How do you manage data privacy in People Analytics?
We had the opportunity to catch up with Ben Waber from Humanyze (a people analytics company that uses smart badges and other data sources to give companies access to new datasets and communication data that they haven’t had access to before) at the Tucana People Analytics conference and ask him about his thoughts on managing data privacy when collecting activity data on employees and is the “hype” about artificial intelligence justified? Check out the video of his interview below as well as the transcript from our discussion. For more videos on the future of HR, don’t forget to subscribe to our YouTube channel.
myHRfuture: How does Humanyze maintain employee privacy when collecting data?
Ben Waber: The way we collect that data is such that we're not actually exposed to things like names or email addresses, and so all those things are essentially anonymised first of all on our customers end, but then even beyond that, when we're analysing the data, we feed back to companies our aggregate statistics, like group level and above and that's important for a few reasons...
So first of all that actually addresses the large problems that companies are really trying to tackle using our technology. Beyond that it's provably anonymous, it's the sort of thing where if you just remove names that's actually not anonymous and taking this approach not only do we feel like it's the right way to do things (and is the most effective way to do things), but it also has the advantage of being globally compliant. We can deal with data the same way in the UK and the EU and the US and Japan, without changing our core system and that's really critical.
myHRfuture: What are the typical problems you are solving with your technology?
Ben Waber: Specifically: workspace planning, diversity and inclusion, workload assessment, regulatory risk collaboration, and project delivery. So, really looking at different sets of problems. What's interesting of course is the data that drives those is almost identical, but it's really important (especially at first as companies start to use this kind of technology, remember they never looked at these kind of metrics before), to focus them in on the specific problem they're trying to address today and then over time you can expose them to more and more views on that data that can address most of the management decisions that they're thinking about.
myHRfuture: Do you get involved in projects around workplace design or office space?
Ben Waber: We don't ourselves design the layouts or anything like that, there's obviously folks much qualified than I am that can do that. But what our technology enables you to do is understand what is the state of the world today, for example how explicitly does the workplace impact how people are collaborating, and then what you're able to do is simulate changes in whether it's where people are physically located and see how that would change how people work.
Part of the challenge is if we're talking about things like workspace design, typically HR isn't involved in that. They should be involved, but they're not necessarily one of the core drivers. Similarly, with things like what communication tools people use, or even regulatory risk, again these are things where HR is typically brought in on the periphery but they don't own them. I think from my perspective, at least for people analytics to be as effective as possible, it really requires cross-disciplinary collaboration within the organisation.
myHRfuture: What are the challenges facing People Analytics teams today?
Ben Waber: AI and similar related tools like machine learning, are important statistical tools that people should be using in some capacity, but we shouldn't over inflate their importance. Really, the core methods within both machine learning, and AI more broadly, haven't changed very much since the late 80s. What has changed is the amount of data that we have at our disposal, which makes these things a lot more accurate, but I think that because these algorithms in specific instances are more accurate, it has caused people to certainly overhype and paper over the brittle nature of these algorithms. As soon as you slightly shift the context where you slightly shift on the type of data you collect, these algorithms can break down.
If you are looking to learn more about how to get started in people analytics then check out the myHRfuture academy online course on people analytics titled 'An Introduction to People Analytics' that is taught by David Green and Jonathan Ferrar. It's a great introductory course for anyone interested in learning more about people analytics.
ABOUT THE AUTHOR
Ian Bailie is the Managing Director of myHRfuture.com and an advisor and consultant for start-ups focused on HR technology and People Analytics, including Adepto, Worklytics and CognitionX. In his previous role as the Senior Director of People Planning, Analytics and Tools at Cisco Systems, he was responsible for delivering the tools and insights to enable and transform the planning, attraction and management of talent across the organisation globally. Ian is passionate about HR technology and analytics and how to use both to transform the employee experience and prepare companies for the Future of Work.