
dashboards and scorecards with targets and thresholds for metrics.
(DM Review and SourceMedia, Inc., 2005)
1.2.5 BI software in organizations
When a company’s business information is isolated in different BI tools the
information risks to disappear and to never be used again. Many companies are
therefore trying to tie the information together to create one overall strategy
(Rådmark, 2007). Different suppliers of BI solutions are offering a too wide range
of products as decision makers are only requiring one product that will give them
a better overall picture of the company’s activities and the surrounding
environment.
In the early days, BI software’s focus was on the technical solutions and on the
business analysis process that would provide the decision makers with
information needed. Nowadays a BI-software must focus on making the
information available for more people (workers) in the organization and making it
more usable (Rådmark, 2007). Most companies are using different systems that
control the information torrents, but only those who use BI can exploit the crucial
information from different sources and decide what information to use. The
leaders or decision makers are more interested in that specific information than in
what technology is used exploiting it. It is about the management information
rather than technology, because when the technical side is in focus the attention is
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rather on the applications instead of creating what is best for decision making
through small and complex BI solutions.(Lindström, 2007)
Traditionally, BI takes place high up in the organizations’ hierarchy but in today’s
organizations there is a strong demand for BI solutions that gives all decision
makers access to relevant information, regardless of the level in the organization.
One problem, Rådmark points out, is that if there are several solutions in the
organization, there is a lack in the common strategy and responsibility
distribution. Since BI, in its best form, should cut through the whole organization,
or the bigger parts of it, it is not possible to place responsibility on one certain
function. Therefore, the problem that many organizations face today is that BI
tools are requiring a change in the organizational structure to create the best
possible environment to not isolate vital business information but rather to spread
and distribute it throughout the whole organization (Rådmark, 2007). The
possibility of bringing fast information and making in transparent is very
important. It is not only economically effective but also a competitive advantage
to be able to analyze information faster and more effectively than your
competitors (Lindström, 2007).
1.2.6 Expectations and needs of a BI software
A research conducted by BetterManagement (division of a SAS institute Inc.
which does researches about business management issues around the world) in
2005 showed that only nine percent of BI software users were always provided
with all the necessary information from the BI software to make effective business
decisions and that only 45 percent of the users did sometimes get all the
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information they needed (Miller, Bräutigam, & Gerlach, 2006). These numbers
indicate that many corporate leaders have high expectations on a BI software
before purchasing it but in very few cases the decision makers will actually
completely rely on the information extracted from the software. What was instead
demanded, or needed, by the companies, according to the survey, were the
following statements:
1. Improved quality of information available to them.
2. Access to relevant information in easy to use reporting interfaces for ad
hoc reporting.
3. Assistance with interpreting and drawing conclusions from the
information.
4. Access to relevant information in standard reports.
5. An overview of which data is available for analysis.
6. A formal assessment of their information needs.
7. Training on how to use BI tools.
(Miller, Bräutigam, & Gerlach, 2006)
1.2.7 Common issues regarding BI usage
Companies that have started data warehousing projects or have purchased large-
scale data mining software suites often have very high expectations but also many
disappointments related to failure in the way that data is conceived, designed,
architected, managed and implemented. The vague understanding of what BI
methods and products can do frequently results in a lack of a proper value
proposition on behalf to the business sponsor (Loshin, 2003). Also the scope of
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the project is not always fully understood which causes delays in delivery to the
decision maker. Another issue that companies face when using BI is insufficient
technical training of the users. This prevents company’s developers and analysts
from using software products to the full capacity and from doing what the vendors
claim they do. Poor understanding of technology infrastructure also leads to
disadvantages such as poor planning and scheduling which often leads to lack of
trustworthiness in the results due to poor data quality. Some BI software users
also lacks a clear statement of success criteria, along with a lack of ways to
measure program success and this is inevitably leading to a perception of failure
(Loshin, 2003).
1.2.8 Market of BI solutions today
According to a report from Datamonitor (leading provider of online database and
analysis services for key industry sectors) the market for business analysis is
increasing tremendously fast. The report shows that the value of the BI market
will increase from four billion dollars in 2006 to an estimated eight billion in
2012. This means an annual raise is about 12,5%. The battle between small
independent BI suppliers is losing attention while the focus is now on the big
giants that are constantly buying smaller BI suppliers (Wallström, 2007).
According to Gartner, the world’s leading information technology research and advisory
company, the market of BI solutions is basically shared between three mega-suppliers,
Oracle, SAP and Microsoft who together own about 20% of the global market.
Fusions between these mega suppliers and smaller ones are occurring constantly.
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Today’s BI tools have a broader area of usage and BI is not only about reports and
analytics but also about real time dashboards and scorecards, predictive models,
workflows, visualizations and searches. Basically, the market for BI tools consists
of two segments, Query, reporting and analysis (QRA) and advanced analytics
(Adv. An). (A more detailed explanation of the two segments will follow in the
theory chapter). In 2006, as shown in Table 1, the BI tools market grew 11.5%
and reached $6.25 billion in worldwide license and maintenance revenue. During
that time there was no significant consolidations in the BI tools market (Vesset &
McDonough, 2007). A huge number of mergers and acquisitions occurred
between larger BI tools vendors and smaller software vendors.
Table 1 - Worldwide Business Intelligence Tools Revenue by Segment, 2004–2006
Revenue ($M) Share (%) Growth (%)
2004 2005 2006 2004 2005 2006 ’04-‘05 ‘05-‘06
QRA 4,004.9 4,487.6 5,008.5 79.5 80.0 80.1 12.1 11.6
Adv. An. 1,031.9 1,118.6 1,244.6 20.5 20.0 19.9 8.4 11.3
Total 5,036.7 5,606.2 6,253.0 100.0 100.0 100.0 11.3 11.5
(Vesset & McDonough, 2007)
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In Figure 1 the geographic allotment of the BI tools market is shown. The
Americas region has the largest segment of the market, followed by Europe, the
Middle East, and Africa (EMEA) and Asia/Pacific.
Figure 1 - Worldwide Business Intelligence Tools Revenue Share by Region, 2006
(Vesset & McDonough, 2007) (IDC, June 2007)
1.3 Definitions
Business Intelligence Software, -System, -Application – program that makes
decision making more efficient and easier through different processes like
information gathering, analysis, spreading of information and communication
within a company.
Business Process – a complete series of activities in a company or an authority.
Dashboard/Scorecard - a dashboard or scorecard is a graphical display that
compares performance against predefined goals. A dashboard records actual
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performance or behavior, like an automobile dashboard, while a scorecard
measures that performance against objectives or goals. A dashboard tells how you
are doing, a scorecard, how well. (Eckerson, 2005)
Embedded Business Intelligence – a business analysis that is built into different
business programs and that does not exist as separate program.
Neural Network – an interconnected group of artificial neurons that uses a
mathematical or computational model for information processing
OLAP – On-line Analytical Processing – a technique for searching gathered data
from databases while they are online. OLAP is used for sales analysis and
decision making. OLAP can be used as an alternative to data warehousing and
data marts.
Portal - a web system that provides the functions and features to authenticate and
identify the users and provide them with an easy, intuitive, personalized and user-
customizable web-interface for facilitating access to information and services that
are of primary relevance and interests to the users.
Real-Time BI - an organization’s ability to react to business needs and changing
business circumstances within a single day. (White, 2003)
TCP/IP - the Internet protocol suite (commonly TCP/IP) is a set of
communications protocols on which the Internet and most commercial networks
run.
SOA - Service Oriented Architecture is a search engine technology and the main
integration component in an information system
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Open Hub services - service used in analytical applications to distribute specific
data
1.4 Limitations
Due to the time that was provided for writing this thesis (6 weeks), working
conditions were a little bit tough. Hence it shall be acknowledged that time was a
limit.
When contacting respondents for the survey, besides time, money was also a
limit. More efficient ways could have been used when collecting respondents if
the right amount of money was invested into certain databases on the Internet.
In this thesis a model was created as a result of existing theories. The model is
called The PET model of BI implementation and consists of nine different
foundations divided into three layers. Better research conditions might reveal
other interesting facts that can change the appearance of the model, improve it or
in worst case scenario completely reject it.
Not all questions that were put in the questionnaire were analyzed either. In the
creation process of the questionnaire, some questions that could be related to the
theory provided in this thesis were not asked. For example in the theory chapter,
Real-Time BI system is described. But due to the limitations of time no analysis
was made upon this subject.
