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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


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


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


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


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


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.


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).


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


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.


• 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


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


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


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.


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)


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


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


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.


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


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


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.


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


(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).


(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


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.


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


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).


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


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


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)


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


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)


(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


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).


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).


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


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


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).


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


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.


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


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.


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.


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


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 ?


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


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


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


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


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.


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


the companies’ understandings and expectations can be extracted, and from the

bottom Task Layer the companies’ needs can be extracted.


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


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.


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.


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


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


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


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.


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


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.


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


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


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.


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.


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


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.


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


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.


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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


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


Appendix 3, Questionnaire Results

Questionnaire Result

Start Date/Time

End Date/Time

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2008/5/26 1:44:45

2008/6/15 1:42:42

19 days 23:57:57

67 [email protected]

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?


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?


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?


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?


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?


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?


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


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?


Appendix 4, Questionnaire


Appendix 5, Industry - answers

Business Intelligence Software - DiVA portal231171/FULLTEXT01.pdf · Business Intelligence Software...

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