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HRx Radio – Executive Conversations: On Friday mornings, John Sumser interviews key executives from around the industry. The conversation covers what makes the executive tick and what makes their company great.

HRx Radio – Executive Conversations

Guest: Ben Waber, Ph.D., President and Co-Founder at Humanyze
Episode: 378
Air Date: September 11, 2020




Important: Our transcripts at HRExaminer are AI-powered (and fairly accurate) but there are still instances where the robots get confused and make errors. Please expect some inaccuracies as you read through the text of this conversation. Thank you for your understanding.

Full Transcript with timecode


John Sumser: Good morning and welcome to HR Examiner’s Executive Conversations. I’m your host, John Sumser and today we’re going to be talking with Ben Weber, who is the president and co-founder of Humanyze and a fairly regular guest here on the show. So, how are you Ben, and would you take a moment and introduce yourself more deeply?


[00:00:33] Ben Waber: Doing well, my name’s Ben Waber. I’m one of the co-founders and I’m the President of Humanyze. And that’s a workplace analytics company that spun off of the PhD research that my co-founders and I were doing at MIT, really around trying to use data about how people interact and collaborate at work. Think email, chat, meeting data.


[00:00:53] We were all in offices. Also looking at [unintelligible] data to try to understand how people interact in a face to face setting. But really trying to use that, to see how do behavioral patterns and communication patterns predict changes, things like performance, engagement, what have you. And we’ve written a lot academically on the topic, but you know, now as a company, we’ve grown to a point where, you know, we’re deployed across every single employee at some of the biggest companies in the world. We can start to say some more general things around how people work than obviously also in the near term, how that’s been, how that’s been changing.


[00:01:24] John Sumser: It must be a kind of a crazy time. Because the heart of the original work has to do with physical interaction and now physical interaction is almost a fond memory.


[00:01:37] So what was it like to go through that change? That must have happened, kind of, abruptly.


[00:01:42] Ben Waber: Yeah, I think it was very interesting because, you know, I can speak obviously for my own experience, which probably everyone has this version of a story where, you know, in the U.S. at least, you’re getting into March and starting to be concerned that there’s going to have to be some pull back from the office for some period of time and really unclear how long even that that would be.


[00:02:05] And then, you know, we started to spend time, really, at the beginning of February, at least thinking about what were we likely going to lose. I’m just given our own data around us, you know Humanyze, as a company, starting to work remotely. And then, you know, I think a lot of the things that we planned have actually been fairly effective, but also that they’ve still been inadequate.


[00:02:25] And then I think that’s what’s been interesting, not just for us, but also looking at our customers, which are, you know, in almost every country in the world. The speed with which we’ve seen behaviors change is really unprecedented, at least in our data. And I don’t think that’s maybe surprising to anybody, but I mean, just to give you a sense of how quick that was.


[00:02:44] So if I look, pre-pandemic the average information worker globally, had 2.9 close contacts. The definition essentially is these are people that you spend an hour or more with in one-on-one communication a week. Right, so people who you work with very closely and that’s the average. And if you go look by any months, over the past year plus that number, you know, even as we add new customers, even as global things changed, it wouldn’t move by much more than 0.05 a month, it was very stable.


[00:03:15] All of a sudden, you get to the end of March and that number skyrocketed to over six, which is just crazy. And we can talk about why that likely is, but that is a very rapid change in how people collaborate. And I think there’s a lot of reasons for that, but it’s also something that it would have been very, very hard to predict is that exact magnitude of change beforehand, even looking at previous employees or companies that had people working remotely, it’s a very different thing.


[00:03:44] It’s been interesting to look at and obviously, you know, a challenge for even us, even who have all this data on how we collaborate, is still a challenge to continually try to adapt to these changes. Because what we’ve just seen is even when we find something that seems to make a positive impact on how people collaborate at work, its typically a limited time effect.