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2 Method
In this chapter a presentation of how the research for this thesis has been
conducted is given. It will give a better understanding of how the theoretical and
empirical reasoning has contributed to the purpose. It will also describe the
different methods used in this study.
2.1 Choice of methodology
The aim of this paper is to present a basis upon which the reader can gain an
understanding of how companies in various industries in Sweden relate to BI.
Hence the central point of this thesis is to provide an argument for and analysis of
what is expected from a complete BI Software Solution.
Companies’ relation to BI Software Solutions will be measured and mean values
will be calculated. The results will be presented in cross tables as well as in a
model, which is based on the existing theories, to illustrate an overall picture of
the companies’ relation to BI. Flowcharts and diagrams are also used to present
the results. Hence a deductive approach, discussed more in the research
philosophy part is applied.
2.2 Research philosophy
The research problem of this thesis is built on existing theories, what means that
the research approach is of a deductive nature. The opposite, an inductive
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approach is not suitable for this research since the research is based on already
existing theories.
When working with an observable social reality and when the result of a research
can be made to draw law-like generalizations, a research is produced with
quantitative and deductive nature with a positivistic approach (Saunders, Lewis, &
Thornhill, 2007). It is also likely that the existing theory about BI in this paper
will be further developed and tested by further research. According to Saunders et
al. (2007) this is also an indication that the research philosophy in this thesis is of
a positivistic nature. The thesis aims to observe and study the companies’ points
of view and their relation to BI. For that purpose a questionnaire is applied. A
questionnaire is a kind of study that fits with a positivistic research approach and
from the questionnaire the quantifiable data can be examined and analyzed.
2.3 Choice of theory
Books that were used for this thesis all come from the library of Kristianstad
University. Most of the electronic articles were either downloaded from various
journals on the Internet or other online databases such as Emerald and The Data
Warehouse Institute or from the Kristianstad University’s First Class
Email/Course client. There are many high-tech explanations of BI found on the
Internet, in various books and in articles but the first thought when collecting
information about BI and writing about it, for this thesis, was to build a
appropriate and relevant theoretical ground to present an introduction of the
subject on a very low technical level so that the readers will easily understand
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what BI is and how it works. The idea was also to maintain the “easy-to-
understand” level throughout the thesis. Although in some parts it is essential to
use complex terms and idioms necessary for the explanation of a matter.
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3 Theoretical framework
This chapter will provide the reader with information about how BI software
functions and how we classify the different BI analytics tools available on the
market today and what such applications consist of. In this chapter theories about
the organizational structure and the placement of BI inside the organizations will
also be discussed.
3.1 BI software classification
BI tools are a part of the broader market called business analytics, which is
illustrated in Figure 2. The market for BI tools includes both standalone packaged
software and embedded BI tools provided by database management software
vendors (Vesset & McDonough, 2007). The BI tools market itself is divided into
two market segments, Query reporting, analysis and Advanced analytics, and
these are the two areas of BI tool applications that this thesis is focusing on. In
Figure 2, these areas are the two dash-boarded rectangles.
3.1.1 End-user query, reporting, and analysis
Query, Reporting, Analysis (QRA) software includes ad hoc query and
multidimensional analysis tools as well as dashboards, scorecards and production
reporting tools. These tools are designed specifically to support ad hoc data
access and for report building by either IT or business users and do not include
any other applications or tools that may be used for report building what so ever
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(Vesset & McDonough, 2007). Yet they are justified as multidimensional analysis
tools that include both online analytical processing (OLAP) servers and client-
side analysis tools that provide a data management environment that is used for
modeling business problems and analyzing business data. Packaged data marts
are also included in this function. These data marts are preconfigured software
used for combining data transformation, management, and access in one single
package and are usually presenting the results in various business models (Vesset
& McDonough, 2007).
3.1.2 Advanced analytics
The main occupation of advanced analytics software is data mining and statistics.
Technologies that are used are neural networks, rule induction, and clustering,
among others, in order to discover relationships in data and then make hidden, not
apparent or complex predictions for reporting and multidimensional analysis
(Vesset & McDonough, 2007). In this sector there are technical, econometrical
and other mathematical operations that provides libraries with statistical
algorithms so that the data can be processed and analyzed. Most common
functions are frequencies, cross-tabulations and chi square but there can also be
some other specialized and sophisticated functions focusing on the functional area
such as the industrial design, clinical trial testing, exploratory data analysis, and
high-volume and real-time statistical analysis (Vesset & McDonough, 2007).
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(Vesset & McDonough, 2007)
3.2 Analytical applications
An analytical application, just as Business Intelligence itself, is very difficult to
define and many professional programmers and users of BI tools will have their
own definition when explains the tool, the technology or the architecture. In this
thesis though, the author has found one definition is used that will hopefully
satisfy most of the analytical application industry’s “pundits”: (Eckerson, 2005, p.
5):
An analytic application consists of a series of logically integrated, interactive reports, including dashboards and scorecards, that enable a wide range of users to access, analyze, and act on integrated information in the context of the business processes and tasks that they manage in a given domain, such as sales, service, or operations.
Business analytics software
Performance Management tools and applications
Financial Performance and strategy mgmt.
applications
(budgeting, planning, consolidation, profitability, mgmt./ABC, scorecards)
CRM analytical applications
(sales, customer service,
contact center, marketing, website analytics, price
optimization)
BI tools:
Supply chain and service operations analytic
applications
Workforce analytic application
Analytic spatial information
management tools
Data warehouse platform (data warehouse mgmt. and generation)
Query reporting, analysis
(includes dashboards)
Advanced analytics (includes data mining and
statistics)
Figure 2 – Classifications of BI software
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Generally an analytical application consists of elements whose purpose is to build
up a business logic that will take the user through a series of interactive reports
where it will be possible to access, analyze, and take necessary action to optimize
the activities in a specific business domain. Analytical applications are, therefore,
not about randomly created reports that a user can upload from an “inbox” or from
a “my reports” folder, but rather about the interactive and dynamic play where the
user is given the possibility to utilize something that is highly valuable for his/her
company’s endurance (Eckerson, 2005).
3.2.1 Logical integration
The first part of a BI analytical application is called logical integration and is
about stepping the user through different series of interactive reports and views of
dimensional data, which will lead to the important point of action or to the request
for more information. Different users have different knowledge or know-how
when it comes to usage of analytical applications so therefore the navigational
logic is important when a user wants to navigate through different reports on the
“reports page” to effectively analyze data and make decisions. Interactive
dashboards and scorecards are used to inform the user what metrics or data to
examine so another important logic of a BI analytical tool is also offering of
recommendations (Eckerson, 2005). This is about giving the user, novice or
professional, the best possible overview of the data and to make sure that
important information is not missed or neglected.
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3.2.2 Interactive reports
The interactive reports key is about giving the user opportunity to interactively
search through the reports for additional information by simply “drilling” from a
top-level view to a lower level. Reports should be unfixed and possible to change
into tables, charts, or other transactional data. Some technologies worth
mentioning that are used for delivering such interactive reports are OLAP cubes,
parameterized reports, linked static reports, advanced visualization techniques,
dashboard/scorecards, numeric searches, et cetera (Eckerson, 2005).
3.2.3 Integrated information
Various data and information from different sources should be put in analytical
applications and then stored in one single warehouse where all data is processed
and analyzed once again. Large companies, like Continental Airlines, have many
different analytical applications running against one single enterprise data
warehouse where all data, for example tracking flight process, fraud detection, or
revenues management, are put through one large analytical procedure. Integrating
the information will help managers to avoid problems when seeking one
consistent version of the enterprise information (Eckerson, 2005).
3.2.4 Addressing of a Business domain
Different business areas (domains) such as sales, service, or manufacturing, have
different information requirements and analytical applications are defined by
those specific requirements. A sales analytical application may monitor a
production line performance or other sales representatives and regions or it can
Business Intelligence Software 26
examine the sales and contact history, et cetera. It is the interconnection of these
domains that must be used and placed within a logical model because several
business areas actually represent the same company (Eckerson, 2005).
3.3 Types of Business Intelligence Systems
3.3.1 Model-driven BI system
In a model-driven BI system, the information / intelligence is mostly presented
thorough a series of different models. The user can access and modify financial,
optimization and/or simulation models of various kinds (Hedgebeth, 2007). The
most basic function of the model-driven BI system is the provision of quantitative
models.
3.3.2 Data-driven system
In data-driven systems the most basic functional level occupies search tools that
access simple file systems (Hedgebeth, 2007). Here the user has access to and can
modify real-time internal and external data.
