Chicago Booth Review Podcast Does Collaboration Really Produce Better Ideas?

Michael Gibbs: Putting different minds together leads to better thinking, sharing of different kinds of expertise and comparative advantage. But I think another thing we can't prove, but I think is maybe true, is when you have multiple people working on an idea, they're going to challenge each other's thinking. So it raises just the quality of thought for both of them.

Hal Weitzman: Most companies talk about the importance of innovation and collaboration, but the connection tends to be more of a hunch than a demonstrable fact. So can we measure whether collaboration really produces better ideas? Welcome to the Chicago Booth Review Podcast, where we bring you groundbreaking academic research in a clear and straightforward way. I'm Hal Weitzman, and today I'm talking with Chicago Booth's Mike Gibbs about his research on social networks and innovation. Does having a bigger network make you more likely to come up with new and better ideas? And how has remote work affected networking and innovation? Mike Gibbs, welcome back to the Chicago Booth Review Podcast.

Michael Gibbs: Hi, Hal. Good to be here.

Hal Weitzman: Now we got you here to talk about your research, which is about social networks and how they affect innovation. Those both seem like pretty vague terms, social networks and innovation. What's the data? How do you measure this kind of stuff? What's the data you use?

Michael Gibbs: Well, there's two parts, but they come from the same thing. We have innovation data from an Indian company, HCLTech. This is the fourth study we've done with data from HCL, and they have an employee suggestion system, which they consider to be very important to them, and they run it for many years. And we collected data on ideas suggested by employees. So that's the innovation data. And I can tell you more about that if you like later. And then the second part is we use those data to get measures of social networks among employees who are innovating. So many ideas are suggested by multiple employees, for example, and that's a connection. And we also knew the part of the organization they worked in, their client teams specifically.

Hal Weitzman: Okay. So you're looking at what teams they're in, what ideas they're coming up with through this suggestion system and that yes, we will hear more about it. But just explain a little bit about the terminology you use here, because your focus is on social networks and you talk about three important characteristics of social networks. They are degree, network size, and bridge centrality. So explain what those are and then what do they have to do with, how do they relate to innovation?

Michael Gibbs: Okay. Degree is the number of collaborators that you have in a given period. So this research I'm doing with Friederike Mengel and Christoph Siemroth at the University of Essex, so that's three people right there. My network degree I guess would be two, although I do have other co-authors. So it's the number of people that I collaborate with in a given period of time. Network size is the size of the group of people that I'm associated with, so that's going to be people I'd collaborate with who might be in my team, might not be in my team, and other people who are in the team that I might not be suggesting ideas with. And then bridge centrality is kind of an esoteric concept coming from sociology. It's derived from very influential work by former Booth Professor Ron Burt on social networks. And he wrote a very famous paper and then a book about bridging what he called structural holes in a network. And so bridging centrality is a measure of the extent to which each employee plays that role or doesn't play that role in bridging across gaps in the network.

Hal Weitzman: Okay. When you say gaps in the network, what does that mean?

Michael Gibbs: Yeah, so-

Hal Weitzman: What will be an example of a gap?

Michael Gibbs: A gap, okay. So sociologists, I'm not really a network sociologist. I'm an economist pretending to be-

Hal Weitzman: Okay, but this is your framework. So the framework that you're using from your [inaudible 00:04:01].

Michael Gibbs: That mostly comes from sociology, although economists study networks too. So networks are ubiquitous in our life. You have networks with parents of friends of your children, for example, and people who might go to the church you go to or that you're in some kind of club with. I have networks of former students all over the world and so forth and so on. So there are networks at work and there are networks outside of work. What's interesting for sociologists often is how those networks function and the value they might bring to someone's life, and in particular their career, in my case and the work by Ron Burt.

And for many, many years, they talked about weaker or stronger ties. So a weak tie might be someone that you know, but not very well. You don't interact with them very much. A stronger tie would be someone you interact with relatively frequently, maybe in multiple dimensions. So you work with the person, maybe you socialize with them, maybe commute with them. That's three different levels of interaction. And there are other measures that can be used to measure that, such as is the interaction symmetric or bidirectional and so forth.

