Most people ask: “Why do universities produce so little innovation per dollar spent?” or “Why don’t university labs focus on real-world innovation?” The problem is that we keep using metrics that don’t capture what’s actually happening.

Universities are playing a very different game than companies. They don’t just chase performance. They teach. They serve public missions. They take on harder problems—ones others walk away from. And most of their innovation efforts? They aren’t failures. They’re options—investments in ideas we can’t yet predict.

So when you hear someone say “university patents don’t make money” or “companies do it better,” they’re forgetting the whole point: we’re terrible at predicting success. In fact, most business leaders fail at this too—they just get to pick from projects that already look successful.

If we want real innovation, we need to stop asking why universities aren’t more efficient. The real question is: how do we make life good enough for the people who can see around corners—so they actually want to show up and build?

I’ve spent the last 10 years building a platform to make research better.

To make it less lonely.

To make it more joyful.

To make rejection less painful.

At first, I thought people would jump in.

I assumed: “If I build something good—something that helps—people will just show up.”

They didn’t.

I kept building anyway.

And along the way, I learned the hardest part of innovation isn’t the tech.

It’s not funding.

It’s not even the science.

It’s belief.

Getting people to believe something new is possible…

That’s the game.

And most of us are too tired, too overworked, too skeptical, or too burned by the system to believe.

So we tell ourselves:

• “I don’t have time.”

• “I haven’t heard of it.”

• “I’m already overwhelmed.”

And those are real. I get it.

But here’s what I’ve learned:

If I want to build something that changes anything at all, it’s my job to figure out how to break through that.

Not yours.

You don’t need to believe in my platform.

But maybe this:

If something feels hard to share or grow, it’s not because people are wrong.

It’s because people are tired. Burned. Stuck.

That’s not an obstacle.

That’s the reason to keep building.

Because maybe—just maybe—someone else is quietly trying too.

And they need to know they’re not alone.

The research career is hard in a way that’s not often talked about. It’s not just intellectually difficult — it’s personally difficult. It functions a lot like entrepreneurship. You are left entirely to your own demise. You have near-total autonomy, and what that does is amplify whatever your default tendencies are.

If you are a high-anxiety person — which describes a large number of successful researchers — you will likely internalize everything. You’ll obsess, push harder, and feel like the world will fall apart if you don’t accomplish something today. That’s often why people succeed. But it also means you can burn yourself out or break down completely. The anxiety becomes the thing that eats you alive.

On the flip side, if you are naturally more relaxed or chill, it’s easy to default to avoidance. You just won’t get much done. You tell yourself it’ll be fine — and nothing happens. And nobody is really there to push you, because there’s nobody watching.

The whole system reinforces whatever your crutch is. If you’re prone to loneliness, you’ll feel it more. If you’re prone to overwork, you’ll overwork. If you need structure, there isn’t any. And over time, it becomes clear that the hardest part isn’t the research — it’s regulating your own head.

Most of the damage comes from being left to your own psychology. And that’s what makes the research profession so much like building a startup. It’s rarely about your ideas. It’s whether you can survive being left to yourself.

I’ve become increasingly skeptical of the peer review system—not because the intention behind it is bad, but because of the complicated world in which it’s embedded. On paper, the process sounds idealistic: submit your research, get anonymous feedback, revise, and resubmit. But in practice, it’s a messy system shaped by invisible games, ambiguous standards, and enormous variability in what counts as “good” science.

In this episode, I reflect on what it feels like to send work off into a black box—where editorial decisions are shaped by uncertainty, disagreement, and sometimes just luck. We talk about how reviewers often don’t agree, how “A-level” work depends on who’s judging it, and how real people’s careers and livelihoods are affected by invisible rules no one fully understands.

I still believe in the value of careful research. But I also think we need to get honest about the cost—emotional, intellectual, and financial—of playing the current game. And maybe, just maybe, we need to imagine a better system.

Why do we choose this strange, difficult career of research—and what makes it worth it?

David Maslach sits down with Olav Sorenson, Professor of Strategy at UCLA Anderson and one of the most influential voices in organizational theory and entrepreneurship.

“We’re professional problem solvers.”

In this powerful conversation, Sorenson shares how curiosity—not credentials—built his career. From almost launching a startup to shaping the field of entrepreneurship, he reminds us why the real reward in science is the process, not the prize.

We talk about:

• Why choosing “weird” ideas matters.

• How to build real, lasting relationships.

• Why intrinsic motivation is more powerful than prestige.

This is a reminder that being a good scientist means staying brave, sometimes irrelevant, and always learning to love the climb.

Most people give up.

They try a few times. It gets hard. It gets quiet. No one notices.

So they stop.

And that’s why the game is winnable.

That’s why you never see professors building open platforms.

Why researchers tell you not to start something new.

Why smart people will laugh at your idea and say,

“That’s not how it’s done.”

