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. Companies have been talking about how to measure learning and HR for a decade or more. Back in 2005, after several frustrating years trying to figure out how to measure training, Josh Bersin, 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 and 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 (typically 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.
In the 1990s vendors like PeopleSoft, Oracle, and others built analytic products to support this market. They didn't sell very well, primarily because companies had such complex HR systems they didn't have the budget or IT support to build the HR data warehouse. (Some companies did this, and they have been benefiting from this for many years.)
About five years ago the book “Moneyball” was published, and we started a global marketplace called "Big Data." Tools like Hadoop, R, and other parallel data management tools became productised and industries like marketing, advertising, and finance started to analyse massive amounts of data. Much of this started at Facebook, Google, LinkedIn and other internet companies who simply had to analyse enormous amounts of data to run their businesses.
Along the way the term “data scientist” was invented, and today there are hundreds of jobs for "Data Scientists." (Typically defined as people who understand information management, Big Data tools, statistics, and modeling - a rare breed.)
During the last ten years we observed the discussion with HR remain very tactical, focused on operational reporting and simply fixing the mess of the incompatible HR systems we have. There were many HR 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.
Suddenly around 2011, with the focus on Big Data, a shift in the market was on the rise. A small number of companies were investing heavily in predictive people analytics, but most were barely getting started.
The whole idea of "Big Data in HR" was to help HR organizations realize that they, too, could enjoy the wave of interest in Moneyball and BigData. HR is not as interesting a topic as cyberwarfare or digital marketing, but it's a big area of spending (more than $4 trillion is spent on payroll around the world) so there's a lot of opportunity in this huge data set. And the world of "People Analytics" was born and is here to stay for quite some time.
There is a deep history of data analysis in the HR profession, starting with Frederick Taylor in the late 1800s. The article "Datafication of HR” describes this evolution, and I think everyone in this space should read this article to 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 to 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 have heard this all before, however at times as HR professionals we can be headstrong and produce data which business leaders don’t need.
A word to all HR professionals, get up to speed with Analytics and bring on those Geeks within the function, otherwise you will lag behind!