Hal Weitzman: Okay. And so you were talking about the holes. Holes-

Michael Gibbs: [inaudible 00:05:13] the gaps, yeah.

Hal Weitzman: The holes between that people are bridging.

Michael Gibbs: So if we imagine a network of 10 people and we all have strong ties to each other, there's no holes in that. That's a dense network. Imagine instead though, that there are three people who were closely tied to each other, and then there's another seven that are closely tied to each other, but there's only one loose tie between those two sub-networks. Whoever the people are who are that loose tie between the two networks, we would say they are bridging that gap and that gap is often called a structural hole in the network.

Hal Weitzman: If you have a sales department and an IT department, and there's only a couple of people who professionally interact across those networks, then they're the bridges.

Michael Gibbs: Yeah. I'll give you an example from Ron Burt's work. He collected data on social network in a electrical supply company, and then he focused on the most important 89 executives I think it was. And he plotted the diagram of the network, and then he shaded different parts that were corresponded to the people working in the same division as each other. And you could clearly see that if you're working in the same division, most people are relatively strongly tied to each other and it's a relatively dense network. But then you could also see that there were very few connections from one division to another. In some cases, none. In the middle was corporate headquarters and sort of each division was tied to corporate headquarters, and then HQ was tied to all the other divisions and then here removed headquarters from the picture. And what you see is just a couple of dashed connections between some of the divisions, and those are structural holes.

Hal Weitzman: Okay. And some people are able to bridge those holes. Okay, all right. So bridge centrality means?

Michael Gibbs: It's a measure of the extent to which you are doing that or not.

Hal Weitzman: Okay, excellent. So those are the three characteristics of networks. How do they relate to innovation?

Michael Gibbs: Well, innovation is widely believed, well, innovation has many causes, but one of the most important one is your access to information, knowledge, ideas, expertise, someone you can tap when you have a problem you need to solve. We think it comes from mixing people with different perspectives, different backgrounds. It could be different types of human capital, could be they come from different countries and so forth and so on. In our MBA program, we'll have student study groups. And the reason for that is we think learning will be better if the students are working together, collaborating. And in a microeconomics class, some will be strong in the math, others will be strong in intuition and so forth and so on. In our executive MBA program, we go so far as to try to create groups where the students come from different countries or even continents in some of the classes, and it's all for the same idea.

Hal Weitzman: So it sounds like innovation often comes from getting people who are not in the same network or would not normally be in the same network to force them together into the same network. Is that right? Or at least interact?

Michael Gibbs: That's the-

Hal Weitzman: You're reminding me of our colleague, Richard Thaler said, "I took ideas from psychology, applied them to economics." And thereby was one of the forefathers of behavioral economics, for which, of course, he won a Nobel Prize. Is that how innovation, not at that level, but the same kind of process works across all organizations?

Michael Gibbs: I think that's true. Again, it's not the only source of innovation, one of the important ones is just expertise. Digging deep into a problem by yourself can lead to some innovation reflecting, reading, and so forth. But it is, I think, an important one.

Hal Weitzman: Okay. So you find a strong association between, we talked about network degree, the number of direct collaborators and the quality of employee ideas. So explain that and what it means for, what it tells us about collaboration.

Michael Gibbs: Well, first of all, the quality of ideas, I should mention. This employee suggestion system, employees suggest ideas, enter them on the internet. Within a couple of days, their supervisor is supposed to evaluate them, decide whether he or she thinks they're worthy of consideration. Usually they will, but sometimes they can reject them and then they'll try to, if necessary or if helpful, refine the idea with the employee. And then those ideas are sent to a panel of senior executives who meet every couple of weeks on the internet, and they judge the ideas. A little bit like a new venture challenge at the University of Chicago.

Hal Weitzman: Entrepreneurship competition.

Michael Gibbs: Exactly.

Hal Weitzman: So we're assessing whether these experts think that these are good ideas or not?

