Mount Allison University
Mount Allison University
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Data-Driven Operational Consultancy

OPRE 6367
Closed
The University of Texas at Dallas
The University of Texas at Dallas
Dallas, Texas, United States
David Parks
David Parks
Associate Professor of Practice
(9)
3
Timeline
  • January 1, 2018
    Experience start
  • January 16, 2018
    Project Scope Meeting
  • April 27, 2018
    Experience end
Experience
3 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any
Consumer goods, Energy, Food, Industrial, Retail

Experience scope

Categories
Operations Project management
Skills
data analytics business consulting business strategy operations management supply chain
Learner goals and capabilities

Individual 4th year Undergraduate and Master's student-consultants conduct a data analysis for your company to develop recommendations that address an operational opportunity or challenge.

Learners

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

Student-consultants will present the following in an in-person or virtual management presentation and within a written project report:

  • Clearly identify the challenges your organization is facing relevant to the data.
  • Uncover the root cause of the identified challenges
  • Propose viable solution(s).
  • Recommend the best course of action.
  • Justify the position through metrics.


Students will also provide tangible copies of their work as it pertains to their individual project.

Project timeline
  • January 1, 2018
    Experience start
  • January 16, 2018
    Project Scope Meeting
  • April 27, 2018
    Experience end

Project Examples

Requirements

Beginning this January, student-consultants will work 50+ hours each to address one of your companys data opportunities or challenges.


They will employ analytic and statistical software such as Tableau, SAS, Micro-strategy, Power BI or other methods to conduct research and inform their decision-making process. Based on their findings, they will develop tailored recommendations for your organization.


Some examples include, but are not limited to:

  • Analyzing e-commerce data to understand buyers 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.
  • Applying prescriptive analytics using customer segmentation.
  • Personalizing Customer relationship management (CRM).
  • Implementing online recommendation systems.
  • Conducting web mining.
  • Designing lead scoring systems to understand opportunities worth pursuing.
  • Developing predictive sales models.

Additional company criteria

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

  • Q - Checkbox
  • Q - Checkbox