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The Innovators Studio with Phil McKinney

The Innovators Studio with Phil McKinney

By: Phil McKinney
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Summary

 Forty years of billion-dollar innovation decisions. The real stories, the hard calls, and the patterns that repeat across every organization that's ever tried to build something new. Phil McKinney shares what those decisions actually look like. Phil was HP's CTO when Fast Company named it one of the most innovative companies in the world three years running. He co-founded a company and took it public. Now he runs CableLabs, the R&D engine behind the global broadband industry. This isn't theory. It's what happened. And what you can see coming if you know what to look for. Running since 2005, originally as The Killer Innovations Show, now The Innovators Studio. Tens of millions of downloads. Full archive at killerinnovations.com. New episodes at philmckinney.com.Copyright 2005-2026 Techtrend Group LLC. See philmckinney.com Economics Leadership Management & Leadership Personal Development Personal Success
Episodes
  • How to Overcome Confirmation Bias

    How to Overcome Confirmation Bias
    May 6 2026
    Confirmation bias is shaping your decisions right now. Not occasionally. Every day. And the unsettling part is that the smarter you are, the harder it is to see it happening. By the end of this episode you'll know exactly what confirmation bias is. How to recognize when it has taken over a room. And three specific practices that actually work. Not borrowed frameworks, but what forty years of high-stakes decisions has taught me. Let's get into it. What Is Confirmation Bias? Confirmation bias is your brain's tendency to seek out, favor, and remember information that confirms what you already believe, filtering out everything that contradicts it. Most people think that just means seeking out information that agrees with them. That's part of it. But here's what makes it truly dangerous. Once you form a strong belief, three things happen automatically. Unequal Evaluation. Picture two studies landing on your desk. One says your strategy is working. One says it isn't. You read the first and nod. You read the second and start looking for the flaw: the methodology, the sample size, the funding source. Selective Memory. Your brain doesn't store evidence equally. What supports your belief stays accessible. What contradicts it becomes harder to recall the longer you hold the belief. The Backfire Effect. When someone directly challenges a belief you hold, your brain treats it as a threat. The response isn't reconsideration. It's defense. Studies show you actually leave the argument more convinced than when you entered it. Together, the longer you hold a belief and the more it matters to you, the harder it becomes to change, no matter how much evidence says you should. Confirmation Bias in Today's World Confirmation bias has always been part of human thinking. What's changed is the environment around it. Algorithms feed you content that matches what you already believe. Social media shows you opinions from people who think like you. Search engines rank results based on what you've clicked before. Every system you interact with daily is built to confirm your existing views. Not by accident, but because confirmation keeps you engaged. The result compounds. The more confirming information you consume, the stronger your existing beliefs become. The stronger your beliefs become, the more your brain filters out opposing information. The more that information gets filtered, the harder it becomes to update your thinking, even when updating is exactly what the situation demands. This is mindjacking in action. The systematic replacement of your thinking by systems built to do it for you. And confirmation bias is one of its most powerful tools. It's visible everywhere. In public discourse where people can no longer agree on basic facts. In organizations that keep funding failing strategies long after the evidence says stop. In leaders who build teams designed to tell them what they want to hear. You might assume that smarter, more experienced people are less susceptible to this. The research says otherwise. The Smartest Person in the Room Gets It Wrong Here's what surprises most people. Confirmation bias doesn't get weaker as you get smarter. It gets stronger. Dan Kahan at Yale ran a study. He gave people a math problem where the correct answer contradicted their political beliefs. The smarter the person, the more likely they were to get the answer wrong, in the direction that protected their belief. More intelligence, applied more effectively, in service of the conclusion they'd already reached. A smart person who has formed a wrong belief is better at defending it. They find flaws in the opposing data faster. They construct more sophisticated arguments. They're more convincing to others and to themselves. I watched this play out in a board meeting. A CEO had championed a major strategy. Three separate analyses came back contradicting it. Each time, he found a different flaw in the methodology. By the end of the meeting he'd convinced the room the data was unreliable. The strategy continued. The outcome was exactly what the data predicted. He wasn't dishonest. He was skilled. His intelligence was working against him. And everyone in that room let it happen. If you're intelligent, experienced, and confident in your judgment, you are not immune to confirmation bias. You are more vulnerable to it. If you know someone who is always the smartest person in the room, send them this episode. They need it more than most. How to Overcome Confirmation Bias: What Actually Works Knowing about confirmation bias doesn't stop it. I know this from experience, not from research. I've been in rooms where everyone understood exactly what was happening and it happened anyway. What works is different from what you've probably been taught. Catch It in Yourself: The Flip Debate The moment I've most reliably caught confirmation bias operating in myself hasn't come from a checklist or a framework. It's come from a specific kind of conversation. I keep...
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    15 mins
  • Why Most Organizations Aren't Funding Innovation

