Is HR getting People Analytics wrong?

Is HR getting People Analytics wrong?

Analytics offers many possibilities, but it also has implications...

Would it be useful for you to know when your employees are considering quitting? What about being able to identify the moment candidates become disengaged during recruitment? Or, imagine being able to detect the most common health issues in your organisation so you can plan ways to deal with it?

People analytics is a rapidly developing field, promising to offer you all this, and more. Companies such as Qlearsite, are using the latest research techniques in AI and machine learning to spot trends and patterns in the huge amounts of data you can store on your employees.

“Who is most likely to leave? Who will be most productive? What will be the future performance of people who have received training? Who will be most likely to be promoted? Like any scientific discovery process, we don’t place limits on the questions we can answer – accordingly our technology is built to predict all KPIs and the drivers of any recorded employee behaviour,” explains Peter Clark, Co-Founder of Qlearsite. “This flexibility is hugely powerful.”

However, some firms still have not grasped the possibilities. Gero Pickert is the Vice President of HR for Nokia. He believes people analytics is going to grow in importance, but HR needs first understand it to remain competitive.

“For most, it is a very new territory,” he explains. “There is no doubt about it: The potential is huge. The question is more how to manage the use in a compliant and sustainable way. While technology is racing ahead, it might be the biggest challenge – especially in HR – to qualify our people to be able to make good use of the new possibilities. We are dealing with very sensitive data – you cannot afford to make mistakes by ‘driving too fast’.”

Yet, some organisations are already putting this into practice, such as pharmaceutical giant AstraZeneca. Maggie Spong, the firm’s Vice President Talent Acquisition, explains data on staff retention is helping them to inform and refine their strategies. “We have a really good analytics team,” she says.

“We don’t want to fall into a cycle of ‘we hire, they leave, we hire’, so we look at the data to give us an insight into why they are leaving. Sometimes it is the manager, so we can offer them training to prevent it happening again. Sometimes, it’s the environment, or their day-to-day work,
or an experience they have had.” 

The key is, that once the HR team can see where the problem lies, they are far better equipped to reach the root of the problem and fix it. “We’re starting to look at reasons, rather than just tracking our attrition rates,” said Spong.

However, Alec Levenson, a Senior Research Scientist at the Centre for Effective Organisations at the Marshall School of Business, warns that it is all too easy to approach analytics from the wrong angle. “Turnover is a classic bit of information that people want to understand from their analytics, but it’s not as simple as just trying to get that number down,” he warns. “You might find, for example, that you’re losing an unacceptably large number of your high performers.

“But your high performers might be joining you because they see you as a way to go on bigger and better things – and potentially that means leaving your company. So is the way you drive down that turnover rate by hiring people who aren’t such high performers that they don’t move on? Or do you need to accept they’ll be a high performer with you for a couple of years and then they will leave after giving you that value? It turns out losing those high performers wasn’t necessarily a bad sign.”

How can you avoid misconstruing data?

“We can analyse any and all types of data, as long as it relates to people within the organisation,” Clark elucidates. “In practical terms, this means data held within the core HR systems that hold descriptions of people within the organisation, their job, their tenure and other basic information. We then add all of the other rich forms of data that can help inform our analysis, such as training and learning management systems, recruitment systems and performance management systems, etc.” Qlearsite then combine all of this data, to give you an overview of your employees.

You can also attach data that records the conversations held between employee and employer, such as performance reviews and training assessments, to give a more qualitative overview. “Importantly this information captures the soft, qualitative, contextual information that informs the hard, quantitative data on productivity, performance, sales and the people KPIs that matter to a business,” said Clark.

Whilst gathering your data sets may seem useful, it’s essential that you’re asking the right questions to extract the analysis you need. Levenson explains: “For example, you might want to look at your turnover rates of LGBTQ+ employees,” he said. “But if you have a limited amount of time and money, you need to put this down on a list of similar questions and prioritise them ruthlessly."

"On the other side, you have the kind of questions that are driving your business strategy – such as where people are collaborating well, or where they are sharing key information. These are the questions asked by the C-suite, the ones addressed by the strategy consultants. But they aren’t questions we’re currently turning to people analytics for.”

Therefore, the wisest way to approach analytics, would be to avoid expecting it to answer everything at once. “Don’t try to do it all in one big step,” Pickert advises. “The topic is still only developing, technology is a little less mature than some suggest, and we need to afford the organisation time to learn.” Instead, he suggests a pilot installation, with a small team keeping private data well under control is the best way to evaluate how it can benefit your organisation.

Following that, in Levenson’s opinion, analytics work best when it brings together business problems and people problems. “The problem comes when there are two different groups of people dealing with these two types of question,” he said. “One isn’t an expert in business, and one isn’t an expert in all the people issues such as staff motivation. You see a bifurcation, with business problems on one side and people problems on the other. People analytics as a function will evolve when it can bring those two together.”

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