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WORKFORCE INTELLIGENCE

Introduction

What is Workforce Intelligence?

The practice of analyzing data related to human capital started about two decades back with pioneering work done by companies like GE, Motorola and the famed Saratoga Institute. At the time, HR was largely thought to be an experience and intuition-led area with decisions guided by experienced judgment about how people will react.Several factors contributed to growth into the area now known as "Workforce Intelligence".

These factors are:

  • Increase in empirical studies in behavior science - researchers started looking for data and experiment based methods to find a cause-effect analysis into human behavior.
  • Collaboration between data scientists and Subject Matter Experts in behavior science - this made advanced statistical tools available to either prove or disprove what the subject matter experts already thought they knew.
  • Availability of data modeling tools.
  • A general shift in management from experience and hierarchy based decisions to data-driven decision making.

Applications of Workforce Intelligence:

What are the uses of workforce intelligence to an organization? There are many applications of this powerful methodology, which can become differentiator for organization success:

  • To identify potential great hires
  • To analyze and optimize staff costs
  • To identify high potential future leaders
  • To predict and de-risk attrition of high performers

Specifically, Workforce Intelligence spans Talent Acquisition, Talent Development, Succession Planning, Leadership Development, Performance Management and Rewards areas.

How to build a Workforce Intelligence Practice?

Building a Workforce Intelligence practices requires several disciplined steps:

  • Developing hypothesis and business questions
  • Building internal datasets
  • Using business intelligence across internal datasets and business processes
  • Using systems for statistical and analytics
  • Building algorithms for multi-variate analysis and testing hypothesis
  • Using statistical results for better quality decision making
  • Using results Big Data and external benchmark results
  • Predictive modeling and future scenario building

Conclusions:

Workforce Intelligence, with its progress in the last five years, is being used to make a big impact on business decisions. The statistical and data-driven approach is helping businesses to make smarter decisions with respect to people practices