the power of business intelligence on the decision-making
TRANSCRIPT
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Linköping University | Department of Management and
Engineering Master’s thesis, 30 credits | MSc Business Administration -Strategy and Management
in International Organizations
Spring 2018 | ISRN-number: LIU-IEI-FIL-A--18/02856—SE
The Power of Business
Intelligence on the
Decision-Making Process at
Linkoping University
A Case Study
Author
Hoda Lahbi
Advisor: Andrea Fried
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English title:
The Power of Business Intelligence on the Decision-Making Process at Linkoping University
(A Case Study)
Author: Hoda Lahbi
Advisor: Andrea Fried
Publication type:
Master’s thesis in Business Administration Strategy and Management in International
Organizations
Advanced level, 30 credits Spring semester 2018
ISRN-number: LIU-IEI-FIL-A--18/02856—SE
Linköping University
Department of Management and Engineering (IEI)
www.liu.se
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Glossary:
BI: Business intelligence, a term used to describe gathering, storing and
analyzing data for the purpose to facilitate decision-making.
DMP: Decision-making process
LIU: Linkoping University
IPB: Internal proficiency benefit
ROC: Reduced operational costs
CRB: Cost-reduced benefits
SPB: Staff productivity benefit
Statement of authorship
I declare that the work in this thesis has never been submitted before. All the
information it contains apart from my research is cited in the reference list.
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Acknowledgements:
This work represents the final achievement of my Master of Science in Strategy
and Management in International Organization. It has been two challenging
years, but great at the same time. I’m grateful to be part of the master’s program.
I would like to extend a special thanks to my husband and family, who
supported me throughout all of my studies.
I would like to express my gratitude to my advisor, Andrea Fried, for her
guidance and support. Special thanks goes to the staff of the controllers in the
Finance and Planning division in the administration office at Linkoping
University, to the dean of the faculty of Arts and Human Sciences, and to the
controllers of the four faculties at Linkoping University: Faculty of Arts, Faculty
of Medicines, Technical Faculty and Faculty of Education. The personnel whom
I cited contributed to my thesis and provide me precious information.
I’m especially thankful to my initial contact with the head of the Department of
Computer and Information Science at Linkoping University. He provided me
useful information and guided me in finding the right person with whom I begin
my research journey.
Thank you all for your
encouragement.
Linkoping, May 2018
Hoda Lahbi
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I. Table of Contents
Glossary:.......................................................................................................................................... 3
Statement of authorship ................................................................................................................. 3
Acknowledgements: ........................................................................................................................ 4
I. Table of Contents ............................................................................................................................ 5
List of Figures ................................................................................................................................. 7
List of Tables ................................................................................................................................... 8
1. Introduction .................................................................................................................................... 11
1.1 Research Gap .......................................................................................................................... 14
1.2 Research Purpose ................................................................................................................... 15
1.3 Research Question ................................................................................................................. 16
1.4 Thesis Structure ...................................................................................................................... 16
2. Theoretical Background.................................................................................................................. 17
2.1 Organizational Decision-Making ............................................................................................ 17
3.7.1 Decision-Making Review ................................................................................................ 18
3.7.2 Decision-Making Process ................................................................................................ 18
2.2 Business Intelligence .............................................................................................................. 21
3.7.3 The History of Business Intelligence ............................................................................... 23
3.7.4 The Business Intelligence Architecture .......................................................................... 25
2.3 The Business Intelligence Benefits ......................................................................................... 27
2.4 Business Intelligence in Higher Educational Institutions: ....................................................... 30
3.7.5 Qlikview .......................................................................................................................... 31
2.5 Theoretical Framework .......................................................................................................... 33
2.6 Literature Review Summary ................................................................................................... 37
3. Methodology .................................................................................................................................. 38
3.1 Research Approach ................................................................................................................. 38
3.7.6 Qualitative Research ...................................................................................................... 39
3.2 Research Process .................................................................................................................... 40
3.3 Literature Review ................................................................................................................... 41
3.4 Research Design ..................................................................................................................... 41
3.5 Sample Selection .................................................................................................................... 41
3.6 Linkoping University ............................................................................................................... 42
3.7 Data Collection ....................................................................................................................... 43
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3.7.7 Data Collection Method ................................................................................................. 43
3.7.8 Data Collection Process .................................................................................................. 46
3.8 Data Analysis .......................................................................................................................... 47
3.8.1 Coding and Comparison ................................................................................................. 47
3.9 Validity and Reliability ............................................................................................................ 49
3.9.1 Internal Validity .............................................................................................................. 49
3.9.2 External Validity .............................................................................................................. 49
3.9.3 Reliability ........................................................................................................................ 50
3.9.4 Objectivity ...................................................................................................................... 50
4. Findings........................................................................................................................................... 52
4.1 Business Intelligent System at Linkoping University .............................................................. 52
4.2 Positive Effect of Business Intelligence on Decision-Making.................................................. 52
4.3 Decisions Before the Implementation of the Business Intelligence ........................................ 53
4.4 Decisions After the Implementation of the Business Intelligence ......................................... 53
4.5 General Use of the Business Intelligence System .................................................................... 53
3.9.5 The Use of Qlikview ........................................................................................................ 54
5. Discussion ....................................................................................................................................... 57
5.1 The Power of Business Intelligence Benefits Over Decision-Making Process ........................ 57
5.2 The influence of Qlikview on Decision-Making Process ......................................................... 60
5.3 Summary of the Interviews .................................................................................................... 61
6. Conclusion ...................................................................................................................................... 76
6.1 Answers to the Research Question ........................................................................................ 76
6.2 Thesis Contribution and Implications for Future Practice ...................................................... 77
6.3 Suggestion for Future Work ................................................................................................... 77
6.4 Limitations .............................................................................................................................. 77
7. List of References ........................................................................................................................... 78
8. Appendices: .................................................................................................................................... 98
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List of Figures
Figure 1: The Hype Cycle of Technology Life (Gartner, 2018) ............................................................. 12
Figure 2: Thesis Outline ......................................................................................................................... 16
Figure 3:The Business Pressures Responses Support Model (Turban et al., 2011, p. 5) ...................... 18
Figure 4: The Steps of Decision Support, (Turban et al., 2011, p. 12) ................................................. 19
Figure 5:Huber’s Model (Huber, 1980, cited in Asemi et al., 2011, p. 169) ......................................... 20
Figure 6: BI Turning Data into Information (Azvine et al., 2006, p. 2) ................................................. 21
Figure 7:BI Architecture (Ong et al., 2011, p. 4) ................................................................................... 25
Figure 8:Tangible and Intangible BI Benefits (Eckerson, 2003, p. 11) ................................................. 27
Figure 9: BI Benefits (El Bashir et al., 2008, p. 144) ............................................................................ 28
Figure 10: The Gap Between the Human Brain and the Machine (Cronström, 2012). ......................... 31
Figure 11: Magic Quadrant (Gartner, 2017 cited in Underwood, J. 2017) .......................................... 33
Figure 12:BI Benefits (El Bashir et al., 2008) ....................................................................................... 34
Figure 13: The Theoretical Framework ................................................................................................. 34
Figure 14: The Approach of the Research Study Based on the Taxonomy of Different Studies (Järvinen
2008, p. 37) ............................................................................................................................................. 39
Figure 15:Conceptual “inverted pyramid” ............................................................................................ 40
Figure 16:Forms of Interviews (Saunders, 2007, p. 313) ...................................................................... 44
Figure 17:Uses of Different Types of Interview in Each of the Main Research Categories (Saunders,
2007, p. 314) ........................................................................................................................................... 44
Figure 18: Uses of Different Types of Interview in Each of the Main Research Categories (Saunders,
2007, p. 314) ........................................................................................................................................... 44
Figure 19: Data Approach Analysis (Lahbi, 2018) ................................................................................ 48
Figure 20: Coding Table ........................................................................................................................ 49
Figure 21: Number of Users in 2015, 2016 and 2017 until November15 .............................................. 55
Figure 22: The Use of Qlikview as a Decision Support (Internal Document LIU, 2018) ...................... 55
Figure 23: Qlikview and Other BI Tools at LiU and Some Examples of Their Applications( Internal
document from Liu). ............................................................................................................................... 56
Figure 24: Current Data Sources for Qlikview and the Sources for Rapport.liu.se. ............................. 56
Figure 25: The Thesis Outcomes ............................................................................................................ 75
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List of Tables
Table 1: Different Definitions of BI (Singh & Samalia, 2014, p. 52 ) .................................................... 22
Table 2: BI History from 1856 to 2018 (Davies, 2018).......................................................................... 24
Table 3: Table 3: BI Architecture and Layers (Ong et al., 2011) .......................................................... 26
Table 4: Details of interviews ................................................................................................................ 45
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Abstract
The decision-making process (DMP) is based on two elements: Organizational and technical
(Poleto et al., 2015). The organizational element is related to managers’ everyday decision-
making based on the organization strategy (Poleto et al., 2015). Its aim is to set up specific
actions for the planned objectives for the business (Rouse, 2018). The second element is the
technical DMP. According to (Poleto et al., 2015), it is related the set of tools that are used as
an aid in the DMP, which includes information technology and big data.
Business intelligence (BI) is the decisionmaking helping system (Ali et al., 2017).
Consequently, BI helps make better decisions, and it has become popular in many
organizations. As a result, it is important to show BI’s power over DMPs and to show how the
tools used in BI facilitate the DMP.
“Higher education institutions worldwide are operating today in a very dynamic and complex
environment” (Kabakchieva 2015, p. 104). As a result, universities that are within higher
education are threatened because competition is serious (Barrett, 2010).
Moreover, higher education is another area that will potentially impact big data research
(Ong, 2016). Consequently, the application and use of big data in higher educational
institutions may result in better quality education for students and a better experience for the
university staff (Ong, 2016).
As a result, HEI is adopting new technologies with the aim of sustaining its position on the
market. DMPs at higher academic institutions require structured data from a sophisticated
system, which can be only done through efficient and effective use of BI tools.
This thesis will investigate how the BI system is used at Linkoping University (LIU) and how
its benefits have changed DMPs. We studied the BI tool (Qlikview) that has been used at LIU
for 10 years.
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To answer the research question, a theoretical framework was developed that was based on
two models: Simon’s (1997) and Huber’s (1980) DMP models. The two models were
combined with the BI benefits that were based in El Bashir et al.’s (2008) model.
The research is done through a qualitative method of data collection and data analysis. At
LIU, seven interviews were conducted with BI users and with strategic decision-makers. The
findings show that the BI system, alongside Qlikview, has a positive effect on DMPs at LIU
as a public HEI. The factors affected are the information gathering time, the quality of data
provided and the accessibility to information by all BI users.
Keywords:
Business intelligence, decision-making process, framework, Qlikview, Linkoping University,
time, accessibility, quality, higher educational institutions, efficiency, BI benefits.
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1. Introduction
This chapter introduces decision-making process (DMP), business intelligence (BI), HEI and
BI benefits. Moreover, it studies the research gap and why the topic is interesting. In addition,
this chapter discusses the research question and the thesis structure.
