Predictive people analytics: how is it impacting the way we manage people?

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Predictive people analytics is changing how we manage people. But how exactly?

Although the emergence of people analytics in HR is increasingly well documented, how it changes day-to-day practices for HR professionals and managers has been little explored.

To learn more about the impact of analytics on how people are managed, and the changing role of HR professionals and managers, we take a look at two recent analytics cases that improved business outcomes through people practices. 

People analytics that delivers value

Before we dive into the examples, we should take a minute to think about what people analytics, or HR analytics, is. According to researchers Sjoerd van den Heuvel and Tanya Bondarouk, people analytics is the systematic identification and quantification of the people drivers of business outcomes.

This means that people analytics is not only about optimising what HR is doing but, foremost, about driving business results through better people practices. According to Dr Max Blumberg, Visiting Professor of Leeds University Business School, “people analytics enables HR professionals to demonstrate the causal chain linking people processes to business outcomes”.

People analytics is changing how we do business for the better.

Only when there’s a focus on these business outcomes, will people analytics increase the value that HR delivers to the organisation.

This is often referred to as value-adding analytics, which is unfortunately a relevant specification that should be a pleonasm. Often vendors and HR departments will focus on reporting and providing insights using basic numbers that do not significantly impact decision making.

Case study 1: People analytics that adds value in practice at Credit Suisse

One of the better known people analytics projects took place at Credit Suisse, quite a number of years ago. The organisation was coping with high turnover in its young talent population – a lot of money was invested in attracting and training young talent, but this didn’t pay off because these workers left prematurely.

Using turnover analytics, the people analytics team was able to identify the key drivers of employee turnover and predict on an individual level which employees were most likely to leave.

In the end, HR can set a people strategy but line managers are tasked with the implementation.

How was this information distributed? The individual predictions were given to specially trained managers who would then work with these ‘at risk’ employees and see if they could move them to positions where they were more at place.

This information was not distributed to everyone – arguably to prevent awkward situations where a direct manager would ask: “Jill, I see you have an 80% chance of leaving this year. Why would you?!”

The role of the direct managers also changed. First of all, retention of employees became part of their responsibility and managers with high turnover received extra training. In addition, managers received data about the aggregated drivers of turnover in their teams. This enabled them to prevent turnover in the most tangible way.

According to an article about this case in the Wall Street Journal, these measures saved the company 75 to 100 million US Dollars in unwanted attrition costs annually.

Case study 2: Analytics at a large restaurant chain

Another case was a large restaurant chain that was coping with decreasing profits over a longer period of time. The key drivers for revenue for this chain were:

  • Customer count
  • Customer satisfaction
  • Employee turnover

The researchers that were asked to investigate this restaurant decided to map the relevant soft factors that were measured in engagement surveys and compare them to these outcomes. This resulted in the following quadrant. Note: performance on these factors is mapped on the Y-axis and the level of impact on the business outcomes is mapped on the X-axis.

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This overview was given to the managers who could then focus on areas that could easily be improved and stay away from areas that might seem relevant (e.g. compensation, career development) but didn’t make as much of an impact on the most relevant business drivers.

In the end, HR can set a people strategy but line managers are tasked with the implementation.

According to this people analytics case study, the impact of this focus was a 16% increase in customer satisfaction, 18,000 more customers a year, and 10% less staff turnover.

The impact of people analytics on the business

The elements that made the above use cases so relevant are twofold.

  1. They focused on relevant business outcomes that were impacted by people practices they could influence.

  2. They implemented their findings through clear communication and guidance of line managers and business partners. In the case of Credit Suisse, the incentives of managers were even changed to guarantee buy-in.

A lot of the articles about people analytics focus on how it revolutionises HR. However, as these examples show, it impacts the role of the manager just as much.

In the end, HR can set a people strategy but line managers are tasked with the implementation.

This has, of course, always been the case. However, analytics enables an easier buy-in from managers as the relevancy and impact of the HR policies becomes much clearer – especially when these are connected to business outcomes.

The role of HR in regards to people analytics will focus on implementing these changes and coaching managers to make better people decisions. This role is especially relevant for the HR business partner who is in constant touch with the line manager.

Ultimately, people analytics is changing how we do business for the better.

 

About Erik van Vulpen

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