GROW: Using Artificial Intelligence to Screen Human Intelligence

Synopsis

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.

Copyright:

2017

Book Details

Book Quality:

Publisher Quality

Publisher:

Harvard Business School

Date of Addition:

07/18/18

Copyrighted By:

President & Fellows of Harvard College

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Business and Finance

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.