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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: Ellen Nussbaum, Chief Executive Officer, Humanyze
Episode: 345
Air Date: November 8, 2019

 

Transcript

 

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 0:13
Good morning and welcome to HRExaminer’s Executive Conversations. I’m your host, John Sumser and today we’ll be talking with Ellen Nussbaum, who is the newly appointed CEO of Humanyze. You may recall Hymanyze because we’ve had Ben Waber on the show a number of times over the years. Ellen, how are you?

Ellen Nussbaum 0:32
Fine, how are you John?

John Sumser 0:33
I am on top of the world. You know, I live out in Sonoma County. So I’m just getting back to the house after a week’s worth of evacuation. It’s an interesting time here. Would you take a moment and introduce yourself to the audience and I know they’re dying to get to know you?

Ellen Nussbaum 0:50
Oh, absolutely. Thank you. As you mentioned, I just joined Humanyze about two months ago as CEO calling in from sunny but chilly, Boston, Massachusetts. I’m excited to speak with you today.

John Sumser 1:02
That’s fantastic. So let’s just review. What does Humanyze do?

Ellen Nussbaum 1:06
Yeah. So our goal is to help companies understand where and how employees collaborate. So in that way the company can create the right environment for their employees. So we’re really focused on as work evolves, and people work in different locations and use different technologies to really understand what about infrastructure? What about the physical space? Is there helping or hindering employee collaboration so that companies can then you know, evolve that to make it more more productive for their employees?

John Sumser 1:36
How do you do that? I guess, I guess, I guess, rather than making fun of you right off the bat, I’ll ask you how you do that.

Ellen Nussbaum 1:42
So you know, you mentioned Ben, that you’ve had on the show before, the company is really very deeply rooted in science. It was founded by a group of people who were working on their PhDs at MIT, and they were really studying collaboration. And what they realize is that, you know, if you have the right data, you can really have Understand, are people working face to face? Are they having web conference meetings? Are they emailing? What are the different ways that people are working? And you can really try and correlate that with some performance? and say, well, which of these various collaboration cells are working fast? Is there an optimal amount in terms of how much time should I spend in meetings? How much time should I spend on email free time to focus on doing work? And while there’s no one universal answer for all companies and all industry, again, I think you can start to connect this with what is what is the performance in which managers are seeing the highest engagement from their teams? Where are we seeing the best employee retention? And to really start to say, oh, how do we connect that to the way the organization and the environment is structured, and you really can see things that are to move the needle in terms of making the environment better and therefore helping the employee to be more successful?

John Sumser 2:54
Well, I want to drill into what you can see in just a second, but let’s talk about how you collect the data. What actually do you collect? And what do you know?

Ellen Nussbaum 3:03
Sure. So the primary thing that we collect is what we call digital data. And so what that is, is we take information from the email system from the calendaring system, if people are using instant messaging or you know, Slack, and specifically what we don’t take as content, we don’t care what they’re talking about. We don’t care, you know, that topic or any of the nuance of what’s in it, but we do care about who they’re talking to, and how long they’re talking. And are they meeting face to face? Or are they doing it? You know, again, in a in a remote environment is email is it live. And so most of the data that we work with comes right out of those systems that the companies have in place today to really understand how people are working. We also if people are interested in knowing physical space where people are sitting, which competitions are meeting in, we also can use information that comes from the badges, you know, potentially badges that you already have for your building entry systems that we can really understand how they move around the building in terms of where work is getting done. Are they meeting in the collaboration space that you built in a meeting and conference rooms? Or is everything being done not face to face and a different type of collaboration. So what we collect comes from both the cars, the building entry cars, as well as from these digital systems, we don’t take information about who the person is. So we never collect any PII data. It’s not important to us that is john talking. It’s more which team are you on? Which office? Are you based out of could potentially be things like, how long have you worked for the company, if we’re trying to understand anything about onboarding new employees, there could be some demographic, but it’s very explicitly not tied to who you are individually. We never get that information from the companies. They don’t send it to us. So it really is about the group that you work in the location that you work in and the activity that you’re having, as opposed to your name or the content of your conversation. And that’s essentially the data that we collect. You know, we really like to get it on an ongoing basis, you know, on a monthly basis, for example, because we know these things are not static. It’s not a one and done. We’ve made our assessment. And now we know the answer. It’s really looking at how people are engaging, is that changing over time, and as the leadership comes up with different decisions, so for example, I want two groups to collaborate more, so I’m going to quickly locate them next to each other, well, then we want to watch that didn’t have the intended conference. And we’re going to evaluate and say, where do we need to course correct? Where are we heading in the right direction and so forth. So it really is it becomes a core tool for the HR executive and for the functional leader understand how people are working and are the decisions that management is making, helping them to collaborate more easily or actually making it harder for them to collaborate.