[00:04:03] And then after a month or two, you need to switch it up and try something else.


[00:04:08] John Sumser: What you’re saying, I think, is that we went from tiny little clusters of collaboration with a lot of support wrapped around us, to expanded clusters with less support wrapped around us. Is that fair? How would you characterize the change?


[00:04:28] Ben Waber: Yeah, well, I like that conceptualization. In that, if we look at, you know, people who are your close collaborators now, by this definition, these are still people that you worked with pre pandemic. It’s not like they just appeared out of the either and you started communicating with them. It’s more that again, you had to elevate certain relationships because to your point, the supporting structures around them are weaker.


[00:04:50] If we were in one or two meetings together a week but that, you know, occasionally we’d bump into each other in the office or one of, you know, a person we know in common would sits near me and as we’re chatting, he said, Oh yeah. Did you actually hear, there is some problem with the budget on this project, right? Those are the things that are extremely difficult to make happen when people work remotely.


[00:05:14] And we don’t really think about those consciously as a really important part of our work. But that when it comes to the structure of how we collaborate and how information flows, they really are critical. And so I think people have realized that if we don’t proactively schedule, listed you know, meetings and information exchange, then we’re going to miss a lot of things. This is totally accurate at the same time, further out into the, the weaker parts of your network. It is the need for those conversations is a lot less clear, you know, this person who I bumped into by the coffee machine for five minutes, every, you know, once every two weeks, should I schedule a zoom meeting with them once a month? I don’t know.


[00:05:54] As an individual, it’s almost impossible for you to know, is that actually worth my time? I mean, some of them might not be, and that, you know, the cost of doing that. Of having those interactions in an office in our ms. Quite low, whereas not just in a work from home environment, but also emphasize in a dynamic environment where it’s likely you’ve got other things on your mind and you’d be, you know, you’re taking care of your kids at home.


[00:06:16] Like I am, or it could be that there’s literally wildfires outside your house. And you’re trying to figure out what to do. I mean, all of these things do impact. What would otherwise be a much more frictionless information exchange. And I think that that had a really strong effect on our networks.


[00:06:31] John Sumser: So, you know, in my work, my work has completely transformed as the result of the dynamic that we’re talking about. So I would talk to, well, maybe a slightly larger group that you’re describing three or four people every week for an hour or so. I spent a lot of time. I’m in a lot of conference rooms and a lot of cities with a lot of people who I would only interact with once or twice a year for five or 10 minutes piece.

[00:07:02] But that’s where I learned.


[00:07:07] Ben Waber Yeah. Yeah.


In the absence of that, it feels like the world just very insular feels like the loose connections that allow sparks to happen are muffled. And it’s much harder to see for me in my work than it was in the past, because that next layer, the next layer, beyond that out in the network are simply, it’s just for me.


[00:07:35] And there’s no way to schedule those transactions because. I’ve got this hammer and nail called Zoom when I can schedule a meeting as short as 15 minutes, but they don’t work. And so, so I am limited to these fast interactions with people that have formal structures around them and no time going in and leaving the meeting to exchange stuff.


[00:07:59] So it’s a very different world. And I wonder all the time. Whether or not, we’re actually producing the same value that we used to produce because the work methods have changed so completely and abruptly.


[00:08:13] Ben Waber: I really think that a lot of the changes that we’re seeing, like you described, they are starting to show up in economic output.


[00:08:22] It is very hard to disentangle right now and maybe forever the impact of changes in collaboration patterns from really real impacts and changes to things like supply chain, finances as well. And, you know, if you look at there’s companies like the iPhone, please, the new iPhone getting, and you could chalk that up to, Hey, we have supply chain issues at the same time.


[00:08:44] You could also chalk that up to, we’re not able to collaborate effectively on hardware because there’s a lot of physical collaboration that needs to happen. But you are also seeing in software company, you’re actually starting to see real delays in product releases and things like that. And I’m starting to work on a piece to really clearer, but that is really my concern.


