Coaching Makena Lane

Ethan  Bernstein

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Teaching Note | HBS Case Collection | May 2019

Coaching Makena Lane

by Ethan Bernstein

Abstract

Teaching Note for HBS No. 418-031.

Language: English

Format: Print

64 pages

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Citation:

Bernstein, Ethan. "Coaching Makena Lane." Harvard Business School Teaching Note 419-082, May 2019.

About the Author

Ethan S. Bernstein

Edward W. Conard Associate Professor of Business Administration

Organizational Behavior

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Technical Note | HBS Case Collection | August 2018 (Revised August 2019)

A Note on Compensation

Ethan Bernstein and Michael Norris

This note provides an overview of the important terms, concepts, and frameworks that a manager should know about compensation—whether it be their own or that of an employee. Because compensation in practice is fraught with pitfalls, this note presents an overview of the various aspects of compensation of which any general manager should be aware to anticipate and avoid missteps. It was written for the second-year MBA course "Managing Human Capital" at HBS and would fit well in any Human Resource Management course.

Keywords: compensation design; benefits; Perks; Variable Compensation; Compensation and Benefits; Executive Compensation; Stock Options; Profit Sharing; Job Design and Levels; Labor Unions; Wages; United States;

Citation:
Bernstein, Ethan, and Michael Norris. "A Note on Compensation." Harvard Business School Technical Note 419-020, August 2018. (Revised August 2019.) View Details

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Case | HBS Case Collection | August 2017 (Revised July 2019)

GROW: Using Artificial Intelligence to Screen Human Intelligence

Ethan Bernstein, Paul McKinnon and Paul Yarabe

Over 10% of all 2017 university graduates in Japan used GROW, an artificial intelligence platform and mobile app developed by Tokyo-based people analytics startup IGS, to recruit for a job. This case puts participants in the shoes of IGS founder and CEO Masahiro Fukuhara, a first-time entrepreneur, as he considers the varied ways the "big data" he is collecting is being used--and whether some uses promised more meaningful (or less potentially misleading) impact than others.

After briefly introducing IGS, Fukuhara, and GROW, the case outlines exactly how GROW works, starting with a mobile app to assess competencies and personalities of candidates and ending with artificial intelligence (machine learning) to produce high-quality recommendations to companies about whom they should hire. The case then articulates precisely how three companies--airline ANA (All-Nippon Airways), global conglomerate Mitsubishi Corporation, and advertising/media company Septeni--use GROW in very different ways to manage talent recruiting, screening, hiring, placement, and development.

The case asks students to consider two questions: (1) Which of the three companies' approaches to using people analytics for talent acqusition and development is most appealing (or most concerning)?; and (2) Should Fukuhara turn on the most advanced part of the artificial intelligence engine, allowing GROW not just to provide recommendations to clients about whom they should hire, but also (based on performance and attribute data of previous hires) to overrule clients' specifications (or biases) about the competencies they should be targeting in their ideal hires?

Accompanying the case are the (anonymized) data one of these companies used to make their hiring decision, so that students can experience first-hand the opportunities and challenges of using people analytics in hiring. The case also provides an accessible yet thorough explanation of the key aspects of artificial intelligence (supervised, unsupervised, and reinforcement machine learning).

The case is well-suited to courses in Managing Human Capital, People Analytics, Talent Development, Organizational Behavior, or General Management.

Keywords: big data; artificial intelligence; Talent and Talent Management; Recruitment; Selection and Staffing; Human Resources; Information Technology; Financial Services Industry; Air Transportation Industry; Advertising Industry; Manufacturing Industry; Technology Industry; Japan;

Citation:
Bernstein, Ethan, Paul McKinnon, and Paul Yarabe. "GROW: Using Artificial Intelligence to Screen Human Intelligence." Harvard Business School Case 418-020, August 2017. (Revised July 2019.) View Details

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Case | HBS Case Collection | November 2017 (Revised June 2019)

Winning (and Losing) the Olympics: Boston 2024 (A)

David Fubini, Ethan Bernstein, Mark Saadine, Sarah McAra and James Barnett

Two leadership groups from Boston 2024 negotiate with government bodies, community leaders, and Olympic officials in an effort to bring the 2024 Olympics to Boston.

Keywords: Negotiation; Negotiation Process; Projects; Boston;

Citation:
Fubini, David, Ethan Bernstein, Mark Saadine, Sarah McAra, and James Barnett. "Winning (and Losing) the Olympics: Boston 2024 (A)." Harvard Business School Case 418-024, November 2017. (Revised June 2019.) View Details

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Coaching Makena Lane

Abstract

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