Jennie Maze Limited: Enhancing Call Center Performance Using Predictive Analytics

Purpose

This case study assignment allows you to demonstrate your ability to apply evidence-based management concepts, assigned readings, and lecture content to investigate a real business problem, evaluate alternative solutions, and propose evidence-based recommendations. You will use the HBS case study method and the provided dataset (BAB265-XLS-ENG.xlsx) to analyze challenges faced by Jennie Maze Limited in forecasting and managing call center performance.

Instructions

1. Read the Case & Review the Data

· Read the case materials for Jennie Maze Limited: Enhancing Call Center Performance Using Predictive Analytics available in the required coursepack.

· Open the accompanying Excel dataset ( BAB265-XLS-ENG.xlsx Download BAB265-XLS-ENG.xlsx) and review its structure.

· Review the “Case Study Refresher” page posted earlier in this module.

2. Conduct the Analysis (in Excel) Use Excel to explore and analyze the dataset. You may use features such as sorting, filtering, descriptive statistics, pivot tables, and regression (via the Analysis ToolPak) as needed.

3. Write Your Case Analysis (1–2 pages, max 500 words) Your submission should follow the structure below:

I. Introduction

· Identify the key business problem(s) facing Jennie Maze Limited.

II. Background

· Provide context, relevant facts, and a summary of the most important data issues or organizational challenges.

III. Address Case Questions

· What is the central business problem, and what predictive analytics approach would you recommend to solve it?

· What data inconsistencies did you identify, and how would you resolve them? Explain the structure of the data and describe how you would clean and prepare it for analysis.

IV. Solutions & Recommendations

· What next steps should Jennie Maze Limited take to create a fully functional and automated approach for forecasting call volume at its six U.S. call centers?

· Support your recommendations with evidence from Excel outputs (tables, graphs, descriptive results, or regression findings where applicable).

4. Formatting & Submission

· Length: 1–2 pages (maximum 500 words)

· Format: Times New Roman, 12-point font, double-spaced

· File Type: .doc or .docx

· Upload to the Case Study #3 assignment

· Include graphs, tables, or screen captures from Excel as appropriate.

Grading Criteria (100 points total)

· Introduction & Background (20 pts) – Identifies the key problems, presents comprehensive background information and relevant facts.

· Address Questions (30 pts) – Applies course concepts to provide thoughtful, evidence-based responses to case questions with analysis clearly demonstrated.

· Solutions & Recommendations (30 pts) – Provides actionable and well-supported recommendations. Evaluates alternatives and connects solutions to predictive analytics concepts.

· Professional Writing (20 pts) – Organized, clear, professional tone; minimal to no errors; sources cited if used.

Case #3:

Jennie Maze Limited: Enhancing Call Center Performance Using Predictive Analytics

Case Questions:

1. What is the business problem and what would be your predictive analytic approach to solving it?

2. What data inconsistencies did you find and how would you resolve them? Explain the structure of the data and how you would clean the data.

Solutions and Recommendations:

What are the next steps that should be completed to have a fully functional and automated approach for forecasting incoming call volume at each of the six call centers across the US?