The challenges of today's economic climate and the highly competitive market place make it essential for organisations to continuously measure and monitor their performance to identify areas for optimisation and improvement. It is widely recognised that the strategic application of business intelligence (BI) is a key contributor to unlocking the business value of information across the organisation. Timely access to pertinent information, which can be easily assimilated by business users, leads to better business decisions and ultimately improves business performance (De Voe & Neal, 2005; Evgeniou & Cartwright, 2005; Lönnqvist & Pirttimäki, 2006). BI is not a new concept and in studying the available literature it is clear that several consistent best practices and guidelines are available to organisations to help them avoid the potential pitfalls (Rogers, McDonald, & Brown, 2005; Watson & Wixom, 2007). It is also well documented in the literature that BI is recognised by management and senior executives as an essential component to gain a competitive advantage in the market place. The significant amounts that are being invested in BI by industry testify to this. Further support for this notion is found in the fact that implementing BI has been a top priority for CIOs and CFOs for several consecutive years. (Eckerson, 2008; Evgeniou & Cartwright, 2005; Rogers et al., 2005). However, in studying the literature it becomes evident that even though companies have been spending large amounts on their BI investments, most organisations have failed to achieve a culture of pervasive BI. Instead of having a BI strategy, most companies have multiple BI projects on the go and are desperately trying to standardise in order to overcome the information silo's that have been created by the various business departments within the organisation (Davenport, 2006; Rogers et al., 2005; Williams & Williams, 2004; Williams & Williams, 2007). The CIO of a consumer products company in South Africa stated in the 2009 IBM CIO survey that "Business is not yet fully exploiting the business intelligence that is available" (The new voice of the CIO, 2009). In another recent survey, conducted by TDWI, it was found that of the entire population of users that were given legal access to a BI tool, only 24% of these users were actively making use of these tools in their decision making (Eckerson, 2008). Successful adoption and usage means that BI forms an integral part of the decision making activities that occurs within the business. In other words, the pervasive use of BI implies a culture of fact based decision making that exists across all levels of the organisation. It also indicates that the outcomes of these decisions are continuously integrated with the existing information at hand, thereby adding further value to the information. However, according to the latest Gartner report for BI platforms most organisations "fail to link BI content with the decision itself, the decision outcome, or with the related collaboration and other decision inputs" (Davenport, 2006; Sallam, Hostmann, Richardson, & Bitterer, 2010). So, with all the proven benefits that can be derived by adopting pervasive BI; why are only a small percentage of organisations successful in establishing a fact-based decision making culture? And what can be done differently to promote the pervasive use of BI within organisations? The purpose of this study is to gain deeper insight into the factors that influence continued adoption and usage of BI, specifically in the South African market place. Ideally the outcomes of this study will benefit organisations by providing better insight into how their BI investment can be used optimally to facilitate fact-based decision making that will result in improved performance for the organisation.
Objectives The objective of the proposed research project is to determine the factors that can assist South African companies to be more successful in achieving pervasive use of BI across the organisation. This study will comprise of research into the following areas: Examine the factors that influence continued adoption and usage of BI within organisations. Evaluate and compare the current state of BI adoption and usage in South Africa against these findings. Describe the factors and possible reasons behind South African companies' success or failure to achieve pervasive use of BI within the organisation.
Research Philosophy The research will adopt a positivist research philosophy since the aim of this study is to objectively examine and describe the factors that influence the pervasive use of BI within South African organisations (Saunders, Lewis, & Thornhill, 2009).
Approach The research will take a deductive approach to the theory as it will commence by establishing a theoretical framework based on the available literature and then collecting data that will be analysed and measured in context of this framework (Saunders et al., 2009).
Purpose The purpose of this research is both descriptive and exploratory as it will first attempt to portray an accurate profile of the factors that influence continued adoption and usage of BI within organisations. Secondly, it will then focus on South African organisations in particular by studying the usage of BI in the South African market place in relation to these findings and try to ascertain the factors that influence the pervasive use of BI within South African organisations. Based on the outcomes of this study the researcher hopes to gain new insight into factors that influence the continued usage and adoption of BI in South African organisations (Saunders et al., 2009).
Research Strategy As a first step, a critical literature review will be conducted as part of the deductive approach to the research in order to develop a theoretical framework for the proposed study. The primary data collection will be in the form of a survey which will comprise of a questionnaire that will be distributed to BI users and practitioners. The questionnaire will gather some demographic data, but will mainly focus on gathering data around the current state of BI usage and adoption in South African companies. The questionnaires will be supplemented by semi-structured qualitative interviews in order to gain further insight into the factors influencing the pervasive use of BI. This mechanism will allow the researcher to ask additional questions based on the interviewee's responses to the questions, as well as give the interviewees the opportunity to elaborate further on their responses (Saunders et al., 2009). This study therefore uses a mixed method that involves quantitative as well as qualitative techniques to collect data (Saunders et al., 2009).
Timeframe The timeframe of this research will be cross-sectional as it will be studying the factors influencing the pervasive use of BI at a particular point in time (Saunders et al., 2009).
Survey Instruments A survey-based questionnaire and semi-structured interviews will be used to collect data. The researcher is considering using expectation-confirmation theory and an augmented version of technology adoption model (TAM) as a possible model for developing the questions for the survey (Bhattacherjee, 2001; Saunders et al., 2009; Yi, Jackson, Park, & Probst, 2006). However, further research into the various models and construction of effective questionnaires is required before the survey instrument can be designed and finalised. The semi-structured interviews will comprise of a list of themes and questions to achieve some degree of standardisation. The interviews and questions may vary in terms of order and follow up questions depending on the nature of the interview and the interviewee's responses to the questions.