Michael Gibbs: Yeah, exactly. And these are senior executives, which gives you some idea of how seriously HCL is taking the system. These are significant resources that are involved. These executives have valuable time and so forth. It also means it's a high quality measure of quality because it's a subjective assessment of all the dimensions of the idea, not just some kind of numerical analysis or something like that. And that's the best way to assess something. There's often going to be intangibles from an idea that's suggested, for example. And then, so the first measure of quality was accepted by this panel for implementation. In many cases, the ideas are then submitted to a client because HCL is hoping that employees will suggest ideas that can be directly beneficial to their clients as consultants to Microsoft or whoever the client is. And so our second measure is when the ideas are submitted to the client, were they accepted for implementation or not? And again, that's a very meaningful measure because the client is external to the organization, they have no incentives to bias their evaluation of these ideas.

Hal Weitzman: So the high quality of the idea, the greater the network degree, is that the association?

Michael Gibbs: Yes, the correlation, I guess you could call it.

Hal Weitzman: The correlation, okay. So the more direct collaborators have been around the one particular idea, the higher quality it tends to be?

Michael Gibbs: That's true, but also I may suggest multiple ideas. So it's the number of collaborators I have, and they may not have worked on this particular idea with me.

Hal Weitzman: I see.

Michael Gibbs: For example, I have co-authors for other research. They're part of my degree. But the main idea is if I collaborate with multiple people, my ideas tend to be of higher quality, which I think is really nice evidence of this idea that putting different minds together leads to better thinking, sharing of different kinds of expertise and comparative advantage. But I think another thing we can't prove, but I think is maybe true, is when you have multiple people working on an idea, they're going to challenge each other's thinking. So it raises just the quality of thought for both of them.

Hal Weitzman: Okay. But I also noticed that you found that this, as you call it, positive collaboration effect, is instantaneous and short-lived. What was that finding about and how do you explain that?

Michael Gibbs: Yeah, I think the way I think about that is I've collaborated with you on this idea, now I'm going to move on to other things in my work or other ideas. And if I'm not collaborating with you on those ideas, our relationship doesn't really matter for this new idea because if it did, I would probably be going back to you.

Hal Weitzman: So it's not the collaboration in itself, it's the collaboration on this particular idea that is actually the thing that produces the innovation.

Michael Gibbs: Or the quality of that, yeah.

Hal Weitzman: Okay. So you referred to this literature, the classic literature, Ron Burt influenced a lot of it on social networks and this idea of structural holes in organizations. And we explained a little bit about what that is, but your findings, I think, diverge a little bit from the conventional view of the significance of these structural holes. What's the traditional view and then what's your nuance that you gloss onto that?

Michael Gibbs: The traditional view is that if I'm bridging across structural holes, I'm going to be more innovative. I might have more ideas, I might have better quality ideas. Just simple, full stop. And there's empirical research, including Ron's, which finds that that's exactly what happens. Okay? I think our data, arguably the best quality data that have yet been used for this kind of thing, many studies will go into an organization, they'll ask an employee suggest, come up with some ideas just as a survey. It's not part of their job, but the researcher asks them to do that, and then they'll ask others to evaluate the quality of Hal's new idea. And that's a useful way to study innovation. But we're working with real innovation. The other thing is we have data on the same people over time. We see them collaborating with some people sometimes and sometimes not.

Sometimes they don't suggest ideas, sometimes they do. So we can look at sort of the dynamic aspect as well. So what we find is that if you are bridging a structural hole, the quality of your innovation tends to be lower during that period of time, which is what's different than the conventional wisdom. However, later on, say next year or the next year after, the quality of your innovation improves compared to what it would be otherwise. And the net effect is positive. So bridging does improve your innovation, but it takes some time. And the benefits accrue only after the cost of playing the role, broker it across structural holes.

Hal Weitzman: And what's driving that? Is it because I'm just not an expert and as I'm getting up to speed and as I'm bridging the hole?