John Sumser 5:52
So one of the things that is on my puzzle list right now is is to find a good definition of work. I couldn’t explain to you what work is and how you would tell the difference between work at Boeing versus work at Deloitte. So what I’m wondering is, how do you tell what work is right? You’ve got all of this interaction information. And it definitely happens in the sort of container of the company. But work is not the aggregate of interaction. Work is the production of value. And so the question of how you see the thing that you’re talking about measuring is is a great interest to me. What do you think work is?

Ellen Nussbaum 6:30
What do you think about your instrument slightly different way? I think it’s, it’s an important point you raise and I think what we’re trying to do is to say not what’s right or what’s wrong, but which behaviors and which activities are driving the results that the company is trying to drive. And let me a couple of examples might help but one of our customers really wanted to understand what are the common behaviors among the top performing sales people right, we can see that these people are doing well but is there anything about the way they With the organization, how could they talk to how frequently they talk to that would suggest, you know, it’s the best practice, we can help people be more productive. And one of the things that we were able to show very clearly is that don’t people who spent more time talking with the engineering team would have higher sales results. And you know, again, exactly why that is or what the work is that they’re doing together. We don’t know we didn’t, we don’t have the content. But we could see that there was a very clear correlation. So whether it was building their own expertise or getting the engineers more engaged with the customer, the result was that these two things were highly correlated, and so that our customer was able to change the seating plan to encourage that type of collaboration. So I’m not sure if that directly against your question, but again, that notion of what is it those groups are doing together is less what we’re focused on and more if we get the right groups to collaborate, and we see that that encourages the outcome that we’re looking for, then that’s the direction that we want to move.

John Sumser 7:58
It’s such an interesting Staying field. It’s such an interesting field. So I was wondering as, as you were talking about a problem that I’m seeing quite a bit in the HR technology space, which is that the sales people don’t actually know what they’re talking about a lot of the time. And yet, if you measured them on outcomes, whether or not they know what they’re talking about this and their relevance, it only becomes relevant if it turns up as a customer satisfaction problem somewhere down the road. And that kind of feedback is really hard to get an integrated into something that looks at moment to moment interactions. So how do you tell if people are doing the right thing?

Ellen Nussbaum 8:37
Well, you know, you’re reminding me of another example another customer engagement that we’ve worked on, which was less about sales per se, but we had, you know, very large multinational 10s of thousands of employees, and they went to their annual performance evaluation process, and they noticed that, you know, there’s a group of people that were identified as top talent, the group of managers, I should say, manage There’s not that were identified as top talent to the performance evaluation process. So, you know, their managers preseason, very highly. They were at the top of the heap. But then they also looked at the managers that were viewed by their own teams by the upward feedback as being the best managers. And you know, an observation was there are some overlap between the top talent and the top managers, but not as much as you’d like, right. And so I think that gets a little bit to your question of, are the top performers necessarily doing all the things that you want? And in this case, are they building teams? are they building loyalty and so forth? And so the question they asked you and is what are the behaviors that you can observe that would help us understand well, what are the top performers doing? What are the top managers doing? And then in particular, that that subset of people that sits in growth groups, what are they doing? And is there something that we can do to help teach and develop our managers Now again, because we don’t collect individual data, we can’t go to Susie and say, hey, you’re not doing x y&z This is what you should be doing. But what we can do is start to train people on these are the ways that you can both build your career as a company, as well as build, like loyal and high performing teams underneath them. And I think it was a really interesting way to kind of juxtapose performant with also the the behaviors and the activities that lead to long term success of the organization.

John Sumser 10:22
One loss of answers. So you’re talking about a system that forces its user to only think of an aggregate level and only examine things at an aggregate level. And generally speaking, the the HR department is more concerned about individual transactions. So so when you talk to somebody in HR, how do you help to bridge the sort of negative bias of HR to the individual transaction to this idea that you could possibly manage the workforce as an entity?

Ellen Nussbaum 10:53
So I don’t think we want to diminish the impact of individual data. I think what we want to say is, let’s have both sides of the story. And as we look at it one of the things that in my career, I’ve worked at a lot of different data analytics or, you know, bi related solutions and function by function. There’s been this transition away from numbers, I can run an Excel or things I can look at individually to what are the patterns, I see organizationally. And I think what we’re trying to do is encourage HR to take the individual insights that they already have, which are, I think, very critical and to supplement that and say, What can they learn about my organization as a whole, and there is not a one size fits all even within an organization. different functions are going to have different cultures and different behaviors, different geographies, different offices will have cultures and behaviors, countries and people in the country. And so what we’re saying is we can be data driven about really understanding what works and what doesn’t work, and then again, use that to complement what what they’re already aware of and using on the individual level. I don’t think it’s either or I think it’s both is a short answer.

