People analytics is growing at an astounding pace, with organizations around the world pouring more and more resources into it every day. According to Ben Waber, founder and CEO of Humanyze, what we're seeing now is just the tip of the iceberg. I first met Ben in Madrid when we were both speaking at a conference. Ben got his PhD at MIT in the Human Dynamics group and has studied behavioral analytics for many years. His company creates badges that employees wear at work, but these badges take traditional employee ID badges to the next level. They are equipped with a variety of sensors, such as radio-frequency ID that allows the badges to act like true ID badges, Bluetooth that measures someone's location in an office, infrared that can tell who you are facing, and a microphone that measures not what you say, but how you say it and how much time you spend speaking--all metrics that truly measure human behavior.
This type of data can be used to help organizations understand things such as whether marketing is talking to engineering, whether the manager of a team actually spends time with his or her people, what top-performing employees do differently, and how the most successful salespeople speak with their customers. This type of approach is rarely done inside of organizations simply because the behavioral data doesn't exist. Eventually it will, which will allow organizations to optimize and improve everything from how teams are structured to how compensation packages are created. Ben acknowledges that survey data is still useful and important to have, but it paints only a part of the picture. However, it's still what most companies have. In the next decade or so, only a handful of companies will actually get to the next level of behavior analytics.
In many organizations, the people analytics function sits in HR. The challenge is that many HR teams don't have data science capability because it's a new skill set. HR has primarily always been about dealing with people and their interactions, hiring, and firing versus actually analyzing people from a data science perspective. However, as this area becomes more advanced, it is quite possible that it will grow into its own department that reports directly to the CEO.
There is, of course, a dark side of people analytics because data can be used to make decisions that either positively or negatively affect people. For example, people analytics can be used to calculate mass layoffs or determine ways to manipulate people. This is a delicate balance for organizations--not to mention the potential creepy factor of employees having data collected about their every move and action! People analytics models are designed by people, which means they will be inherently flawed. In her book Weapons of Math Destruction, Cathy O'Neil tells the story of a middle school teacher named Sarah Wyocki who was let go from a job with a Washington, D.C. school district because an algorithm decided that she was doing a poor job. The school district was determined to improve underperforming schools by eliminating bad teachers. Although she got rave reviews from the principal and parents, somehow she was classified as being in the bottom 2% of teachers. It turns out the elementary school where Sarah's students came from was one of several schools under investigation for cheating on standardized tests by teachers who were erasing the wrong answers and filling in the correct ones to help preserve their own jobs. This meant that when Sarah's students took standardized tests where no cheating was involved, their scores dropped considerably, thus making it look like they weren't getting the education they should have been. Naturally the blame fell on the teacher. In this situation, the algorithm would have no way of picking this up, and Sarah and over 200 other teachers were fired. This story illustrates just how important it is for us to not place all of our decision-making eggs in the people analytics basket.
Today we are still at the very early stages of what's possible with people analytics. Perhaps the biggest challenge for companies today is organizing, cleaning, aggregating, and standardizing data, a project that can easily take years depending on the size of the organization.
With technology advances and the integration of AI, you will one day be able to use voice commands to ask a smart assistant things like:
What's the employee turnover?
Who are the top three employees on my team at risk for leaving the organization?
How many contingent workers are we using, and how much are we paying them each year?
What are the top skills and weaknesses on my team?
Which teams are the highest performing inside of our organization?
What employees should I consider for a new marketing team in California?
People analytics is absolutely growing into a core business capability that every organizations must invest in heavily. It is truly the foundation of employee experience.
Learn more about the future of people analytics here.