“Information technology is a key success factor influencing the performance of decision
makers specifically the quality of their decisions” (El Gendy & Elragal, 2016, p. 1071).
According to El Gendy and Elragal (2016), digital technologies are changing how
organizations function.
Indeed, with the ideological change and the technological revolution in a global competitive
world, companies are building their presence by creating competitive advantages that ensure
their continuation in the market and their survival among competitors (Gupta et al., 2008).
Moreover, with the quality of information provided, modern organizations are able to get the
information needed from the large amount of data available to them, which offers a source of
strength against other competitors (Fujitsu, 2016). According to Fujitsu (2016), since it is hard
to convert data into information, modern technology provides the resources with which to
obtain better results. In the same context, the effective use of a large amount of data enables
the transformation of the organizations’ economies, giving them a competitive advantage
against competitors (McKinsey, 2011).
With the new technologies, organizations are looking for better ways to possess information
and to obtain value from the data provided for efficient decision-making (LaValle et al.,
2011). In the same context, Gartner (2018) discussed the hype cycle for emerging
technologies and how digital organizations are using this hype cycle to know where the
organization is and what its needs will be in the future. Furthermore, Gartner (2018) explains
the hype cycle, as is shown in Figure 1. The cycle is a graphic design that represents the
development of the adoption of technologies and how relevant that adoption is to solving
problems and finding new opportunities for organizations.
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Figure 1: The Hype Cycle of Technology Life (Gartner, 2018)
As a result of having the ability to turn data into information, organizations become able to
store and analyze data, thus providing better decisions (Elgendy & Elragal 2016). Since BI is
used to analyze big data, it is mostly used by businesses (Elgendy & Elragal 2016).
Since all large organizations are using BI and it is impossible to find a successful organization
that is not implementing BI systems (Chaudhuri et al., 2011), “universities should not be just
a neutral setting, but the place in which to create and share knowledge, an innovative and
prolific actor in interaction with the economic, administrative, and cultural environment”
(Bresefelean & Ghsoiu, 2014, p. 43). Therefore, the concept of BI is that of a field of
research that focuses on practical and the theoretical part of getting the right information from
data to make better decisions (Alexander et al., 2011). Moreover, “Business intelligence
systems combine operational data with analytical tools to present complex and competitive
information to planners and decision makers. The objective is to improve the timeliness and
quality of inputs to the decision process” (Negash, 2004, p. 177).
BI tool use has many positive effects regarding business process performance and
organizational performance (El Bashir et al., 2008). First, it provides better data and
information quality (Wieder & Ossimitz, 2015). According to Wieder and Ossimitz, (2015),
“The main objective of the BI system is to provide high quality information for managerial
decision making” (p.1165). Second, the BI tools develop efficiency (Gardner, 2017). This
means that once the right information is found, it is quickly assessed and turned into reports
that help save time and boost efficiency (Gardner, 2017). Furthermore, BI tools provide open
access to information (Gartner, 2018). Thus, the BI tools enable access to analyzing data and
information to make better decisions (Gartner, 2018). As a result, BI aims to provide support
for DMPs to improve performance (Ramakrishnan et al., 2012).
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To answer the question of how BI is used to support DMPs at the university, the BI system
should be discussed.
BI improves DMPs via processing, storing and analyzing data and turns it into insights
through which managers make efficient decisions to improve the organization’s performance
(King, 2016). In the same context, BI plays the role of leveraging critical information from
the whole value chain to make better decisions (Avosys, 2016).
According to Avosys (2016) and to improve corporate performance, BI is accredited to
enabling an organization to extract value from big data. However, the study of the power of
the BI system in the academic field has been limited. The focus of the impact of BI over DMP
has been reduced to the organizational life (Elbashir et al., 2008; Turban et al., 2011; Poleto et
al., 2015; Ziora, 2015).
Consequently, since the BI system is an information technology tool that helps with decision-
making and that has a positive impact on the DMP, there was limited research in the higher
educational area. In that context, Gorgan (2015) discussed decision support systems in the
academic field, arguing that “Decision support systems are software based systems that
supports business or organizational decision-making activities. Although they are mature
technologies that have proven their usefulness in business, their use in academic environment
is only in an incipient phase” (p. 451).
Therefore, the aim of this research is to investigate and study how the BI benefits have
changed the DMP at HEI. The study was conducted using a qualitative single case study at
LIU, a public Swedish university, via semi-structured interviews. The analysis was done by
analyzing the changes that occurred within the DMP based on the models by Simon (1997)
and Huber (1980). After analyzing the results, the aim of this research paper is to show the
factors that are positively affected due to the use of the BI system.
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1.1 Research Gap
Literature and research have shown a gap in the use of BI in DMPs in general. Davenport
(2006) argues that the focus on being an analytics competitor is on using highly sophisticated
information and being more technology oriented. Although BI supports decision-making,
research is this area is limited (Arnott & Pervan, 2008; Davenport 2006). Although many
articles discuss DMPs and BI, the literature did not go into detail talking about the use of BI
in the DMP (Shollo, 2011). In the same context, in their studies of 1,093 articles that were
published in 14 journals, Arnott and Pervan (2008) explored decision support as an
informatics system that improves managerial decisionmaking. However, the results showed
that “Overall, 15.2% of published papers between 1990 and 2004 were in the decision support
system field” (Arnott & Pervan, 2008, p. 660). Moreover, the results of another study of 103
articles related to BI from 1990 to 2010 showed that literature is focused on information
technology rather than decision-making (Shollo & Kautz, 2010).
Indeed, the focus of the literature was on the technological aspect of BI (Kimbal & Rouse,
2002; Immon, 2005; Kleese & Winter, 2007). Furthermore, literature focuses on the
competitive advantage of BI when creating a business intelligence competency center for
organizations (Miller et al., 2006) and creating an effective BI in organizations (Gilad &
Gilad, 1988). Also, it discusses the design of BI, including the organizational culture,
structure, and the skills and competences required (Burton et al., 2010). The literature also
discusses the BI tools (Heinrichs & Lim, 2003; Oyku et al., 2012; Rasoul & Mohammad,
2016), and it discusses the development of BI (Chandhuri et al., 2011; Chen et al., 2012).
The critical research gap also lies in the fact that there was little focus on the BI role in DMPs
in the educational sector (Gorgan, 2015). Moreover, Hassan et al., (2016) state that even if
universities are facing a new style of decision making based on BI, there is a challenge in the
readiness to implement and to use a BI system. In that context, Hassan et al., (2016) state that
“Currently, few published studies have examined BI readiness in HEI environment” (p. 174).
Moreover, Kabakchieva (2015) argues that despite the data that are available at universities,
managerial decisions are not always based on those data.
Since decision-makers make poor decisions despite the information technology they have
access to (Martinsons, 1994), organizations should focus on their DMPs and how to use BI as
an information technology for efficient decision-making (Kowalczyk et al., 2013). As a result,
many organizations do not understand what the relationship between BI and DMP actually is
(Hostmann et al., 2007).
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1.2 Research Purpose
“Data can be the lifeblood of an organization if it is allowed to flow freely across the entire
ecosystem” (Heyns, 2015, p. 7). The purpose of this study is to show some theories that were
used in DMPs in the past and to show the current importance of BI and analytics.
In the past, decisions were made based on the balance sheet and on the assumptions of how
much the company will generate as a profit (Heyns & Mazzel, 2015). On the other hand, big
data and data analytics are used to create more value for the organization by providing a
general overview of the needs of the customer and the market and the potential risks of future
projects (Heyns & Mazzel, 2015).
“Proper processing of the data could reveal new knowledge about our market, society and
environment, and enable us to react to emerging opportunities and changes” (Chen et al.,
2013, p. 157). As a result and after generating the large amount of data, the data generated
should be analyzed.
Indeed, Green et al. (2009) explained that “We recognize that there is no ‘one-size-fits-all’
approach to implementing BI strategy within universities” (p. 52).The reason we choose this
study is to investigate the use the BI system and its tools at LIU and how its benefits have a
power over the DMP. This study is motivated by the lack of research on the use of BI system
in the academic field especially at LIU.
The research will be done in the four faculties of LIU and will analyze the use of BI in DMPs
from an academic perspective. Moreover, it aims to suggest further research is necessary in
the field of the BI tools used at LIU. The potential results are expected to show how the
university is using BI tools and how its benefits have changed DMPs.
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1.3 Research Question
The general goal of this paper is to answer the following research question: How have the BI
system benefits changed DMPs at LIU?
1.4 Thesis Structure
Figure 2: Thesis Outline
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Chapter Summary:
Since there was a gap between the use of the BI system and DMPs in an academic context, we
have chosen to investigate the use of the BI system and its tools at LIU to develop the study of
our case. Accordingly, we have prepared a question for the research paper.
2. Theoretical Background
In this chapter, the literature review where DMP, BI, Qlikview and BI benefits were
presented, as well as the use of BI in HEI, is demonstrated. Finally, this chapter describes the
theoretical framework that will be used to answer the research question.
When dealing with a research paper, the literature review is an important component, as it
gives an overview of the direction the researcher follows (Kim, 2018). In the same context,
Yin (2009) argues that the purpose of a literature review is to provide answers to the topic.
Thus, in the following chapter, we will talk about DMPs. Moreover, we will provide a
theoretical background for BI and its tools, architecture and benefits. We will then talk about
the Qlikview tool and the use of BI in higher educational institutions. Finally we will provide
a theoretical framework upon which answers to the research question will be provided.
2.1 Organizational Decision-Making
Decisions play an important role in an organization’s existence. Thus, “Decision making is
the study of identifying and choosing alternatives based on the values and preferences of the
decision maker” (Govindarajan, 2014, p. 690). According to Govindarajan, (2014), making a
decision implies having many choices at hand.
According to Parkin (1996), the literature on decision-making is divided into three categories.
The first category is the body of knowledge that describes the decision theories that help in
the DMP. The second category is derived from psychological research, which includes
models of decision-based behavior. Thus, it describes the limitation of the human mind in the
DMP. The third category describes the DMP in organizations.
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3.7.1 Decision-Making Review
Historically speaking, decision-making dates back to 1910 and Dowery: “Since 1910, when
John Dewey first introduced the five‐stage decision process, it has been a widely accepted
concept” (Bruner & Pomazal, 1988). They classify the five stages as follows: the problem
recognition, the information search, the alternative evaluation, the choice and the outcome
(Bruner & Pomazal, 1988). Moreover, in 1938, “Chester Barnard, a retired telephone
executive and author of The Functions of the Executive, imported the term ‘decision-making’
from the lexicon of public administration into the business world” (Buchanan & O’ Connell
2006, p. 33).
In the same context, and according to Buchanan and O’ Connell (2006), theorists such as
James March, Herbert Simon and Henry Mintzberg continue the foundation for the study of
decision-making.