Michael Gibbs: Kind of. When you're seeking help from others outside of your direct network, you're probably doing so because you want access to their ideas or knowledge or expertise or something like that. But first of all, you need to spend some time making that connection because by definition, it's going to be a relatively weak one. And second, some translation might be needed. I might be asking a sociologist to help me understand network sociology, but then I have to listen to that person. I'm getting new ideas, I have to absorb them, I have to understand them, I probably will do so imperfectly at first. So there's some effort involved and some translation cost in brokering, but it does pay that benefit later. And then the other thing we found is that if you're a broker, while it may harm your innovation initially, it benefits your colleagues in your network immediately. So it's as though you have what [inaudible 00:15:20] would call a positive externality effect.

Hal Weitzman: Okay. And the difference with the conventional thinking is that people thought that that, or the idea was that that benefit came immediately, that you were immediately more innovative just through the act of being a broker?

Michael Gibbs: As I understand that literature, coming at it from the outside.

Hal Weitzman: Okay.

Michael Gibbs: I'm crossing boundaries here myself.

Hal Weitzman: You're introducing this idea that it is beneficial, but only over time?

Michael Gibbs: Right. And there's a cost involved with a payoff later. And then the second thing, which I think is not really a surprise, but is important is that you have this positive externality for your colleagues. The fact that you have gone to the trouble of playing that role means they benefit right away because they don't have to pay the cost, they just have a direct tie to you.

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Mike, in the first half of the episode, we talked about social networks, the effect they have on innovation, and essentially the finding was that the more direct collaborators you have, the better quality your ideas are. We talked about how you measure quality, and we talked about this idea of brokering between different groups, filling these structural holes in organizations. But of course, one of the main things that you and I have talked about in the past couple of years has been remote work and how remote work, both when it was fully remote during the pandemic and more recently when it's been hybrid, has affected the productivity and innovation, everything else. So what did you find about how remote work affects these innovator networks that you were studying?

Michael Gibbs: So it wasn't really our intention to write a paper on remote work, although we've written two before with data from HCL, but it did occur to us that we might as well see what are the effects of working in the office or remotely on social networks. So we collected data in three different periods. The fully in the office period before the pandemic, the fully at home period during the pandemic, and the period they're now in, which most companies are trying to figure out which is hybrid mode. So employees are expected to be at the office maybe two days a week at least, but they can also work from home some days a week.

Hal Weitzman: And what is the hybrid structure in the company you were studying?

Michael Gibbs: Just that.

Hal Weitzman: It's two days?

Michael Gibbs: As I understand it, yeah, you're expected to be in at least two days, and I think they'll hope for more. So what we find is that compared to working fully at the office, social networks weaken in both working fully at home and in the hybrid mode. If anything, maybe hybrid is a little worse, although it's possible that they're still trying to figure it out and it'll get better. In fact, that's probably likely, but both seem to be worse than if people are just working in the office together fully. So I guess, let me be a little more precise about that.

What we find is with hybrid or fully remote, that people collaborate with fewer colleagues, so that's network degree. And there's less acting as a broker across social networks too. Now, in the previous paper, which we published last year, we looked at innovation and remote work, but we didn't measure networks. But what we found there was that innovation suffered both in fully remote and in hybrid mode compared to fully at the office. And I think now we have an explanation for why that is, because the networks suffered and the networks are a key to innovation.

Hal Weitzman: I'm wondering though, listening to you talk about that whether organizations could force networks to be formed, whether I could force Mike to go and work with Jerry from accounting, even though you don't know who that is, because I know that something wonderful is likely to come from it, or I somehow put... And organizations have tried to do that. So I mean, is it necessarily about the modality or is it about just what the modality causes, which is people tend to retreat to the group they know?

Michael Gibbs: So part of it is the modality. I'll come back to your first question in a second about forcing people to work with new colleagues. What we found in the previous study of innovation is that hybrid had a particularly negative effect on innovation for teams that weren't coordinating when they were in the office or when they were at home. We had data on when they went into the office because they had to swipe their ID, so we knew exactly which days they were there, which hours they were there, literally, and we knew which team you were on. So when teams were not coordinating so that they all showed up at the office at the same time, their innovation was significantly worse. So that's an obvious thing that could be fixed and that will help. But that doesn't mean it resolves the problem, which is we're not all in the office all the time. Sometimes we're at home, sometimes we're interacting at the office.

