Business Intelligence System and Analytics Techniques - Management Report

The intended Learning Outcomes (LOs) that are assessed by this coursework are:

LO1: Identify the required components of a BI system by systematic analysis of a perceived problem area, appraisal of available techniques and tools, and the critical evaluation of developed systems.

LO2: Conceptual understanding of a range of predictive analysis techniques, critically evaluating current research and new insights.

LO3: Design appropriate BI systems using appropriate BI approaches.

When completed you are required to submit your summative coursework:

1. As a Word or PDF Document via Turnitin If for any reason Turnitin is not working at the date/time of the submission deadline, please provide it as an attachment to an email to the module leader by the specified deadline date/time and a subsequent Turnitin submission can be completed as soon as the facility is available again to use.

If you need any support or advice on completing this coursework please visit the Student Matters tab on the Faculty of Computing, Engineering and Media Blackboard page.

Late submission of coursework policy: Late submissions will be processed in accordance with current University regulations which state: “the time period during which a student may submit a piece of work late without authorisation and have the work capped at 40% [50% at PG level] if passed is 14 calendar days. Work submitted unauthorised more than 14 calendar days after the original submission date will receive a mark of 0%. These regulations apply to a student’s first attempt at coursework. Work submitted late without authorisation which constitutes reassessment of a previously failed piece of coursework will always receive a mark of 0%.”

Your task is to prepare a management report in which to illustrate to management how the techniques of forecasting and optimisation (linear programming), and Business Intelligence could be useful to the organisation. As management knows little of these techniques, you need to demonstrate how they will work in practice. For this purpose, data has been supplied for you to carry out some of the techniques.

Requirements and Instructions

1. The report should be broken down into three parts (Part 1 – 3). Your report should include your workings and/or spreadsheets for the practical exercises and a reference list. We will have access to your SAS BI work on the SAS server so you do not need to supply anything other than the screen shots of your SAS BI work within your report.
2. It is expected that you will prepare and submit a comprehensive word-processed, structured, logical, technical report in the correct format.
3. The report is to be electronically submitted through the Turnitin link on the IMAT5264 Blackboard shell by 12h00 noon, Wednesday 26th May 2021.
4. A typical report structure includes: Title page, contents, introduction, and main body of report, conclusions, recommendations, and appendix (where appropriate).

• Note: The title page should contain: Module code and your p-number (name optional), assignment title, deadline date, module tutor’s name. You should include your p-number in the footer of every page along with page numbers (there should be no page number displayed on the title page).

Forecasting

1. a) As a consultant at East Midlands Candy, you are required to introduce and motivate for the use of Forecasting techniques by:
2. Providing an overview of how forecasting techniques could be useful.
3. Discussing the challenges and/or implications that East Midlands Candy could face in the application of forecasting approaches/processes?

iii. Discussing the four keys questions that management at East Midlands Candy should consider when measuring the success of their forecasting techniques.

1. b) Use the following guidelines and instructions for the application of forecasting techniques:
2. Review the data supplied in Appendix 1.
3. Use this data to demonstrate how the different products (A, B & C) show different characteristics with regard to forecasting (Hint: identify and describe the pattern using a time series plot).

iii. Identify the most appropriate forecasting technique for each of the three products given and justify your choice.

1. Give forecasts for Year 4, for each product.
2. Critically evaluate your results highlighting whether you consider the forecasting model to be good or not (Hint: consider forecast accuracy).

Linear Programming/Linear Optimisation

1. a) Provide an overview of how optimisation and linear programming (LP) could be useful in supporting decision-making at East Midlands Candy.
2. b) Discuss how optimisation mathematical modelling could be used in the area of the production/manufacturing of candy products (Hint: identify possible decision variables,  results variables, and uncontrollable variables/parameters)
3. c) Use the following guidelines and instructions for the application of linear programming techniques.
4. Review Problem Case 1 (Production) and Problem Case 2 (Staff Allocation) in
5. Formulate a Linear Programming model for:

1) Problem Case 1 (Production)

2) Problem Case 2 (Staff Allocation)

NB: There is no requirement to solve this problem or make calculations. A model is only required, which includes decision variables, a result variable, objective, and uncontrollable variable