3.7.2 Decision-Making Process
Throughout history, decision-making has been considered an act that has been influenced by
past experiences, cognitive biases, commitment, age, believe in personal relevance and
individual differences (Dietrich, 2010). Turban et al. (2011), on the other hand, explained the
business pressures that make competition very high in such a globalized and digitalized
world. They go further by arguing how organizations take advantage of their external
environment and the information technology support for their decision-making, as illustrated
in Figure 3.
Figure 3:The Business Pressures Responses Support Model
(Turban et al., 2011, p. 5)
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According to Turban et al., (2011), decisions should be more analytical, methodical and
thoughtful. In the same context, Harris (1998) defines decision-making as a study-based
process to identify and choose between existing alternatives and a process by which to reduce
uncertainty about those alternatives to make better choices. Based on Simon’s (1977) work,
there are two types of decisions: programmed and non-programmed (cited in Asemi et al.,
2011).
The programmed or structured decisions are made when routines and repetitive problems
occur, and thus standard solutions exist (Turban et al., 2011). For this reason, decisions are
made according to the organization’s guidelines (Asemi et al., 2011). On the other hand,
unstructured or non-programmed decisions are made with fuzzy, complex problems and when
there are no cut-and-dry solutions (Certo, 1997, cited in Asemi et al., 2011). Thus, one-shot
unstructured decisions are made (Certo, 1997, cited in Asemi et al., 2011).
Simon (1977) discusses the DMP as a process with three phases: intelligence, design, and
choice (Turban et al., 2011). Later, a fourth phase was added the implementation phase. This
phase is shown in Figure 4.
After Simon’s (1997) model, in Huber’s (1980) DMP model, we found the implementation
and the monitoring phases, which are shown in Figure 5 (Asemi et al., 2011)
Figure 4: The Steps of Decision Support, (Turban et al.,
2011, p. 12)
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Figure 5:Huber’s Model (Huber, 1980, cited in Asemi et al., 2011, p. 169)
The five phases are defined as follows:
Intelligence: This phase contains searching for conditions that make the call for decisions
(Turban et al., 2011). It means that decision makers in this phase examine the existing realities
to precisely identify and investigate problems (Markoviće, 2018). As a result, the intelligence
phase includes defining the objectives of the organization, collecting data and then identifying
and classifying problems (Markoviće, 2018).
Design: This phase is the invention, development and analysis alternatives for solutions
(Turban et al., 2011). Moreover, during the design phase, a model should be constructed
based on defining the relationship between the variables that are found thus making possible
choice for potential solutions (Markoviće, 2018).
Choice: This phase contains the selection of solutions from the alternatives that are available
(Turban et al., 2011). As a result, decisions are made.
Implementation: During this stage and after decisions are made, the implementation phase
involves adapting the selected solution to a decision-based situation (Turban et al., 2011). As
a result, the implementation can be successful or unsuccessful ( Markoviće, 2018).
Monitoring: According to Cambridge (2018) dictionary, monitoring means to check
something carefully. It means that after decisions are implemented, monitoring is important.
To monitor decisions means to do the follow-up and check its efficiency.
To compare decision making between private and public organizations, Kim et al, (2014)
stated that both sectors have different goals and values. The differentiation lies in that private
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organizations are looking for profit while public organizations are looking for development
and sustainability (Kim et al., 2014). Moreover, in the private sector, decisions are short term,
while in the public sector, decisions are long term (Kim et al., 2014).
2.2 Business Intelligence
Decision-making can be properly done through the appropriate decision support systems
(Dillon et al., 2010) and with the information provided (Watson & Wixom, 2007; Hočevar &
Jaklič, 2008). As a result, using the information system will function as a competitive
advantage for organizations (Rezaei et al., 2011). In the same context, Turban et al., (2011)
argue that the use of information technology is vital for organizations in the way that it
possesses capabilities that facilitate DMPs. Turban et al., (2011) went further by emphasizing
the importance of computerized decision support systems, such as the BI tools.
In literature, BI has multiple definitions. According to Azvine et al, (2006), BI is not well
defined; this means that some consider it to be data reporting while others talk about business
performance management. Furthermore database analysts emphasize data extraction while
analytics highlight the analysis of statistics and data mining (Azvine et al., 2006). In the same
context, since decision-makers no longer trust the KPI nor the dashboards (Azvine et al.,
2006), BI is changing the way companies are managed, decisions are made and employees
perform their jobs (Watson & Wixom, 2007).
As a result, BI is “All about how to capture, access, understand, analyze and turn one of the
most valuable assets of an enterprise—raw data—into actionable information in order to
improve business performance” (Azvine et al., 2006, p.2).
Figure 6: BI Turning Data into Information (Azvine et al., 2006, p. 2)
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The various definitions of BI, according to Singh and Samalia (2014),
are listed in Table 1.
Definition Author (s)
The process of gathering and analyzing
internal and external business information.
Okkonen et al., 2012
BI is an architecture and a collection of
integrated operational and decision-based
support applications and databases that
provide the business community easy access
to business data.
Moss & Atre, 2003;
Papdopoulos & Kanellis 2010
Information to better understand business to
make more informed real-time business
decisions
Raisinghani, 2004
An organized and systematic process by
which organizations acquire, analyze and
disseminate from both internal and external
sources that are significant for their
business activities and for decision-
making
Lonnqvist & Pirttimaki, 2006
BI includes technologies and applications
employed in the use of several financial and
non financial metrics, key performance
indicators to assess the present
state and the method of deciding future
course of action for a business.
Hari, 2007
BI means leveraging information assets within
key business processes to achieve improved
business performance.
William & William, 2007
BI refers to the various solutions for
enhancing the overall business performance
Wang & Wang, 2008
BI is the conscious methodical transformation of data into new forms to provide information that is business-driven and results oriented.
Ranjan, 2008
BI is a set of business information and business analyses within the context of key business processes that lead to decisions and actions
Popvic, Turk & Jaklic, 2010
Table 1: Different Definitions of BI (Singh & Samalia, 2014, p. 52 )
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The definition that explains the concept of BI follows:
“Business intelligence consists of the processes, tools, and technologies required to turn data
into information and information into knowledge and plans that drive effective business
activity” (Eckerson, 2003, p. 49).
As a result and according to Eckerson (2003), BI is like an oil refinery that converts raw
material—crude oil—into the refined material—gas oil. This means that BI converts data into
knowledge and this is done through a process cycle (Eckerson, 2003).
3.7.3 The History of Business Intelligence
Based on Davies (2018) and shown in Table 2, from 1856 to 2018, there is a tremendous
change in the meaning of BI.
The Year The Events
1856 Richard Miller Devens talks about BI in his
Encyclopedia of Commercial & Business
Anecdotes. He looks for how to obtain
intelligence that will lead to a successful
business. Thus, he knows about the market
issues before his competitors.
1958 Hans Peter Luhn published an article called
“A Business Intelligence System,” in which
he outlined the basics of a BI system in a
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sketchy diagram. When documents entered to
the system, it undergoes a process before
actions took place
1960 The data increased and became difficult to
manage and to get knowledge from. Thus
something new needed to be developed.
1970: Enter the Big Boy Siebel and IBM entered the world of modern
BI. At that time, BI became a must have for
many organizations.
1990–2000: Business Intelligence
1.0
During these years BI became big money but
unfortunately it needed to extract the most
valuable knowledge from the big data.
2000 Onward: Business Intelligence 2.0 BI users extracted the valuable information
from data. Moreover, more technologies
were used that supported decision-making.
2018: The Tools of Today BI nowadays represents a powerful tool that
organizations have. BI has many functions
and provides the organizations different
benefits. As a result, BI information and
knowledge are used for sales, marketing,
finance, planning and decision making.
Table 2: BI History from 1856 to 2018 (Davies, 2018)
As a result, these definitions show how BI has a special architecture.
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3.7.4 The Business Intelligence Architecture
Turban et al (2011) define BI as “an umbrella term that combines architectures, tools,
databases, analytical tools, applications, and methodologies” (p. 19). Rouse (2018), however,
defines BI architecture as a framework by which the data, information management and the
components of technology are organized for building BI systems. Moreover, Ong et al.,
(2011) argue that BI architecture includes the types of data that need to be collected and the
method used to analyze those data to present the information needed. According to Ong et al.,
(2011), the layer of metadata should be included in BI architecture, as it is shown in Figure 7.
A good BI architecture should include a layer of metadata which is important to storing and
monitoring data (Ong et al., 2011). Moreover, Table 3 presents the BI architecture according
to Ong et al., (2011)
Figure 7:BI Architecture (Ong et al., 2011, p. 4)
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Layers Definition
Data Source
Layers
Data can come from internal or external sources. An internal data
source means that the data come from inside the organization. These
data are related to information concerning customers, sales and
products.
External data sources are related to competitors, the market and the
external environment of the organization.
Extract–
Transform–Load
(ETL) Layer
Extract means taking the most relevant data that support decision
making.
Transform means to convert data into a special format that is suitable
for reporting. Load is the final phase. The data are loaded into the
target repository.
Data Warehouse
Layer
This layer contains three components: operational data store, data
warehouse, and data marts.
Operational data store integrates all data that come from the ETL and
put it in a data warehouse.
The data warehouse represents the central storage of data from internal
and external resources. The data are stored for between 5 and 10 years
and is updated regularly.
Data marts play the support role for the data warehouse and provides
specific departments with the needed information, which the data
warehouse cannot do.
Metadata Layer This layer describes the data. This means that it shows how data are
stored, from where they were extracted, the changes that happen to the
data and so on. examples of metadata layers include the following:
OLAP: This describes the structure, level and dimension of the data that Enable
Table 3: Table 3: BI Architecture and Layers (Ong et al., 2011)
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the user to extract the needed data.
Data mining: Its role is to analyze the data to extract the most useful
information from it (Witten &Frank, 2000)
Reporting metadata: It is used to store reports names and reports
description.
End User Layer This layer shows the tools that are used to represent the information
needed by the users. It describes the level where such tools are used. In
each level, specific BI tools are used to extract information.
2.3 The Business Intelligence Benefits
Since BI aims at focusing on creating value by looking for knowledge (Sabherwal &
Fernandez, 2010), organizations use BI to achieve a variety of benefits such as profitability,
reduced costs, and efficiency (Isık et al., 2013). In the same context, Sabherwal & Becerra-
Fernandez (2010) grouped BI benefits into 3 major categories: improvement of operational
performance, improvement in customer relations and the identification of new opportunities
in contemporary organizations. Moreover, Eckerson (2003) discussed tangible and intangible
benefits as is shown in Figure 8. According to Eckerson (2003), the majority of the benefits of
BI are intangible.
Figure 8:Tangible and Intangible BI Benefits (Eckerson, 2003, p. 11)
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Moreover, Turban et al, (2011) argue that the BI benefits of an organization lie in its ability to
provide the suitable information that is the basics of decision-making. Accordingly, El Bashir
et al, (2008) explore 22 BI benefits which are grouped under four factors. Each factor is
related to specific benefits as illustrated in Figure 9.
