Good data doesn’t naturally equate to good business decisions, but it’s certainly a starting point. After all, data can only seek to inspire better human judgement, but few would argue against the fact that it’s better to put science ahead of gut feeling, especially where HR and people management are concerned.
There has been a great deal of talk about big data and analytics, and their potential is unquestionable. Yet how can HR unlock its true value and what does that look like in practice? HR tools are taking best practices from data-driven consumer applications, such as Netflix, that make recommendations and inform human judgement based on analytics and customer information. But what does that mean for HR? Given the cost of recruiting and replacing employees, HR leaders could do with a crystal ball when searching for new talent. According to research from ERE Media, one-third of new hires quit their job after about six months. The challenge intensifies when you add to that the findings from the Deloitte Global Human Capital Trends 2015 global study, which shows that 87 percent of companies now rate “retention, engagement, and culture” as an important imperative and 50 percent rate it “urgent.”
What is painfully clear is that there has to be more to talent management than guesswork. HR is increasingly turning to machine learning and data science in an attempt to take a data-driven approach to these challenges. In the UK, a recent CIPD report – co-created with Workday – showed that more than 92 percent of HR leaders are actively engaged with analytics projects. Despite strong uptake, there remains a great deal of work to do in terms of resourcing HR analytics projects and raising awareness of their value across non-HR business functions. Using analytics to unravel the talent conundrum should be a major priority for HR leaders. Imagine a tool that allows companies to get a better look into which employee is likely to quit, and the options that need to be considered to retain that person. In the next phase, HR should be able to take information—including time between employee promotions, time in current job, and the number of job functions an employee has held—and combine that data with online recruitment data to build a picture of how much it would cost to replace that employee.
Today’s technology goes even further, advancing beyond predictions to provide intelligent recommendations to employees, such as what career moves would be best based on fellow colleagues’ career trajectories. It can also help employees understand what sort of training and development makes sense at this point in their career, and identify where skills gaps exist. These recommendations are delivered in a similar fashion to Netflix customer selections, taking a predictive model of what could happen next and adding context, so employees can be given something more prescriptive, like a specific career recommendation. For example, have colleagues with similar skills successfully moved into a role that would not traditionally be considered by HR to be a natural career path? This illustrates the true value of analytics to HR. HR teams face a number of challenges today – such as the battle to recruit and retain talent, and the need to help the business quickly make the correct strategic decisions on its workforce.
If these are to be overcome, it’s clear that analytics must deliver increased value to HR departments in the coming months and years. The important thing to remember is that analytics alone will not solve these challenges. HR needs most of all to drive employee engagement, and focus on the underlying tools, such as recommendation systems, which use good-quality data to help employees and business leaders make better decisions. HR needs better and more consistent analysis of workforce data to inform and support business strategies. Organisations also need to know how to retain their best talent and recognise when it might be time to promote millennial employees, or find new opportunities to keep them engaged and challenged and develop their skills. Analytics solves both of these problems and more, and that’s part of the reason why it’s set to be a major HR trend for years to come.