3.3.3 Communication-driven system
In communication-driven systems, different networking technologies drive
decision based collaboration activities. Examples of these are video conferencing,
groupware and computer bulletin board systems (BBS) (Hedgebeth, 2007).
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3.3.4 Document-driven system
Via computer storage and processing, a document-driven retrieval is made. Here,
via a search engine, the user may access documents, policies, images, sound,
scanned documents et cetera. (Hedgebeth, 2007).
3.3.5 Knowledge-driven system
In knowledge-driven systems, trained and professional users with knowledge are
used to solve various problems.
3.3.6 Web-based system
Intelligence from a web-based system is presented via a web browser and TCP/IP
(Internet protocol suite) (Hedgebeth, 2007).
3.4 Real-Time BI system
Another BI system that is not mentioned under the previous heading but
nonetheless deserves special attention is called The Real-Time Business
intelligence system. This system is about organization’s ability to react in time and
become more alert and more responsive to various changing business conditions
(White, 2003). In order to make effective decisions, accurate business intelligence
is required. The problem with accurate intelligence is that it always takes time to
collect and deliver it to the right users and it also takes time for the users to act on
this information. As shown in Figure 4 the delay between a business event
occurring, and action being taken, is an issue of decisive importance when the
Business Intelligence Software 28
value of the information is to be determined. The technology used to deploy a
Real-Time BI application must, first of all, aim to reduce a user’s reaction time if
the information value is to be as high as possible (White, 2003).
3.5 How Real-Time BI system works
Basically a Real-Time BI system consists of two operational components (Figure
3). One is for data-integration and the other one is for decision-making. The data
integration component captures business events from operational systems and
then integrates them into the low-latency store. The decision making component,
on the other hand, supports real-time performance management and other
significant real-time analysis and reports (White, 2003).
3.5.1 Time importance when working with BI
As illustrated in Figure 4, a business event’s road to become an action consists of
three latency periods, data latency, analysis latency, and decision latency
(Hackerthorn, 2003). The result of the three latencies is called action time or
action distance and the central objective of a real-time BI system is to reduce the
Operational applications
Real-time data integration component
Real-time decision making
component
Operational data Events
Low latency store
Reports, Alerts & Messages
Figure 3 - Real-Time BI Processing components
Business Intelligence Software 29
action time as much as possible to respond to a business happening. If the
problem is in data latency or the analysis latency the time gap can be reduced by
improving the technology used. On the other hand if the problem is decision
latency, then the latency depends on the user. Therefore, the information that is
provided to the user must be improved to solve the decision latency problem.
Another solution could also be an automatization of some BI processes that will
automatically take action on behalf of the user (White, 2003). Hackerthorn (2003)
describes how decision latency may be reduced by applying three requirements to
the system; alerting, information, and guidance. He finds that the system should
be configured in a way which alerts the user if some unusual business situation
occurs. Secondly the system should be able to show situational-specific business
information so that the user quickly gets an understanding of the business
environment he is working in. Thirdly, the user should be guided by the system
that suggests the most suitable action for the specific situation.
Action taken
Information delivered
Data stored
Business event
Val
ue
TimeAction time or action distance
Figure 4 – Latency in Business Intelligence decision making (Hackerthorn, 2003)
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Another important success aspect in realizing the benefits when working with
Real-Time BI is recognizing that the Return on Investment (ROI) depends on two
factors, the time that it takes to reduce an action and the organizations ability to
modify its business practice. Figure 5 illustrates that there is a point (exploration
threshold) beyond which reducing the action time any further has no value to the
business. The smaller the action time required, the bigger the Information
Technology (IT) costs are (White, 2003). Figure 5 combined with Figure 4 show
us that a shorter action time gives higher value to the intelligence but it also
increases the costs for the investment in required Information Technology. First
after a certain time (at the break-even threshold) the costs for the Information
Technology will become so low that ROI becomes positive.
Figure 5 – Real-Time BI; Action time vs. IT costs (White, 2003)
$
Action time
Incremental IT costs
Business benefits
Break-even threshold
Exploration threshold
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3.6 The different user-groups of BI
BI is a relatively new organizational function, and most companies will have no or little experience in its implementation.
(Solberg Søilen, 2008)
Different users necessitate different intelligence and a BI tool’s main priority
should be to provide the right user with the right intelligence. In Figure 6, on the
bottom axis, different user groups can be identified with the specific intelligence
presentation requirements (on the vertical axis). Executives tend to have little or
no time to read long reports and are therefore only interested in fast figures or the
“executive summaries”. These can be presented in Scorecards or Dashboards
shown as Key Performance Indicators (KPI). Analyst or Senior managers on the
other hand like to work with advanced online analytical processes and explore
different way of making analysis. Written reports are in the interest of department
managers. These are interested in reading and analyzing compiled text reports
such as, sales analysis, budgets et cetera. that will give them a good basis for
making correct decisions. Workers on lower levels in the organization work with
invoices, shipping, logistics et cetera.
Business Metrics
Performance Production Times
Customer Churn
Sales Totals Lead Analysis Click through
Relations Budgets
Invoices Shipping Documents
Pick List
Executives
KPI’s Scorecards and Dashboards
Analysts,Senior managers
Department managers
Employee partners
Production reports
Management reports
OLAP exploration
Figure 6 – Different BI user needs in the hierarchy (Solberg Søilen, 2008)
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(X)
Figure 7 – The special department model of intelligence(Solberg Søilen, 2008)
X
Figure 8 – The advisory model of intelligence (Solberg Søilen, 2008)
3.7 BI placement in the organization
3.7.1 The special department model of intelligence
In the special department model the intelligence
function is placed in a separate department as a
part of e.g. marketing department. The idea is to
have a special intelligence department bedded
inside an already established department where it
would be easy make analysis and draw conclusions by already established
employees. A problem that can occur with this model is mostly isolation because
special intelligence departments often close themselves in. This creates
misunderstandings and develops self initiated projects that often are not sure to be
useful for the company. Communication between top managers and the
departmental team must be very well established in order to make correct and
needed analysis (Solberg Søilen, 2008).
3.7.2 The advisory model of intelligence
The advisory model places a senior advisor to
the CEO and to top management. The senior
advisor is then responsible for two functions in
the intelligence cycle, formulating the questions
to be answered, and delivering the results. All
though the information gathering and the analysis making must not necessarily be
performed by the advisor himself. Some advisors simply do not have the time or
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X
Figure 9 – The professional model of intelligence (Solberg Søilen, 2008)
the skills to search for necessary information so, therefore, a separate department
or even an outsider could be used according to the needs. In this model, the senior
advisor has access to a certain number of workers who he believes have the
certain knowledge that is required to perform the intelligence work. But the
problem often lays in the quality of intelligence that is carried out. Reports and
analysis tend to be less accurate, relevant or effective than if they were done by
professionals (Solberg Søilen, 2008).
3.7.3 The professional model of intelligence
In the professional model, special personnel
have gone through sufficient training in form of
university studies and some practical training in
intelligence work and are therefore used by the
organization for their specific professional
knowledge. Their main priority is intelligence work. In this way the organization
can use professional workers and benefit from a broader supply of services
offered like field-work, in-the-terrain intelligence gathering or desk jobs with
intelligence analysis, reporting and presentations. In most cases the professional
model is a question of resources. Mid-size and smaller companies find this model
expensive and in very few cases they will have the funds available to make
investments in this kind of skilled intelligence personnel (Solberg Søilen, 2008).
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X
Figure 10 – The top-down model of intelligence (Solberg Søilen, 2008)
X
X X X X
Figure 11 – The integrated intelligence model (Solberg Søilen, 2008)
3.7.4 The top-down model of intelligence
The idea of this model is to gather and
communicate intelligence and knowledge from
the top of the organization. Top management
processes all intelligence and spread it out on the
need-to-know basis downwards throughout the
organization. Companies that use this model are often small or midsize and have
low-tech production based organizations with low-skilled workers. Top managers
are often the ones with most knowledge and best qualifications in the company
and are classified as the most important persons for the running of the firm. The
problem that can occur with this model is that the top management stops listening
to what other workers have to say (Solberg Søilen, 2008).
3.7.5 The Integrated Intelligence Model
In integrated intelligence model, intelligence
activities are run on a basis where every
employee, on every level in the organization,
contributes with intelligence. In this way the
whole organization’s experience and effort are
collected. When working according to this model, the intelligence seems to be less
secretive and less dangerous, which of course is an advantage when building trust
and creating an atmosphere where everyone is feeling that information they share
is important. This model is very often practiced in Japan (Solberg Søilen, 2008).
