By Stowe Boyd, Managing Director, Gigaom Research
The growing availability of more data may be a path away from the perception that human resources (HR) is stuck in the past. In a recent KPMG report, fewer than half of non-HR executives agree that HR leaders are ‘able to clearly demonstrate tangible correlations between people management initiatives and business outcomes’.
HR is basically out-of-step with modern evidence-based management approaches, where the best available scientific evidence and analysis is applied to decision-making. This has been well-developed in medical, policy, manufacturing and technology domains. And the emergence of big data-driven analytic tools is putting real pressure on HR to join the evidence-based management movement. David Feinberg, CEO of the UCLA Hospital System and president of the UCLA Health System, said, “HR is still suffering from an old school approach. Our workforce is changing, their demographics are changing, the patients they are caring for are changing. But, I don’t think we are seeing a similar level of change within HR.”
However, things may be improving: The percentage of respondents to a 2014 KPMG-sponsored survey who said their organization’s HR excels at ‘insightful and predictive analytics’ increased to 24 percent, up from 15 percent in 2012. But 24 percent is still fairly low, relative to what companies would like, obviously.
Overcoming obstacles
The barriers are considerable: Data is disorganized, and there is a cultural resistance to moving to evidence-based management thinking. Per Scott, vice president of Human Resources at RBC, said: “Evidence-based HR can be especially threatening to people if they don’t have the skills to participate in the transition to a new style of management. What does this all mean for their future? The pathways to business decisions also start to change, and that affects people’s perception of where they stand in the company.”
This approach also raises the stakes in terms of responsibility, according to Rob Briner, professor of Organizational Psychology at the University of Bath, said “Evidence suddenly makes people accountable, quite an uncomfortable feeling for some people.”
As one example of how evidence-based decision-making led to really significant results consider this case study from Abhishek Mittal. He was working with a client company where the leaders were pushing back on employees who were transferring across business units because they believed their technical competencies would not transfer well. Mittal created an analysis plan, examining careers of those who actually moved across business units. He said:
“After a few days of number-crunching, the verdict was out – high-potential employees who moved across businesses achieved an average 7 percent more than those who moved within their business units. This easily helped changed [sic] mindsets at the executive leadership level and led to wider roll-out of their talent mobility program.”
Lazlo Bock, Google’s head of People Operations, is perhaps one of the best-known advocates of data-centered people analysis. Google looked into the issue of work-life balance as an aspect of a twice-yearly survey, but has reframed the discussion as being about well-being: Work-life balance – in today’s connected, high-velocity world – is a red herring, he argues. What did the company discover from its analysis? As Bock explains:
“[…] only 31 percent of people are able to break free of this burden of blurring. We call them “Segmentors.” They draw a psychological line between work stress and the rest of their lives, and without a care for looming deadlines and floods of emails can fall gently asleep each night. Segmentors reported preferences like “I don’t like to have to think about work while I am at home.”
For “Integrators,” by contrast, work looms constantly in the background. They not only find themselves checking email all evening, but pressing refresh on email again and again to see if new work has come in. (To be precise, people fall on a continuum across these dimensions, so I’m simplifying a bit.)
Of these Integrators (69 percent of people), more than half want to get better at segmenting. This group expressed preferences like, “It is often difficult to tell where my work life ends and my non-work life begins.”
The fact that so many Integrators want to have a greater separation from work is troubling. Based on those findings, Google’s Dublin office created a program to help Integrators called Dublin Goes Dark, where employees could drop off mobile devices at the front desk on their way home, helping them to disconnect.
But the most important takeaway from this – and the Mittal case study – is that the companies involved are shifting to take actions based on evidence and scientific analysis, and not relying on guesses, hunches, and folklore. So, we might face barriers, but we’re headed in the right direction.
This post was written as part of the Dell Insight Partners program, which provides news and analysis about the evolving world of tech. Dell sponsored this article, but the opinions are my own and don’t necessarily represent Dell’s positions or strategies.