[00:09:04] And I do think it’s important to point out that it is not impossible to have these conversations virtually it just as much harder. And there are likely cultural changes. Like you’re talking about that need to happen for us to do that effectively. Again, I’ve just personally started to do things where, for people who I might see once or twice a year at conferences, I’ve just, you know, every week I’ve scheduled a couple of calls just to catch up, which has been nice.


[00:09:29] But I will point out that even though those calls are helpful, I can do that because these people are already part of my extended network. I already know these people, not super well, but I do know them. What’s much harder than even that is trying to meet new people. That’s where you get even better and newer ideas.


[00:09:47] And those are the things that I personally haven’t found a great way to do that virtually again, does that say zero connections over the past six plus months, but it’s been. Significantly less than previously in something we see in our data as well. Not just even in my role, sort of like yours, that I’m actually between lots of organizations.


[00:10:06] But when you look at new employees coming into organizations, there also appears to be a much slower rate of new Thai connection compared to previously. And I do wonder what the impact of that is going to be research would say that is definitively going to impact the novelty of new products, the speed of the release, things like that.


[00:10:26] But I also wonder about the actual longterm impact on the careers of especially folks who are just getting started. Or people who are still in frontline roles because these ties and creating new ties are the things that very strongly correlated with increased promotion rates and job mobility. And I do wonder if there’s going to be this group of people, people who are at a critical time in their careers now.


[00:10:50] That are for the longterm going to be heavily negatively impacted because they aren’t going to have the same types of networks as people who are, who came before them. But also people come after them, you know, presumably after we get this under control. So again, just more evidence of things that, you know, in person, you might have to deal with a little bit in terms of someone interrupting you. But the social cues are much more there.

[00:11:13] John Sumser: It’s a great example, even though we’re in the middle of this ridiculous, weird smoke here in California. And one of the things that you notice is my phone. When I go to have it look at the sky, my phone wants to make the sky prettier, right? So you see lots of people showing examples of a picture of the sky and a picture of what the phone wants you to be.


[00:11:42] And so weird errors, all of these systems that assumed there was a kind of stability that may not actually be there. Imagine you’re seeing consequences like that. The organizations.


[00:11:57] Ben Waber: I mean, I think that’s one of the other questions. I mean, it’s something that we’ve been thinking about a lot in that a lot of our metrics and predictions, you know, we’re obviously developed to deal with pre pandemic data and that when you look at the question is how much do they apply today?


[00:12:14] I don’t think they’re applicable at all. And I do think they’re quite applicable. And at the same time, I do think there’s a question of, for example, Yeah, pre pandemics. If you work from home, essentially more than 1.5 days on an average week, it was very likely that your network was significantly different than people who are in the office, you know, for like more than that.


[00:12:35] Right. So, you know, 3.5 days or more per week. And did you wonder that because people now and again, if you go above that, I really worry about retention and you could predict the likely attrition to people or likely performance impacts to the team based on just that simple fact. However, I do wonder if that has shifted and it’s something that we’re just very cautious and we’re looking at what is the exact impact of changes we’re seeing in networks.


[00:13:00] Now, again, we’re starting to see some hard KPIs that we can definitively tie to hinge and collaboration patterns that has taken this 0.6 plus months to really be able to show. But I do think it’s not going to be exactly equivalent. Till we saw pre pandemic because this is such an extraordinary period.


[00:13:20] And so I do think that whenever you’re using algorithms or technology, to try to interpret a very abnormal situation, to your point, you get the same effect where it’s going to try to look through the lens of what is normal and what’s going on right now is very much not normal. And so you don’t want to get a picture of the organization.


[00:13:39] That’s just color corrected, even though everything’s on fire. You want to be able to understand what that state is and it’s. I don’t think there’s an easy answer to how to keep correcting for that. It really is just constant effort to see, you know, validating what we’ve been using before, what things appear to be no longer valid.


