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Key Topics
- Requirement
- Solution
- Case Study 1: Monster Thickburger by Hardee's
- Introduction.
- RAKID Analysis.
- DAKAR Analysis.
- Implementation.
- Comparison and Contrast.
- Lessons Learned.
- Case Study 2: Brokers' True Profitability at Tradition Financial Services
- Introduction.
- RAKID Analysis.
- DAKAR Analysis.
- Implementation.
- Comparison and Contrast.
- References
Requirement
You need to write an essay, maximum word count 1,000, excluding references and appendices. This is a tight word count – but it is possible to write a good report in this limited number of words. It forces you to really think about the content. The purpose of the essay is to demonstrate an understanding of key principles of Business Intelligence and its business benefits and issues.
1. Choose 2 Business Intelligence case studies (for example from SAS, Oracle, IBM, CIO.com, etc.) (Please research the two cases studies and they must be linked to one of those above and business intelligence). Reference your sources clearly. Make sure you choose your case studies wisely, so you can adequately address the questions set out below. If you are in any doubt, please check with the module leader about the suitability of your chosen case studies.
2. Use the DIKAR model to critically analyse the case studies separately. For each case study you need to show:
? What were the planned business needs (note that ‘having a BI system’ is not a business need – you need to look at what the organisation thinks what it needs the BI system for), actions, necessary knowledge, information, data? (RAKID)
? What data was used in reality, what information and knowledge generated, what actions supported and what were actual business outcomes? (DIKAR)
Business Intelligence Case Studies - Analysis and Conclusions
In this essay we will consider two case studies of business intelligence and analyze them and explore the lessons that can be learnt from them.
Solution
Case Study 1: Monster Thickburger by Hardee's
Introduction.
The first case study we will do is about the launch of Monster Thickburger by Hardee's fast-food company and is based on a report by Levinson (2007). The burger in question is extremely oversized with a single burger accounting for 1420 calories and is an odd product. Business Intelligence (BI) was used to decide about not only launching such an outlier product but also devoting 7 million US dollars to nation-wide advertising.
RAKID Analysis.
The results desired were better sales, more profits and adding an item to the menu which competitors did not have. The action for meeting such goals would be the launch and publicity of the mentioned Monster Thickburger. For arriving at this decision and allocating a large advertising budget knowledge about the success and the change in total sales from test runs of the burger were used using the information of sales of this burger, sales of other burgers and the total sales. One of the key question was whether this burger was being successful on its own or was being chosen by the customers in lieu of existing burgers.
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DAKAR Analysis.
For BI, the new burger was test launched at various locations and data about the sales of this burger, sales of existing burgers and total burgers were used. From this data, information about the effect of this burger on total sales, and the change in sales of existing burgers before and after the test launch were used to provide the knowledge that if these burgers selling on their own without reducing the sales of other burgers. Such was the case in test launches. Using this information, the burger was introduced in chains nation-wide and advertising was done.
Implementation.
The burger was launched in test markets. The data was recorded using in-house BI system known as CPR (CKE Performance Reporting). We also note the boldness of the company and its faith in the results of the test markets and the BI input.
Comparison and Contrast.
Compared to other case study, this was a one-off requirement and the effects were internal to the company only. The methodology for this case study aligned with the theoretical frameworks. Also, we notice that the costs incurred were less in this case study.
Lessons Learned.
From this case study in which the BI proved to be a success, we learn that if the analysis in test cases is done correctly and we have data and knowledge to prove it, then we can safely trust the BI and go ahead with the original plans. This case study highlights the importance of input of clean and relevant data. Also, the formulations of reporting logic in this case study are commendable and we appreciate that the reports should provide some insight and not be a rehash of the reports already available in standard office software.
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Place Your OrderCase Study 2: Brokers' True Profitability at Tradition Financial Services
Introduction.
The second case study we will do is about the accurate and timely profitability report to the financial services provider company Tradition of the brokers its pays out to. This is based on report by Wolpe (2013). The company depends upon the brokers for its financial success and pays them out depending upon many factors, and the company spends on them under various heads. The company's leaders had no clear idea which broker was profitable and which was not and decisions were being made on gut feelings. The entire database was being managed in Excel files and they used to become unwieldy after a few months of data. Even the services of Excel expert could only produce the required reports after a couple of months, and also errors were possible in the laborious calculations.
RAKID Analysis.
The results required were quick and accurate data-backed analysis as to the profit and loss of each broker. The results were required quickly so as to enable fair contract renegotiations and so that unproductive ones could relieved. The action for this is the analysis by the company's leaders, using the knowledge which is based upon the information and data about the incoming business from a broker, company expenditure on him e.g. commissions, entertainment allowance, travel allowance etc.
DAKAR Analysis.
The data for the new system is the details of business brought in by the broker and the expenditure of the company on them available under various heads. This data is processed to build an information on the profitability of each broker. This report is required to be calculated at will. Using this report, the company's leaders can decide which relationships to renew and which relationships to issue a notice for termination. The results are active brokers who are aware that their performances and more profit for company.
Implementation.
The company hired Cubewise (http://cubewise.com/) and chose IBM's Cognos Express (http://www.ibm.com/analytics/us/en/technology/cognos-software/). Two servers (one production and one backup) were required. Also, the software is capable enough of taking on new tasks in the company and that was one of the convincing factors for the company leaders to invest in this technology. We notice that the management was satisfied with the existing slower system if the company performance was okay but moved to the new when it needed to prune the unproductive brokers. Also, we see that the leaders are only concerned with their results, the means to achieve it do not matter to them.
Comparison and Contrast.
Compared to other case study, this is an enhancement which will be used regularly to make decisions about downsizing, and thus effects not only the morale of people, but also the profitability of the company on ongoing basis. The methodology for this case study aligned with the theoretical frameworks. Also, we notice that the costs incurred were much more in this case study and the benefits for the company extend in using it for evaluating other departments also.
Lessons Learned.
We learn from this case study that using a ready-made software and hiring the services of a reputed service provider may be better for a company so that they may continue to focus on their business without getting involved in technical details. Also, we appreciate the importance of quick and accurate information for the decision makers.
References
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Levinson, M. (2007). The Brain Behind the Big, Bad Burger and Other Tales of Business Intelligence. CIO. Retrieved 15 October 2016, from http://www.cio.com/article/2439016/business-intelligence/the-brain-behind-the-big--bad-burger-and-other-tales-of-business-intelligence.html
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Wolpe, T. (2013). Case study: How one firm used BI analytics to track staff performance | ZDNet. ZDNet. Retrieved 15 October 2016, from http://www.zdnet.com/article/case-study-how-one-firm-used-bi-analytics-to-track-staff-performance/
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