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MBA Data Analysis for Decision-Making

KMCI 940
Closed
Northwestern University
Northwestern University
Evanston, Illinois, United States
Joel Shapiro
Professor
2
Timeline
  • February 11, 2018
    Experience start
  • February 26, 2018
    Project Scope Meeting
  • March 15, 2018
    Experience end
Experience
4 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any organization with a well-established business decision and reasonable sources of data
Any industries
Categories
Leadership Organizational structure
Skills
data analysis and decision-making data analytics decision-making
Learner goals and capabilities

MBA student-consultants will shed light on your important business decisions through analysis of quantitative data and knowledge of the business context.

Learners
Any level
50 learners
Project
20 hours per learner
Learners self-assign
Teams of 5
Expected outcomes and deliverables

Phase 1 – Project Plan: Students will meet with organization representative(s) to devise the project scope and prepare a detailed plan for completion of the project.

Phase 2 – Project Execution: Students will work on deliverables outlined in the project plan. Teams will periodically communicate with organization representative(s) as needed to complete project tasks.

Phase 3 - Outcome - Report and Presentation: Students will submit a detailed 10+ page presentation deck, as well as deliver a 20-30 minute presentation. Organization representative(s) are invited to attend these presentations.

Project timeline
  • February 11, 2018
    Experience start
  • February 26, 2018
    Project Scope Meeting
  • March 15, 2018
    Experience end
Project Examples

Beginning this February, a group of 5 graduate students taking their MBA in Business Analytics will dedicate 100+ hours to complete a project for your organization. They will gather and analyze data to solve a data-driven business challenge you are facing.

Analytical data can validate or refute your initial opinions or hypotheses. It allows you to take actionable insights into your decision-making processes and create more effective strategies for achieving organizational goals and objectives.

Possible project examples include, but are not limited to:

  • Using customer-level data to build a predictive model identifying customers most likely to churn, leading to the creation of strategies to enhance retention.
  • Assessing prospective customer data to test hypotheses about what kinds of marketing activities best yield new customers.
  • Assessing operational data to predict performance and inform decision-making.
  • Reviewing existing data at your company and helping you develop an analytics strategy to answer specified business questions.

Projects can be in any of the following business areas:

  • Supply Chain Optimization
  • Scheduling Optimization
  • Customer Segmentation
  • Employee Performance
  • Market Analysis
  • Financial Forecasting
  • Predictive Modeling
  • Product Analysis
  • Sports Analytics
  • Donor Base Analysis
  • Predictive Law Enforcement
  • Valuation Models

Companies must answer the following questions to submit a match request to this experience:

Appoint a point person to be available to students for questions throughout the project

Be present, either remotely or in person, for the students' final presentation

Provide feedback to the students on their work.

It is critical that the company have a well-formulated business question and can provide reasonably clean data to help answer that question.