Big data has become a big topic in the media these days. In the past 12 years studying corporate training, we have seen data and measurement continue to challenge corporate HR and training departments.
In Bersin by Deloitte’s most recent spring survey, we discovered that only 16 percent of organizations say they can adequately measure training impact, and fewer than 60 percent measure satisfaction. In this age of big data, I challenge you to think about the “datafication” of HR and specifically the datafication of learning and development.
“Datafication” means to take an existing business and turn it into a data business. Facebook has datafied our friend network; Google has datafied our search and information retrieval behavior; Twitter is datafying news and real-time information. General Electric Co. is even datafying its engines, power plants and machines.
The point of datafication is to rethink the process from a data perspective. This datafication process is what we call talent analytics. In the learning industry we are awash with data, and we can leverage it to go beyond the Kirkpatrick model used to measure training, to understand the true value and correlated impact of various training programs and social systems on business performance.
Unfortunately, the measurement process in many companies today translates into little more than end-of-course surveys. Think about learning from a data perspective. You are capturing vast amounts of data in training: enrollment and completion data, volumes of training, assessment and competency data, as well as data about employee productivity, performance, progression, engagement and retention.
Ideally, you as a learning executive like to analyze many things: How is learning spending being consumed by different parts of the company and in what areas? What is the relationship between various training programs and the career progression, performance and retention of high performers? How well are you encouraging innovation and product delivery through learning and development programs and systems? And in a more modern organization, what if we analyze the patterns of information producers and their social networks and looked at how those components affect other people’s performance, quality and innovation?
These are all big data analytics opportunities — available to every learning department if you think about the problem in the right way.
Bersin by Deloitte recently completed a study of leadership progression for a major energy company. This company was concerned about its pipeline of high-potential leaders in Asia and was trying to understand how it could develop leaders faster in these emerging economies. Of course, one of the important ideas was “maybe we need more training” or “maybe we need different training” in these countries.
After looking at training data, matched with demographic data, job progression and a variety of other factors, the company found that leaders in these countries were younger, came up a different career path and actually had different academic backgrounds than leaders in the U.S. When the company looked at performance ratings to understand which leaders performed the highest, it found that strong leaders in Asia needed much faster career paths and totally different development than those in the U.S.
Our research shows that more than 60 percent of all companies are still stuck trying to develop efficient operational reports from their HR systems, and most have yet to build an integrated data warehouse or consolidated database to analyze. It’s time to rethink how we analyze learning and talent programs. Let’s move beyond the traditional satisfaction ratings and look at the rich wealth of data we have to manage and understand our learning investment.
With the help of a statistician and some investment in data quality, any organization can find exciting new ways to add value by better understanding how learning and development investments drive results. It isn’t always obvious how and where learning adds value, but by applying big data concepts in a focused way, we can reinvent how learning is perceived in our organizations.