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X X X XFigure 12 – The down-up model of intelligence (Solberg Søilen, 2008)
X
Figure 13 – The departmental model of intelligence (Solberg Søilen, 2008)
3.7.6 The down-up model of intelligence
In companies where employees on the lower
levels in the organization have access to
especially important information, a down-up
model can be applied. It is common that
competitive sales and marketing driven
organizations use this model when they work with intelligence gathering and
intelligence processing. When workers, often sales people or other field and out of
office workers, have a direct contact with the customers it is crucial that they
bring their knowledge and intelligence back to the company where top managers
and CEO’s can deal with it and support decision making. It is common that
companies that use this model also reward their low level workers in form of
incentives, such as higher salary, so that information they bring home is more
valuable and more effective. Some companies even use Intelligence Reward
Systems where information is divided into different classes and workers can
systematically be rewarded via the company’s intranet system, for the information
they bring home. The more value the information has, the more money on the
paycheck (Solberg Søilen, 2008).
3.7.7 The departmental model of intelligence
In the departmental model of intelligence, a
company dedicaties a whole department for only
Business Intelligence operations. Companies have
full time intelligence officers and analysts
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working in the BI department. It is common though that these also work in other
departments or as a supporting function to top management. The idea is to
increase the focus on intelligence gathering as much as possible. It could be a
question of security and development of new technologies as well as on the rising
the level of information quality, effectiveness and perfection (Solberg Søilen,
2008).
3.8 Some BI Tools on the market today
Oracle Enterprise BI Server is a tool designed by the Oracle Corporation which
is the world’s largest enterprise software company. This tool includes dashboards,
ad hoc queries, intelligent interaction capabilities, enterprise and production
reporting, financial reporting, OLAP analysis, data mining, and other Web
Service-based applications (Oracle, 2008).
Business Objects Enterprise is formerly designed by Business Objects, now
SAP Company and is built on a service-oriented architecture. Some key features
are: Auditing, BI content Search, Information Portals, Web based Queries and
graphical design tools (Business Objects, 2008).
SAP NetWeaver BI is designed by SAP Company and is installed in the
organization’s network and can be accessed by most users. It consists of data
warehousing, OLAP, Business planning, Queries, Reports, Analysis, Open Hub
services, Information broadcasting et cetera (SAP, 2008).
SAS Enterprise BI Server is a server, designed yet again, by SAP Company and
allows organizations to quickly access and derive the information they need to
Business Intelligence Software 37
make better decisions. Some key features are Targeted fit-to-task Web and
desktop reporting interfaces, Multiple self-service query interfaces, OLAP,
graphic data presentation options, integration with Microsoft Office, a dynamic
desktop interface for guided analysis and model development et cetera (SAS
Enterprise, 2008).
TM/1 & Executive Viewer is an advanced analysis and reporting tool designed
by IBM Cognos and is a working through real-time Web-based access to
information from OLAP. Some other key figures are Ad hoc analysis and
dynamic graphical reports (IBM Cognos, Cognos TM1, 2008).
BizzScore Suite is a tool designed for nonprofit organization by EFM Software.
The tool is build upon four components Bizzscore (management dashboards,
extensive analytics, built-in action management and messaging), Bizzdefiner
(strategy based formulation of the performance management blue-print and KPI's
from mission to measure), Bizzdata (for integrating a variety of data-sources and
scheduling its import), and Bizzquality (for input of “soft” data such as customer
satisfaction and employee motivation using web based questionnaires) (Bizzscore,
2008).
WebFocus is designed by Information Builders and is a one single platform for
enterprise business intelligence. It contains integration tools such as: web services
including data and application adapters, Real-time transformation, and Process-
driven BI. WebFocus also includes; dashboards and scorecards, queries and
analysis, reporting, portals, and information delivery (Information Builders,
2008).
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Excel, Performance Point, Analysis Server are all designed by Microsoft
Corporation. Excel can be used as ananalytical tool working in a spreadsheet
environment for exploratory data analysis. Researches show that Excel is the most
used spreadsheet tool in the world today (Kelly, 2008). Performance Point and
Analysis Server are designed to monitor, analyze and plan for the organization so
that the changing business conditions are met at all time. Some key figures are
scorecards and dashboards, analysis, planning, budgeting et cetera (BI, 2008).
QlikView is an analysis tool designed by QlikTech. Some key features are:
Analysis (online and offline), dashboards and scorecards, reports, alerts, and zero
footprint DHTML-client that gives user the access to full web-based analysis
without any installation requirements on the client machine (QlikTech, 2008).
Microstrategy is designed by the Microstrategy Company, and is a real-time
business monitoring tool. Besides real-time functions, it contains analysis,
reporting and other intelligence-integration functions such as heterogeneous
joining of data and data marts (Microstrategy Inc, 2008).
Hyperion System was formerly designed by Hyperion Company, but was later
bought by Oracle. This system consists of several functions such as financial
managing including planning, strategy and quality management. It also includes
performance scorecards and dashboards (Oracle, 2008).
Actuate is a reporting application designed by Actuate Company. This tool
focuses mainly on reporting designs and modifications as well as users’ analysis
of information. It uses electronic spreadsheets, electronic reports via an open
Business Intelligence Software 39
source Business Intelligence and Reporting Tool (BIRT) technology (Actuate,
2008).
Cognos Series 8 is designed by IBM Cognos Group and is a complete BI tool on
one single Service-Oriented Architecture (SOA). It contains reporting and
analytical technology as well as dashboards and scorecards and can be used and
applied throughout the whole organization (IBM Cognos, 2008).
3.9 Subsoft – brief presentation
Subsoft is a BI system used to scan an organization’s environment simply by
analyzing the information that a user has manually put in into different
environment-areas via a data-based system. It is installed either directly on an
online web database or onto the organizational intra-network. Subsoft can be used
by both private and public organizations. The system is run by an administrator
who has complete control over it. Users can register onto the system and are
afterwards, by the administrator, divided into different user groups with certain
user rights for usage of the software. Some users are allowed to input, edit or
delete the intelligence while others are only allowed to read it (Solberg Søilen,
2005).
As Figure 14 is illustrates there are both internal and external environmental areas
for an organization. Based on the users information input, the system is creating
different analysis and reports to help decisions makers gain knowledge about
his/her organizational environment and hopefully make better and more efficient
decisions.
Business Intelligence Software 40
Subsoft does not use any dashboards or scorecards to present the processed
intelligence. Instead the strength of the Subsoft system is in its capability to create
analysis of the manually inserted text (intelligence) about an organizational
environment. The different analyses are: SWOT analysis, PEST analysis,
Spreadsheets, Statistical analysis, Trend analysis, Power Analysis, Signal
Analysis, Benchmarking, Early Warning Analysis, Simulations, Devil’s
Advocate, Forecasting, Cost and Ratio Analysis, Scenario Analysis, and Game
theoretical approaches (Solberg Søilen, 2005). Subsoft also hav a function that
processes analyzed data/text and converts it into a fixed and standard report.
Political
Judicial Ecological
Infra-structural Social
Techno-logical Demo-
graphic Economic
Our Company
Exit barriers
Clients
Influences
Competitors
Entry barriers
Suppliers
Substitutes
Figure 14 – Subsoft model of Internal and External factors (Subsoft, 2008)
= internal = external
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3.10 Theory model creation
Theory that has been presented in this thesis so far has given a foundation for
creating a model that will help to examine the different areas of BI
implementation in an organization and study how they are understood, needed and
what is expected from them. Hence a model called PET model of BI
implementation (Figure 15) was created to try to illustrate the different
areas/foundations of the BI implementation.
The model is divided into three layers, the Purchase, Employment, and Task layer
which all together represent the process of BI implementation. The whole process
consists of nine different foundations.
The first three foundations are presented in the Purchase layer. When companies
are about to purchase a BI system they ask three questions; What kind of system?;
What is the motive for purchasing?; and What purpose will this system serve?. In
the System Foundation, a company’s choice of system will be examined. There
are a lot of BI systems on the market today, and the purpose of the System
Foundation is to find out what specific system suits a specific company in a
specific industry.
The Motive Foundation is examining what motives lay behind the purchase of the
system. There might be many reasons for a company to purchase a BI system. As
presented earlier in this paper some companies like to have a greater visibility of
their business environment, shorten their reaction time, improve the execution of a
strategy, or improve revenue/customer growth, et cetera.
