Collaborate with Future Consulting Leaders

The University of Virginia
Charlottesville, Virginia, United States
Educator
4
Timeline
  • February 19, 2025
    Experience start
  • February 21, 2025
    Case Overview Provided to Students
  • February 26, 2025
    Client Discovery Call Questions Due
  • February 27, 2025
    Conduct Client Discovery Call
  • February 28, 2025
    Client Follow Up Questions Due
  • March 20, 2025
    Subject Matter Expert Interview Notes Due
  • April 5, 2025
    Experience end
Experience
1/1 project matches
Dates set by experience
Preferred companies
United States
Any company type
Any industries

Experience scope

Categories
Data analysis Market research Project management Competitive analysis Market expansion
Skills
quantitative data analysis data-driven decision making qualitative data analysis data analysis microsoft excel consulting project management teamwork problem solving
Student goals and capabilities

The University of Virginia’s PhD Plus Consulting Program, led by Dr. Brendan Boler, is designed to equip PhD students and Postdocs with the essential knowledge, skills, and confidence required for a successful career in consulting. Participants in this course master a hypothesis-driven structured problem-solving approach, and develop proficiency in data analytics using Excel and storytelling using PowerPoint.


Our learners are advanced PhD students and postdoctoral researchers who bring a high level of analytical ability, critical thinking, and academic rigor to their work. They are eager to apply their skills to real-world consulting projects, gaining hands-on experience that will be invaluable for their professional development. The aim of this collaboration is to provide students with practical experience while offering employers fresh perspectives and innovative solutions to their business challenges.

Students

Students
Graduate
Beginner, Intermediate levels
10 Students
Project
50 hours per Student
Educators assign Students to projects
Teams of 4
Expected outcomes and deliverables

Deliverables will vary depending on the scope of the project. However, these deliverables must be discussed and agreed upon prior to the start of the project.

Project timeline
  • February 19, 2025
    Experience start
  • February 21, 2025
    Case Overview Provided to Students
  • February 26, 2025
    Client Discovery Call Questions Due
  • February 27, 2025
    Conduct Client Discovery Call
  • February 28, 2025
    Client Follow Up Questions Due
  • March 20, 2025
    Subject Matter Expert Interview Notes Due
  • April 5, 2025
    Experience end

Project Examples

Requirements

Ideal projects for this experience should align with the course's focus on hypothesis-driven problem-solving, data analytics, and effective communication. Suitable projects will challenge students to apply their academic skills in a practical consulting context.


Here are some examples:

  1. Market Entry Strategy: Develop a market entry strategy for a new product line, including competitive analysis, target market identification, and go-to-market plan.
  2. Operational Efficiency Improvement: Analyze and recommend improvements for a company's operational processes to increase efficiency and reduce costs.
  3. Customer Segmentation Analysis: Perform a detailed customer segmentation analysis to identify key customer groups and tailor marketing strategies accordingly.
  4. Product Pricing Strategy: Create a data-driven pricing strategy for a new or existing product, incorporating competitor pricing and consumer behavior analysis.
  5. Digital Transformation Plan: Design a comprehensive digital transformation plan for a company looking to modernize its operations and improve digital engagement with customers.


Additional company criteria

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

  • Q1 - Text short
    Will you be available for a call in late November with the instructor & students to initiate your relationship and confirm your scope is an appropriate fit for the experience?  *
  • Q3 - Checkbox
     *
  • Q4 - Checkbox
     *
  • Q7 - Text long
    Are the tools and technologies required for the project available as free or open-source software?  *
  • Q8 - Text short
    Will learners be required to sign any agreement to access the data? For example IP release or NDA? If so please note the requirement here.  *
  • Q9 - Text long
    Please provide a brief description of the data set learners will be working with. Include information on the size of the data set and how you will share it.  *