Back in 2011, Google CEO Eric Schmidt said that ‘every two days we create as much information as we did from the dawn of civilization up until 2003’.It’s a mind-boggling concept, but there’s no getting away from the prevalence of data in the business world.
Traditionally however, human resource departments have been among the slowest to use this to their advantage. Much of this, it can be argued, is that HR analysis tends to focus on the past – for example how many staff have been hired, the number of days taken off sick and the volume of training delivered – rather than looking to the future to see what it may hold. Meanwhile, many decisions regarding recruitment are often taken on a ‘gut feeling’. It’s fair to say that few businesses would take this approach with any other vital aspect of their operations.
The rise of ‘people data’, or HR analytics, is rapidly changing this trend. As a result companies are now finding out that they can also use their existing data to answer other business-critical questions, such as ‘How do pay grades relate to improved performance?’ and ‘What ROI will a new training program deliver in terms of sales?’
A lot of the methods used aren’t new to achieve this – such making sure information across business units, geographies and systems is consistent –
but it’s only really since the rise of Big Data that they have becoming commonly used by HR teams. And, as ever, getting the right results takes time and effort.
“The answer does not lie in purchasing expensive technology solutions,” said David Green, business development director with HR outsourcing firm Ochre House recently.
“A fool with a tool, is still a fool – but in simply doing a better job of applying existing data insights to critical business questions. Moreover, it needs to present the insights in a language the business understands. Chief executives want HR data to be like financial data: standardized, specific and clearly linked to outcomes.”
Knowing your goals
This is solid advice. Yet to make it happen, there are a few key points that you should consider before diving deep into your spreadsheets:
It’s vital that the information used is right for the issue at hand. Start with the question you need to answer, not the one you think the data will provide.
The quality of the data is essential.Remember, major decisions are likely to be made off the back of these numbers, so make sure they are correct.
You shouldn’t be expected to draw your own conclusions from the figures that you’re presented with. Instead, there should be a clear narrative, ideally one that shows cause and affect.
As Green says, the findings need to clearly be linked to outcomes. If you can show that steps can be taken to increase revenue, improve staff retention or lower outgoings, then you are on to a good thing.
Sam Wright is a journalist based in Norwich, Norfolk. He writes about small business issues, productivity and the online world.