[00:13:59] And it’s something that as we build our, you know, our organizational health model is something that we’re just, we constantly look at it and you know, I back seven months, things were a lot more stable and it looked like we could look at these changes a lot less frequently. And now it’s something where, I mean on a nearly weekly basis, you’ve got to look at it because you just, you need to see if there’s anything fundamentally different. That’s going on. You know, there’s been going on at least for the past month.


[00:14:26] John Sumser: So I’m going to stretch you of this question. It seems to me that since the cotton mills, since the beginning of the industrial revolution, the pattern in society has been, if you can find something repeatable. And you can make that happen automatically.


[00:14:43] You could make a lot of money and you don’t have to work as hard. Right. And that’s sort of, the engine of industrialization is repetitive. Motions can be done automatically that produces wealth because the labor can fall out of the equation. I think we might be headed in era where there isn’t that much repetitive motion.


[00:15:04] That part of what we’re seeing places where lots and lots of little tiny increments of apparently repetitive motion produced all this value. And now we’re cut off from most things that we have to figure out, create the value of narrower construct. And that means more hard work and less. Wealth creation through automation.


[00:15:33] Ben Waber: There’s likely still a decent amount of mileage for automation to go. Um, I don’t think, but it seems I’m not subscribing to this idea that that means that, you know, 90% of people aren’t gonna have jobs in 20 years or something. I think that is ludicrous even just from a technological perspective and just, you know, I’ve spent a lot of research in this area.


[00:15:53] There are things that for humans seem very, very simple that your peers are just literally. You know, a hundred years away, at least from doing things. And obviously there can be some radical changes that happened, but what’s very interesting is if you look at the actual improvements in the outputs of, you know, different automation technologies, look at AI.


[00:16:11] If you look at robotics, it’s not some fundamentally new algorithm. It’s not like there’s been some discoveries over the past 10, 20 years that are just so crazy. But back with driving these changes just the amount of data. It’s just that we’re using the same algorithms that were developed in the eighties, but that instead of having 10 data points, you have 10 billion data points.


[00:16:30] Guess what, you know, you can do a lot better with statistics, which is what these things are and repeating things out. So you can’t otherwise. But I do think that more and more of the low hanging is being taken and is being automated away and there’s less and less of that, that we can do. But what that leaves is a lot of the stuff that people are very, very good at, and the computers are very bad at.


[00:16:52] And if that is your point, this less repetitive stuff. And this idea that, you know, which was probably antiquated 30, 40 years ago, or even developed this idea that people are cognitive machine and I can just optimize the hell out of a single action. And I’m just going to get more output and I’m going to make more money if I own that company.


[00:17:11] I think that is a lot less true today. And it’s something where more and more of the work, even things that you seem. You know, maybe on the face of it to be university simple, actually have so much tacit knowledge built in, in our, you know, even things like carpentry. It might seem like, Hey, this is an old thing that should be super simple.


[00:17:32] It’s actually extremely complex. And to say that there is going to are going to be people who take a naive approach to try to. Optimize these things from a single unit perspective, but that the real benefits and actually where higher performance comes from it, it’s not doing a single action, 5% better.


[00:17:53] It’s from completely rethinking how you do this thing so that you save 90% of the time. And that is the majority of what. Work has become is a lot less about these like individual roles with the individual output and have little interface with other things. It is increasingly more and more intermeshed work that the primary output is a collaborative product, which requires which higher performance there is about thinking differently and doing each radically differently rather than optimization. And I do think that is an important point.


[00:18:31] John Sumser: So, let me shift just a little bit further. You’ve been doing some work with organizational health about that. Tell me if you’re comfortable with where the science of organizational health is.


[00:18:43] Ben Waber: I mentioned it a little bit earlier. It’s something where we have, we’ve been very cautious about this because we wanted to make sure that if we’re going to put a stake in the ground on organizational health, that we have enough data structure that when we get.