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The Purpose Foundation may sound like it is accomplishing the same task as the
Motive Foundation but it is not. Unlike the Motive, that answers the “why”
question, the Purpose Foundation looks at “how” a BI system will be used.
Perhaps the BI system will be used for Marketing, Finance, Manufacturing,
Logistics, or Forecasting et cetera.
The next three layers are presented in the Employment Layer. The purpose of this
layer is to find out how companies actually employ their BI systems. What
benefits do they experience?; Where in the organization do they place the
system?; and For how long have they been doing so? The Benefit Foundation
examines the actual benefits behind a BI system that a company has implemented.
Has there been an increased user satisfaction since the system has been
employed?; Have any costs been decreased?; Is the decision making speed higher
now than before the introduction of the system?
Depending on the company size, the industry and the organization, companies
place their BI system differently in their organization. Some tend to place it as a
special department while others like to implement it as a part of a Marketing
department, et cetera. The sole reason of the Placement Foundation is to find out
how companies place the BI system in their organization.
It might be interesting, for comparison reasons, to examine the usage time of a BI
system. For how long has the company used a specific BI system, or plan to do
so? How often is the BI system used? On a daily basis, or less often? The result
can then be compared to other foundations in the model. For example; Depending
on the time that a BI system has been used, how has the company chosen to place
their BI system? This is one reason for the creation of Usage Time Foundation.
Business Intelligence Software 43
Other reason might be to examine the time that it takes for a BI system to process
intelligence. It is presented in this chapter that time plays an important role when
working with BI systems because the time, very often, can actually determine the
value of the intelligence.
The last layer of the PET model is called the Task Layer and it is a rather
technical and more detail-demanding layer in the BI implementation examination.
The Task layer consists of an Important Functions foundation, Functional Area
foundation and Analysis foundation.
The important Function Foundation examines what functions the companies
believe a BI system must accomplish to serve for their specific business purpose.
In some businesses, as mentioned earlier in this chapter, where companies often
use Excel Software, Microsoft Office integration is a very important function.
Other companies like to believe that Data Warehousing and Online analytical
processing (OLAP) is a vital function. Depending on the user, whether it is a CEO
or an analyst, Dashboards and Scorecards are preferred. Some like their BI
systems to be able to write Reports and illustrate data in form of diagrams and
models and so on.
Another foundation in the Task layer is called the Functional Area Foundation and
is not examining the actual functions of a BI system like the previous foundation
but rather the whole area of functions that a BI system covers. Some businesses
have implemented their BI System as a system for Customer Relations
Management (CRM) or Knowledge management (KM), while others use their BI
system for analysis only. It is also known that some companies use BI systems for
Business Intelligence Software 44
consulting purposes, for example Business-related consulting, Technical
consulting, Help Desks, et cetera.
The last foundation in the PET model is called the Analysis Foundation. Most BI
systems consist of some kind of analytical processing technology and companies
using these systems, commonly want their BI system to be able to do an analysis.
Therefore, the purpose of this foundation is to find out what kind of analysis the
companies actually demand from their BI system. Examples of analyses are,
SWOT analysis, Cost analysis, Trend Analysis, PEST analysis, Benchmarking, or
Questionnaires, et cetera.
With the help of the PET model and the Research plan, which is presented later in
the Empirical Method Chapter, the survey that will be conducted has now a
greater chance to cover the most important areas of BI implementation and answer
the research proposals of this thesis.
System Motive
Usage TimePlacement
Important Functions
Purpose
Benefits
Analysis Functional Area
Purchase
Task
Employment
Figure 15 – The PET model of BI implementation
BI ?
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4 Empirical method
This chapter is presenting the research strategy that will be used throughout this
thesis. Thereafter the time horizon together with the data collection method and
population used is described. This chapter will also focus on the data analysis
method and the reliability and validity of the research conducted for this thesis.
4.1 Research Strategy
The research strategy that was chosen for this thesis was a web based
questionnaire. This allows quantitative data to be compared. According to
Saunders (2007, p. 138) quantitative data are “often obtained by using a
questionnaire administered to a sample, these data are standardized, allowing easy
comparison”. Therefore the analysis and the modeling of the particular
relationships between variables is possible (Saunders et al, 2007).
The use of a web based questionnaire, will make it possible to investigate how
companies in various industries in Sweden relate to BI, seen from their
perspective. In the analysis of the questionnaire a certain relationship between BI
and a company profile should be found.
4.2 Time horizon
In this thesis, a cross-sectional study is used, meaning that it is a “study of
particular phenomenon at a particular time” (Saunders, Lewis, & Thornhill, 2007,
p. 148). The time for writing this thesis was set to six weeks and the questionnaire
Business Intelligence Software 46
was conducted over a period of three weeks time, where after one week the
respondents were once again contacted in case they did not get the first
notification. Conclusions and the analysis of the answers in the questionnaire were
created in one week (last week before deadline), shortly after the results from the
questionnaire were collected.
4.3 Data collection method
Data can be collected in many ways, through observations, interviews and
questionnaires et cetera. (Saunders et al, 2007). Since a positivistic philosophy
with a deductive approach is used in this thesis, a questionnaire was conducted.
The most efficient way to measure companies’ relation to BI, is through a web
based questionnaire because of two facts, or limitations: time and money. The
time it would take to conduct other researches, for example a qualitative research
with close contact interviews, would be too time consuming and the population
goal would not be reached. Secondly, the costs for conducting qualitative
researches, including transportation to meetings, questionnaire printing et cetera.
would be too high as well. Enough companies need to be reached, at a low cost
and in time, and the best way to do so is reaching them via their e-mail addresses,
alternatively via phone. According to Saunders (2007), web questionnaires tend to
have a very low response rate. The only way to get a high number of respondents
was to send the questionnaire to a high number of e-mail addresses. This was a
good way to still be able to get a statistically approved and required amount of
respondents for the analysis and conclusion of the research. For the result of the
thesis, some kind of generalization is to be made, and for that a certain number of
respondents was required as well. In the book Business Intelligence Competency
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Centers, A Team approach to Maximazing Competitive Advantage written by
Miller, Bräutigam, & Gerlach, (2006) there was an example of a web based
questionnaire. This was used as a starting point and as a template of the
questionnaire first draft.
4.4 Population
At first, the idea was to concentrate the search on a population in Skåne (region in
southern Sweden) but when searching through different search engines and
databases on the Internet, contact information about Skåne’s companies was just
as hard to locate as those in other regions in Sweden. Therefore, a change of focus
tool place and instead of concentrating on one smaller population, the scope
widened. The results might be more interesting if the analysis could be done on a
higher variety of companies and on a larger scale.
It is very difficult to distinguish those companies that use BI from those that do
not. Nevertheless, as mentioned in the introduction chapter, some industries tend
to use BI more than others. Therefore the main search criterion when locating the
companies for the research was industry. Based on the theory in this thesis,
industries were previously chosen and those are the ones that the search was
conducted upon. From 17 different industries, 50 companies from each industry
were selected, giving a total of 850 companies.
The database that was used for finding the contact information about the
companies was 121.nu (one to one) and is one of the leading online business-
catalogues in Sweden, functioning as a search engine, with over 680 000 active
Business Intelligence Software 48
Swedish companies in its register. E-mail addresses were however not provided
by 121.nu, but instead direct links to the companies’ web pages were available.
4.5 Sample selection
Many companies today use an info@ e-mail address that is very often used as a
“first contact” address in case you need to get secondary information about the
company or if you are not entirely sure who you need to contact. There is a
possibility that your email could be forwarded to the right person. The risk with
an info@ address is that very often the response time is too long and in many
cases there is no response at all (Saunders, Lewis, & Thornhill, 2007). For those
reasons, and for the reliability and validity of this thesis, it was important to
contact the right person, with enough insight in the company, directly. The only,
fastest possible, way to collect such “good” e-mail addresses was to visit each
company’s web page and look for that specific information via the “contact” page.
From the 850 companies’ homepage addresses, 408 “good” addresses were found.
The e-mail-collection gave a result of ca 25 companies in each industry. The rest
of the contacts were either info@ addresses or phone numbers. Due to the time
restriction, both info@ addresses and the phone numbers were neglected in the
research.
4.6 Research conduction
After completing the e-mail collection, a web questionnaire (Appendix 4) was
created and published online. Then an e-mail with an explanatory text and the link
to the questionnaire (Appendix 1 & 2) was sent to all 408 contacts. The duration
Business Intelligence Software 49
of the survey was set to 19 days (seven days before the deadline of the thesis). A
limit, or goal, was set to between 100 – 120 responses. This limit was also thought
to provide a good base for empirical analysis.
