Analytics is the new buzzword in talent management, but that doesn't mean it's the new reality. For all of the business insights HR data promises to provide—predicting performance, boosting engagement, improving succession—there are as many questions about how to implement a data program in the first place.
While three in four companies believe using people analytics is important, only 8 percent think their organization is "strong" in the area—with no improvement since 2014. Analytics programs require a significant investment of time, money and resources, presenting a challenge for busy and budget-strapped HR departments.
But for those who invest, the payoff promises to be great: A Bersin by Deloitte study found that companies using sophisticated data analytics see 30 percent higher stock market returns than the S&P 500, and that HR teams are four times more likely to be respected by their counterparts for data-driven decision-making.
We sat down with Josh Bersin, principal and founder of leading HR research firm Bersin by Deloitte, for some Analytics 101. Here, Bersin discusses why HR is late to the big data party, how analytics can provide companies with a huge competitive advantage and where data fits into the future of talent management.
Over the last five years, there's been an explosion of interest in data decision-making. If you look at most big companies, there's a lot of data analytics being used in financial departments; companies know where they are losing and making money. That kind of discipline has been applied to marketing as well. Companies have a pretty good sense that if they spend money on a certain ad campaign, they can expect a certain return.
The unsolved area is how to apply analytics in terms of people. What makes top salespeople effective, and how do we hire more of them? Why is a company's turnover rate higher this year than last? These are all HR — or "people" — problems that we are now looking to predict, understand and analyze with data.
With the use of cloud-based HR systems ... companies now have a large percentage of HR and business data. They can build models and analyze that data in order to understand why certain parts of their business aren't optimized to the best they can be.
People analytics is starting in a small way. [Only] 4 percent of the market is doing sophisticated predictive analytics, and 50 to 60 percent are still cleaning up the data they have and trying to make sense of it. Many companies are in the process of replacing old HR systems with new platforms, which will give them access to analytics tools.
Historically, the HR function is not a very sophisticated group of data people. Now, however, we have HR executives hiring people with PhDs to run teams in HR to look at data. I think data analysis is going to become an established discipline within HR in the next 10 years. Every single department I've talked to wants to implement this.
One of the most common uses of analytics right now is predicting retention. Retention risk calculations can help companies figure out why people are leaving.
A second application of people analytics is recruiting. If a big company receives 500,000 resumes per year, whom do they hire? It's not as simple as scanning through and seeing who went to Harvard and got straight A's. Those may not be the best people to succeed at that company; it may be people who went to community college.
Third is revenue generation. How does a company hire more effective salespeople, get rid of people who aren't performing well and copy things that high performers are doing well? You have to look at business data as well as HR data. Once you do that, you have possibly unleashed the largest source of competitive advantage ever.
First, a company needs executive commitment. Both the CHRO and CEO need to be comfortable making that financial investment.
Second, the company needs to find someone to run that group. Despite a lot of press out there, it's easier to find those people than you may think. A lot of statisticians and mathematicians are interested in doing this kind of work, you just have to look for them in disciplines outside of HR.
Third, you have to invest in good, integrated systems, and IT needs to ensure the data is clean and ready to work with. Understand you're not going to get a great result in three months; you have to commit to the time it's going to take.
You're going to see better-run companies that are able to make better decisions. Organizations will have better people, reduced risk and lower error rates. You name any problem that any company has ever had, and you can trace it back to people. Depending on the priorities of the CEO and business, you can apply people analytics to just about any problem you have.
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