Wharton's Laura Huang and Anoop Menon discuss their research on entrepreneurial activity in the aerospace industry.

Space exploration is a complex, highly technical and increasingly expensive endeavor that traditionally has been the domain of big governments. But more private firms are jumping into the fray and achieving success. In a recent paper, “Watershed Moments, Cognitive Discontinuities, and Entrepreneurial Entry: The Case of New Space,” Wharton management professors Laura Huang and Anoop Menon — along with coauthor Tiona Zuzul from the London Business School — studied the watershed moments that have enabled this frenzy of entrepreneurial activity. Huang and Menon recently spoke with Knowledge@wharton about their findings.

An edited transcript of the conversation follows.

Knowledge at Wharton: Could you summarize what you were studying in this paper?

Anoop Menon: We are big aerospace buffs. There has been a huge amount of buzz in the aerospace industry in the past five years or so. There’s Elon Musk, there’s Mars colonization, space travel. But aerospace is a classic example of a hard-to-break-into industry. This is a really entrenched industry with very high entry costs because of capital requirements, skills that are required, and regulatory connections that you need to have. Many people have tried to enter it to do private space and have failed. But all of a sudden, in the past decade or so, a big change. What happened here? Why? What drove this change, and can we understand something about industry evolution and entrepreneurial entry by studying this particular case? That’s what got us started.

Laura Huang: We were interested in this aspect that there’s new private firms that are entering this industry. I was really interested in looking at these private firms. Anoop was really interested in their cognitive models and their mental models, and our third co-author, Tiona Zuzul, who is at London Business School, was also interested in this aspect of entrepreneurial entry. You have this industry where it’s been so difficult to enter, yet we see progress has been made in the past decade. We wanted to investigate why that was and how did that happen.

Knowledge at Wharton: How did you do that and what did you find?

Huang: We recognized that this is an industry that has a lot of history. We went back to the 1950s and even earlier. We have 21,000 articles, conference proceedings and documents dating back to that time period all the way to the present day. We looked at what was happening. What are the changes? Where do these changes come from? We also supplemented that with lots of interviews with regulators, engineers, people at all the different touch points in the industry.

Menon: One of the really fun things about this project was that I got to talk to an astronaut; I got to talk to a colonel in the Pentagon; I got to talk to NASA people. It was fantastic.

“You have this industry where it’s been so difficult to enter, yet we see progress has been made in the past decade.”–Laura Huang

Huang: Sometimes all in the same day. They have been incredibly willing to share their own thoughts on this industry. We’ve used that and looked at both the conference proceedings and all these documents we had, and we thought about all of these different angles that we could [examine].

Knowledge at Wharton: Was there a particular watershed moment for the industry?

Menon: The academic literature on how industries change, where do opportunities come from, tend to look at either big breaks in technology, big regulatory changes or some sort of social movement or collective action. These are three big buckets that we have been talking about, and there are aspects of that here, too. But what was interesting is this cognitive element as well, and that’s where this watershed moment comes in.

If you think about any industry, especially these kind of stable, long-standing industries, you have the major players who all have beliefs about who does what, how things work, the rules of the game, if you will. If anybody tries to deviate, they get kicked out or pulled back into it. These are relatively resilient mental structures, or collective mental models, that define the rules of the game for the industry. What we are trying to say is that these watershed moments are big, shocking events that cause actors to sit back and wonder if things should always be this way. There’s the initial big watershed moment, which is the Sputnik moment, and it is a term by itself. Sputnik gets launched and all of a sudden we freak out. That causes NASA to be founded, DARPA (Defense Advanced Research Project Agency) to be founded — big changes. All of a sudden, this is the Cold War being played out in space. That gels the collective mental model around the belief that space is for big governments, big firms, failure is not an option, a lot of money is required, only the top talent can be here.