However, for the purpose of this research, only factor number 3 with its 4 benefits is used.
Based on the interviews that were done, only the internal processes’ efficiency benefits are
present at LIU. Finally, only internal process’s efficiency was used in the research paper and
it is presented in Figure 9 and based on El Bashir et al.’s (2008) work.
Internal Process Efficiency:
According to El Bashir et al., (2008), internal process efficiency benefits represent the
benefits that arise from the development of internal processes, such as increased productivity
and cost reduction.
- The improved efficiency of internal processes:
“Key benefits that business intelligence aims to create are the increased efficiency and
Figure 9: BI Benefits (El Bashir et al., 2008, p.
144)
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effectiveness of the organization”
(Hočevar & Jaklič, 2008, p. 94). This means that BI enables
the organization to improve its internal processes to have a competitive advantage and to thus
meet the needs of the market.
- Increased staff productivity:
BI enables the staff to work independently and with more autonomy. In that context, Carver
and Ritacco (2006) argue that BI allows its users to access databases wherever it is stored and
to have the ability to prepare reports to get to know the organization’s situation.
- Reduction in costs of effective decision-making:
“With business intelligence, we can find the causes of certain problems as well as to identify
and to analyze the key success factors” (Hočevar & Jaklič, 2008, p. 95). They go further by
arguing that with the use of BI, effective decisions can be made (Hočevar & Jaklič, 2008).
In the same context, Carver and Ritacco (2006) state that the quality of decisions has a direct
relationship with the costs. As a result and to improve decision quality, organizations should
provide their staff the appropriate means to make decisions (Carver & Ritacco, 2006).
- Reduced operational costs
Williams and Williams (2003) state that “The business value of BI lies in its use within
management processes that impact operational processes that drive revenue or reduce costs,
and/or in its use within those operational processes themselves” (p. 3).
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2.4 Business Intelligence in Higher Educational Institutions:
The main objective of organizations is to convert their global presence into a global
competitive advantage (Gupta et al., 2008). Thus “Becoming a more knowledgeable,
companies must be accompanied by developing the ability to make and implement smart
decisions faster than competitors” (Gupta et al., 2008, p. 148). As any organization does,
universities should maintain their position within a market in which information technology is
spreading fast. In the same context and according to Verjel and Schmid (2015), to develop a
sustainable business, some economical, social and environmental dimensions should be
considered to get optimal solutions for the organization Barett (2010) state that “Universities
were now using mechanisms such as marketplace analysis, managerial capacity, part time
faculty, copyright, and information technology to create profit centers that linked them to a
network of actors that included both other universities and corporations” (p. 26).
Thus, to be successful within the higher educational market, universities should extract power
from the existing forces that can be relevant to their future (Barett, 2010).
Nowadays and due to the availability of solid information technologies, universities are
collecting large amounts of data from their students, staff, and lectures. (Kabakchieva, 2015).
Kabakchieva (2015) go further by arguing that for universities to remain competitive and to
look for new opportunities, they need to be updated and to make efficient decisions via the
use of advanced analytical technologies, such as data mining tools and BI systems.
However, Green et al (2009) say that “We recognize that there is no ‘one-size-fits-all’
approach to implementing business intelligence strategy within universities” (p. 52). Despite
this, implementing and using a BI system has many advantages. First, it provides a better
quality of the needed information (Wieder & Ossimitz, 2015). Second, it enhances the staff’s
efficiency (El Bashir et al., 2008). Regarding time, BI facilitates searching for and gaining
access to information for its users (El Bashir et al., 2008).
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3.7.5 Qlikview
Qlikteck is a Swedish international company (Kabakchieva, 2015). After settling in the
United States, the company offered a BI software solution called Qlikview (Kabakchieva,
2015). According to Qlik (2018), data are only one source of information; however, BI
provides efficient solutions.
BI has many characteristics. The software is easy to manipulate and understand
(Kabakchieva, 2015). Solutions and information are provided through graphics (Kabakchieva,
2015).
Before talking about the tool, it is important to talk about the history of the product.
Based on a blog written by Cronström (2012), in 1994, the first version of Qlikview was
introduced. Qlikview bridges the gap between the human brain and the machine as is shown
in Figure 10 by Cronström (2012).
Figure 10: The Gap Between the Human Brain and the Machine (Cronström, 2012).
After that, Qlikview was called “the associative info mart program” because it became a tool
with a subset of data (compared to the data warehouse). Many words are said to describe
Qlikview; it is said to be intuitive data exploration and a revolution in BI, and now, it is
described as business discovery. Moreover, Qlikview’s function supports the process of
coming from a blank mind to attain knowledge. Qlikview’s functions include its ability to
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explore new data, discover facts and answer questions related to a decision (Cronström,
2012). Furthermore, the software enables its users to access the data history and to develop
applications (Qlik 2018). As a result, it enables users to create KPI reports and make decisions
(Datawarehouse4u, 2009).
Qlikview is composed of three dashboards where the information is extracted and then
presented using graphics (Kabakchieva 2015). The three dashboards are bar and pie charts,
performance indicators and tables and list boxes (Kabakchieva, 2015).
According to Visual Intelligence (2018), Qlikview is a BI platform that converts data into
information. Moreover, Underwood (2017) discussed Gartner’s (2017) quadrant results. As is
shown in Figure 11, Qlik, the vendor of Qlikview, is a leader in the market.
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Figure 11: Magic Quadrant (Gartner, 2017 cited in Underwood, J. 2017)
2.5 Theoretical Framework The framework used is based on Simon’s (1997) and Huber’s (1980) DMP models, as well as
El Bashir et al.’s (2008) BI benefits.
The choice to combine the three components is based on specific reasons. First, as the founder
of research in decision-making, Simon is the key researcher in the area of decision-making
(Pomerol & Adam, 2004). Pomerol and Adam (2004) go further by arguing about Simon’s
(1977) contribution to decision-making and how the intelligent systems changed due to his
influence. Second, El Bashir et al (2008) use 22 BI benefits in their research, which touched
the most important elements of an organization. These elements are the external environment,
which deals with customers and suppliers and the internal environment, which includes the
business’s processes and the internal efficiency.
Furthermore, the models will be mixed to investigate the changes that happen in the DMP.
Figure 5 illustrates the models by Simon (1977) and Huber (1980).
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Figure 12:BI Benefits (El Bashir et al., 2008)
Figure 13: The Theoretical Framework
37
2.6 Literature Review Summary
In the literature review, history, definitions of DMP, BI, QLIKVIEW, BI benefits and the use
of HEI were presented. Harris (1998) defines decision-making as a study process to identify
and choose between existing alternatives and a process to reduce uncertainty about those
alternatives to make the better choice. Moreover, Simon (1997) and Huber (1980) explain
DMP. Simon (1997) writes about the three phases of DMP, which are intelligence, design and
choice, and Huber (1980) adds the implementation and the monitoring phases.
Moreover, Eckerson (2003) defines the BI system as “the processes, tools, and technologies
required to turn data into information and information into knowledge and plans that drive
effective business activity” (p. 49).
Research on BI’s impact on organizations showed that the use of BI systems had many
benefits. Thompson (2004), cited in Turban et al (2011), stated that among BI’s benefits, it
facilitates reporting, improves decision-making, improves customer service and increases
revenues. Moreover, El Bashir et al. (2008), discuss 22 BI benefits, which they grouped into
four factor categories. The categories are the organizational benefits, supplier relation
benefits, internal efficiency benefits and customer relation benefits.
Qlikview, as a BI tool, is easy to manipulate and understand (Kabakchieva, 2015). The BI tool
provides its users access to the data history and allows them to develop applications (Qlik
2018). Consequently, it enables the creation of KPI and reports and thus allows for decision-
making (Datawarehouse4u, 2009). It enables its users to create very useful, accurate KPI,
measurement reports and performance dashboards and make accurate, strategic decisions
(Datawarehouse4u, 2009).
On the other hand, universities are collecting large amounts of data on their students, staff
members, lecturers and other groups (Kabakchieva, 2015). As a result, for universities to
remain competitive and look for new opportunities, they need to be updated and to make
efficient decisions via the use of advanced analytical technologies such as data mining tools
and BI systems (Kabakchieva, 2015).
38
Implementing and using a BI system has many advantages. First, it provides higher-quality
information (Wieder & Ossimitz, 2015). Second, it enhances staff efficiency (El Bashir et al.,
2008). Regarding time, BI facilitates searching and access to information for all users (El
Bashir et al., 2008).
3. Methodology
This chapter represents the research methodology that this thesis follows. It describes the
research approach and the research process. Furthermore, this chapter explains how the data
was collected, and analyzed. It shows the sampling methodology that was followed.
3.1 Research Approach
The term “research approach” is an umbrella term that refers to identical research methods
(Järvinen, 2008). We adapted a qualitative method as a research approach for various reasons.
First, it helps develop a theory after we study the real world (Järvinen, 2008). According to
Rahman (2016), “A qualitative research is not statistical and it incorporates multiple realities”
(p. 102). Second, with qualitative research, it is easy to interpret the participants’ points of
view and experiences (Denzin, 1989). As a result, researchers can use the qualitative approach
to describe a phenomenon (Flick, 2014).
Following Järvinen (2008), in the research paper, we empirically study the past and present
using theory-developing methods, as we have a theoretical framework that guides our
research paper. Using the theory developing method, the research approach ends with a
theory- developing study where we rely on one case study.
Figure 14 illustrates how we use this research approach based on Järvinen (2008).
39
Figure 14: The Approach of the Research Study Based on the Taxonomy of Different
Studies (Järvinen 2008, p. 37)
The grey boxes represent the selected areas in our research approach.
3.7.6 Qualitative Research
According to Kneebone and Fry (2010), qualitative research uses words to show how people
act and answer without using numbers. Accordingly, in this thesis, a qualitative research
method is adapted because it is suitable for our case study.
According to Rahman (2016), using qualitative research has some benefits: First, qualitative
research enables researchers to detect the participant’s feelings and interpret them. Second, it
allows for the study and understanding of the human experience. Third, it provides a clear
view of events and meanings. Fourth, “the studies using qualitative approach can help us to
understand the markers’ working assumption about what is to be assessed and the meaning of
the score or grade” (Rahman 2016, p. 104). Fifth, through the use of qualitative research,
researchers directly interact with the participants in interviews. Last, with qualitative research
design’s flexible structure, complex issues can be understood without difficulty (Rahman,
2016).
Oates (2006) writes about the strategy as an approach to answer the research question. He
goes on to write about the six strategies: survey, design and creation, experiment, case study,
action research, and ethnography. Furthermore, Oates (2006) defines the case study single
study of an organization to investigate its complexity and gain insight about it.
40
As a result, in the research paper, we adapted a qualitative method using a deductive
approach. We used a single case study that included interviews. This choice of case study was
based on Yin’s (2009) argument that case studies are the best choice when “how” and “why”
questions arise and when the focus is on a contemporary subject.
