Project 1: Business Analytics

Analytics in the Real World

This individual project is worth 10% of Course Grade. This should be done on your own.

Deliverable: Approximately 3-5 page report, 1.5 spaced describing an analytics, management science or model challenge in the real world and the methods and/or technologies used to solve it. Five (5) references are required which can be a combination of articles or links that support the writing in the report. Exhibits and tables can be included in the text body of the report, and long tables and exhibits can be included as appendices. All writing should be in the third person.

Students may pick any problem or set of problems, in any real-world context, from business (financial, marketing, operations, management, human resources, etc.), science, government or society. The problem should be described in words including the challenge at hand and the implications of effective solutions to managers, customers, clients, tax-payers and/or human society. The problem should be one that is currently being addressed or should be addressed. Students could choose a problem from their place of work or desired industry/job.

The problem(s) should be described in detail. This requires presenting it in a manner that would be required for understanding how to address it using the models and tools like those covered in BUS 609. This could (should) include the data that is available, the mathematical technique(s) that is(are) applied and the tools (software/hardware) that are used to solve the problem. Indication should be made as to why the technique is appropriate for this particular setting.

The current state of solutions to the problem should be described. Where are modelers and decision makers in the process of finding good/effective solutions? What is limiting the quality of the results if the results are not yet effective? What makes the solutions found useful if they currently are? What are the implications of an effective solution to the problem?

The last section of the report should discuss the future opportunities and challenges of solving the problem. What will help solutions improve? What limitations remain?

Topic:

Business Analytics and

Modeling with Spreadsheets

Data Presentation, Description and Pivot Tables in MS Excel

Applications of Linear Programming

Networks and Integer Programming

Topics in Optimization

Regression Review

Time Series Forecasting

Forecasting

Simulation Modeling

Decision Analysis

Ragsdale, Cliff: Spreadsheet Modeling & Decision Analysis: A Practical Introduction to Business Analytics, 7th ed., Cengage Learning, 2015. ISBN 978-1-285-41868-1.

Week 13: Decision Analysis (May 5/7) 


Week 12: Simulation Part Deux (April 28/30) 


Week 11: Simulation (April 21/23) 


Week 9 and 10: Data Mining-Universal Bank Example (April 7/9 and 14/16) 


Week 8: Time Series Analysis (March 31/April 2) 


Week 7: More Regression (March 17/19) 


Week 6: Regression Review (March 10/12) 


Week 6: Non-Linear and More Difficult Optimization Problems (March 10/12) 


Week 5: Integer Programming (March 3/5) 


Week 4: Network Problems (Feb 24/26) 


Week 3: Linear Programming Applications + Sensivity Analysis (Feb 17/19) 


Week 2: Introduction to Optimization (Feb 10/12) 


Week 2: Visualing and Exploring Data (Feb 10/12) 


Week 1: Introduction to Business Analytics and Problem Solving using MS Excel (Feb 3/5) 


Week 13: Decision Analysis (May 5/7)

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