The first set of shocking watershed moments happened at the end of the ’80s. You get the Challenger disaster — which very shockingly, very vividly demonstrates to the public that maybe the government doesn’t always get it right. Maybe things can go really badly wrong. At the same time you get the Cold War ending, the Berlin Wall falling, and that causes many people to question why we are spending so much on space. Then committees get formed. How do we rethink space? That causes what we call the initial shake-up of the model.

Huang: What Anoop is referring to is this dislodging of this mental model that was there. A lot of this entry, a lot of this disruption that we’ve seen in the past was happening through technological discontinuities, through regulatory discontinuities, through collective action. But we’re finding in our data and analysis of this context that it’s these cognitive discontinuities that are catalyzed from these watershed moments. Watershed moments here are these very emotionally resonant, very publicly recalled moments — like Challenger, like the fall of the Berlin Wall. Those dislodged. Then we find three other ones that re-solidified, that brought about this new mental model. In 1986 we had Challenger, in 1989 we had the Berlin Wall, then we have the Columbia disaster. It’s something that we all vividly remember. I can remember watching this and can recall where I was when Columbia happened. Then we also have the awarding of the COTS (Commercial Orbital Transportation Services) contract and Ansari XPRIZE. We’re seeing that there is this new entrant, this relatively unknown company that is getting awarded this contract that was going to people connected to the government. We’re seeing this sort of shift that it’s not just the government; it’s not just a national endeavor. Now these private firms are coming in.

Menon: That initial model, which was called the Old Space or the Big Space model, gets really shaken at the end of the 1980s, and then the government tries pretty hard to encourage private sector engagement. They try different programs through the 1990s, but there isn’t much success. There is a Texan banker billionaire named Andrew Beal, who was like Elon Musk before Elon, who put in [something like] hundreds of millions dollars of his own money into Beal Aerospace, his private venture. But he shut shop in 2000 or so, and there’s a very public letter that he put out where he blames NASA. He says, “Hey, you say you want private space to be involved, but you’re still making your sweet deals. You give your sweet deals to the Boeing and Lockheeds of the world. We small guys just can’t compete.” It’s this transition period where we’re trying to bring in private space but we don’t know how to do it. There is no consensus or a collective mental model on how this should be done.

“We need data in order to make our decisions, but we also need to remember that you need to have a lens with which to analyze this data.”–Laura Huang

But after Columbia happens and then the Ansari XPRIZE, a private company with private money was able to build a plane that went to space, came back, turned around, did that again. Private people can actually do this. That’s a big shock to everybody. Once they believe it is possible, things start to get into motion. Then we have the precursor of the COTS contract. It’s like NASA should become more like a venture capital firm rather than this cost-plus regulator who is controlling everything. It’s a big mindset shift that happens, and then you start converging towards the new model that we see today.

Knowledge at Wharton: What can the space industry take from this research? Also, what can other industries learn from it?

Huang: That’s a great question because we are relatively contextualized. We’re looking at this one industry. We would love to look at other industries as well. But in general, we tend to think that disruption and entrepreneurial emergence happens from these big technological shocks. Something big happens, and that paves the way for other new entrants to come in. Or there’s a big regulation that changes the incentive structure and allows other people to come in. What I think industries can take from this is that it’s more complicated than that. There are lots of things that are happening. There are these emotionally resonant events that are happening all of the time. We don’t know what form it’s going to take necessarily, but they are affecting the mental models. Even if there are technological shifts, it’s co-evolving alongside these other changes in our ways of thinking, in our mental models, our mental schemas and prototypes. Keeping that in mind as industries are evolving and as companies are trying to play within these sorts of rules is really important, I think.

Menon: In entrepreneurial courses, we ask where the opportunities are. Let’s analyze the industry landscape, the technological landscape and the regulatory landscape to find where the opportunities are. What we are seeing is that maybe we can also analyze the mental landscapes, the cognitive landscapes of the agents, what their beliefs are and how they are changing, as another avenue to think about where opportunities might be and where change might come from.

