In April 1965, Gordon Moore, one of the co-founders of Intel Corporation, predicted in the journal Electronics that computational processing power would increase year-on-year by a factor of two—later revised in 1975 to occur biennially. 43 years later, his hypothesis still rings true.
Indeed, the exponential growth of computer processing since Moore’s Law was incepted has guided us towards a technological epoch in which change is happening at a quicker rate than humankind can adapt to it.
Alongside this progress, the emergence of big data has created new possibilities for companies to mine, analyze, and use vast quantities of data to drive internal growth.
Human Resources (HR) teams within companies are now able to streamline their strategic vision with the help of hard, objective evidence. HR teams are having to adapt and modernize, challenged by the notion that big data analytics gives them a lot more scope for understanding where key areas of productivity are within a firm, and what areas need developing.
Research suggests that organizational change is enacted and better-shepherded if a company understands the social networks of its employees, explains Brandy Aven, associate professor of Organizational Behavior and Theory at Carnegie Mellon, Tepper School of Business.
“New research also indicates how organizations might quantify and understand their culture, which in turn can inform smart hiring decisions,” she adds.
That is why companies are hankering to amass as much data on their employees and processes as possible to help tackle a multitude of performance goals. Brandy says that this is why Google is set apart from its competitors in terms of talent attraction, development, and retention, by constantly collecting and analyzing data on its most valuable asset; its people.
Brandy points out that HR managers and leaders are beginning to realize the value of making data-driven decisions.
“Data analytics is central not only to HR Management but to organizational leadership,” she says. “[It] presents new ways to measure outcomes and processes that until recently had been a ‘black box’ to many HR managers, such as how the sentiment within a team, branch, or division affects talent retention.”
How are business schools adapting?
At Tepper, MBA students are taught that every decision from operations to HR is driven by data. This transcends the top layer of business, as students are taught to understand every nook and cranny of an organization through data and modeling advances.
Brandy teaches the Managing Organizations and Networks module at Tepper, where students collect data from a variety of sources like Compustat, Glassdoor, independent interviews, and surveys to examine critical aspects of organizations.
The novel ways of teaching MBA students the potential of data analytics in relation to company growth has sparked an interest in this new wave of data-savvy grads.
“Companies are coming to us looking for ways to attract, develop, and retain top talent,” Brandy says. “They want to know how to foster better team collaborations and facilitate effective organizational change.”
Dave Ulrich, professor at Michigan Ross and the founding father of modern HR, who spoke at the recent executive education MERIT Conference in Lisbon, notes that top business schools have relied on data analytics for HR training for decades.
It is the increase in capacity though, and the ability to hold much larger quantities of data than ever before, which means whereas in the past a company’s strategy could suffer from myopia, there is now a much larger, solid base of objective evidence to work from.
“They [HR teams] will be able to sift data-based HR insights and recommendations from personal opinions; identify and invest in HR practices that have an impact on company goals; help identify talent, organization, and leadership choices that will deliver employee, customer, and investor results,” adds Dave. “They should be able to bring rigor to their recommendations.”
More than modular mundanity
Sebastian Reiche, associate professor of Managing People in Organizations at IESE Business School, and the associate editor of Human Resource Management Journal, agrees that data analytics provides a means to better justify the decisions of HR teams.
HR needs to become more “heterogeneous”, Sebastian says—a change he’s starting to see.
“More candidates are moving from different functions into HR,” he explains. “and more MBA grads are moving into rotational positions where you might end up in HR but you experience functions like marketing, and finance.”
Working in HR now means speaking the language of engineering, marketing, sales, and finance, and understanding the issues around what the business is actually about more broadly—“this leads to asking the right questions,” Sebastian says, “otherwise you are just flooded by data that you don’t know how to use.”
For Sebastian, the future is an HR function more ingrained within the wider strategy of the company itself. “If HR has to be strategic it doesn’t make sense to have it exist as its own function, as a lot of the problems that need to be solved will be cross-functional,” he says.
The fresh potential of HR comes with one major caveat though, Sebastian warns. Cue, a paradox whereby in trying to justify itself by coalescing with analytical developments, HR forgets its roots, and loses the purpose for which it was originally invented.
“There are still a lot of qualitative issues to deal with, solving personal issues, making decisions about fit corporate values,” Sebastian concludes, “[and] the risk is that HR jumps on that bandwagon of ‘we need to justify our existence through data’ and forgets its USP.”