Information quality as a critical success factors of BI 

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Methodology

“A researcher’s methodological approach, underpinned by and reflecting specific onto-logical and epistemological assumptions, represents a choice of approach and research methods adopted in a given study” (Hay, 2002). Principally, the progression of any re-search is based on an inclusive plan for the activities necessary to expand the knowl-edge. Therefore, the research should be started with clear problem discussion, followed by the theoretical reference of it, to construct a proper research design for expanding knowledge. Finally, the last step is data collection followed by data analysis to derive results from the collected data. This is the summary of the procedures used to organize the research process. The following parts will consider different research methodolo-gies, and motivate the reason of selecting particular methods.

Research approach

While doing a research project, it is crucial to choose between different researches ap-proaches that would be best suit to the research. Understanding to these approaches is fundamental to enhance the efficiency of the study. Moreover, the extent to which we are clear about the theory at the start raises an important question concerning the design of research project. This is whether research should use inductive or deductive approach (Saunders et al., 2007).
Inductive research is approach in which theories are emerged from specific observation. In deductive approach, the explicit expectations of a hypothesis are built base on general principle: we commence from existing theory and then find its confirmation. Inductive research is open-ended and exploratory mainly in the beginning. Deductive research is specific in nature and is involved testing or confirming hypothesis (Srivastava et al., 2011). Figure 2-1 illustrates the main points of differences and steps involve in each ap-proach. In fact, all studies that have taken place in different contexts are a continuous cycling of induction and deduction approaches and combination of both (Srivastava et al., 2011; Saunders et al., 2007).
Figure 2-1: Inductive vs. Deductive (S. M. Aqil Burney, 2008)
Initially we decided to conduct a deductive approach, so we started with an in-depth lit-erature review to find a proper theoretical framework to describe influences of IQ issues on decision-making and utilize it as guidance to collect data and test hypothesis. Since our theoretical framework is not comprehensive enough to be tested through data collec-tion and yielding a sufficient answer to our research question so we decided to employ it as guidance for developing interview questions to observe these influences and ending with a conclusion or a theory (inductive rezoning). Also starting a kind of inductive re-search from a theoretical perspective link our research into the existing body of knowledge in our subject area, help us to get started and provides us with an initial ana-lytical framework (Saunders et al., 2007).
To sum up, this study is neither pure inductive nor pure deductive. It inherited compo-nent from both approach, but mostly toward inductive. We started with literature review and we could only figure out 13 dimensions that affect quality of information (figure 3-4) but not influences of these issues on business performance. Therefore, this theory used to investigate and identify information quality issues in our selected case. The the-ory provided us a prospective during empirical data collection and analyzing quality is-sues in the company. Moreover, after the empirical data collection and identifying IQ issues in the case, the inductive reasoning used to categorize data and discover influ-ences of identified IQ issues on decision making which has not been considered in the theoretical framework. According to Figure 2-1, we tried to commence with a theory (left side of picture), to deduce the information from the sample. The theory used to ob-serve and investigate IQ issues. Then it became somewhat inductive given that the in-terviews functioned as the step “observation” of the right side in Figure 2-1, to recog-nize pattern and identify relationships between collected data to come up with a theory about influences of IQ issues on decision-making and business performance. Such ap-proach enabled us to present subjective analysis with the help of real life example.
However, this developed theoretical position then need to be deductively tested for its applicability through subsequent data collection and analysis, which is going to be ad-dressed in ‘Discussion’ section later as a suggestion for further work. This implies the continuous cycling of induction and deduction approaches highlighted by Srivastava et al., (2011) and Saunders et al., (2007).

Research design

Research purpose

In order to formulate the research question, we necessarily started to think about the re-search purpose. The categorization of research purpose most often suggested in litera-tures is the one of exploratory, descriptive, and explanatory (Saunders et al., 2007).
The purpose of descriptive research is to draw an accurate profile of individuals, events, or circumstances (Robson, 2002). Causal relationship between variables can be estab-lished by explanatory research. The stress is on examining a circumstance or a problem for explaining the association between variables (Saunders et al., 2007). An exploratory research, which is adopted for this thesis, is valuable way of understanding what is oc-curring; to look for new insight; evaluate events with asking questions (Robson, 2002). There are three leading methods of carrying out exploratory study; search of literature, interviewing expert in the context of research, and conducting focus group interviews (Saunders et al., 2007). In addition, exploratory research is generally carried out, if there is no former theory/ model to lead us or if we wish to have, some initial idea to find out the problem to be studied (Srivastava et al., 2011).
The purpose of this research is to design an exploratory study. Since we did not know much enough about the situation, which was influences of different dimensions of In-formation quality on decision-making and yet we wanted to have some assessment.
However, we could not find Information, theory, or model available as to how same problem was solved in the previous researches. Therefore, through the extensive litera-ture review we tried to create a framework that would lead us in gathering relevant em-pirical data by conducting focus group interview with expert BI users/ implementers. Through the exploratory study, we focused on understanding more about the topic and identifying variables that could be cause of low quality of information and influences of these variables on decision-making.