Knowledge at Wharton: It does seem to be a kind of cautionary tale to other industries. You may have the technology to do it, but if people don’t believe you can do it or don’t believe it’s your place to do it, then they’re not going to buy into it.

Huang: Yeah, the technology is absolutely an enabler. We tend to think of the aerospace industry as a very technologically heavy industry. There are advancements, and those are enablers. Without the internet, this wouldn’t have happened. But those were not responsible for the disruption. They were not responsible for this entry. We’re seeing lots of incremental advancements. It’s not one big technology shift or one big technology disruption that was causing this.

Menon: It’s the tech that catches the attention, right? But the cognitive thing is a big subtle. I’ve had rocket scientists who are the best in the business say, “We know how to do this. We’ve had the capability for decades, but nobody would believe me, nobody would fund me. So what can I do?”

Knowledge at Wharton: This research relied a lot on personal interviews. These days, we hear a lot from companies about the need to analyze data. Do they need to go out and talk to people more?

Huang: We talk so much about big data now, and I think data is absolutely critical. We need data in order to make our decisions, but we also need to remember that you need to have a lens with which to analyze this data, with which to understand this data. That’s where I think these sort of personal interactions — bringing together what your mental model might be, looking at different contexts — are really necessary in order to make sense of the data.

Menon: One of the other research streams that I have is working on big data and machine learning. One of the things that I’m trying to do with that is to extract people’s mental models from what they say and what they do using big data techniques. While talking to people is still what I like to do, and that’s one very good way to get at this, I don’t think it rules out data either. There is a lot that you can say about how people are thinking that you can do from machine learning.

Knowledge at Wharton: What sets this research apart from other research that’s been conducted on the topic?

“These watershed moments are big, shocking events that cause actors to sit back and wonder if things should always be this way.”–Anoop Menon

Huang: What we mentioned before is that there are different ways of understanding emergence and entrepreneurial entry. We’ve seen lots of these different ways that definitely resonate in a lot of different contexts, and this context as well. But what we’re finding here is that there is another route that perhaps could co-evolve with these things. It could co-evolve or it could potentially supplant. We also find that through these emotionally resonant events, through these watershed moments, that there are catalysts that are changing the way that proceeds. I think it’s important to get this holistic understanding in all of its complications and all of the different forms that it could come about.

Knowledge at Wharton: Can you identify a watershed moment while it’s happening, or is it only possible to do that looking back?

Menon: That’s a very good question. Right now, it’s all historical. Can we do it live? That’s something we need to think about. I’m sure psychologists like Laura can quickly develop metrics to see the emotional resonance that certain events are having and what long term impact that it could have on the industry.

Huang: Because there’s this solidifying sort of process, we could perhaps identify that this is an important, emotionally resonant event. But to actually understand the effect of that, more things need to go into it. Something that Anoop and I have talked about is that it’s really important to understand how this continues to evolve. Something goes wrong and something is blowing up — we see this all over the news. It’s important to continue to track this.

Menon: Recently, the Space X rocket exploded on the launch pad. People have said this is a very touchy industry exactly because how visible and explosive everything is. People are worried that one big failure is enough to go back to where we were. What determines the impact that any one event is going to have? I think that’s a great question for future research.

Knowledge at Wharton: How will you continue this research?

Huang: We want to understand a little bit more of the micro-drivers of this. Right now we’re looking at what’s happening; we’re looking at these changes in mental models. But one thing that we’ve talked a lot about, and with our co-author Tiona as well, is understanding more of the granular mechanisms behind this and what’s happening on this more individual level.

The other thing that we mention a lot is context. This is an in-depth look into one particular industry, one particular context. We believe there are other contexts where these emotionally resonant, or watershed, moments are going to have this big effect on mental models. But they may operate in different ways. In some industries it could be technology that’s driving it, and these watershed moments are taking more of an ancillary role, or it could be the opposite. I think those are all different things that we and other scholars will continue to look at so that we can really understand this phenomenon of entry and disruption.