John Sumser 12:00
That’s great. That’s great. So how did you how did you get here? You’ve got a background in bi, you’re on the board at WTVH. You’ve got this broad Harvard Business School Renaissance woman portfolio, and now you’re in a test and measurement environment for human capital. How’d you get here?

Ellen Nussbaum 12:19
Yes, that is that is a long and windy road. I will say, you know, as you as you point out, I’ve been about 20 years and technologies. And you know, my primary focus has been growth really helping companies to grow. And I’ve never had a specific one industry or one function. It’s really been about companies that have a technology that has the potential to be transformational, though. In the early days, it was bringing forecasting and optimization science to retailers, which actually starkly been about you got he became a successful retailer, if you could pick the right fashions at runway show. The most common data analysis tool is Excel. And so really saying Well, hey, there’s a lot of data here. How can we how can we put it in the ways that business leaders can make better decisions. Now, when I worked at memento, which was acquired by FIS, it was the same thing. But it was around fraud detection in particular banks, but lots of organizations lose millions of dollars to fraud each year. But the idea was with the right curation and structure of data, you can really start to identify patterns and notice things that are a typical and then ultimately weed out or reduce fraud that takes place. And to me, you and I, another thing like that, which is it’s an opportunity for applying data in ways that haven’t been used before. And again, it’s like there’s such a potential associated with this technology to really be transformational. And that that I think, is really exciting. That’s why I joined like the going back to what we were talking about before. It’s very deeply rooted in science and analytics, which appeals to me and it’s pretty much been consistent, every company I’ve been at, but again, this notion that we can change the way people work and what’s more powerful than that.

John Sumser 13:58
Awesome. So you’re brought in, you’re the second CEO of the company. I’m sure that your charter is something like take us to the next level. But how about more specifically than take us to the next level? What do you hope to get done there?

Ellen Nussbaum 14:11
So what I’m hoping to get done is, you know, you mentioned Ben, Ben is really a thought leader in the face. And he loves learning more about it, studying it, evangelizing it meeting with customers, and so forth. So what I’m hoping is that two heads are better than one. And we’ll let Ben really focus on the technology and are we modeling and understanding the right things? Are we getting to the right answers? And I’m going to really help with how do we take this technology and build out our market facing side? How do we make sure that we’re supporting our customers in the way that they need to be supported and to really focus on the front of the house, you know, the marketing, the sales, support, customer success and so forth. And so Ben and I speak every single day I think is a really great marriage of the skills that he brings, and then me trying to help with that the go to market side of things. Got it.

John Sumser 15:00
Got it. So what do you think the big ethical issues are assuming that you don’t start collecting individual data? What are the ethical issues beyond that?

Ellen Nussbaum 15:08
I would say that, you know, in my time here and the customers that I’ve been meeting with, the question I’ve heard is, you’ve got all this data, why not add the individual information? Couldn’t we be more impactful if we could show them how they compare with our colleagues? Or if we could let the managers know focus on this person, they need to prove x y&z and that to me that the ethical question and you know to use your description, assuming that we’re not collecting content, we’re not doing any of that piece like that. That’s fundamental. That’s starting points. But the ethical question that comes up is to say, could we be more impactful? And could we actually help the employee more if we provided individualized data? And I think that’s an interesting conversation. But Humanyze really comes down very strongly on the side of we’re not focused on the individual. We’re going to let the direct manager collect and evaluate you know, individual performance. We really are focused on the organization, we feel like that’s where we can have the most impact. And again, you know, one of the things that we do is when we share metrics back to our customers, we won’t show any metrics for a group that’s less than three people. So not only won’t we give it individually, we won’t show it in a small group that people could then reverse engineer and so forth. And you know, that’s not always popular among our customers among the manager, like they may say, I want the individual data, there’s more questions I could answer here. And in my mind, in some companies may go down that path. But for us, that’s been a real fundamental starting point to we’re going to prioritize the employee experience over, you know, individual employee productivity and so forth. And that really drives a lot of our decisions around data and privacy. And it really drives the direction of our product. So again, you know, some companies may go a different path, they may say, you know, we’ll give you all this information about Tom vs. vs. Harry, we’re not going to do that. That’s, in my mind, one of the ethical questions that’s really shaping our product roadmap. Got it. So I wonder if You talk about understanding managers in their groups, essentially, is it possible with Humanyze to identify a demographic group or a project group? That’s an ad hoc group so that you can see behavior inside of those constructs? And do you think about doing that? And is that ethical in your view of ethics? So I was a is a conversation with the company around what question are we trying to answer? And how do we get at that? So if the questions are about diversity and inclusion, right, then we would want to collect certain information and answer that, you know, our people have specific grouping and in the conversation, I may be invited to meetings, are they being engaged at the same level as their peers? So those are questions that we can answer. I will say that we have an ethics committee that anytime a customer asks for something that is, you know, different that we’ve done, or maybe it’s pushing the edge that the group will get together and they’ve been, you know, specifically trained to really think about, you know, what is the question? We’re trying to answer is it an ethical question to answer? Is there any way that the company could then reverse engineer try to use it in the wrong wa?y And I will say that they err on the side of caution and not answering a question or not doing a specific grouping if they think that there’s something questionable about it, but there is no you know, there’s there’s great areas to a bunch of things. So I think it’s important that we have this group that meets regularly and really start to discuss what are the questions that are being asked what is the best way to get asset? Is there anything that we wouldn’t want our product to be used for? And then we’ll go from there. But there’s a lot of potential to answer some of those diversity inclusion grouping questions as long as it’s set up in the appropriate way.