Target population Business users across all levels of organisation will be targeted. The aim is to include users at executive, tactical and operational levels within the organisation as well as BI practitioners responsible for implementing BI solutions.
Sample The researcher is considering a non-probability sampling technique based on the snowball sampling method for this research project. The aim is to survey approximately 100 cases and interview 10 to 15 business users and BI practitioners (Hart & Henriques, 2006; Saunders et al., 2009). Potential candidates for participation will be contacted telephonically or via email and invited to participate in the study. The survey-based questionnaires will be distributed electronically to willing participants with a letter explaining the purpose and objectives of the survey. Following up on the questionnaires will be done via phone calls or emails to ensure a high level of returned responses. The interviews will preferably be done face-to-face using a voice recorder to ensure all details of the conversation can be reviewed thoroughly at a later stage. If this is not possible, video conferencing or telephone will be considered as alternative methods for conducting the interviews.
Data Analysis Quantitative and qualitative analysis techniques will be applied to analyse the data. A statistical tool, SPSS, will be used for detailed statistical analysis of the data.
Ethics and confidentiality Participation in the survey-based questionnaire and interviews will be on a voluntary basis. The purpose of the study will explained to participants verbally or in the form of a cover letter. Approval has already been obtained from Synergy Business Intelligence that their customers may be contacted to participate in the study. Prior to contacting potential participants, approval will be obtained from their respective organisations permitting their staff to participate in the study. All respondents' details and as well as information about their organisations will be treated as strictly confidential and will not be published as part of the study.
Timescale The following dates for deliverables have already been predefined by the UCT IS department:
DELIVERABLES 24 March Submit Written Proposal 25 Mar - 04 May Meet with Mentor 05 May Submit Literature Review 10 May - 22 Jun Meet with Mentor 23 Jun Research Design Hand In 25 Jun - 24 Aug Meet with Mentor 25 Aug Present Technical Report 26 Aug - 28 Sep Review &finalise Technical Report 29 Sep Technical Report Hand In
Preliminary Bibliography Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370. Davenport, T. H. (2006). Competing on analytics. Harvard Business Review, 84(1), 98-106. De Voe, L., & Neal, K. (2005). When Business Intelligence equals business value. Business Intelligence Journal, 10(3), 57-63. Eckerson, W. W. (2008). Pervasive business intelligence: Techniques and technologies to deploy BI on an enterprise scale. Retrieved March 7, 2010, from http://www.corda.com/pdfs/tdwi-pervasivebi-report-july08.pdf. Evgeniou, T., & Cartwright, P. (2005). Barriers to information management. European Management Journal, 23(3), 293-299. Griffin, J. (2007). Putting the business back into Business Intelligence initiatives. DM Review, 2, 15. Hart, M., & Henriques, V. (2006, June 25-27). On the influence of facilitating conditions of DSS usage. Paper presented at the Proceedings of the 36th SACLA Conference, Cape Town, South Africa. Howson, C., (2008). Successful Business Intelligence: Secrets to Making BI a Killer App. Columbus, OH: McGraw-Hill. Lönnqvist, A., & Pirttimäki, V. (2006). The measurement of Business Intelligence. Information Systems Management, 23(1), 32-40. Petrini, M., & Pozzebon, M. (2009). Managing sustainability with the support of business intelligence: Integrating socio-environmental indicators and organisational context. Journal of Strategic Information Systems, 18(4), 178-191. Pierce, D. (2007). Cultivating high performance through information management findings from the Accenture CIO survey 2007: Business intelligence. Retrieved March 7, 2010, from http://www.accenture.com/NR/rdonlyres/B500F42A-36A3-469E-87E2-9439DD8AB44E/0/3660_AIMSCIOSurvey_BIfindingsfinal.pdf. Popovic, A., Turk, T., & Jaklic, J. (2006, April 16). Business value of business intelligence systems lies in improved business processes. Paper presented at the 5th WSEAS International Conference on Applied Computer Science, Hangzhou, China. Rogers, S. B., McDonald, K. D., & Brown, V. A. (2005). CFOs positioned to drive BI integration. Financial Executive, 21(7), 46-49. Sallam, R. L., Hostmann, B., Richardson, J., & Bitterer, A. (2010). Magic quadrant for business intelligence platforms. Retrieved March 7, 2010, from http://www.gartner.com/technology/media-products/reprints/oracle/article121/article121.html Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students (5th ed.). London: Pearson Education/Prentice Hall. The new voice of the CIO: Insights from the global chief information officer study. (2009). Retrieved March 7, 2010, from http://www-935.ibm.com/services/us/cio/ciostudy/download-02.html Watson, H. J., & Wixom, B. H. (2007). The current state of business intelligence. IEEE Computer Society, 40(9), 96-99. Williams, S., Williams, N., & Consulting, D. P. (2004). Assessing BI Readiness: The key to BI ROI. Business Intelligence Journal, 9, 15-23. Williams, S., & Williams, N. (2007). The profit impact of Business Intelligence. San Francisco, CA: Elsevier/Morgan Kaufmann. Yi, M. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management, 43(3), 350.