How People Analytics Improves Employee Performance
Analytics around human performance is increasingly of interest to organizations — here’s how one company provides them.
Topics
Digital Leadership
MIT Sloan Management Review: We’ve heard about big performance gains companies were getting as a result of data and analytics. What sort of exciting things do you have going on? What recent advances has Humanyze made? Where are you now?
Ben Waber: There are many changes on both the technology and business model fronts. We analyze data on how people interact and collaborate at work in two ways. One is these next-generation ID badges, which are about the size of those plastic ID badge holders. They have RFID and NFC (near field communication) so you don’t need a separate badge; they can completely act as your ID. They transmit data wirelessly, so they’re much easier for people to use. We also have digital data — email, chat, meeting data, and phone call data — because that’s also an important part of how people work.
In the past — say, two years ago — when we would bring people on, we’d have them start using the badges, and if they were using digital data, we would use that. We had a general-purpose people and analytics platform that could solve lots of different problems. Now we’ve done a 180. We start out looking at only digital data: email, chat, meeting data, who communicates with whom, when do they communicate, no content, that sort of thing.
We provide dashboards that highlight specific business problems, including collaboration of project delivery, workload assessment, diversity inclusion, workplace planning, and risk assessment. This direct insight into where businesses need to be looking is why over the last year, we’ve at least doubled our business and the number of users every quarter.
We went that way because it allows companies to use the data they already have and apply it to specific business problems, allowing them to easily identify and use it. We did a lot of work developing those dashboards to make sure that these metrics are predictive across a wide variety of companies, that they solve these business problems.
For example, there’s diversity inclusion. Lots of companies have diversity and inclusion initiatives. But fundamentally, they don’t know what real impact they have. A couple of months ago Google LLC announced that it had spent $217 million on such programs over four years, and they had no effect.