Regarding time, case studies took various approaches (Yin, 2009). Yin (2009) identified three
types of studies: historical, contemporary and long-term. The thesis discussed a contemporary
case study as it was related to something that is happening in the moment not historically.
3.2 Research Process
The process began with a literature review, in which we first analyzed articles and then
discussed the use of a BI system from organizational and academic perspectives. The purpose
of the research was to discover something new and useful, which we did by studying the
current state of knowledge (Maier, 2013). Maier (2013) developed a conceptual framework of
the steps in writing a literature review.
Figure 15:Conceptual “inverted pyramid”
Models of Steps in the Writing of the Literature Review
(Maier, 2013)
41
The first step was identifying the problem domain. The second step was searching for what
previous researchers had accomplished. The third step was identifying the research gap and,
finally, setting the paper’s objectives.
We believe that we covered the five steps. First, we had thorough knowledge about the area of
our study and the problem domain. Second, we read about the history of the BI’s and DMP’s
previous benefits and the use of Qlikview and BI in HEI. Third, we explored the gaps in the
literature concerning BI’s uses, its DMP and its uses in HEI. Finally, we set the research
paper’s objectives by developing a theoretical framework through which we would answer the
research question.
3.3 Literature Review In the research, we included the literature review concerning the BI system, DMP, BI benefits,
BI tool, Qlikview and use of BI in HEI. After developing the theoretical framework, we
contacted LIU staff members that were using the BI system for semi-structured interviews.
Next, results were coded and analyzed. Lastly, we used the theoretical framework to answer
the research question. The results show how BI benefits have changed with BI tools. The four
factors were internal processes, staff productivity, costs of decision making and costs of
operations
3.4 Research Design
Because the research paper’s aim was to extract meaningful results from the data, a qualitative
method was adapted using a deductive approach. Moreover, we used a single case study and
conducted semi- structured interviews.
3.5 Sample Selection
In the research paper, we followed a purposeful sampling approach and snowball sampling.
According to Patton (1990), “The logic and power of purposeful sampling lies in selecting
information-rich cases for study in depth. Information-rich cases are those from which one
can learn a great deal about issues of central importance to the purpose of the research, thus
the term purposeful sampling” (p. 169).
42
Moreover, we used homogenous sampling as a technique of the purposeful sampling
approach (Lund Research Ltd, 2012). The selected sample in our study should have some
homogenous criteria:
- First, the organization had to be one of the BI technology users.
- Second, because our aim was to discover the changes resulting from use of the BI system,
the organization should have used the BI system for many years to enable studies before
and after the implementation of the BI system.
- To get a homogenous sample, the interviewee should know about the DMP and the BI
system.
Moreover, in a qualitative study and to get a homogenous sample, we used a snowball
sampling methodology to gather data from the interviewees. The snowball method “uses a
small pool of initial informants to nominate other participants who meet the eligibility criteria
for a study. The name reflects an analogy to a snowball increasing in size as it rolls downhill”
(Given, 2008).
3.6 Linkoping University
Linkoping University (LIU) is situated in Sweden. It gained its status in 1975 (LIU A, 2017).
According to the annual report (2017), in 2016, the university had 27,000 students and 4,000
employees with a total revenue of 3,700 M SEK (LIU A, 2017).
Linköping University has four faculties: the Faculty of Arts and Sciences, the Faculty of
Educational Sciences, the Faculty of Medicine and Health Sciences and the Faculty of
Science and Engineering (LIU B, 2017). Each faculty has its own function. Moreover, it has
four campuses. The first campus is situated in Valla, Linkoping. The second campus is
situated at the university hospital. The third campus is in Norrkoping, and the fourth is in
Lidingo, Stockholm (LIU B, 2017).
As an international university, many students all over the world choose it as a place of study.
In this context, LIU has an Internationalization Plan for 2013-2020 that includes measures to
ensure the quality of the university services (LIU C, 2017). This plan has two aims, the first of
which is to increase educational quality and the second is to boost itself competitively at the
national and international levels (LIU, C 2017).
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3.7 Data Collection
In the following chapter, we present the method and process used to collect data
3.7.7 Data Collection Method
Documents and interviews are the primary data sources used in qualitative research (Merriam
& Tisdell, 2015). Moreover, interviews are beneficial because they yield data quickly in
quantity (Marshall & Rossman 1999). Accordingly, in this research paper, some documents
from LIU on BI tools and seven semi-structured interviews are used as data sources.
The number of interviews to be conducted must be defined. The saturation strategy is the one
that we use to show an end to data collection. Saunders et al. (2017) define saturation as the
criteria for stopping or discontinuing data collection.
We stopped conducting interviews when we noticed repetition. As a result, we may not reach
the estimated number of interviews planned.
3.7.1.1 Interviews
The two types of interviews are standardized and nonstandardized (Saunders, 2007). In our
thesis, we conducted nonstandarized semi-structured interviews. Figures 16 and 17 show how
we selected interviewees.
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Figure 16:Forms of Interviews (Saunders, 2007, p. 313)
Doyle (2017) defined a semi-structured interview as a meeting where the interviewer does
not strictly follow a formalized list of questions but instead asks open-ended questions. With
open-ended questions, the respondent feels free to express his or her full point of view
because the questions always start with “how” or “what” rather than limiting the answers to
“yes” or “no.”
In our interviews, we record the discussion to avoid missing any important points.
Respondent selection:
Figure 17:Uses of Different Types of Interview in Each of the Main
Research Categories (Saunders, 2007, p. 314)
Figure 18: Uses of Different Types of Interview in Each of the Main
Research Categories (Saunders, 2007, p. 314)
45
After investigating the university’s BI system users, I was guided to meet the interviewee 1 in
the planning division of the dean’s office in the Faculty of Arts and Human sciences. For the
other respondents, according to the snowball sampling methodology, I was guided to whom
we should meet next. We stopped the interviews when we felt that the information was
repeated and we did not need to conduct anymore interviews—in other words, when we
reached the saturation point. Figure 18 includes an explanation of how the interviews were
conducted. Furthermore, Table 4 contains the interviewees’ information.
Table 4: Details of interviews
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3.7.1.2 Internal Documents
According to Oates (2006), documents are not only written material but include other sources
of data. In our case study, we used multimedia documents for the BI tool, Qlikview.
According to Oates (2006), multimedia documents include visual data sources, such as the BI
models and pictures.
We used a private internal document and the Qlikview vendor website for a general
presentation of the product.
3.7.8 Data Collection Process Regarding the data collection process, the first step was getting permission to conduct the
study. We received permission in our first informal interview. After the informal interview,
we created a questionnaire, which contained general and specific questions. Based on the
theoretical framework, the specific questions were elaborated.
The objectives of the questions were to receive more information about the topic discussed in
the research paper develop the framework and answer the research question. The specific
questions concerned BI benefits, the DMP and its five phases. Its aim was to determine how,
with the presence of BI benefits, the DMP has changed. Other questions concerned the
organization and use of the BI system with the BI tool, Qlikview. Its aim was to describe
DMP before and after the BI system’s implementation.
The semi-structured interviews were based on open-ended questions. Seven interviews were
conducted, six face-to-face and one via email. The interviews were recorded and transcribed
with the help of the Nvivo software to make the codification. To make the research more
valid, we used secondary data, which included internal documents that described the use of
the BI system at the university. The document was prepared with one of the BI experts in the
university’s administration office and was reviewed by the financial manager. Because the
document was in Swedish, the BI expert translated its key elements, allowing us to begin our
data analysis.
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3.8 Data Analysis
Data analysis is defined as the process of reducing a large amount of collected data to make
sense of it (Kawulich, 2004). In the same context, LeCompte and Schensul (1999) argue that
data analysis includes inscription, description and transcription of the collected data. From the
documents that we got and from the interviews that we conducted, the first step in our
research paper to analyze the data was transcribing the interviews and translating some of the
document’s important elements.
3.8.1 Coding and Comparison
In the thesis, we developed a theoretical framework to answer the research question. In the
theoretical framework, we had four BI benefits that were placed with DMP phases. To
analyze data, we presented our findings and then compared the interview answers to the
documents LIU provided.
According to Bernard and Russell (2012), the theory includes three steps: coding texts,
linking coded texts into theoretical models and then validating the models.
First, coding involves naming the themes with the help of NVIVO (Bernard & Russell, 2012).
In the same context, Strauss and Corbin (1990) talks about three types of coding: open coding,
axial coding, and selective coding. Based on Strauss and Corbin (1990), open coding is where
data is broken down analytically, and axial coding entails connecting these categories with
their subcategories. Finally, “selective coding is when the categories are gathered into one
core category while all the other categories that need explanation are filled with detailed
description” (Strauss and Corbin, 1990, p. 14).
As a result, we followed the data analysis process based on the work of Hasa (2017). The first
step was the collection of data through interviews. Second was the review of the records and
extraction of ideas and concepts that were classified by codes. Third, these codes were turned
into concepts, then into categories and finally, these categories were the sources on which a
theory was based (Hasa, 2017).
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Figure 19: Data Approach Analysis (Lahbi, 2018)
In this research paper, we will present our findings to reach the conclusion. The next part, an
analysis of the data gathered from interviews and documents we received from LIU, will be
presented.
49
Name Description
Choice - Reliable facts
- Reliable information
Implementation - Easy spread of information
Monitoring - Easy access to information
- Easy checkup, extraction and monitoring of information
Reduced Operational
Costs Benefit
Intelligence - Accessibility to information
- Manage much more data
Design - Costs are reduced due to the information provided
Choice - Information is increasing
Implementation - Information is spread very quickly
Monitoring - Easy access to decisions
Reduction of Costs
Benefit
Intelligence - Much cheaper to have electronic information
Design - Decreases costs of searching for alternatives
Choice - DMP has sped up
Implementation - Easy to spread the information with reduced costs
Monitoring - More informative decisions
Staff Productivity Benefit
Intelligence - Increases productivity in the information searching
- Short time in gathering information
- Advanced jobs for the staff
Design - More alternatives to choose from
Choice - Fast and flexible reporting
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Name Description
Implementation - Easy access to decisions
- More flexibility and adaptability
Monitoring - Easy access to information
- Self-monitoring
Figure 20: Coding Table
3.9 Validity and Reliability
Strategies that are implemented to evaluate utility and trustworthiness are important in a
qualitative research paper (Morse et al., 2002), which means that both are important criteria to
attain rigor in a qualitative study (Morse et al., 2002). Moreover, Lincoln & Guba (1985)
wrote about trustworthiness that is composed of four elements: internal validity, external
validity, reliability and objectivity. The four components are used to assess the qualitative
data.
3.9.1 Internal Validity
Credibility or internal validity is the first element of trustworthiness (Lincoln & Guba, 1985).
