HR Must Walk Before It Can Run a Talent Analytics Program

Great Article from our HR Blog by Brian Kropp

Across the last few years there has been a massive rush by most organizations to make significant investments in talent analytics—in fact, in a recent survey we conducted at Gartner, 74 percent of organizations said they were planning on increasing their investments in talent analytics in the next year.

While there certainly is great potential in the use of talent analytics, Wharton management professor Peter Cappelli argues in the Harvard Business Review that companies shouldn’t simply be throwing money at it with the hope that something good happens. Most HR functions, Cappelli points out, don’t have enough high-quality data to justify a sophisticated analytics project:

As with most of “the next big thing” stories in business, big data is really important in some areas, and not so important in others. As a literal definition, HR does not actually have big data, or more precisely, almost never does. Most companies have thousands of employees, not millions, and the observations on those employees are still for the most part annual. In a company of this size, there is almost no reason for HR to use the special software and tools associated with big data.

For most companies, the challenge in HR is simply to use data at all — the reason being that the data associated with different tasks, such as hiring and performance management, often reside in different databases. Unless we can get the data in those two databases to be compatible, there is no way to ask even the most basic questions, such as which applicant attributes predict who will be a good performer. In short, most companies — and that includes a lot of big ones — don’t need fancy data scientists. They need database managers to clean up the data. And they need simple software — sometimes even Excel spreadsheets can do the analyses that most HR departments need.

This data quality problem is truly the big (and not at all sexy) problem that most talent analytics functions are facing. Another data point from the survey mentioned above: 70 percent of talent analytics executives cite data quality as the biggest barrier to doing their work. Which raises the question: What can you do to improve the quality of data in the organization?

While most companies turn to buying new systems and new technologies, what the best talent analytics executives are doing is building better relationships across the HR function and the broader organization to improve the quality of the data entered into their systems. Building the right relationships is more than twice as effective as buying new technology when it comes to improving organizational effectiveness at talent analytics.

View our new webinar replay to learn about the most effective strategies for improving talent analytics.

By Brian Kropp