[00:19:00] Yeah, new customers, or when we get new data from existing customers, that it doesn’t change. The distributions don’t change very much and we don’t have to get into the, you know, mathematical explanation, but why that is. But it is really important for us to make sure that we were doing something valid.


[00:19:17] And so, like I mentioned, it is at this point now where there’s a number of just basic things about work that I can say with a very high level of competence. Right around, you know, how much time do people spend in meetings? How much do people collaborate with their boss that I can actually say? And the answer that I can give from our data is going to be almost exactly what the global average.


[00:19:42] Right. And that’s pretty interesting. Cause it’s that say we’re deployed across every single company in the world. It’s just that the distribution we have so far has gotten to a point where yeah, we can stay there. And so the challenge has always been to maybe convey those actionable behavioral metrics.


[00:19:58] To those managers, well leadership at companies who haven’t worked with this kind of data before, right. How to get their heads around. Well, how should this imply that I change my onboarding program or change where people are located. And so what we did is also build up a Cedric into things into higher level concepts that then, you know, things like engagement and productivity to people.


[00:20:21] Can understand. And it also, we’ve been able to show that, Hey, even if you don’t have hard KPIs on those things, if you’ve done it, even survey, get a product, if your product be metrics, I can show that our, that our definition of that and our metric of that. Right. And our benchmark on that does correlate quite strongly.


[00:20:39] You know, we’re talking know R squared 0.6, which again, we don’t have to get too into it. If you’re in the social sciences, that’s like God’s word basically. It’s a very strong. Right. And so we know we can do that at the same time. We do know we’re not capturing the entire essence of things like engagement.


[00:20:56] And it’s always important to note that again, data from surveys from human observation are important component to understanding these things that we’ve, you know, what we’re really focused on and really good at is understanding this behavioral data. And so, you know, really try and get to a point where when an organization starts to look at these analytics first, you can see, Hey, where do you stack up?


[00:21:16] Globally against other company, where should you focus your attention, right. That which teams, which departments are really suffering, but then also importantly, really being able to quickly see if the changes you’re making are likely gonna improve, you know, the healthy organization. So I think there’s been a ton of work.


[00:21:31] We’ve done there to get it to this point. And so it’s been pretty exciting to, you know, to now we can actually talk about these numbers, but I think there’s always going to be more work to do there. And we’re always trying to expand our, our models. But I do think that this. This is an important step for organizations to actually be able to look at themselves and be able to put some hard numbers and on, on how they’re doing.


[00:21:54] And I think eventually externally, it’s something that companies are, you know, frankly, whether it’s our metric or someone else that you think is something that, you know, eventually if you’re a public company you’re going to have to report this stuff out. And so I think we’re seeing a lot of folks jump on that already, but it’s quite exciting.


[00:22:10] It’s been, you know, working on this for what I guess, you know, nearly 15 years and to be able to get to a point where we can, can really definitively say stuff like this is, yeah, that’s what we’ve been working on for a long time to finally getting to that point.

[00:22:23] John Sumser: That’s gotta be my favorite thing about you and Humanyze is that it is a scientific endeavor about exploring the edges of things. It’s been a great conversation. Thanks for doing this. Would you take a moment and reintroduce yourself?


[00:22:38] Ben Waber: Definitely. So again, Ben Waber, one of the co-founders and the President of Humanyze and, uh, yeah, again, thanks John, really enjoyed, enjoyed the discussion as always.


[00:22:47] John Sumser: Yeah, thanks Ben. Really, thanks for doing this. You’be been listening to HR Examiner’s Executive Conversations. We’ve been talking with Ben Waber, who is the President and co-founder of Humanyze. You should take a look at them on the web, it is the advanced guard in what organizational analysis looks like going forward. Thanks for tuning in and we’ll see you back here next week. And thanks again, Ben. Bye, bye now.

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