Research strategy

In this part, we concentrate our attention to the research strategy that is adopted in this thesis. According to the Yin (2003) for exploratory, descriptive, and explanatory study, we can utilize each of the research strategies. Some of these strategies obviously fit to deductive approach, and some of them to the inductive approach. In some cases, allot-ting strategies to one approach or another is unduly oversimplified. The selection of re-search strategy is directed by research question and objective, the degree of existent knowledge, available time and resources, in addition to philosophical approaches (Saunders et al., 2007). According to Saunders et al. (2007), different strategies that can be employed include experiment, survey, case study, action research, grounded theory, ethnography, and archival research.
Robson (2002) specifies case study, which is employed in this research, as a strategy for conducting research, which includes an empirical study of a specific existing events within its real world context by means of different source of evidence. The case strategy was of specific interest to us, since we desired to obtain a rich perception of the field of the research and processes being enacted (Morris and Wood, 1991). Additionally, case study has noticeably capability to generate responses to the question ‘Why?’, ‘What?’, and ‘how?’ therefore it is employed in this study (Saunders et al., 2007). However, an-swers to ‘What?’ and ‘how?’ questions of this study predisposed to be more the concern of survey strategy (Saunders et al., 2007) but due to the lack of time and resources it was somehow impossible to conduct a survey study in industry. Data collection tech-niques used for this strategy may be different and are possibly to be utilized in combina-tion. They may involve, like interview, observation, and questionnaire (Saunders et al., 2007). Also, according to Yin (2003) case study strategy is suitable for this research since the form of research question is ‘how?’ and the focus was on contemporary events and it did not require control of behavioral events (figure 2-2).
The selected data collection technique according to the research strategy is focus group interview, which is going to be explained in more detail in ‘data collection and analysis’ section. Multiple sources of evidence, instead of relying only on interview, and using triangulations logic could improve the validity of this research. However, due to privacy issues in the company we could not achieve this. This matter is further explained in ‘Validity’ and ‘Discussion’ section.
Yin (2003) differentiates between four case strategies based on two dimensions: single case vs. multiple cases; Holistic case vs. embedded vase (Figure 2-3). Our strategy in this study is to perform a single-embedded case study. We were aware that single case study needs a strong justification for a critical, unique, or representative case in testing a well-formulated theory (Yin, 2003). Therefore, we desired to conduct multiple-cases to study more than one company. In this way, we could institute if the findings of the first case happen in other cases and, consequently, the requirement to generalize from these findings through replication logic (Saunders et al., 2007; Yin, 2003). Although, multi-ple-case study could not be achieved, since companies either refused to have an inter-view or did not implement BI system. Therefore, we decided to investigate the only company that agreed to have an interview with us, and consequently following single-case strategy.
In addition, embedded dimension is adopted since this research is interested in examin-ing more than a unit in the organization (Saunders et al., 2007). In view of the fact that various units of organization involve in decision-making; so, this thesis was attended to the business team who use BI technology for assessing business environment, so we could investigate influences of IQ on business environment. In addition, we considered the BI unit of the organization to investigate information quality issues and possible causes of failure in delivering high quality information. Furthermore, it must be notice that, even though the interviewed business analyzers are part of BI unit as a liaison be-tween business and IT and their main responsibility is to work with business team, so we consider them as another sub unit. This justifies our embedded view.
The last concern in this section is to answer why retail industry. Tapscott (2008) claims that the retail industry was one of the first to implement BI system to facilitate collect-ing and integrating suppliers and consumers’ data. Data driven decision-making is criti-cal for retail industry to appropriate decision about price, assortment, replenishment etc. Competition in this industrial category is becoming ever rougher as the quick product cycles, and changing consumers’ preferences continue to change many segments (Tapscott, 2008). Therefore, mass quantity of data regarding suppliers and customers need to be well organized and met acceptable level of quality to be able to make appro-priate decision in timely manner and maintain competitiveness in the market place. Since they have to deal with large amount of data, regarding different product catego-ries/ brands, suppliers, and customers, the management of information would be a com-plex and sensitive task. This complexity can also increase probability of encountering information quality issues and thereby failure to meet market demand (Tapscott, 2008). Therefore, it is necessary to investigate the reasons of IQ failures in BI system and their corresponding impact on their performance to increase awareness about importance of IQ and have an initial idea about the problem to be further studied in future. This im-plies an exploratory case study.