Credibility requires the researcher to connect the research findings with reality to show the
findings’ truth (Statisticssolution, 2018). Moreover, it shows the consistency between the
participants’ views and the researcher’s presentation of the findings (Ryan et al., 2007). To
have internal validity and credibility, we used a triangulation method. Triangulation
methodology is the use of various data sources to understand the issue well (Patton, 1999
cited in Carter et al., 2014). Moreover, we used triangulation of data sources (Carter et al.,
2014). In the research paper, first we collected data through interviews until we reached a
saturation point, and we used some internal documents. In that way, we relied on multiple
resources rather than a single data source.
3.9.2 External Validity
Transferability or external validity means the results can fit outside the study field (Lincoln &
Guba, 1985). According to Kalu and Bwayla (2017), the results of all good research can be
applied generally and easily. Therefore, if research has external validity, its context should be
described properly so the reader can generalize the findings and apply them externally (Cirt,
2018).
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In our research paper, we applied “rich, thick description,” which entails providing a rich
description of the participants, setting and themes (Creswell & Miller, 2009). The aim of the
“rich, thick description” was to provide readers with a detailed description of events and
people involved to establish credibility from the reader’s perspective (Creswell & Miller,
2009).
As a result, we provided detailed descriptions of the interviewees. Moreover, we provided
deep descriptions of the findings. Additionally, in our analysis, we provided some quotes
from the interviews to make our work rich.
3.9.3 Reliability
Reliability means the consistency with which the findings could be repeated or replicated
(Cirt, 2018). Reliability, or dependability, also refers to the information’s stability over time
(Lincoln & Guba, 1985). However, Silverman (2016 cited in Kalu & Bwayla, 2017) argued
that reliability is difficult to predict in a changing world. This was also true in our case. The
study was replicable but the findings were different due to changing technology.
As a result, to make our findings reliable, we used “audit trails.” According to Creswell and
Miller (2009), “In establishing an audit trail, researchers provide clear documentation of all
research decisions and activities. Through this process of documenting a study and a review
of the documentation by an external auditor, the narrative account becomes credible” (p. 128).
In our research paper, we made a chronological order of the data collection and analysis
processes.
3.9.4 Objectivity
Objectivity means how research findings were supported by data collection when examined
by others (Cirt, 2008). Moreover, to show the research paper’s conformability, a detailed
description of the research process should be provided (Kalu & Bwayla, 2017). Therefore, in
our research paper, we used “rich, thick description,” as previously explained. We provided a
detailed description of the research approach, research process, research design, sampling
methodology and data collection and analysis. In doing so, we provided a clear vision of the
process we followed.
3.9.5 Ethical Considerations
Some ethical issues must be considered throughout the research process such as respect for
51
persons (Scott, 2017). In a qualitative research study, the researcher should consider
transparency in the way the research is conducted, especially when dealing with participants
(Kalu & Bwayla, 2017). Therefore, in our thesis, we informed every interviewee about the
interview’s purpose via email and then again during the interview. We also asked all
interviewees whether they preferred that we use their full names or just their first names.
Moreover, we asked for permission to record the entire interview.
By showing respect for the participants, we made our research more credible and ethical.
Chapter summaryThe aim of the research paper was to answer the research problem. For this
reason a theoretical framework was developed. The research method was composed of
qualitative data using a single case study which was LIU. Moreover, the interviews and
internal documents were the means through which the data was collected. The analyzed data
was coded with the help of Nvivo software. After the codification, we will fill in the
theoretical framework as an answer to our research paper.
52
4. Findings
This chapter represents our findings from the collected and analyzed data.
4.1 Business Intelligent System at Linkoping University
BI leverages critical information from the whole value chain for better decisions (Avosys,
2016). At LIU, the BI system provides an easy way to handle various administration systems,
such as HR and accounting and to get more information, which interviewee 1 mentioned. He
said that “BI is an essential system through which it becomes easy and fast to look for
information and to shape it.” Second, it is used in decision-making, which interviewees 2, 3
and 7 mentioned. In that context, interviewee 7 said that “BI is a sort of system to collect data
from different sources in order to present an indicator of the business (financial or other) or to
ground decisions.” Third, it is a system where data from various sources are gathered and
combined to serve the department needs. Interviewee 3 claimed that the “BI system takes
different data in different ways and put it together in a friendly way.”
Overall, the BI system at LIU plays an important role in handling various administration
systems, such as HR and accounting. Furthermore, it helps with decision-making, which
means that it helps in the presentation of the needed data because it serves as a thorough
generator of information from various data sources.
4.2 Positive Effect of Business Intelligence on Decision-Making
At LIU, the BI system is beneficial in many ways: First, it speeds up data gathering.
According to interviewee 1, the BI system “helps to get data from different departments and it
helps to package information easily.” Interviewees 1, 3 and 7 agreed that the system improves
the quality of decisions. Regarding that matter, interviewee 7 said that “managers can rely on
good information in order to make difficult decisions.” It also provides multiple users access
to the same data at the same time as interviewees 4 and 7 stated.
53
In summary, and regarding decision making, the BI system helps the university speed up data
collection for decisions. Moreover, the quality of decisions is improved due to the quality of
information that is provided. It is a system that provides users access to necessary
information, wherever they are.
4.3 Decisions Before the Implementation of the Business Intelligence
Decisions were made before the BI system’s implementation by the university board
(interviewee 6), and according to interviewees 3 and 6, the information provided was based
on the data that was saved in computers as everybody has his or her own way to save data.
Finally, decisions were made without any detailed data (interviewee 1) and were based on
previous decisions (interviewee 2).
4.4 Decisions After the Implementation of the Business Intelligence
After the BI system’s implementation, the information provided was more reliable
(interviewee 7). Second, decisions were driven from the system (interviewee 1). Moreover,
the information provided for decisions was gathered and summarized in the BI system
(interviewees 3 & 4). However according to interviewee 2, relying on history is the basis of
decision making and the BI system is a tool that facilitates gathering the needed data.
Moreover, interviewee 6 said that “decision making is not changing at the university because
decisions take time.”
In summary, some controllers stated that the BI system initiates change regarding decision -
making, data reliability and the method of gathering and summarizing information in the BI
system. The dean of the Faculty of Arts and the controller of the Faculty of Medicines stated
that BI facilitates information gathering for decisions.
4.5 General Use of the Business Intelligence System
The BI system has many uses at LIU. It is used in multiple departments and at multiple
decision-making levels. First, it is used to collect and gather data for reporting (interviewee
1). Second, it is used to follow up on decisions according to interviewees 3 and 7. Moreover,
interviewee 2 said that as a decision maker, she is not using the BI system but she is receiving
the information from controllers.
Consequently, the BI is an important system at LIU that is used to collect and gather data for
decision makers and a follow up system that provides decision makers the needed information
from the controllers.
54
3.9.5 The Use of Qlikview
Based on the interviews that were conducted, Qlikview is the BI tool that is used at LIU. It
has many uses at the university. First, it is used to develop applications regarding the
department’s needs (interviewee 1). Second, the HR department and the administration use it
to follow up the number of students (interviewee 4).Third, it generates various reports
combines data from various sources and generates one report, as interviewee 6 stated.
According to the BI management plan at LiU (2018), Qlikview is a supporting tool of the BI
systems that is used for planning and follows up. It consists of Qlikview Server and Qlikview
Publisher. It is also a decision support tool that is used to simplify research and complete
follow-up in various departments. LIU uses Qlikview to take data from the information
system. In the same context, Qlikview contains many applications its users can develop.
55
Between 2016 and 2017, the number of Qlikview users increased, as shown in figure 20.
As a decision support tool, one of Qlikview’s functions is to provide decision makers with
needed information and knowledge. As a result, the BI tool is used first in research and
education. Second, it is present in the process of supporting activities where statistics are
required for decisions. Moreover, it is used in the planification department. Figure 21 explains
further where Qlikview is used.
As an operations support system, Qlikview is a BI tool that contains various applications
developed by its users, which means that it can be developed into applications according to
decision-making needs Moreover, with Qlikview, one can choose to view data either as a set
of statistics or as graphs.
Other BI tools further support decision-making at LIU. Figure 22 shows a clear
picture of the
applications used with Qlikview and other BI tools.
Figure 21: Number of Users in 2015, 2016 and 2017 until November15
Figure 22: The Use of Qlikview as a Decision Support (Internal Document LIU, 2018)
56
.
Figure 23: Qlikview and Other BI Tools at LiU and Some Examples of Their Applications (
Internal document from Liu).
The Information Technology Support System
Figure 24: Current Data Sources for Qlikview and the Sources for Rapport.liu.se.
57
The Information Technology department at the university manages operations in Qlikview’s
two servers. Qlikview’s management and development take place in the finance and
planification department. Ladok sources are managed externally. Moreover, the sources that
are managed internally are HR Primula and Raindance. Consequently, support from data
sources administrators is required in the development of new Qlikview applications.
5. Discussion
This chapter presents a discussion about the findings results and theoretical framework. It
also presents a summary of the interviews.
5.1 The Power of Business Intelligence Benefits Over Decision-
Making Process
According to Simon (1997) and Huber (1980), the DMP includes five steps: the search for
information, the choice between alternatives, the choice of decisions, the implementation of
decisions and the monitoring of decisions.
- Faculty of Arts and Human Science: Interviewee 1
Internal proficiency benefits and DMP:
In the phase of searching for and gathering information, the BI tools speed up the process of
gathering data. It is more flexible and it saves time. For the choice of alternatives, there is a
general understanding of the process. In the decision-making phase, the BI system provides
models and graphs for decision makers. In the implementation phase, the BI system clarifies
why decisions are made and their possible consequences.
58
Staff productivity:
For staff productivity, the BI system speeds up the process of searching for information and
makes the reporting more flexible.
Reduction in the cost of effective decision-making:
The process of decision making is sped up, and in DMP all users are more informed about
decision making.
Reduced operational costs:
Costs of operation are not greatly reduced because they are not measurable.
- Faculty of Physics Biology and Chemistry: Interviewee 5
Internal proficiency benefits and DMP:
Regarding the DMP’s internal proficiency, the BI system is used to gather information and
compare periods to make a choice. The BI system is also used to make information more
accessible to everybody and to monitor decisions.
Staff productivity
For staff productivity regarding the DMP, the BI system changed the staff’s productivity
regarding their ability to search for information, and produce many options. Furthermore, the
combination of many applications, enables users to make a choice and search for suitable
decisions. The monitoring of decisions is much more efficient as the system provides its users
access to the necessary information.
Reduction in the cost of effective decision-making:
The cost of decision-making was reduced due the availability of various electronic data. It
becomes easy for everybody to implement decisions and to follow up on decisions.
Reduced operational costs:
With the presence of the BI system, operational costs were reduced due to data’s accessibility.
Therefore, the user can manage more data. Second, because of the open accessibility, the user
can have various data in one file, making it easier to make a decision that leads to reduced
costs.
59
Faculty of Medicines: Interviewee 6
Internal proficiency benefits and DMP:
The BI system facilitates information gathering. It enables users to find multiple choices but it
doesn’t help them make decisions, which would necessitate another process. The BI system is
not used to implement decisions rather it provides access to monitor decisions.
