Business Intelligence and Business Alignment

Background
Companies invest millions of dollars in business intelligence (BI) systems to gain useful BI data that helps leaders/managers to make management decisions and build predictive models of what may or may not happen in order for the company to gain a greater competitive advantage. Implementing such systems is no easy task (CGI Group Inc. 2004; Hedgebeth 2007). Studies have shown that there are a limited number of factors that make or break the success of BI within the organisation (Yeoh and Koronios 2020). To analyse the process more closely and ensure an organisation gets the greatest return on investment (ROI) and on the limited resources available, this study will contribute to these studies through highlighting the success factors and barriers faced by businesses. It attempts to provide better understanding for BI systems adoption, as well as the challenges when BI diffusion does not go well.
Proposed Null and Alternative Hypotheses

This proposal presents a quasi-experimental, time-study methodology to confirm the diffusion model and maximise successful implementation of a BI system as measured by return on investment (ROI).
H01 –Businesses do not put more emphasis on accurate and timely data to make operational decisions to gain a competitive advantage.
HA1 -Businesses do put more emphasis on accurate and timely data to make operational decisions to gain a competitive advantage.
H02. The factors affecting business intelligence implementation do not affect managers’ business decision-making ability.
HA2. The factors affecting business intelligence implementation affect managers’ business decision-making ability.
H03. Change management skills are not required by users adopting a new business intelligence system as measured by increased utilisation of BI system by the user.
HA3 Change management skills are required by users adopting a new business intelligence system as measured by increased utilisation of BI system by the user.
H04. Human resource management skills are not required by users adopting a new business intelligence system as measured by increased utilisation of BI system by the user.
HA4 Human resource management skills are required by users adopting a new business intelligence system as measured by increased utilisation of BI system by the user.
H05 A model for implementation of BI is not needed for smooth diffusion and maximum results of the BI system as measured by ROI.
HA5 A model for implantation of BI is needed for smooth diffusion and maximum results of the BI system as measured by ROI.
Methodological Approach & Research Design Approach
The conceptual framework for this study is utilising the positivist assumptions to determine as much as clear cause and effect as possible for a smooth diffusion process. The emphasis throughout will lead to a clearer understanding of the cause of successful BI system implementations and the effect of successful and unsuccessful BI implementations (Swanson and Holton 2005). The cause and effect will also be studied regarding use of a framework/model during a BI implementation. To get to the primary factors, the positivist approach is the proper choice to. If this factor is present (x) then a smooth BI diffusion will take place (y) and the organisation will see improved results and increase its’ competitive position.
This cause and effect, positivist framework will lead to a quantitative, longitudinal study. A quasi-experimental, time series design will be employed in this study which will be conducted over several years. This will be done to assess the progress of business results and BI data results as an outcome from the BI model diffusion, i.e. “to determine the influence of a variable or treatment on a single sample group” (Swanson & Holton, 2005, p. 91). The data analysis is measured before and after the intervention or treatment. In this case, that would be the BI model of diffusion with changes as a result of the literature analysis. A limitation to the time series is that it is difficult for the researcher to “separate out interaction effects out of the organisation or (some) other environmental reason” (Swanson & Holton, 2005, p. 91). This correlates to the literature as this is the area that has not been studied for a great length of time.
This study will be conducted over a 3-year period as the longitudinal method gathers measurements over an extended period of time so as to be able to study long-term ROI with the main concern being dealing with the attrition factor which makes such studies more expensive. Opinions will be elicited from IT executives representing two types of companies: those which adopted BI systems and those which have had problems doing so or have not done so yet. Two questionnaires will be used, one for each type of organisations. The first questionnaire will be organised into four sections: general data; BI success measures; factors for BI adoption; and challenges to BI adoption. Previous surveys will be used to create the survey tool and modified to fit the context (Kamhawi 2008). The second questionnaire will be organised into four sections as well: general data; reasons for problems with implementing BI systems; attitudes; and future intentions towards BI systems. Measurement items for such sections will be developed using previous studies (Kamhawi 2008). The questionnaires will be field tested and pilot tested to ensure validity and reliability. Based on the pre-test and pilot test minor changes may be made to the phrases used in the scale questions of the questionnaire, how worded, and how questions will be classified and may be made clearer. Responses to the phrases of both questionnaires will be given through a 5 point-Likert scale.
Researcher’s Previous Related Work
This researcher has been involved with business and information technology alignment since the mid-1990s which is the area which this research falls into. After having returned from academic studies abroad to southern Africa the researcher was confronted with the task of having to evaluate projects from international donor organisations such as German Technical Cooperation (GTZ), projects that would otherwise be classified as white elephants because the technology used was too advanced for a developing country. This resulted in this researcher submitting an MBA project to Nottingham Trent University in 1999 entitled “.” This area of interest was further enhanced as the researcher was a lecturer on the MBA programme of the University of East London responsible for a course on “Organisational Change and Business Processes.” As the researcher has been working with SAP BI for a few years the implementation of such complex system has further enhanced the interest in researching in this area, defining the linkage between business and technology in BI. Though the writer has not come up with any publications due to the nature of his work, this research would correct that and lead to publications of the researcher’s expertise.
Significance of this Study
The real world of the organization change management can prove challenging and this study could contribute significantly to the existing literature by filling gaps within existing studies and creating new knowledge. As well done as the qualitative study was by Yeoh and Koronios (2010) their model does not account specifically for the effects of human resource management or for the unexpected. The critical and unique elements that this study will be provide:
Conclusion
• Conclusions and perspectives from a global standpoint as a result of retrieving samples from locations worldwide as opposed to one-country focused literature review.
• This study will be a quasi-experimental, time-series study as a result of the literature review where previous studies have been from one point in time.
• Create a weighting system for the success factors to determine which one has the most impact on a successful diffusion process. This will be helpful for organisations that have limited time and resources when implementing the BI into the company.
• Determining the position of change management and human resource management in the BI diffusion model. Many of the model or studies reference training for users as an example, or change management in broad terms, but few are specific about the position of change management in the model or the position of the needs of the people during the transition.