Master's Business Consulting

OPRE 6367
Closed
Main contact
The University of Texas at Dallas
Dallas, Texas, United States
David Parks
Associate Professor of Practice
(9)
3
Timeline
  • August 29, 2019
    Experience start
  • January 20, 2019
    Project Scope Meeting
  • May 12, 2019
    Midway Check In
  • December 3, 2019
    Experience end
Experience
4/5 project matches
Dates set by experience
Preferred companies
Anywhere
Any company type
Any industries

Experience scope

Categories
Data analysis Operations Project management Product or service launch
Skills
business consulting data analytics management project planning business strategy
Learner goals and capabilities

Student consultants spend approximately up to 10 weeks working with your company in analyzing data sets using a variety of analysis methods according to your needs. The results can provide in-depth insights into the operations of your business, a detailed perspective of your customers, and solutions to complex problems. Students can leverage industry standards for analysis using various tools such as SQL, Excel, SAS, PPT, and Tableau.

Learners

Learners
Undergraduate
Any level
35 learners
Project
45 hours per learner
Learners self-assign
Teams of 5
Expected outcomes and deliverables

Student-consultant groups will produce the following:

  • Written project report of findings with supporting analytics and model.
  • Management presentation either in person or web/video conferencing.
Project timeline
  • August 29, 2019
    Experience start
  • January 20, 2019
    Project Scope Meeting
  • May 12, 2019
    Midway Check In
  • December 3, 2019
    Experience end

Project Examples

Requirements

In groups of 5, student-consultants will work 45+ hours assisting your company by providing analytical research and recommendations tailored to one of your company’s data opportunities or challenges. They will employ analytic and statistical software such as Tableau, SAS, Micro-strategy, Power BI or other methods to inform their decision-making process.

Some examples include, but are not limited to:

  • Analyzing e-commerce data to understand buyers and buying habits across several selling platforms,
  • Understanding profitability, retention, referrals, and attrition rates for your customers
  • Creating comprehensive dashboards to enhance your data visualization for customers, teams, and executives,
  • Prescriptive analytics using customer segmentation
  • Customer relationship management (CRM), personalization
  • Online recommendation systems
  • Web mining
  • Product assortment, and designing lead scoring systems to understand opportunities worth pursuing and developing predictive sales model, etc.

Students will complete the data analysis and present their findings in final a presentation (virtual or in-person.) They will clearly identify the challenges the organization is facing relevant to the data, uncover the root cause of the identified challenges, propose viable solution(s), and recommend the best course of action as well as justify the position through metrics. Students will also provide tangible copies of their work as it pertains to their individual project.

Additional company criteria

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

  • Q1 - Checkbox
  • Q2 - Checkbox
  • Q3 - Checkbox