Small Bets, Big Wins

Introduction: Why Traditional Innovation Is Failing

Greg: Hey everyone, and welcome to Next Moves with AI, a special series of the Make Next Happen podcast, where we explore how AI—and innovative thinking—can help you build a truly Intelligent Innovation System. I’m Greg Galle, co-founder of Solve Next.

Daniel: And I’m Daniel Buritica, Solve Next’s Chief Operating Officer. Today, we’re talking about a crucial shift in how organizations innovate—one that could make the difference between staying ahead or falling behind.

Greg: And that shift begins with a simple truth: traditional innovation is failing.

Daniel: Right. Too many teams go big on untested ideas—wasting time, capital, and credibility when those ideas bomb. Others move so cautiously they never learn anything meaningful.

Greg: And the biggest issue? Most innovators are flying blind. They don’t have a system that tells them:

Greg: Which assumptions matter most,

Greg: What’s the smallest, smartest test we can run,

Greg: or how to turn learning into action.

Daniel: That’s why we developed the Intelligent Innovation System—to transform innovation from a high-stakes guessing game into a structured, capital-building process.

Greg: And at the heart of that system are small bets. Done right, they let you test critical assumptions, minimize risk, and maximize learning.

Daniel Buritica: But how you design, execute, and measure those small bets—especially at scale—is where the Small Bets Builder—AI Assistant comes in.

The Intelligent Innovation Framework: People, Process, Platform

Greg Galle: Before we dive into the AI Assistant, let’s zoom out for a second. What does real innovation management look like?

Daniel: It’s not just about ideas. You need a system—what we call the Intelligent Innovation Architecture.

Greg: That system is built on three key layers: People, Process, and Platform.

Daniel: Greg, from your perspective, what’s the number one thing great innovation teams nail?

Greg: They never treat innovation as a side project. They bring the right mix of talent, leadership, experience, and skills—people who embrace uncertainty and harness AI as an amplifier rather than a replacement.

Daniel: Exactly. Technology alone won’t solve the innovation dilemma—you need the right people who see why it matters.

Greg: And who know how to get it done. So, let’s talk process. How teams practice innovation is as vital as who’s on them.

Daniel: Yeah. The extremes of “go big or go home” or “analyze forever and never act” don’t work. The Intelligent Innovation System strikes that balance: structured yet nimble, letting teams test quickly, learn continuously, scale what works—and redirect or stop what doesn’t

Greg: That’s where our Small Bets Builder—AI Assistant really shines.

Daniel Buritica: Right. It’s not just a tool, but an expert guide that helps teams design and run small bets with precision.

The Small Bets Builder—AI Assistant: A Smarter Way to Innovate

Greg: So, Danny, give us the elevator pitch. What does the Small Bets Builder—AI Assistant actually do?

Daniel: Think of it as your co-pilot for experimentation—it helps you: Identify and prioritize Super Vital Assumptions (SVAs), Design and run small, low-risk experiments, Validate hypotheses with real-world data, And track progress and align teams around learning.

Greg: It also integrates Think Wrong Drills—structured drills that break inertia, reframe challenges, and spark creative solutions.

Daniel: That’s right. Rather than a vague “let’s test something,” you get a step-by-step method for designing high-impact small bets.

Greg: And the AI Assistant not only helps set up your experiments—it provides you with a way to analyze results in real time, giving you instant insights on what to change, amplify, or stop.

Case Study: Boeing vs. Spotify—A Tale of Two Innovation Strategies

Daniel: Alright, let’s ground this in real-world examples. This isn’t just theory—it’s the difference between winning and crashing, literally.

Greg: Yeah. Let’s start with Boeing’s 737 MAX tragedy. Boeing, once the gold standard of aviation engineering, made a high-risk bet on under-tested technology—and it cost them billions.

Greg Galle: Instead of building a new aircraft to compete with Airbus, Boeing rushed modifications to an older design. They introduced MCAS, an automated flight control system, but skipped small-scale testing that could have caught fatal flaws. And here’s the key mistake—they assumed MCAS would work seamlessly. Instead of testing with real pilots, they relied on internal simulations.

Greg Galle: The result? Two catastrophic crashes, 346 lives lost, and a $20 billion financial and reputational disaster.

Greg: Had they taken a small bets approach, they would have: Run limited prototype tests to assess MCAS behavior under real-world conditions. Collected pilot feedback before full-scale deployment. And used an incremental rollout strategy instead of betting everything on a rushed launch.

Greg Galle: Boeing’s failure wasn’t about bad engineering—it was bad innovation management.

Daniel Buritica: Now, let’s contrast that with Spotify, which built its success one small bet at a time.

Daniel Buritica: Instead of launching globally overnight, Spotify started small—testing in Sweden first before expanding.

Daniel Buritica: They experimented with different pricing models to see what worked—freemium, invitation-only, and limited free streaming—before scaling the most effective one.

Daniel Buritica: And when they expanded beyond music into podcasts, they didn’t just throw billions at content deals—they tested small acquisitions first, analyzed user engagement, and only then made bigger investments.

Daniel Buritica: That’s why they’re the world’s leading streaming service today—because they scaled only what worked.

Practical Takeaways: How to Apply Small Bets

Greg Galle: So, how do small bets really fit into the broader framework of an Intelligent Innovation System?

Daniel Buritica: Remember the five components of that system: Next Development, Next Decision Making, Next Portfolio Management, Next Operating Principles and Governance, and Next Funding. Every one of them benefits from structured, purposeful experimentation.

Greg Galle: Right, because small bets oil the gears of your innovation engine—lowering risk, speeding up learning, and letting you adapt before you overcommit resources.

Daniel Buritica: And that’s what we call the LFI Mindset—Learning From Investment. It’s not about “fail fast” or “move slow”—it’s about deliberate, data-driven steps that yield clarity and confidence.

Closing CTA: What to Do Next

Daniel: Alright, let’s wrap. Small bets might be “small,” but they deliver big wins. They help you de-risk, learn more quickly, and scale only the best stuff.

Greg Galle: And that’s why the Small Bets Builder—AI Assistant is such a powerhouse: it gives you a real-time, step-by-step approach to experiment smarter, not harder.

Daniel Buritica: So here’s your next move:

Daniel Buritica: First, check out the Small Bets Builder—we’ve dropped the link in the show notes. Then, try the two-week free trial of Next Lab Pro—gain access to all the AI assistants and see how they can shape your entire Intelligent Innovation System.

Greg Galle: If you’re ready to take the next step in building an Intelligent Innovation System, let’s talk. You can find us at hello at solvenext.com or connect with us on LinkedIn.

Daniel Buritica: Until then, happy innovating. Remember: start small, stay disciplined, and build that capital—human, intellectual, political, social, reputational—AND financial.

Greg Galle: Thanks for tuning in to Next Moves with AI. We’ll catch you on the next episode—where we’ll keep exploring how to make innovation truly intelligent.

Daniel Buritica: Don’t forget to subscribe so you don’t miss our upcoming AI tools.