PREPARE to increasingly hear two words this year: workforce analytics. In 2009, IBM found just 28% of 400 HR professionals used any form of analytics for defining knowledge, skills and capability requirements needed to execute the business’ strategy. Since then, an extra 500,000 people in the UK are jobless, tuition fee rises have seen a 10% drop in university applications and no retirement age now means the number of people working beyond 65 is projected to be 6% (up from today’s 2.9%) by 2019.
“These are the things that are forcing businesses to move from being process-based and inward looking, to being far more predictive and outward looking,” says Roger Edwards, principle consultant at workforce analytics consultancy Pilat. “It asks where talent is, where it’s going to come from, or how it’s going to be attracted.”
It is a big challenge, because in theory so many variables suddenly seem to matter – everything from perception of the employer brand, demographic change and even world trends (for example, China will soon have more graduates than the whole of Europe combined). Howard McMinn, partner in Deloitte’s human capital practice, says: “Companies that devise headcount purely through their financials will be at-risk businesses. The next level up is about thinking about where the business is going, what people it needs, and then how this links to the finance department.”
Aberdeen Group’s 2011 HR Executive’s Agenda found that those who integrate workforce analytics data into their analytics tools are nearly three times more likely to achieve “Best in Class” than those that do not. And, says McMinn, thinking small is often not a bad way to start: “A benchmark point needs setting so FDs can see, for example, how a decline in a certain skillset could pan out, and what remedial action is needed to avert something business-critical 18 months down the line.”
Edwards adds: “Effective analytics is looking at pockets of skills rather than everyone. Good data is key, so trends in retirement, for example, can create gap analysis going forward, to work out who to promote, or who needs hiring in from outside and where they might come from.”
Technology providers have been buying analytics software companies to boost their existing offerings. Kronos added OptiLink in January, on top of other purchases since 2010. For LondonWaste, which relies on highly-skilled engineers to recycle London’s rubbish, two years’ worth of Kronos-based analytics is paying dividends.
“We’re moving from traditional compliance/hours worked analysis to using data to predict future staffing levels,” says chief IT officer Mark Beattie. “We can see by overtime hours if we’re understaffed for projects; this then feeds more accurately to knowing the numbers we need when we tender for new work.”
LondonWaste has created new “floating roles” – permanent staff who dip in and out of existing projects as needed – and it also has a better picture of future skills needs by knowing retirement rates.
SAP’s head of line of business, Philip Wood, says all the main providers are now “turbo-charging” their software to make analytics work harder. “The trend will be for more ‘in-memory’ analytics (getting data onto memory – and able to be manipulated via tablets or mobile phones – that can be accessed fast),” he says.
SAP’s Mobile Skills Gap application gives HR/IT and FDs the ability to search for skills and see the real-time impact of skills gaps through mobile devices in 13 seconds. Meanwhile, Midland HR’s Matching Gap predictive analytics not only enables profiling to be modelled according to skills; the software can even be extended to those being interviewed, reviewing them in terms of what they could best offer years ahead.
“Firms did a blunt job of culling staff during the recession; often whole lines of management or product areas went without looking at what skills they had, their performance, or whether they were suited for future growth,” says Karen Bull, Midland HR’s product strategy manager. “There’s a feeling this can’t be allowed to happen again.”
Many commentators argue a genuine revival in analytics is underway, aided by more firms entering the fray, including psychometric testing provider SHL.
“We’re offering analytics around whether a company’s own staff stack up with what we know is good from a productivity, likelihood to leave or quality of decision-making point of view,” says chief product officer Paul Levitt. Ten firms are already beta-testing it.
Health and wellbeing workforce analytics can also be run in conjunction with pure skills-based analytics, because according to Jess Colling, product director at vielife: “There is hard evidence that people assessed as high risk take more days sick, are unproductive, more likely to leave and are disengaged. Some 28% of the population fit this category.”
Wood concludes: “In the past people asked questions and didn’t really get the answers they wanted or needed. Now the tools are here for joined-up heads of IT/HR and finance to plan the people strategies needed to achieve their business strategies too.” ?
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