23 e-mails of 408 were directly sent back with the notice that the contact person
was not available or was on holiday, business trip, et cetera. 67 responses were
received, generating a total of 16.4 % response rate. According to Braun Hamilton
(2003) a total response rate of an online survey is approximately 13.35 %, but he
also points out that the response rate may vary from survey to survey depending
on a variety of aspects. According to Saunders (2007) a covering e-mail and a
good design of the questionnaire will help to increase the response rate. For the
questionnaire design, a Windows application called “E-mail Questionnaire”,
created by CompressWeb Company, was used. “E-mail Questionnaire” is an
online questionnaire system that allows the user to create, design and then send
the questionnaire to a specific list of respondents.
4.7 BI research plan
Based on the theory presented in this thesis, the author has created a research
model/plan that will help creating the questionnaire and the construction of a
better research. Together with the PET model of BI implementation, the idea is to
create a plan/model that will cover the most areas of BI and then strategically
investigate them. For a better overview and for the sake of simplicity the model is
divided into three main blocks (Figure 16). Every block consists of several areas
of investigation and each area will be included in the questionnaire in form of
various questions specific for that area.
Business Intelligence Software 50
The first block of the research model will provide a profile of the investigated.
This block consists of five areas of investigation; Company size, Company type,
Industry, and for the sake of validity and reliability of the research, a Job level of
the respondent and his/her Job function in the company.
The second block consists of two large areas of investigation, Understandings and
Expectations. The use of strategically formulated questions are aiming at finding
out what the companies understand and expect from a BI software.
After observing how companies relate to BI and weather they use it or not, a third
research block is created. This block consists of one main area of investigation;
Needs. This is the part of the research requiring the most work. The Needs-area is
segregated into five sub-areas (Specific Needs-areas) which try to find out what
kind of specific needs the companies have when using BI. Examples of the
Specific Needs-areas questions are; Where in the organization is BI used; What is
BI used for?; How is BI used and for how long?; Who is using the BI? et cetera.
The Needs-area is also taking into consideration those who do not use BI, trying
to detect the reason for that and also to detect what can be done to make those
companies use BI.
In the analysis process of the thesis, this BI research plan/model (Figure 16) could
also be used to easier understand how and where the different statements fit in and
belong, in case a “memento” is needed.
A BI research plan can be embedded into the PET model on BI implementation so
that the two are completing each other. From the Purchase and Employment Layer
Business Intelligence Software 51
the companies’ understandings and expectations can be extracted, and from the
bottom Task Layer the companies’ needs can be extracted.
Business Intelligence Software 52
Figure 16 – BI research plan
What is expected from a BI software?
What is understood by a BI software?
Is BI used?
Top ManagementDpt. Managers Division heads
Analysts Developers
Experts Consumers
Responsibilities
For how long How often
Info. Perfectiveness Info. Effectiveness
Info. Quality Info. Relevance
Analytical apps. Modifications Scope of usage
Requests Reports
Financing of BI Org. structure
Separate units? Conclusion
drawing Data overview
Training
Finance & AccountingSales
Marketing Forecasting
Budgeting & PlanningCustomer Service Human Resources Shipping/Logistics
Manufacturing Procurement Expansion
Other
In Organization Geographically
What needs do BI fulfill?
Blo
ck 1
B
lock
2
Blo
ck 3
Business Intelligence Software 53
4.8 Data analysis
Data will be collected and put in a table for comparison. The mean value of each
answer will be presented. Answers from each industry will be summarized and
put in a cross table where the number of respondents and mean value of each
answer are presented for comparative reasons. Answers for the research questions
of this thesis will be extracted from the cross table and analyzed. Conclusions will
drawn from the analyzed data.
4.9 Research questions
The following research questions will be analyzed:
1. What do Companies in Sweden understand by a Business Intelligence
Software? For this question it is necessary to follow the respondents’
reactions already in the early stages of the contacting process. It is of great
importance to notice the responses you get from various companies when
you approach them with the questionnaire about Business Intelligence.
Later, an effort in analyzing the answers from the Purchase and
Employment layer in the PET model will be made.
2. What are the Swedish Companies’ expectations of a Business Intelligence
software? Here, the main effort will be put in the analysis of the answers
mean values. Also in this case, Purchase and Employment layer in the
PET model will be examined.
Business Intelligence Software 54
3. What needs do Swedish Companies have from a Business Intelligence
Software? The main effort, for this question, will be put in the analysis of
the answers’ mean values. In this case, the Task layer in the PET model
will be examined.
4. How can Subsoft be improved to meet these expectations and needs?
According to the survey and as far as it reaches, the Subsoft’s
characteristics will be compared to those that are extracted from the
questionnaire.
4.10 Reliability and Validity
For the sake of validity, the “right” respondents needed to be contacted. These are
people with the insight in the company or at least they need to have certain
knowledge about their company’s BI history, usage and needs. Since the response
sample is so small, there is no chance of stating that the results will remain the
same if the same research was conducted again. Most surely, a higher response
rate would help to widen the picture and increase the certainty of each answer’s
validity level. As much as this is a problem of validity, it is also a problem of
reliability.
Business Intelligence Software 55
5 Analysis
This chapter presents the results of the survey that was conducted for the purpose
of this thesis. Empirical findings, data analysis as well as a conclusion are
included.
5.1 Empirical Findings
From the 67 respondents to the survey, 11 different industries were represented.
The industry that returned most answers was the Manufacturing industry with 18
respondents followed by the Consulting/Professional Services with 10 and
Information technology industry with 9 respondents.
Figure 17 – Survey respondents represented from different industries.
Since the vast majority of all industries returned a too low number of responses it
is, therefore, not possible to carry out any tests where generalization of the
Business Intelligence Software 56
industry is a factor. But all answers combined are important for other tests. For
example the value of an answer on each question can be measured and put in a
table for comparison between different industries. Since the manufacturing
industry had the most respondents, it will be used to exemplify how we can
interpret and compare data from the survey.
Table 2 – PET Model’s Purchase Foundations in the Manufacturing industry
Table 2 is an example of the Manufacturing industry’s BI system implementation.
Here, the first three foundations from the PET model are shown, BI system,
Motive, and Purpose. The complete table with all foundations and all industries
with further explanations can be found as an Appendix 5. As shown in Table 2
there is a total number (n) of 18 respondents from the manufacturing industry. In
the BI system foundation, 15 are using Excel, 1 is using Oracle Enterprise BI
Server (OEBIS) and 2 are using Qlikview. In this industry, 83 percent of the 18
companies (according to this survey) use Microsoft Excel BI. This might not be
the only BI system they use, but they do use it for some BI purposes.
The motive, according to 4 of the companies (22%), (independent from the
previous foundation) is that they use their BI system in order to improve their
strategic planning. 17 percent answered that they experience Revenue and
Industry (n) n BI
System % n Motive % n Purpose %
Manufacturing (18)
15 1 2
Excel OEBIS Qlikview
83 6
11
2 3 3 1 4
Better Coordin. Rev. Cust. Grow More Ef.Process Faster reaction Better Str. Plan.
11 17 17 6
22
7 2
17 4 8 3 2 3 1
Sales Scorec. Dashb. Finance & Acc Forecasting Manufacturing Budg. Planning What if scen. Shipping Log. Expansion
39 11 94 22 44 17 11 17 6
Business Intelligence Software 57
Customer growth as well as more efficient business processes. Some also
answered Do not know on the motive question and they are, therefore, not
represented in the table. In the Purpose foundation, more than one alternative
could be answered. The majority of the respondents answered that Finance and
Accounting is the biggest reason for them to work with BI systems. Thereafter,
they use BI for manufacturing (44%) and sales (39%).
In Table 3 the same type of data is presented, but for all the industries combined.
The statements in the “foundations” are also tested against each other and an
average value has been produced.
To start with, 15 of 67 respondents in the survey said that they do not use any kind
of BI tool or system in their business or organization. 69 percent of all
respondents say that they use Microsoft Excel when they work with BI. They
might use Excel as a permanent standard system in their organization or they
might just use it for some occasional BI purposes. Excel is used frequently
throughout all the industries that took part in the survey. 13 percent of the
respondents also say that the system they are using is not listed as an alternative in
the questionnaire. The second most popular system in the list is Qlikview and was
used in the Service and Manufacturing industry.
