The debate: Are analytics over-hyped?
Author: Brian Spencer
Big data has been heralded as HR’s magic bullet. But, as these experts argue, the reality is more complicated than it seems
HR must take a proactive role in attracting, growing and retaining the best people – and that means having the right intelligence at your fingertips
An organisation needs a full, 360-degree view of data on its staff, which means HR has to become data-savvy and provide its business partners with “actionable intelligence” – getting the right information into the hands of the right people, in time to make decisions that change outcomes.
For example, Google’s HR analytics team found a spike in the attrition rate occurring after maternity leave. They worked out that they could reduce staff turnover by 50 per cent by providing more leave. The calculation was right, and the cost of an extra four weeks of leave was vastly lower than the cost of losing talent.
Google had the right structure of vision, data acquisition and processes to ensure the output was actionable. An HR leader needs a vision for their department and a strategic business question to answer with big data. Start by understanding the relationships between the data. Next, build a playbook to take action. The final stage is optimisation, where you use additional statistical data to refine the outcomes further.
Does HR need to move forward from where it is? Yes. But to deliver measurable value to their business partners, HR leaders need access to the right intelligence.
Keith Carter, visiting senior fellow, Department of Decision Sciences, National University of Singapore Business School, and author of Actionable Intelligence
You need a human touch, and the intuition that makes a great HR professional. Data won’t replace that – but it can become another string to HR’s bow
The current interest in HR analytics reminds me of when social media first arrived: companies knew they needed to embrace it, but figuring out how to do that was a challenge.
It’s expensive to roll out analytics systems globally, and when you’re talking about large organisations it’s difficult to achieve consistency on a global level. That, I think, is the source of some of the reluctance around big data. It’s a big investment and it involves a lot of change. Many companies just don’t know how to deal with it.
The world’s smartest businesses are harnessing these new capabilities in the HR function so that they can move from reporting on the past to actually predicting the future. But to get to that stage, there’s a lot of work to be done. We’ve participated in a lot of roundtables, and the general consensus is that, other than the Googles and the Facebooks, predictive analytics is aspirational for most companies at this point.
Analytics will help HR partner with the business and make better decisions. The ability to convert data into meaningful insights, and sell them to the business successfully, will be important but will be just one part of HR.
Tim Spriggs, senior director, The Chapman Consulting Group
‘Big data’ itself is a ‘big’ term that many people don’t understand. I think the concept has been over-glamourised in recent years
‘HR analytics’ simply means getting hold of relevant data for sense-making and supporting human capital decisions. Organisations need to know what kind of HR-related data is necessary to analyse a specific area. But there is no single solution for all companies, and raw data does not provide comprehensive answers – decision-makers need to understand the people issues.
Headcount or FTE metrics, for instance, are commonly compiled to monitor movement. This is relatively easy to do in reporting, but more work needs to be done to gain insight on the actual triggers of the movement. Short-term attrition data is meaningless by itself, but over a period of time, with breakdowns on the reasons leading to attrition – by department, demographics, manager, location and length of service – it can provide key insights to support plans for improving attrition rates.
Many companies measure recruitment lead time, and focus much effort on assessing recruitment performance, which again is relatively measurable. However, we should ask ourselves if we have placed an equal amount of effort on our internal staff development for pipeline building. Many people do not have a clear measurement of these efforts because it is much more difficult to quantify.
It’s important that we go back to basics, to consider what we want to measure or how we want to make use of HR data, remembering that there will be no foolproof system or solution that can fully predict human behaviours. HR professionals who can master the ability to gather relevant data, and present smart interpretations of this data to support decision-making, will evolve the most strongly.
Gey Wee Ang, head of HR, global shoe production and sourcing, ECCO Shoes
Within the next seven years, HR analytics will become like a utility – no company, of any size, will be able to do without them
Many of us working in the field don’t understand the hype around this topic when the use of analytics in HR already has a strong history. The only difference today is the greater volume of data available.
When they are properly applied, analytics help improve managerial decision-making. You can do that with small data or big data, but the more data you have the more it helps improve explanations and increases the accuracy and general reliability of the results. An over-emphasis on HR analytics, however, could be dangerous. For example, analysing people based on when they log into their systems, how long they work for and the time they take to finish a particular task – these are all objective measures that can be tracked. But that would add stress to employees because they would feel constantly monitored, and I suspect it would reduce productivity.
HR currently measures attitudes through climate surveys, but do it too often and it leads to survey fatigue and non-response. Quick-and-dirty surveys don’t really give us a good understanding. We shouldn’t be afraid to fall back on human intelligence: just going down to the floor and talking to employees. In the whole HR analytics process, there is space for both quantitative and qualitative data – an over-emphasis on one or the other is counter-productive.
Dr Damien Joseph, associate professor of information technology, Nanyang Technological University