4.1 SUMMARY
Chapter 1 discussed how data is quickly becoming an asset for organisations, and as a result, organisations are implementing business intelligence (BI) solutions to obtain insight into their data. However, research has shown that just 30% of BI projects that are undertaken are successful. Furthermore, only 26% of organisations have fully implemented BI practices and tools.
Literature has suggested some explanations why many BI implementations fail. Among the reasons is a continuing lack of understanding about the critical success factors (CSFs) that contribute to the success of a BI project.
Traditional BI implementations are not scalable, and as a result, they are incapable of handling a growth in data and system demand. Another explanation given by the literature is that there has been minimal research into frameworks for successfully implementing BI systems. It has also been demonstrated that the method used to develop a BI system has a direct impact on the system's success or failure.
According to an in-depth critical review of the literature, scalability and flexibility are two of the most significant success elements to consider when developing a BI system. Furthermore, when it comes to the success of a BI system, system quality, information quality, system usage, and user satisfaction were discovered to be major factors.
Existing research on BI system implementation was also analysed, and it was discovered that none of the studies addressed all the success factors found in literature. Furthermore, some of the research lacked a framework and did not take scalability into account.
As a result, there was a need to develop a standard framework for developing a scalable BI system that is successful in terms of system and information quality, as well as system usage, which would inevitably lead to high user satisfaction. As a result of incorporating steps from existing BI systems, a new 8-step framework was proposed in Chapter 2. The steps were as follows:
1. Requirement’s Identification 2. Data Warehouse Creation 3. BI Tool Selection
4. Report Templates Creation 5. BI Portal Creation
6. Testing 7. Deployment
8. Support and Maintenance
In Chapter 3, a BI system was created for an Energy Savings Company (ESCo) that has mining clients. It makes use of a cloud-based data warehouse as well as the PowerBI platform.
Because the storage size of the data warehouse can simply increase and decrease, this allows
A framework for implementing a scalable business intelligence system 87 the BI system to be scalable. Additionally, by using an external BI tool, users can develop custom reports that are tailored to their specific requirements.
Following the deployment of the BI system, several employees of the ESCo developed a variety of reports for various mining initiatives. These included reports on compressed air systems, water usage, and fuel management, to name a few. Using the implemented BI system, a total of 72 different reports were produced over the course of a year. Furthermore, these reports require 2.5 GB of data. This was a sign of increment in system usage.
A survey was distributed to the BI system users to validate that the BI system addresses system quality, information quality, and user satisfaction. The End-User Computing Survey paradigm found in the literature served as a foundation for this survey. Users were essentially asked to rate an aspect of the BI system on a scale of 1 to 5, with 5 indicating that they are very impressed and 1 indicating that they are not impressed.
In terms of system quality, the system's reliability, ease of use, and speed were all evaluated.
More than 66% of respondents responded positively with the system's quality. Furthermore, by analysing the system's report failures, it was discovered that a report will successfully refresh at least 93% of the time. In terms of information quality, the system's precision, accuracy, sufficiency, format, and information user needs were evaluated. More than 60% of users were pleased with the aspect of information quality.
However, only 41% of those polled were satisfied with the information that allows users to build custom reports. Finally, to analyse the overall user satisfaction with the BI system, users were asked to rate the system's success as well as their overall satisfaction. More than 80%
of respondents reported that they are pleased with the BI system.
Considering the findings and success factors, the implemented BI system was effective in delivering scalability first and foremost. Furthermore, the BI system met all the success criteria, including system and information quality, as well as system usage and user satisfaction.
The BI system also benefited several users in acquiring data insight related to their work.
Furthermore, the organisation can now offer data insights to a broader audience and potentially expand their offering to their existing or new clients, which may result in increased efficiency and revenues.
As a result, the framework was able to construct a scalable BI system that took various success factors from the literature into account. As shown in Table 4-1, the BI system met the study's objectives and, as a result, addressed the problem statement of this study.
Table 4-1 Research objectives
Research objective Was it met? Section Information quality Yes 3.4.1
System quality Yes 3.4.2
System usage Yes 3.4.3
User satisfaction Yes 3.4.4
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4.2 LIMITATIONS
Several limitations were encountered during the development of this framework, and some of these limitations may have an impact on the framework's effectiveness and long-term use.
These constraints are discussed further below.
The primary limitation encountered was a lack of resources, including financial, human, and technological resources.
The implementation of a BI system necessitates the purchase of BI software, data
warehouse infrastructure, and additional software programs such as an ETL tool, all of which cost money. As a result, the framework's efficiency is affected by how much money is spent.
Furthermore, to effectively use a BI system, a user must have a certain level of expertise. As a result, if organisations do not invest in such expertise, or at least train people to have them, the usefulness of the BI system may be undermined.
Finally, technological resources are a limitation in that the type of computer used to create or view BI reports affects the user experience. Because report creation is not cloud-based, a computer with sufficient processing power and memory is required to effectively use the BI system.
4.3 RECOMMENDATIONS FOR FUTURE WORK
In terms of future work, other methods of getting data into BI reports should be examined to reduce the BI system's reliance on an external machine. This analysis might consider various data sources, ease of development, scalability, and cost. The reliability of a BI system should be improved by providing many effective methods of extracting data into BI reports.
Secondly, future studies should include looking into more technical success factors of BI systems and ways to measure those success factors. This study began by employing a few measurers that are typically used to assess the success of information systems.
Furthermore, the primary tool for measuring these success factors was a survey. The overall limits of survey results can be improved by offering a different approach for measuring success criteria.
Thirdly, for future work, a comparative assessment of the proposed framework vs other current frameworks, such as those examined in this study, should be considered. The study's findings will aid in establishing the efficacy of the proposed framework as well as gathering feedback from users to see whether their expectations were satisfied by the various frameworks.
Finally, it is recommended that other organisations develop a BI system based on the proposed framework. Furthermore, using a different BI platform as well as a different data warehousing system would aid in determining how generic the proposed framework is.
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