The motives that the companies had for using a BI system were also convincingly
high with regard to one statement: Greater visibility into the business. 28 percent
of the respondents say that a BI system is helping them to better understand their
business and its environment. 18 percent also say that a BI system is a helpful tool
for strategic planning. It is not clear what specific tool these respondents use, but
Business Intelligence Software 58
38 of 67 respondents described their job level as managers and there might be a
chance that these managers use BI tools for strategic planning as well as a
supportive tool in decision making. 13 percent of the respondents said that a BI
system helps processes to be more efficient. Some respondents also say that they
react faster to certain events and that the coordination among groups is better
thanks to a BI system.
When it comes to finding out how the respondents use their BI systems, there
seem to be four major areas of usage. 17 percent said that they use BI systems in
Finance and Accounting, 16 percent answered that they use it in Sales, 11 percent
said that a BI tool is a Forecasting tool, and 10 percent use BI tools for Marketing.
9 percent of 67 respondents use BI tools for budgeting and planning while only 6
percent actually uses a BI system for supervision of the business through
Dashboards and Scorecards. Some users use BI tools for Shippings and Logisitics
as well in the production and customer service. 8 of 9 respondents who answered
than Manufacturing was their purpose for using BI tools came from the
manufacturing industry. A surprisingly low number of respondents uses any kind
of BI tools when expanding their businesses.
Business Intelligence Software 59
Table 3 - PET Model’s Purchase Foundations in all industries combined
Industry (n) n BI System % n Motive % n Purpose %
11 industries (67)
46 9 4 4 2 1 1
Excel Not Listed He QlikView Do not know Business Ob Analysis Server Oracle Enterpr
6913
66311
191512
976521
Greater visibility i Do not use BI soft Better strategic pla More efficient pro Do not know Faster reaction to Revenue/ custom Better coordinati Better execution
2822181310
9731
30291918161511
99663333
Finance & Accoun Sales Forecasting Marketing Budgeting & Pla Do not use BI so Scorecarding/ Da Shipping/Logistics Manufacturing Customer Service Expansion Human Resources "What if" scenar Other Do not know
17161110
98655332222
∑ 67 100 76 100 180 100
Table 4 - PET Model’s Employment Foundations in all industries combined
In Table 4, where Employment of a BI System is presented, more than 30 percent
of the respondents answered that increased decision making speed was the biggest
benefit they experienced. The second largest benefit was Increased Business User
Satisfaction and was answered by 18 percent of the respondents. 10 percent of the
respondents said that the increased usage of BI tools is a benefit, closely followed
Industry (n) n Benefits % n Placement % n Time Usage %
11 industries (67)
25 15 14
8 7 7 4
Increased decid Do not use BI Increased busi Increased usag Better underst Do not know New ways of a
31191810
995
15 15 9 9 6 4 3 3 3
Integrated Do not use BI Professiona Do not know Departmental Spec Departmentc.) Advisory Up down Down up
22221313
96444
231915
73
1 year to 5 years more than 5 years Do not use BI 6 months to 1 year 1 to 6 months
34282210
4
∑ 67 100 67 100 67 100
Business Intelligence Software 60
by those (9 %) who said that the Better understanding of the Value of BI is a great
benefit.
22 % like to place a BI system as an integrated intelligence tool used by
everybody in the whole organization. While the next biggest part of the
respondents thought just the opposite. 13 percent believed that BI system should
be used only by trained professionals. All respondents are from the Manufacturing
industry and in the Banking industry. In the Food/Beverage industry and in the
Trade industry there is a belief that a Top Down placement is applicable, while in
the Consulting Professional Services industry the Down Up model was more
preferable. Most respondents that used BI systems had a good experience when it
comes to time. More that 30 percent had used their BI system between 1 to 5
years and approximately 30 percent had used the system for more than 5 years. A
vast minority have worked with BI for less than a year.
In table 5 the three last foundations from the PET model: Important functions,
Functional areas and Analysis are presented for all the industries combined.
When it comes to the most important functions of a BI system a majority says that
Microsoft office integration is important. 4 of 9 respondents from the IT industry
say that so is the case. But they also believed, together with the Consulting
Professional Services industry, that the Fixed or Standard reports function is
important. Online analytical processing (OLAP) was also a function highly
appreciable in the IT industry as well as in Trade and Manufacturing industry. 9
percent of the respondents would like their BI system to make predictive analysis.
Business Intelligence Software 61
A BI system’s functional area should, according to the respondents, be Analytics
and Customer Relations Management. 13 % of the respondents answered that
these were the functional areas that their BI system was used for. Business related
consulting and HelpDesks were important in Pharma, Food, and IT Industries.
The analyses that the respondents in various industries believed were important
were mainly Trend/scenario analysis and SWOT analysis. While the SWOT
analysis was outspread evenly over the industries, the Trend/scenario analysis had
the most responses in the IT and Manufacturing industry. All four respondents
from the Bank/Finance industry answered that Trend/analysis together with
Forecasting were the most important analysis. In 10 percent of the respondent’s
BI systems, and almost in every industry, Cost analysis was used. Statistical
analysis was used in the Health care industry, the Food/beverage industry and in
the Consulting Professional services industry.
Table 5 - PET Model’s Task Foundations in all industries combined
Industry (n) n Functions % n Areas % n Analysis %
11 industries (67)
15 15
9 9 7 6 5 3 3 3 3 2 1
MS Office Int Do not use BI Fixed or stand OnLine Analy Predictive ana Do not know Portal Business quer Dashboards Custom Devel E-mailed reports Access to vari Scorecards
19191111
976444421
15131312
987666331
Do not use BI Analytics Customer relati Do not know Business-relate Help desk Data warehousing Inegration proc Technincal consu Systems manag Knowledge ma Contracts mana Free software u
15131312
987666331
302515151412
9877533
Trend/Scenario an SWOT analysis Cost analysis Do not use BI soft Do not know Forecasting Statistical analysis Questionnaire Focus Groups Early warning ana Benchmarking Spread sheets Scenario analysis
20161010
986555322
∑ 81 100 102 100 153 100
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5.2 Critique
The number of respondents is of great importance when conducting surveys
where generalizations are to be made. For this thesis, there were 67 respondents
totally and as many as 18 from one specific industry. In an industry there might be
thousands of companies and a much higher sample of respondents would have
helped to make steadier statements and generalizations. Perhaps a longer survey
duration would have helped to collect more responses.
There are various ways to analyze such data as presented in the Tables 3 – 5.
Some ways might be better and some poorer than the ones used in this paper.
Therefore, due to the different analytical approaches and ways of interpreting
data, there might be some minor analytical flaws in the approach that was used for
this thesis.
The earlier idea with the questionnaires’ results was to test the significance levels
between certain answers. For that to be possible, the questions should have been
asked differently in the questionnaire. Perhaps every question should have had the
possibility to be ranked on a scale from one to five so that the real importance
level could be measured and some significance levels calculated.
Other types of comparisons and cross tables could have been made as well. One
could have looked at companies’ revenue and compared it to the different systems
they use or the requirement they had on BI. But the sample of the collected data
was too small to make any generalizations.
The positive attitude regarding the research population turned out to be a major
disadvantage in analysis work. No company profiles, other than the industry, were
Business Intelligence Software 63
used. Perhaps if the majority of the companies were concentrated into a smaller
geographical area, than whole Sweden, some other conclusion could have been
made.
5.3 Analysis conclusions
In order to answer the first research question for this thesis; What do Companies
in Sweden understand by a Business Intelligence Software?; it must be
highlighted that when the questionnaire was sent out, there were companies who
requested extra information about the “term” Business Intelligence. Only after the
extra information was presented to them, did some choose to participate in the
survey. Later, 15 of 67 respondents did not use any BI system at all. This is an
indication that the Business Intelligence-term has not yet been introduced in some
organizations and this also confirms the conjecture that BI is still in its early
development stages.
Some of the alternatives in the questionnaire got a very high response rate (over
25%) and this signals that more than a quarter of the respondents had the same
opinion on a number of questions. Those that got a response rate over 25 % were;
Increased Decision Speed (31%) and Greater visibility into the business (28%).
This indicates that there is a common understanding of BI software is. One can
draw a conclusion that the companies see a BI software as an instrument that will
improve their decision making speed and gain their knowledge about the business
environment they operate in.
