Week 6 Assignment – Decision Making Through Analytics
The primary aim of this project is to showcase your proficiency in the tools and methodologies we've covered in this course. You will apply advanced analytics to a comprehensive business case study, utilizing Excel as your primary tool, to draw actionable insights and make informed decisions.
Case Study: Optimal Expansion Strategy for 'Superstore' Retail Chain
Background: Superstore is a fast-growing urban department store-style retailer. They currently have stores spread across a number of states and looking to expand. With expansion come questions related to optimal locations, stock assortment, and predicted demand.
Data Provided:
- Superstore.xlsx: This file contains sales data for all stores for the past 10 years. Order numbers, locations, dates, and even profit margins are included in this worksheet.
Assignment Requirements:
- Data-driven decision making: Use the data provided to determine two cities should consider for its next set of stores.
- Sampling and Probability: From the sales data, pick random samples to estimate sales for the new stores. Use probability techniques to predict the range of sales figures.
- Predictive Modeling:
- Use single and multiple regressions to predict sales for new products.
- Build a predictive model to estimate the monthly sales for the new stores for the first year.
- Simulation: Use Monte Carlo simulation or Event Logic and Entity Life-Cycle Logic Models to forecast sales and stock demands for different seasons.
- Linear Programming:
- Use Solver to determine the optimal product assortment for the new stores, given constraints like shelf space, supplier agreements, and predicted demand.
- Factor in simultaneous decision problems, ensuring every decision complements the other.
- Visualization and Presentation: In Excel, create dashboards and charts that showcase your findings in a clear, visually appealing manner. Your final presentation should tell a compelling story about how Superstore should approach its expansion.
Evaluation Criteria:
Depth of analysis and application of course tools: 50%
Quality and clarity of the report: 50%
Submission Instructions:
- A 3–5-page Word Document
- Must include a title page, abstract, and references. These are not counted in the page count/slide count.