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The predictive art of retention – using data to keep your people

As the number of people voluntarily leaving their job roles continues to rise, businesses are experiencing a new workplace phenomenon: the ‘quitting economy’. With the concept of ‘a job for life’ fading further into the past, a new generation is shifting employment from a buyer’s to a seller’s market – posing serious questions to key decision makers about talent retention.

In its 2018 Millennial Survey, Deloitte found that 43 per cent of millennials plan to quit their current job within two years and only 28 per cent plan to stay for more than five years. What’s more, with a new report from Tech Nation recently revealing that job vacancies within the tech industry are at an all-time high, the competition to find the best people and keep them is harder than ever.

Replacing a valued member of staff is estimated to cost up to twice as much as that person’s salary – due to recruitment costs, a fall in productivity and increased training investment. This, coupled with the potential negative impact of staff churn on workplace culture, means business leaders can no longer expect to keep their best staff without making retention and recruitment part of their longer term business strategy.

Within this new, intensely competitive environment, more companies are turning to people analytics to predict and prevent problems within their workforces. This emerging field works by exploring, inferring and communicating significant data patterns to both initiate and support business decisions related to personnel.

Obtaining a ‘Google Earth’ view of the workforce

People analytics revolve around businesses collecting and interpreting accurate data to pinpoint user behaviour and obtain a more holistic view of their people. And as big and small companies scale, only data can provide the level of insight necessary for the C-Suite to really understand their employees. By gleaning valuable insights from this data, leaders can answer business-critical questions like where their best employees come from and why people are leaving the company.

Collecting the right data from an exit interview, for example, can help companies understand their employees’ incentives, allowing them to prioritise where their efforts are best focused going forward. This could be in the form of offering different challenges, more flexible working hours or even better remuneration to existing employees.

Moreover, using data to map key influencers within companies is crucial for predicting in advance the affect that person’s resignation will have on their teams.

Making a connection early and understanding an employee’s motivations as they progress through a business is reliant on valuable data. But it’s one thing to gather this data and another to analyse and act on these insights effectively. If executed well, businesses can use the results to take a data-driven approach to people-related decisions.

Implementing people analytics

When it comes to people analytics, companies cannot rely solely on traditional methods such as annual employee reviews. Additionally, legacy HR technology is not equipped to gather the necessary information from data to allow companies to evaluate their workforce. In fact, people analytics requires companies to completely rethink their entire approach to HR tech and data science.

In practical terms, companies need to centralise employee data from across the whole organisation, incorporating every department such as sales, operations, tech teams and so on. It is imperative that people analytics is not just left to HR. The whole company must cultivate a data-driven ethos, making it routine for employees and managers to input relevant information into the relevant system.

While in the past only larger companies have had the resource to deploy data-driven HR strategies, times are changing. There are many new people analytics solutions on the market that are simple to implement and that automate many admin-heavy tasks. So, once organisations integrate a core HR technology platform with these other solutions, they can gain a broader understanding of exactly what people-driven decisions will yield the best results.

However, when implementing people analytics within a company, it is crucial that organisations ensure the quality of their data is high. Protecting employee data should also be a central priority, making sure that they are complying to data privacy regulations such as the EU General Data Protection Regulation or the California Privacy Act.

Business outcomes

By analysing people data to make informed decisions, companies can employ solutions to keep their best people, while also streamlining processes and improving business efficiency. For example, according to a McKinsey case study, one restaurant chain used people analytics to boost its knowledge around which variables contributed to the company’s success, analysing its data to better understand its frontline staff.

By using data to map its talent value chain, the company delved into who is hired, how individuals are managed and what they do – reaching interesting conclusions around management styles, personality traits and shift patterns. And after making changes based on these results, its customer satisfaction scores increased by over 100 per cent

While it might be impossible to stem the flow of the ‘quitting economy’ entirely, using people analytics to really understand your people can reduce its impact significantly and improve business outcomes as a result. Ultimately, creating and maintaining a central truth and having actionable insight that can be mobilised in a strategic and timely fashion is at the heart of attracting and retaining the best talent.

Joel Farrow, MD, EMEA, Hibob

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