The old fashioned fuddy-duddy HR department is changing.
The Geeks have arrived.Today, for the first time in the fifteen years I’ve been an analyst, human resources departments are getting serious about analytics. And I mean serious. I was in a meeting several weeks ago in San Francisco and we had eight PhD statisticians, engineers, and computer scientists together, all working on people analytics for their companies. These are serious mathematicians and data scientists trying to apply data science to the people side of their businesses.
This last week I had another similar meeting and we had three of the world’s leading insurance companies, two large retailers, three health care companies, and two manufacturing companies with serious mathematicians and scientists assigned to HR.
What’s going on?
As I recently discussed in the article “How People Management is Replacing Talent Management?” there is a major shift taking place in the market for people analytics. After years of talking about the opportunity to apply data to people decisions, companies are now stepping up and making the investment. And more exciting than that, the serious math and data people are flocking to HR.
A little history is in order.
The area of HR analytics, talent analytics, or as it is now called “people analytics” has been around for a long time. As an analyst (and former analytics product manager) I’ve been talking with companies about how to measure learning and HR for a decade. Back in 2005, after several frustrating years trying to figure out how to measure training, I wrote a book called The Training Measurement Book, which sets the stage for L&D teams to move beyond the traditional Kirkpatrick measurement model. Today learning organizations continue to try to analyze the impact and effectiveness of training, but it no longer stands alone.
If you look back in time, ten years ago companies tried to build ”HR Analytics” systems (typicall called HR data warehouses) to help companies look at simple metrics like “total headcount,” “time to hire” and “retention rate” and clean up their messy, often inaccurate people data. Quite a few companies built these databases, but they were primarily used to be a single system of record across the many HR platforms in place.
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Along the way the term “Data Science” was invented, and today there are hundreds of jobs for “ Data Scientists.” (Typically defines as people who understand information management, Big Data tools, statistics, and modeling – a rare breed.)
During the last ten years we watched the discussion with HR stay very tactical, focused on operational reporting and simply fixing the mess of incompatible HR systems we have. There were many HR and learning analytics presentations and a few conferences, but most of the focus was helping technical practitioners improve their reporting systems. The idea of predictive analytics was little more than ROI studies to look at whether a training program worked.
(Full disclosure, I was the head of product management for two companies that built advanced learning analytics solutions in the early 2000s.)
Suddenly around 2011, with the focus on Big Data, we sensed a shift in the market. To understand how well predictive analytics was taking hold, we started our early research on “Big Data in HR” and developed a maturity model (it was published in the Fall of 2012). We discovered a world of “ Haves” and “Have Nots.” A small number of companies were investing heavily in predictive people analytics, but most were barely getting started.
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There is a deep history of data analysis in the HR profession, starting with Frederick Taylor in the late 1800s. The article “The Datafication of HR” describes this evolution, and I think everyone in this space should read this article and get to know the history. Today we are standing on the shoulders of some giants and very innovative thinkers – they just didn’t have computers to help.
Today, while the topic is hot, HR teams are just starting to get good at analytics. The problem has not been the concept, but rather the focus. We spent far too much time trying to measure HR and L&D spending, and figure out which HR programs were adding value. While that seems interesting HR managers, typically business people just don’t care. What they want is information that helps them run the company better: “Get me the right people into the job, make them productive and happy, and get them to help us attract more customers and drive more revenue. I don’t care if your L&D program has a 200% ROI or not.”
We now see this as a huge trend, so we launched a focused research area on this topic. . . . It showed that there were a small set of companies (less than 5% of the market) that were way ahead of the curve. These advanced companies were looking at people-related data in a very strategic way, and they were making far better decisions about who to hire, who to promote, how much to pay people, and much more.
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A few weeks ago I had a meeting with five major Silicon Valley and New York companies who are focused in this area, and the room was filled with statistics PhDs, engineers (like me), and I/O psychologist PhDs. Thus the title of this article:
The geeks have arrived, and we’re all happier for it.
At this point, entering 2015, I believe “The Geeks have Arrived.” Statisticians, mathematicians, and engineers have entered the people analytics space. In this meeting I recently attended, the practitioners, who are among the leaders in this space, were all experienced in bringing together data, cleaning it up, and doing all types of analysis. Of course their companies have various issues with data quality, systems, and infrastructure – but they, as a group “get it.” They understand the potential, they understand the problem, and they have the skills to get work done. And they are not just analyzing HR issues, they are analyzing the business.
Today this new business function is called “People Analytics.” And over time, I believe it doesn’t even belong within HR. While it may reside in HR to begin with, over time this team takes responsible for analysis of sales productivity, turnover, retention, accidents, fraud, and even the people-issues that drive customer retention and customer satisfaction.
- High tech companies now know why top engineers quit and how to build compensation and work environments to get people to stay.
- Financial services companies are now analyzing why certain people commit fraud and what environmental or hiring issues might contribute to such violations.
- Product companies are now analyzing the demographic, educational, and experiential factors that correlate with high performing sales people and why top sales people quit.
- Health care companies are looking at why certain hospitals or departments have higher infection rates and what people issues are behind these problems.
- Manufacturers and product companies are looking at the patterns of email traffic and communications to understand how high performing managers behave and what work styles result in the highest levels of performance.
- These are all real-world business problems, not HR problems. The data which helps support these decisions includes experience, demographics, age, family status, as well as training, personality, intelligence, and dozens of other factors. More and more this will include data on email communications, employee sentiment, and ad-hoc feedback.
Many of the factors which contribute to fraud or turnover have nothing to do with the people – they are environmental. Where is the manager physically located? Who else is hiring in this location? So People Analytics requires a look at external data, not just internal data.
This is why this function eventually belongs outside of HR, it is really a part of a company’s bigger “business analytics” team.
Just for grins I did a Google Trends search on the terms HR Analytics, Talent Analytics, and People Analytics, and look at what I found. “People Analytics” is winning.
As we talk about in our research, this is a huge market opportunity for business – one that is just beginning. Vendors of all shapes and sizes are starting to grow, and most of the large platform providers now include predictive analytics tools embedded in their core HR software. (Flight risk indicators are a good example – not necessarily accurate yet, but the right idea.)
And exciting new companies are joining the marketplace. (Read People Analytics Heats Up for more on all the vendor activity.) Not only are the large ERP players involved, but serious software entrepreneurs are joining the market. Last week I met with two senior software executives (both from large search engine companies and other companies they had sold) now entering the market for HR engagement analytics and measurement systems. I wont mention the company yet (it’s not yet launched), but this is a company that is likely to bring serious software engineering to the people analytics market.
While most HR organizations are still struggling to clean up their data and build their teams, the momentum is coming on strong. And technical talent has now figured out that the old-fashioned backwater HR department may be one of the most exciting places to work.
We’ll be doing a lot more research on this topic over the coming years, but let me simply state clearly “The Geeks have Arrived: People Analytics is Here.”
Read the complete unabridged article on Forbes Online, first published on February 1st, 2015