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Method

Ordinarily, one of the primary goals of a research is attempting to search out new in-formation and knowledge that assist us to realize and elucidate different phenomena. To facilitate collection of such information Either Qualitative or Quantitative techniques or combination of both can be employed (Creswell, J. W., 2009).
Qualitative Methodology, which is adopted in this study, intend to collect an in-depth understanding of thoughts, activities, value systems, concern, incentives, and society as well as the grounds that govern such things (Denzin & Lincoln, 2005). The qualitative method considers the why and how of decision-making, as well as what, where, when. For this reason, more often smaller but focused samples are considered necessary than large samples (Denzin & Lincoln, 2005). Typically, qualitative methods generate in-formation merely on the specific cases studied, and any more generalization is only propositions (informed assertions). After that Quantitative, methods can be adopted to look for empirical evidences for such research hypotheses (Denzin & Lincoln, 2005). However, Yin (2003) believes that qualitative study can also be generalized through replication logic and analytic generalization instead of statistical generalization.
As shown in Figure 2-4 in choosing the research methods the researchers have more than one choice. It is possible to either use single data collection technique and corre-sponding analysis procedure, known as mono method or use more than one data collec-tion technique and analysis procedure to answer research questions that is referred as multiple methods (Saunders et al., 2007).
This research adopted qualitative mono method, which is compatible with the purpose, strategy, and available time for this research as they are discussed in previous sections. By following the qualitative approach, we seek a wide understanding of Business Intel-ligence experts’ interpretation and perceptions about dimensions of information quality that must be considered, causes of information quality issues and influences of those dimension on making intelligent and informed decision. This achieved by means of se-lecting a small sample of BI experts (both expert users and technical people). The aim was to interview professionals who are able to provide us with more in-depth and com-prehensive information.

Time horizon

Two sorts of time horizon that must be concerned for designing a research project in-clude cross-sectional studies and longitudinal studies. The former is often referenced as a “snapshot” since the research is conducted at a specific time. This technique is usually employed for research projects that have a time limitation. The latter is so called also as the “diary” dimension, which studies individuals or events over time. The main question in longitudinal studies is “Has there been any change over a period of time?” (Saunders et al., 2007). Since the objectives and research question aim to study issues related to IQ in past and current time and do not require to observe behaviour of individual or event over a period of time, so the time horizon adopted in this study is the cross-sectional horizon. It means that, the attitudes of the employees and changes over time are not concern of this study, and the research is “snapshot”.

Literature sources

Literature reviewing is considered as a fundamental ingredient of any research, which can provide related information regarding others works in a certain topic of interest. Lit-erature sources can be divided into three groups: primary, secondary, and tertiary (Fig-ure 2-5) (Saunders et al., 2007). The first occurrence of a work is called Primary litera-ture sources such as reports, and thesis. Later publication of primary literature such as books and journals are Secondary literature sources. These are easier to find than pri-mary literature since they are better covered by the tertiary literature. Tertiary litera-ture sources also called search tools, such as indexes and abstracts as well as encyclo-pedias and bibliographies are intended either to assist to find primary and secondary lit-erature or to introduce a topic (Saunders et al., 2007).
To review the related literature in our topic, we used both primary and secondary sources include the books, articles, journals, thesis, and other materials, which were lo-cated through the tertiary sources especially indexes and bibliographies. At first, centre of attention was to have a comprehensive understanding of the terms include, Business Intelligence (BI) and Information Quality (IQ). Through seeking out the main references connected to these terms, we could formulate our research questions and the way of conducting the research.
The process of searching out literature sources that were followed to acquire relevant in-formation regarding to the concerned terms and topic can be summarized as following steps:
1. identifying the keywords;
2. seeking out for books, articles, and other sources via the Google and database of the university’s library to get primary understanding about the subject under study;
3. refining and limiting the keywords and search criteria to concentrate only on the references that could be more useful and relevant to the research questions;
4. Reading, assessing, and sorting the references according to their relevance and input value to our thesis;
Reviewing the previous studies related to our topic gave us:
A comprehensive knowledge from different perspectives to address the research problem
Connect our work to the work that was done by others
Develop theoretical framework and adequate knowledge to guide the empirical data collection
Raise new research question and direction for further work in future.
In addition, considering various viewpoint and concerns to address the problem can produce different results.

