Henry Tam and the MGI Team

Jeffrey T. Polzer; Ingrid  Vargas; Hillary Anger  Elfenbein

Case | HBS Case Collection | October 2003

Henry Tam and the MGI Team

by Jeffrey T. Polzer, Ingrid Vargas and Hillary Anger Elfenbein

Abstract

Within a short time frame, seven diverse team members assemble to write a business plan for a new company and struggle to define their roles, make decisions together, and resolve conflict. Henry Tam, a second-year Harvard MBA student, who joins an aspiring start-up company and a fellow classmate to enter the school's business plan contest. The founders of the company are two internationally accomplished musicians and a 1987 Harvard MBA, all Russian, who are trying to create, produce, and sell a unique computer-based music game. Conflict builds as the team generates a range of ideas about how to market their product, but has trouble agreeing on which ideas to pursue. Henry Tam wrestles with how to fix the problems that have hindered the team's progress.

Keywords: Interpersonal Communication; Business Plan; Groups and Teams; Decision Making; Jobs and Positions; Leadership Style; Human Resources; Management Teams; Conflict and Resolution; Diversity;

Format: Print

17 pages

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Citation:

Polzer, Jeffrey T., Ingrid Vargas, and Hillary Anger Elfenbein. "Henry Tam and the MGI Team." Harvard Business School Case 404-068, October 2003.

This is a supplement to the People Analytics at Teach For America (A) case. In this supplement, Managing Director Michael Metzger must decide how to extend his team’s predictive analytics work using Natural Language Processing (NLP) techniques.

As of mid-2016, national nonprofit Teach For America (TFA) had struggled with three consecutive years of declining application totals, and senior management was re-examining the organization’s strategy, including recruitment and selection. A few months earlier, former TFA corps member Michael Metzger had spearheaded the launch of a predictive analytics team responsible for integrating strategy across TFA’s recruitment and admissions continuum. Metzger believed that predictive analytics could help address TFA’s recruitment and admissions challenges. Now, TFA’s senior management wanted Metzger and his team to put their data models to the test. From a data modeling standpoint, what variables and models should TFA consider as it began a new recruitment season, and more generally, how heavily should TFA rely on predictive models to reverse the negative trends?

A private equity-backed fast food chain has hired McKinsey’s new People Analytics group to help it improve performance. As the final client workshop approaches, Associate Partner Alex DiLeonardo ponders the best way to present the team’s findings, especially those that conflict with the client executives’ long-held intuitions. If successful, the project would help People Analytics build its reputation both internally and with clients. But to be successful, DiLeonardo knows his team must convince the client that their results are credible and actionable.
In addition to discussing the specifics of the fast food project, the case also provides an overview of the people analytics field more broadly through the lens of McKinsey’s client portfolio.

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Henry Tam and the MGI Team

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