Business Intelligence Software 64
The second research question in this paper is about the companies’ expectations of
a BI software. Expectations are related with Understandings because when a
person understands how something works, in this case a BI system, the
expectation is instinctively based upon that specific understanding. Since
expectations are also about performance and mean values, one can say that the
overall expectations of how a BI software shall perform, according to this survey,
are somewhat out spread and divided. If we look closer at the answers, divided by
the PET model’s Purchase and Employment Layer and by each industry, one can
extract a mean value of each answer (as presented in Tables 3 - 4). Besides the
expectations that a BI system should improve decision speed and give an insight
in your business environment, the number one expectation that a BI system should
perform as Finance and Accounting system. In addition to that, Sales,
Forecasting, and Marketing functions are also expected tasks a BI system should
performed.
Based on the understandings and the expectations firms have of BI system, one
can structure the specific needs. Throughout all industries there was one particular
function/need that seemed to be of great importance, a Microsoft Office
integration function. Also there was a need of having a BI tool that could write
Fixed or Standard Reports. Other needs as the Analytical function of a BI system
as well as the Customer Relations Management function were desired. As far as
analyses were concerned, SWOT analysis and Trend/Scenario analysis were the
most desirable ones.
Business Intelligence Software 65
To illustrate what has been said and concluded in this chapter as well as to point
up the most important on a BI system’s understandings, expectations, and needs,
once again the PET-Model of BI implementation is updated.
5.4 Subsoft - compared to the research findings
According to the findings in the research and as far as they cover the technical
functions and areas of a BI system, Subsoft can be improved. Subsoft consists of
many functions similar to those found in Excel such as spreadsheets and
possibility to create diagrams, calculate costs et cetera. But compared to Qlikview
System
Excel Qlikview
Motive
Greater visibility into the business
Usage Time
1 year to 5 years more than 5 years
Placement
Integrated
Important Functions
MS Office Integr.Fix stndrd reports
Purpose Finance Acc. Sales Forecasting Marketing
Benefits Incre. DMS Incre. BUS Incr use of BI
Analysis
Trend/Scenario SWOT analysis Cost analysis
Functional Area
Analytics CMS
Purchase
Task
Employment
Figure 18 – PET Model after the analysis
Business Intelligence Software 66
and based on the fact that Subsoft is mostly a text-analytical software, there are no
Dashboards or Scorecards in Subsoft. The greatest motive for purchasing a BI
system according to the survey was to gain a Greater visibility into the Business.
The sole purpose with Subsoft is based upon this idea. Therefore, this is a very
positive finding confirming that Subsoft can be applicable in most industries. The
three biggest purposes when using a BI system is Finance & Accounting, Sales,
and Forecasting. On this point, Subsoft has yet to be improved. Although it
contains some of these functions, such as Forecasting analysis, improvements
need to be done. The greatest benefit with a BI system is the increased Decision
Making speed. The benefits when working in Subsoft might be somewhat
differently extracted. Instead of making fast decisions, the decisions you make are
accurate. And as shown in the analysis of the research the majority of respondents
thought that a BI System should be placed where it is possible for everybody in
the entire organization to use it. This is also another great finding regarding
Subsoft, which allows any kind of user with specific rights to access the system.
Subsoft on the other hand does not support any function allowing integration with
Microsoft Office, but it does write fixed or standard reports as many of the
respondents requested. Subsoft is an analytical tool, and the functional area that
got the highest mean value among the respondents was analytics which suits
Subsoft very well.
Business Intelligence Software 67
6 Thesis conclusion
This chapter will conclude the thesis. Discussion is brought up as well as
practical relevance of this paper. Also some future research ideas are brought up
in the discussion.
6.1 Practical relevance
The results of the research in this thesis can be used by many actors on the BI
market. Since many interesting facts about companies’ BI usage habits are
discovered, vendors may use the results to build or improve their software. This
thesis is also a great introduction to the BI for any new user and for those who are
planning to use BI in their organization.
6.2 Discussion
The research conducted in this paper shows that BI is yet a term to be introduced
to many organizations. According to the research, 22 % of the respondents do not
use BI in their work. It is unclear whether they actually know what BI is or not, or
if BI is really necessary for their work, but it is sure that these 22 % are missing
the opportunity to explore new ways of learning about their business
environments. Those that do use BI are requiring more and more sophisticated
and special suited solutions for their businesses. This is shown in view of the fact
that of 10 of the most popular BI systems in the world, given as an alternative in
the questionnaire, only 2 were recognized by the respondents. All in all, compared
Business Intelligence Software 68
to the large American market of BI, the results of the research could be seen as
conformation on already stated fact that Sweden is a technologically developed
country and that most companies (78 % according to the survey) know what BI is
and to use it for the advantages that it brings.
The empirics collected in the survey contain more than just one company profile.
Industry was used in this analysis as one company profile. Possibly if other profile
figures are analyzed they might reveal interesting information about the relation
between Swedish companies and BI.
Business Intelligence Software 69
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Appendices
Appendix 1, Email (Swedish)
Hej!
Jag studerar sista terminen på civilekonomprogrammet vid Högskolan Kristianstad och skriver just nu min magisterexamen om olika Affärssystem (Business Intelligence Systems). I min undersökning vill jag ta reda på vad företag förstår, behöver och förväntar sig utav ett sådant system. Er hjälp skulle vara av stor vikt för min undersökning och därför ber jag om ca 10 minuter av Er tid att besvara min webbenkät. Er medverkan är betydelsefull!
Business Intelligence system är något som de flesta företagen använder sig utav för att stödja sitt beslutsfattade. Exempel på sådana system kan vara: Microsoft Excel, SAP Netwear BI, Qlikview et cetera.
För att nå enkäten klicka på länken:
http://www.subsoft.se/questionnaire/questionnaire.html
Enkäten upphör att gälla på sömdag den 15 juni 2008.
Tack så jätte mycket på förhand!
Med vänliga hälsningar;
Adis Sabanovic, Högskolan Kristianstad, 26 maj 2008
Business Intelligence Software 73
Appendix 2, Email (English)
Hello!
I study economics for the last semester at Kristianstad University and at the moment I am writing my master's degree on various Business Intelligence Systems. In my survey, I want to find out what companies understand, need and expect of such systems. Your help would be of great importance for my study and so I ask for about 10 minutes of your time to answer my web survey. Your participation is important!
Business Intelligence system is something that most businesses use to support their decision-making. Examples of such systems can be: Microsoft Excel, SAP Netwear BI, Qlikview, et cetera.
In order to reach the survey click on the link:
http://www.subsoft.se/questionnaire/questionnaire.html
The inquiry will expire on sömdag June 15, 2008.
Thank you very much in advance!
Sincerely;
Adis Sabanovic, Kristianstad University, 26 May 2008
Business Intelligence Software 74
Appendix 3, Questionnaire Results
Questionnaire Result
Start Date/Time
End Date/Time
Open Duration
Total Replies
Author
2008/5/26 1:44:45
2008/6/15 1:42:42
19 days 23:57:57
Questionnaire Title:
Enkätundersökning: Business Intelligence
Which of the following categories best describes your organization’s industry?
How many employees are there in all locations of your company?
Business Intelligence Software 75
What is your organization’s approximate annual revenue/ turnover in SEK?
Which of the following most closely describes your job level?
Which of the following most closely describes your job function?
Business Intelligence Software 76
In your company, is there a BI tool used for improvement of any decision making?
Which, if any, of the following BI systems do you use in your organization?
If you do not use a BI software, what is the main reason for that?
Business Intelligence Software 77
What is the main reason for choosing to work with BI in a company according to you?
If you do use BI, for how long have you been using your present BI application?
How often do you use BI tools in your work?
Business Intelligence Software 78
For what purposes is BI application mostly used in your company?
How or where should BI be placed in "your" organization, in your opinion?
What functional areas do you think should be the responsibility of a BI software?
Which one of these functions do you consider to be the most important one when working with BI?
Business Intelligence Software 79
What benefits if any, do you consider does a company gain from using BI?
When using BI software, what analysis do you consider to be most used?
Business Intelligence Software 80
How important do you consider these criteria to be when working with BI tools?
Information Perfectiveness
Mean value: 3,07
Information Quality
Mean value: 3.93
Information Effectiveness
Mean value: 3,73
Information Relevance
Mean value: 3,70
Business Intelligence Software 81
How important do you consider a BI Tool to be for a better and more efficient decision making?
What do you think will happen with the Importance of BI tools in the nearest future?
Business Intelligence Software 82
Appendix 4, Questionnaire
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Appendix 5, Industry - answers
Business Intelligence Software 93