Bringing in new staff to run and, hopefully, improve the performance of a business means that payroll – alongside commercial rent – is often the biggest expense a company faces; but a typical business knows comparatively little about the real motivational factors that drive their workforce once they have got them through the door.
What if smart use of data could help firms understand their employees better? How would that change the criteria on which they base their hiring choices?
Big Data is usually talked about in terms of what it can do for consumers and customer relationships, but what happens when you apply its principles to staffing?
What happens when a firm starts to look scientifically at information about its employees? What happens when it starts to apply People Analytics?
Data analysis firm Gartner provides a suitable example: one of its clients, a large financial services provider in the US, believed hiring candidates who attended good colleges, and had high grade-point averages, would bring sales success. Then, a few years ago, one of its own analysts looked at the sale performance of new employees over their first two years and compared overall performance and retention rates against a variety of factors.
The results, said Gartner, were astonishing.
The factors that actually drove sales performance didn’t at all match those the financial services firm assumed were key.
What really drove sales was the ability of new employees to work in unstructured conditions, some success in a previous job or successful experience in a high-priced sales job, having completed some education, and an accurate and grammatically correct CV.
What didn’t matter was where the candidates went to college, the grades they achieved, and the quality of their references. Data told a different story to the perceived belief of what contributed to success, and once this was fed back into the recruitment process, the company recorded a $4m improvement in revenue in its next financial period.
The story isn’t an isolated one: McKinsey reported how a leading healthcare organisation used similar techniques to generate savings of more than $100m as it also improved the engagement of its workforce through discovering that highly-variable and unequal pay was disturbing employees and causing attrition. When an optimal maximum and minimum threshold was reached, performance and engagement improved.
“The implications [of using People Analytics] are dramatic because talent management in many businesses has traditionally revolved around personal relationships or decision making based on experience—not to mention risk avoidance and legal compliance—rather than deep analysis,” the McKinsey Quarterly said recently.
“Advanced analytics provides a unique opportunity for human-capital and human-resources professionals to position themselves as fact-based strategic partners of the executive board, using state-of-the-art techniques to recruit and retain the great managers and great innovators who so often drive superior value in companies.”
In much the same way as it’s removing the guesswork from customer-facing parts of a business, Big Data is now helping take assumption and hunches out of the recruitment process by helping to define the real characteristics a firm is looking for in its candidates.
While this use of data can certainly bring radical change to a firm’s hiring principles, when it comes to the practise of getting candidates through the door, analysis is likely to reinforce some of the fundamentals.
Put simply, the criteria used to judge a candidate’s worth may change, but the need to find and screen the right candidates will remain vital.
In fact, when your requirements are increasingly specific, the search for a good pool of candidates from which to draw, and the need to retain a high-quality executive recruitment search team, becomes ever more important.