To your earlier question about forcing employees to work with someone from somewhere else in the organization, to some extent you can do that, but the problem is who? So Ron Burt has a famous phrase, productive accidents, and what he means is a lot of the benefits of networks occur because we form a relationship with someone we never knew before. So most of my academic collaborators are not here at the University of Chicago, they're people that I met at an academic conference or something like that. They're different universities, and I didn't know they existed until I met them at a conference.

So what we'd like is for people to be in the office and interacting, not just with their direct colleagues, but finding ways to bump up against people in other parts of the organization. Maybe we rotate them to different teams or something like that. We have meetings across teams so that people can interact. The structure of our building, our main building, Harper Center, I think achieve some of that with the glass lounge.

Hal Weitzman: At Chicago Booth.

Michael Gibbs: Literally everybody walks through that central space. So you're constantly seeing former students and colleagues that you don't normally run into and so forth.

Hal Weitzman: And your theory would be that accidental nature is more, is going to be more productive or more innovative than if I say, "Well, I'm going to set up a task force and I'm going to put you three on it." Three people who don't know each other.

Michael Gibbs: No, I don't think I'd say that. Deliberately seeking out someone who has an expertise that's complimentary to yours, that makes a lot of sense. So you just find out who that person is or you ask them, do you know someone who knows something? But productive accents matter as well. They can take you in unexpected directions, and that's a really important source of innovation.

Hal Weitzman: And that seems to chime with a lot of the sort of homespun wisdom from CEOs, I guess, their expertise, their hunches about we need to get people back in the office just to have those so-called water cooler conversations, get people to bump into each other. The thing you did mention that I want to pick up on is about hybrid work. You found that hybrid had stronger negative effects on network structure than fully working from home. Why is that, do you think?

Michael Gibbs: I think it's because hybrid makes coordination across the team more difficult. If we're all working at home, at least I know where you are and how to reach you. If we're sometimes in the office and sometimes at home, I may not be sure if this is the day you're in the office or not, it may not be the same as the day I'm in the office, so I have to go to some extra effort to locate you. That'll slow things down. It'll make me less likely to even try to communicate with someone. I'll just try to solve my problem. And our evidence on swiping of IDs really speaks to that, I think.

Hal Weitzman: Finally, I wanted to ask you about, you call it diversity of innovation. What do you mean by diversity of innovation? Is it to do with the quality that you talked about earlier?

Michael Gibbs: So networks may improve the quality of my ideas. They might also improve the number of ideas I have, but they might expand my thinking so that the breadth of my ideas also increases. So we wanted to see if there was any evidence for that. And we measure that two different ways. The number of teams, of collaborators that I worked with, so I don't always have to suggest ideas with someone only on my team. And the second was HCL provided categorizations of the ideas into different types. So we measured how many different categories of ideas you were suggesting, and what we found is that those who were acting as a bridge, more of a bridge across structural holes, had broader diversity of their ideas, which is, I think, a really nice illustration of these concepts. How playing that role brokering to disconnected parts of the network, opens you up to new ways of thinking and unexpected innovation, if you will.

Hal Weitzman: Yeah. Well, Mike Gibbs, this is fascinating. Thank you very much for coming and talking to us about social networks and innovation.

Michael Gibbs: Thank you.

Hal Weitzman: That's it for this episode of the Chicago Booth Review Podcast, part of the University of Chicago Podcast Network. For more research, analysis, and insights, visit our website at chicagobooth.edu/review. When you're there, sign up for our weekly newsletter so you never miss the latest in business-focused academic research.

This episode was produced by Josh Stunkel. If you enjoyed it, please subscribe, and please do leave us a five-star review. Until next time, I'm Hal Weitzman. Thanks for listening.