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Case | HBS Case Collection | August 2017

GROW: Using Artificial Intelligence to Screen Human Intelligence

by Ethan Bernstein, Paul McKinnon and Paul Yarabe

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Abstract

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: 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;

Language: English Format: Print 12 pages EducatorsPurchase

Citation:

Bernstein, Ethan, Paul McKinnon, and Paul Yarabe. "GROW: Using Artificial Intelligence to Screen Human Intelligence." Harvard Business School Case 418-020, August 2017.

About the Authors

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Ethan S. Bernstein
Assistant Professor of Business Administration
Organizational Behavior

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Paul D. McKinnon
Senior Lecturer of Business Administration
Organizational Behavior

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  • Case | HBS Case Collection | November 2017

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    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.  View Details
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  • Supplement | HBS Case Collection | November 2017

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

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    Fubini, David, Ethan Bernstein, Mark Saadine, Sarah McAra, and James Barnett. "Winning (and Losing) the Olympics: Boston 2024 (B)." Harvard Business School Supplement 418-029, November 2017.  View Details
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  • Case | HBS Case Collection | October 2017 (Revised October 2017)

    Coaching Makena Lane

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    The case offers a uniquely in-depth (and intimate) view of how Lane approaches the one-year coaching engagement and the outputs from it, including her pre-coaching self-reflection, agreed-upon purpose and outcomes, 360 feedback, the coach’s advice to her, an in-depth coach’s final report, and Lane’s one-pager of lessons learned.

    At the end of the year of coaching, Lane’s boss unexpectedly departs, leaving Lane with a direct path to promotion. Senior leadership now once again faces the difficult decision of whether to promote Lane, this time based on their assessment of whether Lane has authentically transformed through coaching or just taken superficial steps to check off boxes on the way to promotion.

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    Citation:

    Bernstein, Ethan, and Om Lala. "Coaching Makena Lane." Harvard Business School Case 418-031, October 2017. (Revised October 2017.)  View Details
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