Demystifying Talent Analytics for HR Leaders

Demystifying Talent Analytics for HR Leaders

Published 12th November 2015
Dr Andreas Raharso

Chief Data Scientist at Organisational Analytics

Published 12th November 2015

Talent Analytics is a field where various myths prevent HR leaders from unlocking the potential of data. Dr Andreas Raharso debunk the myths, and through examples, shows how companies can use talent analytics to improve their bottom line.

The most pervasive logic behind talent management is: performance can be improved by a combination of rewards and penalties for good performance and bad performance. Or stated differently, the carrot and the stick are a HR leader’s tools for talent management.

Unfortunately, this logic does not always work. People work harder and are more innovative simply when they have freedom over how they work or if they have an empowering boss, among other factors. This new fact creates an opportunity for cost saving while still remaining a high-achieving organisation. However, HR leaders are rarely able to tap into these savings because performance and reward frameworks are not tested to see if they deliver on expected outcomes.

For example, a HR Director read an analytical report which showed that a big bonus last year actually contributed to the decline of sales in the next year. Many leaders mistakenly think that a bonus after achieving a sales target will automatically increase the next year’s performance. This can be a costly assumption.

Talent management requires constant analytics to validate input against output-- this is essential. Most HR leaders are still sceptical about talent analytics. In a 2015 survey by Deloitte, only 4% of organisations believed they had the predictive talent analytics capabilities compared to what they needed. HR leaders mistakenly believe that, because people can be unpredictable, analytics should not be used to predict people. This begs the question, if this is correct then why would HR leaders believe that financial rewards always lead to higher performance?

Data, not instinct or other companies’ best practices, should drive decision making, especially in HR. The goal of talent analytics is to validate if a basic assumption still holds true. For example, an oil and gas conglomerates discovered that, after analysing data, the salaries of 30% of their employees represented almost 60% of their total employee expenses. The issue was that the 30% no longer generate enough revenue to cover the 60% as predicted. The analytics then found the root cause and suggested a new initiative to restore productivity.

How to Implement Talent Analytics

The most crucial step is to understand that good talent analytics is a result of good research. Contrary to current beliefs, buying expensive software or implementing a sophisticated HR management system will not automatically guarantee accurate analytics.

Companies have to systematically investigate talent management problems in order to establish validation and reach new conclusions.

While statistics are necessary to perform talent analytics, a person who has experience in applying and interpreting the statistical research in the context of HR is also essential. For instance, a HR leader who has an understanding of how to do a simulation to predict the necessary workforce to support a company’s global expansion is valuable. HR leaders should use statistics to make their current talent decisions and need a willingness to adjust based on the facts and numbers.

Finally, data does not guarantee a solution to a talent management problem. A company needs the right data to solve a specific problem so analytical findings are unique and could potentially be conclusive. HR should be aware that the data needed to solve their problem might not be available in the current system.

A couple years ago, a company wanted to know if implementing a reward system lead to an increase in their talent productivity. In this case having data on salary alone was not enough; a small set of data on employee engagement, medical leave usage and employee turnover was needed to find the right answer to a question on incentives. This “low-hanging fruit” is easily available but is often not included in a dataset.

Talent analytics should not be seen as a challenge to the expertise of HR leaders. It should be looked at as an essential tool to help make better and more informed decisions, which will lead to more accurate HR decisions and better financial results.

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