Moneyball for HR

REVA University research group formulates a framework for Employee Life Time Value

Talent Analytics is an important function of an enterprise. Davenport argues that companies using talent analytics are likely to be performing better than others. According to his article, Talent Value Management form the backbone of a long term engagement with high-performance employees, which can yield multifold benefits.

Moneyball is a player selection/retention analytics framework, which has been successfully used to profile players and build a successful team with average but consistent players [2]. Many such studies have defined talent analytics metrics required for this analysis in HR.  One such metric is Employee Life Time Value (ELTV). Articles written by Hire and Maia Josebachvili depicts it as a graph, where the value measurement is expected to increase over time, decreasing only when the employee leaves the organization [3,4]. Maia Josebachvili observes that the benefits of applying Moneyball can lead to 2X to 6X compared to no analytics .

Researchers at REVA University RACE Labs have extended this area of research into a P3 Model; profit, performance and propensity to understand the hidden segments in the employee base to understand potential gains and risks with human resources.

The evidence-based research has analyzed HR data from multiple companies and developed a framework which segments the employees on multiple parameters into distinct groups such as high value/high cost to low value/low-cost groups and in between. The scoring of the employees based on the P3 variables has been used to segment the customer as high risk/high profit to the other end of the spectrum, low risk/low profit. They are also suggesting strategies for each of the segment based on global best practices.

It is interesting to see how this work helps organizations to reap benefits from data as elucidated by Google. Implementing this model leads to the below proactive measures,

  • Identify the strategies for getting best out of employees evidenced by data
  • Understand the career path and improve retention
  • Improve the recruitment quality over a time frame
  • Build a consistently high performing team at optimal cost and more.

To know more about this research, do write to [email protected].

For consulting and adapting this model to your organization, do check here (Link to Consulting – ELTV)

Tag: Insights; HR Analytics; Employee Life Time value; HR Metrics; ROI 



[2] Lewis, M. (2003). Moneyball: The art of winning an unfair game. New York: W.W. Norton.




Dr. J B Simha

Chief Mentor, RACE | CTO ABIBA Systems

Dr. Simha’s core competency is in R&D, business intelligence and analytics consulting. He has implemented several large scale systems for telecom, BFSI and manufacturing industries in business intelligence and analytics. He has been recognized as one of the ‘Top 10 Most Prominent Data Science Academicians in India: 2019’ by Analytics India Magazine.

Dr. Shinu Abhi

Director - Corporate Training REVA Academy for Corporate Excellence (RACE), REVA University

She leads the corporate training programs in emerging technologies for working professionals and organizations. RACE runs top ranked programs in Analytics, Cybersecurity, Artificial Intelligence both regulated and customized programs for working professionals and organizations. Dr. Shinu Abhi is a Fulbright fellow at Lehigh University, Pennsylvania. She is a certified Entrepreneurship Educator with Honours, by National Entrepreneurship Network, IIM Bangalore, Stanford University (STVP) and ISB Hyderabad and have trained aspiring entrepreneurs and start-ups and was instrumental in setting up incubation centers at two institutions. She has two decades plus of experience in industry and Academia of repute. She has a PhD and MPhil in Strategy and Entrepreneurship, MBA in Marketing and PG in Instructional Design (PGDID).

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