Enhancing Productivity Through Workforce Analytics

Our Thinking / Voice on Growth Economies /

Enhancing Productivity Through Workforce Analytics
Calendar06 七月 2017

In the current volatile macroeconomic environment in Asia, raising workforce productivity remains a key, albeit daunting, lever for most organizations. In addition, rising wage inflation, skills gaps amidst increasing automation, ineffectual leadership and low workforce engagement levels are making it difficult for firms to deliver further productivity gains.

In our client work focused on improving workforce productivity, we often think about the causal chain that suggests that effects are an outcome of a unique blend of causes and conditions. For instance, if we are trying to improve sales productivity, we consider the capability sets (“cause”) that lead to high productivity as well as the organizational conditions (“conditions”) that allow a talented sales person to reach his or her full potential.  The goal of our analytical effort is thus to uncover these factors so the organization can make systematic changes to improve productivity (in this example, boost performance across the entire sales team).

This article examines how organizations can leverage workforce analytics to solve for the productivity challenge, including three steps for a successful workforce analytics project.

A Case in Point: Workforce Analytics at a Large Asian Retail Bank

In our work with a large retail bank in Southeast Asia, we were able to deploy workforce analytics to not only unearth underlying productivity issues, but also to strategically address those issues.

The bank was facing over 80% attrition of their frontline sales staff. That coupled with continuing pressures on margins meant that the sales leader was unable to replace every employee she was losing.

Upon investigation, we found that top quartile sales professionals performed 80 times better than those in the bottom quartile. This was a clear indicator that perhaps even more critical than hiring for the right skills was the need to stop hiring for the wrong skills: those found in that bottom quartile. We could lift productivity just by curbing the hire of “poor performers,” accomplished by applying more robust assessment tools at the time of hiring.


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