Organizations are complex. Complexity science can help us understand them.

But over time, as technology has improved, we’ve gotten better at collecting and analyzing data. Much better. In response, a new approach to understanding complex phenomena—a new discipline, really—has begun to take off. This discipline is called complexity science.

When faced with a complex problem—like how the oceans will respond to climate change, or how the neurons in our brains communicate with each other, or how traffic could best be routed in a rapidly growing city—complexity science encourages a holistic view. Instead of breaking the problem into tiny parts and studying each one separately, you can analyze the system as a whole.

And if this all sounds a bit abstract, like something that businesses don’t have to think about at all, think again – because markets and organizations are complex systems too.

In 2023, Kellogg launched the Ryan Institute on Complexityfounded by three Kellogg professors with very different academic backgrounds: Brian Uzzi (a sociologist by training), Dashun Wang (a “reformed physicist”), and Ben Jones (an economist).

Kellogg Insight recently recorded a podcast with Uzzi, Wang and Jones. In it, we discuss why complexity science’s time has come and why you should be paying attention. Here are some highlights from that conversation, edited for length and clarity.

On why it is so important to analyze the whole of a system

Dashun WANG: The normal example is to think of a flock of birds. If you look at the flock of birds, you realize that they go together almost like an organization, but there is no middle manager in this flock. There is no CEO. But as a whole, they exhibit a kind of quality that no single bird can. Individual birds can really achieve very little. as a herd they have a competitive advantage. They can then search for food sources that individual birds could not.

In what counts as a system

Brian Uzzi: In complex systems, system boundaries are always an issue because it’s somewhat subjective as to where you want to define it. So if you look at a rock and roll band, is it the five people in the group? Is it the group and the producer of the album plus the label that markets it? You can open and close the boundaries and see different things depending on where you start and where you end.

Wang: Or another way I see it is: everything is a system, it’s just on a different scale. A team is a system of different minds working together. Every mind of every brain is a system made up of billions of neurons.

On the importance of introducing an interdisciplinary perspective to study systems

Ben Jones: One thing that unites us is trying to understand where great breakthroughs in technology, innovation and science come from. I will come to it with a certain kind of financial context. Brian will do this with more of a sociology framework, which will emphasize more of the network orientation, more of the social context. And Dashun can do this with models that come from physics but are analogous to human behavior. And so when we work together, we are able to open up our conceptual orientations and find a question in a more original way because we can listen to each other and find new and broader ways of thinking.

On what a ‘systems approach’ can tell us about a topic that businesses are likely to care deeply about: innovation

JONES: Is an R&D team like a string quartet, or are they more like the co-pilots in the cockpit of an airplane?

If you had four pilots, two really good and two rough ones, and two planes, would you want to combine the rough pilots or would you want to split them up among the good pilots? You would like to put a good pilot in every plane. You wouldn’t want to mix up the rough pilots because you want to make sure each plane has at least one good pilot, right? Because essentially the quality of the airplane that flies will depend on the best person in the cockpit. So you don’t want to have only bad people in the cockpit.

But let’s say I’m trying to make string quartets. Want to spread my music cartoons? I do not. Because one rough member of the quartet will ruin the whole sound: if one plays off time or off tune, it will ruin the whole effect. What you really want to do is isolate problem cases and you want your best people to work together.

Okay, now you go to an R&D team in an organization. You have some people who have really great ideas. Are you breaking up? Or do you want to combine them? So we studied this by looking at large-scale data and watching what happens as people move from different groups. You see how they perform in different contexts.

It turns out that R&D teams are a lot like string quartets, not pilots. So, in other words, you don’t actually want to spread your best people. You would prefer them to cooperate. And this goes back to people being specialized. In a modern R&D situation, people bring specialized skills to teams, and if you have a weak link in one of the experts, they can cause the entire project to fail.

On why now is the time for complexity science

Wang: If we boil it down to two key factors, it’s data and tools. I think on the one hand there is this large amount of data that captures many aspects of business and a range of human behavior: this data has now become available in a way that was hard to imagine 10 years ago or 20 years ago. So just the unprecedented level of access we have to the data.

But at the same time, I think what is often overlooked is the availability of tools that can help us make sense of this data. And these tools include complexity science and networks as a tool, and large language models or artificial intelligence as a tool. Then you can borrow these kinds of tools to ask very fundamental social science questions that we otherwise couldn’t.

On their goals for the Ryan Institute on Complexity

Wang: Complexity science won the Nobel Prize in physics, but when it comes to its application to business and the social sciences, we’re just at the beginning. We’re really just scratching the surface.

Traditionally, social science research has been individual faculty members working in their offices. But one of the things we hope to do with the Ryan Institute is to bring the kind of laboratory model that exists in the hard sciences to the social sciences. Hopefully, this will allow faculty members at Kellogg, as well as across the university, to more easily form new partnerships, scale faculty time, work together on bigger problems, and attack those problems more quickly.

JONES: Today, we have much more knowledge, technical knowledge, scientific knowledge about how to do things. And so you just can’t be an expert as easily as you were in the past. The Wright brothers were two brothers who built the first airplane and are both considered the leading aeronauts of their time. They think of the airplane, design it, build it, and even fly it. And these are only two people, and they are able to do this work. But a modern airframe, like an Airbus or a Boeing 787, just the jet engines are 30 different PhD-level disciplines. And that’s just the jet engines!

UZZI: As scientists and people trained to solve problems see a smaller part of the world, they are also equipped to solve problems that concern only a smaller part of the world. But the problems have become bigger and more complex and global. And the only way to do that is to bring people back into a network. The Ryan Institute is an incredible opportunity to join the effort to define that future.