Data collection

Indeed, to achieve the purpose of any research, and finding the answer of the research questions, it is necessary to gather relevant data. Thereafter, it would be possible to con-firm the hypotheses, or provide answer to the research question(s). This can be achieved by considering the collected data, to provide credibility to the result.
Furthermore, to become certain that there is a concrete ground for the research, it is cru-cial to clarify which type of data is required, ‘primary’, or ‘secondary’. Primary data are, data collected specially for the research project being undertaken; while secondary data are data were originally collected for some other purposes (Saunders et al., 2007). Besides, a variety of data collection techniques can be employed, such as question-naires, interviews, and observations. Such techniques are utilized to collect essential in-formation to achieve the purpose of the research (Saunders et al., 2007).
In this thesis, we only collected primary data through focus group interviews. Prior to the data collection Literature reviews gave us a foundation for studying and analyzing the other related work in field of IQ and BI and a framework was developed (figure 3-4) to guide the interview with Business Intelligence users and BI implementers.

Selection of respondents

The idea of conducting a qualitative approach is to make it feasible to obtain a deep comprehension about the context. Additionally, it offers as much information as possi-ble to reach this comprehension. Therefore, the chosen respondents should have been met certain condition as follow:
Adequate familiarity, experience, and understanding in the context of BI practice They must be in a position of decision making in organization, to be qualified to answer questions regarding user perspectives about influences of information
quality on decision-making.
In addition, in order to investigate information quality issues and their possible causes from developer perspective chosen interviewees must have adequate ex-perience and knowledge in development and implementation of BI systems.
Furthermore, BI must have already been applied in the selected company and employed in carrying out jobs and tasks.
Through realizing such situations, the empirically collected data could provide a sol-id foundation to find out various opinions regarding the importance of information quality, issues affecting quality of information and the impacts of these dimensions on decision making.

Table of contents :

1 Introduction
1.1 Background
1.1.1 Information quality as a critical success factors of BI
1.2 Problem discussion
1.3 Research objectives and questions
1.4 Interested stakeholders
1.5 Delimitation
1.6 Definitions
2 Methodology
2.1 Research approach
2.2 Research design
2.2.1 Research purpose
2.2.2 Research strategy
2.2.3 Method
2.2.4 Time horizon
2.3. Literature sources
2.4 Data collection
2.4.1 Selection of respondents
2.4.2 Interviews
2.5 Analysis
2.5.1 Transcribing qualitative data
2.5.2 Qualitative analysis
2.6 Research credibility
2.6.1 Reliability
2.6.2 Validity
3 Theoritical frame of reference
3.1 Business intelligence
3.1.1 History
3.1.2 Deinition of BI
3.1.3 components of BI
3.2 BI support for decision making
3.3 Definition of data and information quality
3.3.1 Information quality
3.3.2 Data quality
3.3.3 Relationship between data and information
3.4 Evaluation of information quality
3.4.1 Framework of Strong et al. (1997)
3.4.2 Framework of Lui and Chi (2002)
3.4.3 Framework of Helfert et al. (2002)
3.4.4 Result of information quality assessment
4 Empirical findings
4.1 About the BI unit
4.1.1 Business analyzers
4.1.2 Metadata team
4.1.3 Data warehouse team
4.1.4 OLAP team
4.1.5 Information delivery team
4.2 Areas and benefits of using BI system
4.3 BI architecture
4.4 Reasons and affects of poor information quality (BI developer perspective)
4.5 influences of poor information quality (Business perspective)
5 Analysis
5.1 Areas and benefits of using BI system
5.2 Issues affecting the quality of information
5.3 influences of poor information quality (BI developer  perspective)
5.4 influences of poor information quality (Business perspective)
5.5 importance of documentation (additional analysis)
5.6 summary of the analysis
6 Conclusion
7 Discussion
List of references

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