They’re not wrong.

They’re just done.

But I’m not.

Every day, I show up. Even when no one cares.

Even when I feel ridiculous.

Even when I want to quit.

Because I know the truth:

Consistency outlasts brilliance.

One more day of effort stacks higher than one perfect performance.

And I’ve seen this across research, careers, and life:

The people who win aren’t always smarter.

They’re the ones who refuse to stop when it stops being fun.

They do the boring thing.

The scary thing.

The invisible thing.

Until something cracks.

And then people say:

“Wow, you’re lucky.”

“Must be nice.”

But the truth is simple:

You didn’t quit.

And that’s always been the difference.

I’ve never liked how we talk about retirement. Like life just… ends at 65. You stop being relevant, you stop pushing, and you’re supposed to disappear into golf courses and travel ads. That might have made sense in 1955—when making it to 70 was a miracle. But that’s not our world anymore. Most of us will live far longer than we think, and if you’ve made it this far, chances are you’re healthy, sharp, and still very much alive.

This episode is a gut-check: why “retirement” is outdated, why aging is framed all wrong, and why it’s not too late to build, explore, and press against the world. We’ve confused age with irrelevance—and it’s costing us. It’s time to unlearn what we’ve been sold, respect the long arc of curiosity, and show up again—with all our might.

As a professor and researcher, you’d think I’d be certain about things by now.

But the more I study the world, the more I realize how little we actually know.

We act like understanding is easy—as if truth is just waiting to be downloaded.

But most knowledge is fragile. Most beliefs are assumptions in disguise.

And still, everyone around us—especially in academia—pretends like they know.

This creates a strange culture:

One where people compete by displaying knowledge, not seeking it.

Where learning becomes performance, and doubt is seen as weakness.

But here’s the secret:

The best minds I know live in the tension between knowing and not knowing.

They don’t shout. They ask. They keep peeling things back.

Not because they have the answers—but because they’re still curious.

You are more capable than you think.

Most people won’t tell you that. The world will make you feel small. Rejections pile up. Deadlines feel impossible. And sometimes it feels like quitting is the only way forward.

But here’s the truth: if you’ve made it this far, you already have a level of grit, intelligence, and persistence that few people ever reach.

You don’t need to “prove” yourself to anyone. You don’t need the world’s permission. You are already one of the most capable people in the room.

I’ve been thinking a lot about ultra-wealth—what it means when someone can earn more money in a year than most of us will see in a lifetime, and still have their wealth grow faster than they can spend it. On one hand, they earned it—through luck, skill, or strategy. On the other, we’ve created a world where a few people now sit above every system, every law, and maybe even time itself.

This isn’t a rant. It’s a puzzle.

What happens when wealth becomes untouchable?

What happens when markets can’t contain individuals anymore?

There’s no easy fix. But for those of us studying systems, innovation, and inequality—this is the kind of problem we have to think through. I don’t have the answer. But I think we need to ask better questions.

When I began my academic journey, I assumed science was about accumulating facts that would eventually point to some clear understanding of how the world works. I believed, like many do, that each study added a brick to a larger structure we call “truth.”

But over time, I’ve come to appreciate a more complex view.

In many areas, evidence is often ambiguous, methods rest on assumptions, and interpretation depends on context. The questions we ask, and the tools we use to answer them, shape what we’re able to see.

Pluralism is defined as the view that multiple perspectives, methods, or explanations can each contribute meaningful insights to a phenomenon. In my own work, I’ve found that no single model captures everything. Some scholars use experimental design. Others prefer ethnographic immersion, formal modeling, or archival methods. All have their strengths—and their limitations.

Rather than treating one method as “the” path to insight, I’ve come to rely on what you might call a weighted mental model: I take what I can from each approach and try to integrate these insights in a way that makes sense for the specific problem I’m studying. It’s not always elegant, but it reflects the reality that many phenomena are multifaceted and dynamic.

Truth as Process, Not Endpoint

This doesn’t mean there is no truth. But it does suggest that truth in the social sciences often emerges through approximation—through triangulation across methods, perspectives, and disciplines.

Even strong findings can vary across contexts. A causal mechanism that holds in one setting may operate differently elsewhere. What looks like a robust effect in one dataset may fade in another. This doesn’t invalidate our work—it simply reminds us that most knowledge claims are conditional.

Rigor Still Matters

If anything, this view has deepened my respect for rigor. In complex systems, rigor is not about perfection. It’s about careful design, clarity in logic, and transparency in assumptions. It’s about acknowledging limits while still striving for insight.

The challenge is balancing structure with openness, precision with flexibility.

So Where Does That Leave Me?

Honestly? I still wrestle with doubt. There are moments I wonder whether I’m overcomplicating things—or not pushing hard enough for generalizable results. But I’ve come to believe that uncertainty isn’t a weakness in science.

It’s part of what makes this work so important.