Staff productivity:
The BI system has made the staff more efficient in data gathering in a short time and allows
staff members to present a monthly report on decision follow-ups.
Reduction in the cost of effective decision-making:
The BI system reduces time costs in gathering information and presenting to decision makers.
Reduced operational costs
The BI system does not change operation costs.
- Faculty of Education: Interviewee 7
Internal proficiency benefits:
With the availability of information, the BI system has made the use of information more
efficient. The BI system also provides many alternatives for better and more efficient
decisions. Overall, the BI has changed the implementation of decisions and the way to follow
-up on those decisions.
- University administration: Interviewee 2
Internal proficiency benefits:
The BI system has changed the data gathering process, as it provides many options. To make
decisions, users rely not only on the BI system but also on past decisions. Moreover, with the
BI system, more people are informed about decisions.
60
-
Staff productivity:
Use of the BI system has increased staff productivity in the entire DMP.
- University Administration: Interviewee 3
Internal proficiency benefits:
In the DMP, the use of the BI system has made the internal process more beneficial., and it
has increased staff productivity. Moreover, with the BI system, the university has been able to
save money on decision-making and operational costs.
- University Administration: Interviewee 4
Internal proficiency benefits:
The use of the BI system has changed the time it takes to collect and summarize data, and it
has presented more alternatives to choose from. Therefore, decisions can be made. based on
facts. Concerning the implementation and monitoring of decisions, the BI system has
provided employees access to the data and allowed them to extract and follow up on those
decisions.
Staff productivity:
BI has changed how employees perform advanced jobs and more complex jobs than basic
data collection. It has increased their adaptability and flexibility in implementing decisions
and it has developed their sense of self monitoring when they follow up on decisions.
Reduction in the cost of effective decision-making:
The BI system has saved time in the information. gathering process. It has also decreased the
costs of looking for alternatives and of following up on various decisions and their outcomes.
5.2 The influence of Qlikview on Decision-Making Process
According to the interviewees 3, 4, 5 and 7, Qlikview reduces time spent gathering
information. In summary, Qlikview fills various functions upon which university personnel
rely. Although it doesn’t directly impact the DMP, it supports it.
61
5.3 Summary of the Interviews
- Faculty of Arts and Human Science: Interviewee 1
General questions Interviewee answers
General information about the BI system at
LIU and its benefits
BI is an easy way to handle various
administration systems, such as HR
and accounting.
BI is essential because it makes information
searches fast and easy, and it is an easy way to
shape information.
Positive effect on decision –making It speeds up the time data gathering process by
helping users get data from various
departments. It also packages information
easily.
-The quality of information is increasing rapidly
-The use of information in decisions boosts the
system’s ability to make the information
more useful
Decisions before the BI’s implementation Decisions were made without any detailed data
Decisions after the BI’s implementation More decisions are and will be driven from the
actual system.
The use of BI systems in DMP It is used mainly in collecting and searching for
data and reporting for the decision makers. The
dean is not using the system but she knows that
a system exists, that she can ask open questions
about the faculty and that the system, will
provide answers.
The uses of Qlikview Controllers use Qlikview to develop
applications related to the accounting and HR
systems.
Qlikview is user driven and is used to
create applications based on the
department’s needs.
The influence of Qlikview on DMP The accounting application is an example of an influence on decision-making.
LIU Administration Office: Interviewee 3
General questions Interviewee answers
General information about the BI system at LIU and its benefits
The system takes data and puts it together in a
friendly way to help decision makers.
62
Positive effect on decision making It allows a quick start in looking for information.
It provides all users access to the information.
Decisions before the BI’s implementation Decision makers were using Excel sheets
and data mining.
Decisions after the BI’s implementation Data mining is unnecessary, as the
Information is already gathered and
summarized
The use of BI system in DMP Normally it is part of various processes. It is a
part of small and large decisions Moreover, it is
the background of some reports.
The uses of Qlikview It is a program like Excel that manages
extensive data and it is used for bookkeeping.
Qlikview’s influence on DMP The influence occurs during information gathering.
Faculty of Physics Biology and Chemistry: Interviewee 5
General questions Interviewee answers
General information about the BI system at LIU and its benefits
It is a system that helps complete the
work properly.
Positive effect on decision making A system is needed for controlling and bookkeeping because real figures should be measured.
Decisions before the BI’s implementation Decisions were made by the university boards.
Decisions after the BI’s implementation BI is a bookkeeping system that helps in
decision making.
The use of BI system in DMP Not answered
The uses of Qlikview Not answered
The influence of Qlikview on DMP Not answered
63
Faculty of Medicines: Interviewee 6
General questions Interviewee answers
General information about the BI system at LIU and its benefits
Not answered
Positive effect on decision-making Not answered
Decisions before the BI’s implementation It works more with Microsoft Excel.
Decisions after the BI’s implementation Decision-making is not changing. At the university, changes take time.
The use of BI system in DMP Management members do not utilize the tool
but they get the information from the
controllers. The uses of Qlikview It gathers information from the finance and
HR departments. With Qlikview, one can
combine the gathered data.
It provides access to reports already
completed by others.
The influence of Qlikview on DMP Calculations are made in more efficient time. The quality has to be verified. No risk is involved because the university has a skillful developer
Faculty of Education: Interviewee 7
General questions Interviewee answers
General information about the BI system at
LIU and its benefits
BI is a kind of system used to collect data from
different sources in order to present an indicator of
the business (financial or other) or to ground
decisions. It is an information technology-based
system that puts information together to present it in
an appropriate way.
Positive effect on decision making One has access to the same data throughout the
organization and they are constantly evolving. It
gives managers a good basis for decision making
The most positive thing I can see is the transparency it
provides the public sector, and the sense of security
that decisions are well founded.
Managers can rely on good information in order to
make difficult decisions
64
Decisions before the implementation of the BI Not answered
Decisions after the implementation of the BI The similarity between different parts of the
organization has increased, since everybody has
access to the same information. The reliability of the
data is better, since it is harder to manipulate data to
avoid showing certain things.
The use of BI system in the DMP It is used to present statistics and trends in order to
plan activities and necessary changes. Then
we use confirmed data to evaluate results
afterward.
The uses of Qlikview Qlikview is a system that collects data from the
administrative systems and presents reports and
statistics afterward. It is used to get information about
student volumes, and personnel costs and to collect
financial data from the time before 2017, since we
implemented a new economic information technology
system that doesn’t have historical data loaded
The influence of Qlikview on the DMP Decisions are more well-grounded and have a
higher quality than before. Also, decisions are
easier to follow-up with afterward.
65
Faculty of Arts and Philosophy: Interviewee 2
General questions Interviewee answers
General information about the BI system at
LIU and its benefits
It is an easy way to gather information and become more informed for decision-making
Positive effect on decision-making There are no changes after using BI systems.
Decisions before the implementation of the BI It relied on the history of decisions
Decisions after the implementation of the BI The decision regarding the budget for example is a mixture of history. Looking into the year that proceeds and the information statistics are very important. We rely much on the past history.
The use of BI system in the DMP I’m not just using the BI system to receive the Information
The uses of Qlikview
The influence of Qlikview on the DMP
Qlikview is not used to buy decision makers
such as deans; rather, they see the results from
the system that are represented in figures and
diagrams.
Compared to other companies what comes from
systems like Qlikview is not that transparent
because we saw many economic data.
It has an influence on the process of decision-
making.
66
LIU Administration Office: Interviewee 4
General questions Interviewee answers
General information about the BI system at LIU
and its benefits
It is an easy way to get information, rather
than going to the host system such as the
business system or HR.
It is easy to present things and understand the
information
Positive effect on decision making Decisions will be better if there is a lot of information present.
Decisions before the implementation of the BI Not answered
Decisions after the implementation of the BI More information is available and it is easier to make decisions.
The use of the BI system in the DMP The system is used to know how many
students the university has and to know how
much money the university receives from
the government.
It is easy to follow the number of students for
example and to make decisions. It is a good
way to follow-up on decisions.
The uses of Qlikview Qlikview is used for HR, business
administration, students and so
on.
The influence of Qlikview on the DMP It is a user-friendly system, a combination of
data sources and it is easy to distribute
information. Moreover, time is reduced and
risks are reduced because we have more facts.
For quality, there are more correct figures and
data sources.
67
Power of BI Benefits Over DMP
Faculty of Arts and Human Science: Interviewee 1
Decision-Making
Process
Intelligence
phase Choice of
alternatives
phase
Choice of decision
phase
Implementation
phase
Monitoring
Internal
proficiency
benefits
It saves time. It
is a faster and
flexible process.
It takes data
from the
accounting
system and
changes the
structures to
provide new
ones. It
reduces the
administration
It is one way to
get better
information.
It is an open
source for
decision makers.
It presents
different kinds of
models that can
be produced with
the existing
processes.
BI gives us an
idea of how
our
accounting
system
functions.
It might help
people to
understand why
decisions are
made and where
they may lead.
BI is not
promoted with
the top
management.
Not
answered
68
costs. It
matches data
from the HR
system and the
accounting
system
Staff
productivity
It speeds up the
process of
reporting and it
influences its
flexibility
Not answered It changes the
speed and the
flexibility of
reporting
Not answered The
Monitoring
has increased
Reduction in
thecost of
effective decision-making
Not answered Not answered The actual DMP is somewhat speded up. The changes are not big.
There is no change.
There are moreinformed decisions.
Reduced It is not possible
to measure the
The costs was not reduced.
Costs are reduced to some extent.
Not answered Not answered
operational reduced operational costs.
costs
69
Faculty of Physics Biology and Chemistry: Interviewee 5
Decision-Making Process
Intelligence
phase
Implemen
tation
phase
Choice of
decision phase
Implementation
Phase
Monitoring
Internal
proficiency
benefits
The
system is
used to
gather
informatio
n and to
compare
between
years
Not
answered
It is a system that
compares between
years and months to
make a choice in
decisions.
It is used to spread the
information. The access
is easy to any decision
that was taken before.
Finally, there is a
system to rely on
The system improves monitoring.
This means that every
employee has access
and knowledge about
decisions
Staff
productivity
Before the
system, the
The staff
has
more
No idea In the system, it
is easy to
It is much more
efficient.