John Sumser 18:40
It seems to me that as long as you stay within the lines and boxes, right, and there’s a school of thought that says the lines and boxes management style is on its way out the door, but as long as you stay within the lines and boxes, you can honor and liberty but as soon as you start looking at the way that work actually gets done, most places which is in cross functional teams, it starts being inescapable Who’s Who? And so I wonder if you thought about the fact that your approach limits your ability to see how work gets done.

Ellen Nussbaum 19:11
And I think this goes back to your last question, right, which there is some set of questions that to go to a very fine level of detail, you would need to be able to be willing to provide information that we’re not willing to provide. But I would say that’s actually not the set of questions that we as Humanyze are really focused on, we are really focused on organizationally, what are the patterns? And what are the things that are working well versus less well and less about very specific finite individuals and more about how can you How can the leadership drive organizational effectiveness at a broad level? Because you know, most of our customers are dealing with 10s of thousands, if not hundreds of thousands of employees. So really kind of how do we address some of the large organizational structure questions that can that can have a very significant impact on us all.

John Sumser 19:58
Awesome. Awesome. So wherever Humanyze is going what are the next research horizons for Humanyze?

Ellen Nussbaum 20:05
Great. So I think a couple things that we’re focused on for 2020 is there’s a lot of different possible data sources. And before we go and just kind of stick it into our model, we really want to understand is it impactful? Right. So you know, we’ve got some web conferencing system, which are the ones that people are really starting to use and pick up traction. And we want to know which one should be included in our model is critical. You know, maybe if you’re an engineering, it’s critical that that gets added and so forth. So we’re always looking for how can we improve our models? How can we make sure that they provide as rich as possible and understanding without kind of including noise that that doesn’t really matter? You know, more and more. We’re seeing collaboration with real estate teams and with the emergence of things like smart buildings that companies have more information about geography, and they’re asking real questions around is the open floor plan the right answer? What should collaboration spaces look like? Do I have to Right next up conference room. So I think that’s another one of those different data sources that we’re that we’re building partnerships to incorporate and see, which are the ones that really can be predictive and impactful. The other thing we’re really focused on is, you know, now that we’re really getting momentum and getting more and more companies, we can start to see what these behaviors and what these metrics look like, across companies across industries across geographies. And so that’s something that we’re really excited about. There’s not going it’s never going to be there’s no right or wrong, or everybody should get to this specific number. But let’s have reference ranges, let’s say companies like you tend to operate in in this part of a particular range. And so that way companies can at least see, you know, am I spending more or less time in meetings for my teams? Are people having more or less time available for one to one conversation with their teammates versus managing up in the hierarchy and so forth? And really coming back to you know, there’s no right or wrong answer, but there’s certain pattern and can we collaborate? Which patterns seem to correlate with higher performance versus lower performance? And, you know, again, taking the data that we have across this customer base and really starting to give companies a sense of how they compare with their peers, because I would say for me, that’s one of the most common questions not just at Humanyze but any software company I’ve worked at? It’s always been okay. No, am I did this, but Is that good? Is that bad? What does good look like? And I think that we’re in as good a position as anybody to really start to define what good looks like and what company should we be aiming towards.

John Sumser
How interesting. So thanks again for taking the time to do this. Would you reintroduce yourself and tell people how they might get a hold of you?

Ellen Nussbaum
Yeah, well thank you so much for having me on this morning I really appreciate it. I’m Ellen Nussbaum, if you have questions about Humanyze you can reach us at info@humanyze.com and that’s H-U-M-A-N-Y-Z-E dot com and also please follow us on twitter for more news and exciting updates and that’s @Humanyze.

John Sumser
Thanks Ellen, it’s been great talking with you and thanks everybody for tuning in this morning. You’ve been listening to HRExaminer’s Executive Conversations, and we’ve been talking with Ellen Nussbaum, who is the new CEO of Humanyze. Thanks again, and we’ll see you back here next week. Bye bye now.