Background
BSAN2204 METHODS OF BUSINESS ANALYTICS Project Report – Briefing Notes
The course BSAN2204 Methods of Business Analytics has three assessment items: a project plan, a project report, and a final examination (a “take home” exam). These notes outline my expectations for the project report. Keep in mind that the project report is intended as an extension of the project plan. The plan proposed a possible direction for your project. The project report restates key elements of the plan, documents the methods and results of your project, and highlights the implications for the client (for example, Spotify). Note the project report should be prepared and submitted in PowerPoint format (whereas the project plan was in the form of a Word document).
The overall aim of the report should be to provide “proof of concept” for your ideas; that is, initial evidence to support your claim that something like the approach you are taking is capable of generating “business value” for the client. The report should be comprehensive – sketching out all aspects of the project from beginning to end. Draw on your proposal where it is appropriate to do so (it is OK to use text from the proposal in the introductory sections of the report). The proposal is not a binding document. That is to say, you are very welcome to revise your proposal if you think revision is needed to it. (Perhaps you should signal to the reader of your project report how your project differs from the proposal and why, if it does differ from it in meaningful ways.)
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Furthermore, you will need to find the right balance between the effort you put into the technical aspects of your project and in communicating the value of your project – with the overall goal of having impact on the client business. This is perhaps the key decision you will have to make in coming weeks. One way to reconcile the possible tension between the demands of your project and the reporting requirements is to style your project as a pilot project. Let me elaborate. I do not expect your report to provide a definitive answer to the business problem you are address, but I do expect you to generate an indicative solution to the problem (for example, generating a regression model that addresses the problem and providing an interpretation of that model). My expectation is that the report will provide indicative answers, show what is possible, and provide you with the experience to say with greater confidence what type of project would more definitively address the problem. What is the next analytics project the client should consider?
Key Sections
The project report will likely have the following sections.
1. Background
2. Business problem
3. Proposed solution/method of analysis
4. Analysis plan
5. Results and interpretation
6. Strategy/recommendations (and business case)
7. Conclusion
Per the project plan, the background section introduces the project, placing emphasis on the broad context and highlighting the specific domain of interest (in this case, the importance of business analytics to the music industry). The general expectation is some key business process and/or management decision will be improved through the use of analytics reported in your project report.
The next section of the report should restate the business problem you are attempting to address. What is the problem you are trying to solve? A starting point might be to specify an outcome the target business/client is trying to achieve (for example, “song hotness”). Addressing the following questions may help. (1) What is the specific outcome the business is trying to influence or understand, or both? (2) How is it manifest or measured? (3) What level of that outcome variable has the business achieved to date, and what is the desired level of the outcome variable? (4) What are the likely factors or other variables that are potentially related to the outcome of interest, and how are they measured?
The section on the proposed solution or “line of attack” should focus on the method of analysis – a particular method of business analytics suitable for the problem you have outlined/specified (for example, linear regression). Describe the method in some detail. Highlight the key steps and/or issues in its implementation. For example, an application of predictive analytics might have linear regression as it core modelling framework. This section should also outline the data requirements needed to solve the business problem. In summary, this section should be specific about the proposed method of analysis and the data to be used. The section should clearly identify and describe the key output and feature variables, including writing the model in formal fashion and further elucidating the specification using a path diagram.
The analysis plan is intended as a step-by-step guide to implementing the proposed approach. For example, a regression analysis might involve several key steps, including a consideration of the appropriateness of the data for the planned application, the specification of the outcome and input variables, and some assessment of the how the basic assumptions of regression might be satisfied. This section should now be much easier to write than it was for the proposal – having now had the experience of analysing the data and developing the interpretations. Perhaps this section leads off with approaches to visualising the data (univariate and bivariate) and the descriptive statistics that will be reported, before outlining your approach to predictive modelling (including a report of testing assumptions, etc.).
The results and interpretation may be in three parts. Firstly, you might provide some summary information about the dataset you are working with. How many observations are you working with? How many variables are you working with? Second, you might provide a more specific statistical summary of the data. Reporting summary statistics is important, for example, what are the means and standard deviations of the (continuous) variables? Are the variables normally distributed or approximately normal? This is especially important for the outcome or dependent variable of a linear regression model. Can you visual some of the key relationships by reporting scatterplots? Third, you might report the results of any statistical analysis or modelling such as the results of a regression model. Do not copy and paste raw R output from the console. Ensure any results you include are in professionally formatted publishable tables. Charts can be included without any reformatting.
Provide a written interpretation of each of the outputs you include in your report. Take the case of reporting a regression model, for example. It is important to report (1) information about the overall fit of the model to the data and (2) information about the importance of each of the input or explanatory variables in the model. The adjusted R-squared provides a measure of overall fit of the model to the data – higher values implying better fit. The F-statistic tests overall significance of the model. The strength and significance of the regression coefficients provides insight into the importance of each of the feature variables in the prediction of the output variable.
A key section of the report is the strategy and recommendations section. The implications of your project should become clear in this section. Think about the value of your results from the perspective of the client. What insights have you generated that might be important for the client to know? Provide a succinct list of insights (a numbered list or dot points is encouraged here). Given your results, are there things the client should do more of or things the client should do less or of stop doing? Where should the client start in actioning your results? What is the single most important thing the client should do? What should the client do first, second, etc. As you start to address these questions, you might find that your insights become the precursor for a set of recommendations. Also, think about some of the potential costs associated with your recommendations. What might be more or less feasible for the client? Specificity, tractability and feasibility are all critical here.
Finally, I would like you to include a section on further research in your project reports. Think about what should be done next – what is the next project, what does it look like? One way to think about this question is to think about what you pilot project could have achieved if you had more time, more and/or different data, and more resources. What would you have done differently if you had had more time and resources? Another way to address the question of what further research should be done is to focus on one or more very specific findings from your project. These might be unusual or unexpected findings, or findings that may have great significance for the client but were only addressed in part in your project. A good project finishes by outlining the next project a business analyst might address!
Submission Guidelines
The report is worth 50 percent of your score in the course. In terms of length, I would expect your slideshow to be in the range of 20-30 slides (maximum). Submit only one single file. A .pptx file (made using PowerPoint) or a .pdf file (exported from Google Slides, , LibreOffice Impress, Prezi, Canva, etc). You may use any software package to create your slideshow.
You can start your slideshow now – extract the key information from your proposal you wish to bring forward into the presentation, or rewrite or write these early sections including the business problem, proposed solution, method of analysis, data, analysis plan. Think about how best to present your results. Recall that visual and statistical information should be supported by short written descriptions of the key results. It is critical that you communicate the main findings of your analysis without bombarding your audience with too much data.
Check the electronic course profile for submission dates and for the University’s policy on extension requests. Follow the submission instructions on Blackboard to ensure you submit your assignment correctly.
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