70
Faculty of Medicines: Interviewee 6
Decision-Making Process
Intelligence
phase
Implementation
phase
Choice of decision
phase
Implementati
on phase
Monitoring
Internal
proficien
cy
benefits
It is easy and fast It is easy to find
alternatives by
combining
Data
The system does not
help that much
because it
will be another
We do not
use
Qlikview to
implement
decisions
It is easy to
monitor when
there is
process Easy
access to
Data
Staff
productivit
y
The system has
changed the staff’s
productivity. The
Not answered Not answered Not answered It is
represented in
the presence of
staff becomes A
more efficient. in Monthly
gathering data in Report
a short period of time
Reduction in the Time efficient Not answered Not answered Not answered To spend
cost of effective time here
decision-making and there,
we save
Costs
Reduced
operational costs
No change Not answered Not answered Not answered Not
Answered
71
Faculty of Education: Interviewee 7
Decision-Making Process
Intelligence
phase
Implementation
Phase
Choice of
decision phase
Implementation
phase Monitoring
Internal One thing I can we can see that courses
with few students are
not efficient in terms of
costs, but that the use of
technology to reduce
time in the classroom
for our teachers can
solve these problems in
costs and these courses
can be available
anyway. If alternatives
weren’t found, I’m sure
these would no longer
be on our list of courses
Here I would The The system reminds
us about follow-ups proficiency define is the like to say that implementation
benefits relation between the more reliable of decisions
the amount of information we is more
students and the have as a basis influenced by
funds received to dares the managers culture,
to complete the to make the composition
courses we necessary of people, etc.
provide. This decisions that I’m not sure
relation can be difficult. It BI has the
determines how is often the effect that
much time the necessary to you would like.
teachers can make such
give to the decisions to
students, for achieve an
example. This effective
also leads to organization
more efficient
use of our
classrooms etc.
(reduce costs),
to give
the
students as much time as
possible instead
Staff
productivity
Not answered Not answered Not answered Not answered Not
Answered
Reduction in
the
cost of
effective
decision-
making
Not answered Not answered Not answered Not answered Not answered
Reduced
operational
costs
Not answered Not answered Not answered Not answered Not
Answered
72
University Administration: Interviewee 2
Decision-Making Process
Intelligence
phase
Alternatives
phase
Choice of
decision phase
Implementation
phase
Monitoring
Internal proficiency
Helps the organization to
Many alternatives are
We not only use data from
A short time that I hold this
It is the budgeting
benefits react for
improvement by
gathering
information and
providing data
shown Qlikview to make
decisions but also
from the history to
make decisions more
transparent.
responsibility.
We are more
informed
about the
information
needed
which do the follow-up
on how things are working
Staff
productivi
ty
It increases the staff
productivity Not answered Not answered Not answered Not answered
Reduction in the
cost of effective
decision-
making
Not answered Not answered Not answered Not answered Not answered
Reduced operational costs
Not answered Not answered Not answered Not answered Not answered
73
University Administration: Interviewee 4
Decision-Making Process
Intelligence phase
Implementation phase
Choice of decision phase
Implementation
phase Monitoring
Internal
proficiency benefits
It came with a
change
Not answered Not answered Not answered Not
answered
Staff productivity
More productivity
Not answered Not answered Not answered Not answered
Reduction in the cost of effective
decision-making
Reduction of
costs
Not answered Not answered Not answered Not
answered
Reduced operational costs
We could save money
Not answered Not answered Not answered Not answered
University Administration: Interviewee 3
Decision-Making Process
Intelligence phase
Implementation phase
Choice of decision phase
Implementation phase
Monitoring
Internal
proficiency
benefits
It saves time
and
summarizes
the
results and data
There are
more
chances to
choose
alternatives
People who are
following up
with students
can decide with
regard to
courses and so
on. It is more
based on fact
and not
guessing. Thus,
it is more
objective than subjective
Instead of
spending time,
users know the
results from
using Qlikview.
We extract
and check
through
the BI
system.
74
Staff productivity People have
time to do an
advanced job
for the data
collection
instead of just
doing the
basics. data
collecting.
People can do
more complex
tasks.
Not answered Same answer for
internal proficiency
Adaptability and more flexibility
Self-
monitoring.
People
perform
their
monitoring
themselves
Reduction in the
cost of effective
decision-making
Time is saved
in looking for
information
Decrease the
costs in
searching for
alternatives.
Alternatives
are based on
facts
Not answered The follow-up of
different
decisions such
as following up
on the outcome
of the finance
department.
Reduced
operational costs
It saves
time.
Not answered The information
is increasing
Not answered Not
answered
As far as the interviewees’ opinions are concerned regarding how the BI system has changed
the DMP at LIU, the general answers provided by the interviewees confirm that the BI system
has an influence on the DMP at LIU.
We conclude that the BI system has an influence over DMP. Moreover, Qlikview as the BI
tool used at the university works in favor of its users.
After presenting a summary of what was said during the interviews, we will present a
theoretical framework to show how the BI system has changed the DMP at LIU. In the
framework, we presented the process of decision-making according to Simon (1997) and
Huber (1980) and the BI benefits according to El Bashir et al., (2008).
75
Figure 25: The Thesis Outcomes
Framework for the Power of Business Intelligence (BI) On the Decision-Making Process
(DMP) in Linkoping University
The results have shown that for the internal proficiency benefit, in the whole process of
decision-making, the data gathered from the system enable users to save time, to get more
data and to have an easy spread of and access to information. Comparing the outcomes to the
literature, the results are similar. The authors (Azvine et al., 2006; Watson & Winxon 2007;
Hocevar & Jaklic, 2008) agree on the fact that BI is a system wherein users can understand,
capture and access data.
As far as the reduced operation costs are concerned, the results showed that the information is
increasing with reduced costs. In comparison with the literature, Eckerson (2003) state that
with the use of BI system, there are tangible and intangible benefits represented in cost
savings. Moreover, Isik et al. (2013) talk about value and profitability.
For the reduction in costs, the results showed that with the use of the BI system, there is a
reduction in costs with regard to collecting data and choosing between alternatives. When
compared to the literature, there are similarities. Wiliams and Williams (2003), Turban et al.
(2011) and Eckerson ( 2003) stated that the use of the BI system increases the revenue and
reduces costs. In the same context El Bashir et al. (2008) talk about productivity enhancement
as the cost reduction.
76
As far as the staff productivity benefit is concerned, the results
showed that productivity is increasing throughout the DMP. In
comparison with the literature, we found similarities. Turban et al.
(2011), Eckerson (2003), and Hocevar and Jaklic (2008) talked about
work efficiency.
6. Conclusion
In this chapter, a concluding analysis and an answer to the thesis research question are
provided. Moreover, a suggestion for future studies and the limitations confronted while
dealing with the research paper are presented.
The aim of the research paper is to answer the question, “How have BI benefits changed the
DMP at LIU?” Most of the sources used claim that the BI system has an influence on the
DMP in general with a limited research on its influence on HEI. Our research at LIU revealed
that the BI system benefits have a positive influence on the DMP. Qlikview as a BI tool
enhances this change.
On the one hand, BI is an important system at LIU that is used to collect and gather data for
decision makers and as a follow-up system. On the other hand, Qlikview acts as a developer
of applications, a follow up system and a generator of data.
6.1 Answers to the Research Question
How have BI system benefits changed the DMP at LIU? The analysis part showed that the BI
system and Qlikview as a BI tool are beneficial to LIU’s DMP.
The changes that occurred include the following: The amount of data collected in a short time,
the availability of multiple information, the reliability of data and reporting for decision
makers, cost reduction and efficiency and the access to information by all the users.
77
6.2 Thesis Contribution and Implications for Future Practice
The research paper will contribute to the theory as follows:
The study is new as it is related to LIU. It studied the changes that have occurred in the whole
process of decisionmaking, and the theoretical framework can be used for further studies in
the domain of HEI in Sweden or elsewhere.
For the implication for future practice, the thesis shows the benefits of implementing the BI
system in an organization and especially in the HEI sector. As a result, organizations can take
this thesis as an example of how the use of BI will bring many benefits.
6.3 Suggestion for Future Work
Throughout the interviews that we conducted, we found that the BI system at the university is
a system through which developers develop many applications according to the needs of
departments. As an example, Raindance is a financial system that was integrated into the
university in January 2017. Another investigation can be made for the Raindance system and
its power and usefulness toward finance and economics. Moreover, a quantitative method to
collect data can provide further insight into how the BI system influences the DMP at the
university.
6.4 Limitations
This work contains some limitations. First, the thesis is based on a single case of LIU that is
situated in Sweden. As a public institution, the study was based on higher education in the
public sector. Second, the thesis talks about the BI system as a mixture of technical functions.
In the thesis we talked about the BI architecture but not with a deep explanation regarding its
technical functionalities and the focus was on its functions regarding the DMP. Third, we did
not talk about a special type of decision; rather, we talked about the process of decision-
making as a whole. Moreover, the study is limited to one Swedish university.
The problem that we faced during our research is that the internal documents were in Swedish
with no available translation. Moreover, some questions of the interview were not answered
by the interviewees. Moreover, some decision makers did not answer our request for an
interview, whereas others excused themselves due to their full schedules.
78
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8. Appendices:
Questionnaire:
Can you tell us something about yourself? (Name, job position, tasks,
background, etc.) General questions:
1. How can you define business intelligence?
2. For how long has the company been using business intelligence?
3. How many employees have access to the information from the business intelligence system?
4. Is there any business intelligence system that the faculty uses?
5. If yes what is it and from when it has been used?
6. Can you describe how decisions were taken before the implementation of business intelligence
?
7. Can you describe how decisions are made after the implementation of business intelligence
system?
8. How does the company use business intelligence in the decision-making process?
9. What are the benefits of business intelligence for the university?
10. What are the positive effects of business intelligence for the decision-making process?
Questions for the decision-making process and the business intelligence benefits:
Internal efficiency benefits
- Q1: How have the internal efficiency benefits of business intelligence changed the process of
gathering and searching for information?
- Q2-: How has the internal efficiency benefits of business intelligence changed the
development of alternatives?
- Q3-: How has the internal efficiency benefits of business intelligence changed the choice
of decisions?
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- Q4: How has the internal efficiency benefit of business intelligence changed the
implementation of decisions?
Q5: How has the internal efficiency benefits of business intelligence changed the
monitoring for decision- making?
Staff productivity benefit
- Q6: How has the staff productivity benefit of business intelligence changed the process of
gathering and searching for information?
- Q7: How has the staff productivity benefit of business intelligence changed the development
of alternatives?
- Q8: How has the staff productivity benefit of business intelligence changed the choice of
decisions?
- Q9: How has the staff productivity benefit of business intelligence changed the
implementation of decisions?
-
Q10-: How has the staff productivity benefit of business intelligence changed the monitoring for
decisions?
The reduction in the cost benefit
- Q11: How has the reduction in the cost benefit of business intelligence changed the process of
gathering and searching for information?
- Q12: How has the reduction in the cost benefit of business intelligence changed the
development of alternatives?
100
Q13: How has the reduction in the cost benefit of business intelligence changed the choice of
decisions?
- Q14: How has the reduction in the cost benefit of business intelligence changed the
implementation of decisions?
- Q15: How has the reduction in the cost benefit of business intelligence changed the
monitoring for decision-making?
The reduced operational costs benefit
- Q16: How have the reduced operational costs benefit of business intelligence changed the
process of gathering and searching for information?
- Q17: How have the reduced operational costs benefit of business intelligence changed the
development of alternatives?
- Q18: How have the reduced operational costs benefit of business intelligence changed the
choice of decisions?
- Q19: How have the reduced operational costs benefit of business intelligence changed the
implementation of decisions?
- Q20: How have the reduced operational costs benefit changed the monitoring for decision-
making?
101