Measure for Measure’s Sake

Workforce analytics, the use of employee-related data to inform decision-making in human resources, is now the subject of many conferences and thought leadership papers. But what has it actually achieved? Are we just witnessing a massive public relations exercise by an emerging industry?

The use of analytics in HR is a recent phenomenon, and that in itself is worthy of comment. ‘If I were an HR executive, I wouldn’t boast about using evidence as if it is a great discovery,’ says Rob Briner, Professor of Organisational Psychology at Queen Mary, University of London and Scientific Director of the Centre for Evidence-Based Management. ‘Other functions, such as marketing, have been using it for decades.’

HR analytics claims success in two main areas. The first is employee engagement. ‘For almost twenty years, the “success story” of many analytics groups has involved showing that employee engagement levels were markedly higher in units with better results,’ says John Boudreau, Professor of Professor of Management and Organisation at the University of Southern California’s Marshall School of Business.

The second is employee retention, helping organisations identify why any individual might want to leave, and then prevent it. ‘Recently, analysis has actually started to generate a “turnover risk” on individuals’, says Professor Boudreau, ‘so that organisations can claim to predict which employees are in danger of leaving, even before the employee knows it.’

Cause or effect?

Despite the fanfare, doubts persist. For starters, is the research methodology sufficiently rigorous or the conclusions verifiable? Management consultancy research linking increased engagement with better performance may indicate a correlational, rather than causal, relationship, a line that some might blur for commercial reasons.

In his iconoclastic book, The Halo Effect, Phil Rosenzweig examined employee satisfaction ratings at Cisco. It was very high when the company was doing very well at the turn of the millennium, and much lower when performance deteriorated and layoffs began. ‘Does employee satisfaction lead to high performance,’ he asks. ‘Probably, but it’s hard to say how much, and it turns out the reverse effect is stronger: company performance is a more important determinant of employee satisfaction.’

Moreover, how does one measure with any accuracy individual performance in a knowledge economy? What is the individual contribution of someone in a 30-strong marketing team to a specific marketing campaign? Can one even properly measure the impact of the marketing team itself, in isolation from other factors, on financial performance?

Professor Briner argues that individual company studies fail to capture the whole story. Too often, they neglect decades of usually more rigorous academic material on the subject. ‘It’s like going to the doctor with a medical problem, and being subjected to lots of tests, while the doctor studiously ignores all the general scientific evidence about the same symptoms,’ he says. That’s hardly surprising. Such material tends to be written in arcane academic language or lurks behind a paywall, he adds. It would be hard to know where to start.

Means to no end

In their enthusiasm for analytics, HR executives often fail to ask whether such discoveries are even commercially relevant. Assuming it was possible to predict when a key employee might leave—putting aside all the other complex individual motivations—why would such information be so useful? Wouldn’t resources be better spent reducing the organisation’s dependence on specific individuals? In fact, perhaps, some staff turnover is healthy by making way for fresh ideas.

HR analytics may yet revolutionise talent management. For now, the hype seems more evident than the practical benefits.