    Why Most Organizations Aren't Funding Innovation
    Apr 29 2026
    Twelve official definitions for R&D. Zero agreement. The US government publishes at least a dozen distinct official definitions across agencies, accounting standards, tax authorities, and international bodies. Not one agrees with the others on where research ends and development begins. Trillions of dollars flow through R&D budgets every year. Boards approve them. Investors evaluate them. Governments subsidize them. Analysts benchmark them. And the term at the center of all of it has no settled definition. A company can gut its research investment without triggering a single alarm on its income statement. Researchers who gained rare access to confidential federal R&D data found exactly this: when companies face financial pressure, they cut research while leaving development essentially untouched, and the combined number barely moves. Every benchmark, every board conversation, every investment thesis built around the R&D line may be built on sand. Innovation, ideas made real, requires both. Research is how you find the idea. Development is how you make it real. Strip out the research and you're not innovating, you're iterating on what already exists. Strip out the development and you're just experimenting. The problem is that nobody in the room knows which one they're actually funding, because the definition that would tell them doesn't exist. Someone needs to draw the line. This episode is about why nobody has, and the definition I think should replace the chaos. By the end, I'm going to put that definition in front of you and ask you to push back on it. Not to agree. To tell me where it breaks. How We Got Here Four institutions took a run at defining R&D. Each one got it right for their own purposes. None of them got it right for yours. Frascati: Built for Governments In June 1963, OECD economists met at a villa in Frascati, Italy, south of Rome, and produced what became the international standard for measuring R&D across nations. Now in its seventh edition. The Frascati Manual divides R&D into three tiers: basic research (theoretical work with no application in view), applied research (original investigation toward a specific practical objective), and experimental development (using existing knowledge to produce new products or processes). To qualify, an activity must be novel, creative, uncertain in outcome, systematic, and transferable. Used by governments across roughly 75 countries. Solid for what it was designed to do: let nations compare R&D investment on consistent terms. What Frascati cannot tell you: whether a specific company's spending is creating competitive advantage. It counts the type of activity. It doesn't assess what the activity produces for the organization doing the spending. A company can satisfy every Frascati criterion investigating something every competitor already knows. The knowledge is new to them. That is enough. The accountants drew a different line, for a different reason, with a different consequence. FASB: Built for Accountants In October 1974, the Financial Accounting Standards Board issued Statement No. 2, Accounting for Research and Development Costs, now codified as Topic 730. Every public company filing under US GAAP operates under it. The rule: all R&D costs expensed as incurred. Research, development, basic, applied: one line on the income statement. Their definition: research is a planned search aimed at discovery of new knowledge. Development is the translation of research findings into a plan or design for a new product. The rationale is explicit in the original standard. Future benefits from R&D are, in FASB's language, "at best uncertain." Expense everything immediately. The standard solved the problem it was asked to solve, which was accounting treatment: when to recognize the cost, not whether the cost was strategically sound. The consequence: sustaining engineering, feature maintenance, and incremental product updates all land on the same line as genuine exploratory research. Nobody looking at the income statement from outside can see the difference. The number is technically accurate and analytically opaque. Abraham Briloff, the late accounting professor at Baruch College, put it plainly: "Accounting statements are like bikinis. What they show is interesting, but what they conceal is significant." He was talking about financial reporting broadly. He could have been writing specifically about the R&D line. Researchers at Duke and London Business School spent years tracking corporate scientific output and found that it declined steadily across industries even as headline R&D spending kept rising. The combined number was hiding a substitution. Nobody on the outside could see it. Outside the United States, a different standard governs, and it creates a comparison problem most analysts never account for. IFRS: Built for International Investors IAS 38 governs R&D under IFRS, and its treatment differs from FASB in one significant way. Research costs are ...
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    21 mins
  • R&D Spending Is the Most Misleading Number in Business

    R&D Spending Is the Most Misleading Number in Business
    Apr 15 2026
    Every public company's R&D number is a lie hiding in plain sight. Not because anyone falsified it. Because the number was never built to tell the truth. It was built to satisfy an accounting standard written in 1974. And for fifty years, boards, analysts, and CEOs have been making billion-dollar innovation decisions based on a number designed by accountants to solve a different problem entirely. Here's what makes this genuinely strange. The real number exists. The government has been collecting it from every major US company for decades. It would answer the question every innovation leader and investor actually needs answered. And it is locked away by federal law. Confidential. Never published. Never seen by the people who need it most. It's sitting in a federal database right now. And there's a way to estimate it for any public company, without asking anyone's permission. I know it exists because I spent years building it from the inside. Why the R&D Signal Was Blurry When I was running innovation at HP, we discovered this problem firsthand. We had a connection between R&D investment and gross margin that held up across decades of HP history. Better than anything Wall Street was using. But the signal was blurry. None of us could figure out why. The answer came from a question someone on the team asked almost as an aside. What if R&D isn't one thing? Research and Development Are Not the Same Thing Think about what actually lives inside a typical R&D budget. There's a team somewhere investigating whether a new approach could enable a capability that doesn't exist yet. No product defined. No spec written. Asking whether something is even possible. And there's a team building the next version of a product that ships in eighteen months. Spec locked. Timeline set. Engineering executing against a defined target. Both show up on the same line in the budget. Both get called R&D. Both count equally toward the number that gets reviewed every quarter. They are not the same thing. One is Research. The other is Development. Research is the work you do when you don't yet know what you're building. The output is understanding. New knowledge that might enable future products nobody has designed yet. You can't know exactly what you'll find. If you already knew, it wouldn't be research. Development is the work you do when you know exactly what you're building. The spec exists. The product is defined. The question isn't what to make. It's whether it can be made, on time, at cost, at quality. One creates the future. The other delivers the present. And for fifty years, every public company in America has been required to report them as one indistinguishable number. When we split the HP data along that line, Research on one side and Development on the other, the signal sharpened immediately. Research spend, measured against gross margin three to five years later, was a meaningfully stronger predictor than the combined number had ever been. The blur hadn't been in the gross margin data. It had been in the R&D number itself. Two fundamentally different things, averaged together, producing a number that looked precise and predicted almost nothing. But splitting R from D at the company level was only the beginning. The model was still lying to us. Just more quietly. Why Company-Level R&D Splits Still Mislead Even with the split, something was still soft. HP wasn't one business. It was dozens. Printers, PCs, servers, software, each running on different timelines, different technology cycles, different competitive dynamics. What if the R/D split meant something different depending on where it was applied? We pushed it to the product line level. Then further, to the platform level within product lines. Printers were the clearest example. HP's printer business wasn't one story. There were platforms built on established technology. Mature ink systems, proven print head chemistry, products that had been shipping for years. And there were platforms built on genuinely new core technology. New chemistry. New mechanisms. New approaches to fundamental problems that nobody had solved yet. Research investment by platform told a completely different story than Research investment by product category. The Research going into new technology platforms had a completely different relationship to future margin than Research going into mature platforms. Different time horizons. Different risk profiles. Different margin implications years down the road. Laptops told the same story. A traditional consumer laptop line and a high-performance portable workstation weren't the same investment. One was Development-heavy. Defined product, known market, engineering executing against spec. The other had genuine Research behind it. Unsolved thermal problems, new form factor constraints, and materials questions that hadn't been answered yet. When a single R&D assumption is applied across all of that, treating every dollar the same regardless of what it actually...
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    17 mins
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