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The Innovators Studio with Phil McKinney

The Innovators Studio with Phil McKinney

By: Phil McKinney
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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 Improve Weak Signal Judgment

    How to Improve Weak Signal Judgment
    Jun 24 2026
    Everyone collects weak signals now. Most of what they collect predicts nothing. A weak signal isn't a thing you spot, it's a prediction you make, and the edge goes to whoever bets on it while being wrong is still cheap. So how do you become the one placing the bet, not the one still collecting reports? Let's get into it. What a Weak Signal Actually Is A weak signal is a faint piece of evidence that points to something a customer will want before they can name it, and before the market has priced it in. Faint, because if it were loud, everyone would already be acting on it. Deniable, because you can always explain it away as noise, and most people do. That deniability is the whole point. The moment it becomes undeniable, the advantage is gone and the price has moved. Why Noticing Stopped Being the Edge Ten years ago, noticing was hard. You needed sources, a network, time to read widely, a feel for the edges of your industry. That was the moat. It isn't anymore. Every team has a trend report and three newsletters and an AI tool surfacing emerging behaviors on a schedule. The noticing got automated. What didn't get automated is the judgment about which signal predicts a structural change and which points to nothing real, and the nerve to act early. Inside Roche's Innovation Board I sat on Roche's diagnostics innovation board, the only outsider in the room, helping decide which ideas got funded. At one point we took on diabetes care. I am not diabetic. So I had Roche ship me every meter and test strip they made, and I pricked my finger up to a dozen times a day to feel what their customers felt. You cannot innovate for a customer whose day you have never lived. Skip that, and everything after is a guess. Roche was a leader in blood glucose testing with its Accu-Chek meters, and the math looked obvious. Someone with type 1 diabetes tests around eight times a day, every day, for life. A big, stable business. Type 2 was the smaller story per patient. Those patients tested once, maybe twice a day, so each one looked worth less, and we filed the category under "less interesting." We could already see type 2 climbing. We weighed it against the per-patient math and explained it away. Then type 2 diagnoses exploded into one of the fastest-growing chronic conditions in the world. And the category stopped being about counting tests per day at all, because monitoring went continuous, the always-on sensors people wear today. We had seen the early edge of both shifts. We even predicted them. We just didn't move fast enough, and the reason is the one that kills most weak signals inside a big company. Project approval and annual budgets are built to fund what's already proven, not to chase something still faint. Roche got there. Accu-Chek SmartGuide, its real-time continuous monitor, is on the market now. I just wish we had moved the moment we saw it, instead of waiting for the next budget cycle to make it safe. How to Read a Weak Signal We didn't miss the type 2 signal for lack of noticing. We noticed. We missed it on the three things that come after, and those you can train. The moves start once you've got a signal you can't quite dismiss, and the skill is what you do with it. Tell the Canary From the Costume A canary in a coal mine matters because the air changed. It signals something structural, a shift in the environment that affects everyone in it, whether they've noticed yet or not. A costume is the opposite. A few people put it on, it's striking, it spreads for a season, then they take it off and the room is exactly as it was. On day one the two look identical. A behavior appears, it's unusual, it's spreading. The only question that matters is whether it predicts a change a customer can't reverse, or a moment that will pass. Back in 2018 I wrote about telling a trend from a fad, and the test still holds: ask what need the behavior reveals. Type 2 was a canary, and we read it as a costume, because we counted testing frequency instead of the need underneath it. That need, millions of people learning to manage a lifestyle disease, only grew. The discipline is refusing to let the size of the spike tell you which one you're looking at. Costumes spike too, sometimes higher. You're reading for the need, not the noise. Read the Window A signal's window is short. Too early, you can't tell it from noise and you waste resources chasing ghosts. Too late, it's obvious, everyone sees it, and the advantage is already priced in. The value lives in the narrow gap between. Waiting for more evidence feels like better judgment, but the evidence that finally convinces you has already reached your competitors. Certainty and advantage move in opposite directions, so by the time you're sure, sure is just another word for too late. The question isn't whether the signal is real yet. It's how much longer you can be the only one taking it seriously. Act While Being Wrong Is Cheap This is the move that separates the people who read signals ...
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    13 mins
  • How to Improve Your Second-Order Thinking Skills

    How to Improve Your Second-Order Thinking Skills
    Jun 10 2026
    In 2000, Toys R Us paid Amazon $50 million a year to sell their toys online. It looked like a great deal. The company that defined toy retail for two generations was solving the internet problem in one move. Four years later they were suing each other. Seventeen years later Toys R Us was gone. Every store closed. Every job lost. And every step of what happened was visible from the day the deal was signed. Nobody at Toys R Us saw it. What Is Second-Order Thinking? First-order thinking asks what happens next. Second-order thinking asks what happens to the people who see what happened next. The skill isn't caution. It's the willingness to keep looking after the room has stopped. Inside HP, 2006 In 2005, HP launched Halo, a premium telepresence system co-developed with DreamWorks. For a brief period it reported into my organization. The next year, Cisco launched TelePresence and went straight at us. I called the HP team closest to Cisco and asked what they made of it. The answer was reassuring: Cisco is aiming down-market, we're fine. We were premium; they were chasing volume. That answer satisfied the room. It did not satisfy me. The room was asking "will Cisco hurt Halo?" That was the wrong question. The right one was sitting underneath: why did our partner of twenty years decide to do this without us? Nobody had an answer to that one. The HP team didn't think it was the question. They were focused on the product collision, and I kept coming back to the partnership. A company that had cooperated with us for two decades had just decided they didn't need to anymore. The product was the surface. The relationship had quietly ended, and we were the only ones who hadn't noticed. Three years later, Cisco launched a direct attack on HP's core server business with Unified Computing System. HP responded by acquiring 3Com and going after Cisco's core networking business. A twenty-year alliance ended in under two years. Neither side ran the second-order analysis at any point along the way. By the time the right question got asked, the partnership was already gone. The Three Skills These three skills stand on their own. Each one solves a different problem most decision frameworks miss. The first picks up signals before there's even a decision to analyze. The second uncovers what's actually driving the other party's timing. The third shows you what people will do once they see your decision land. If you've watched the November 2025 episode on the basics of second-order thinking, these skills add to that foundation. If you haven't, you can still apply all three starting today. Sense the Weak Signal, Not the Loud Event Most failures don't announce themselves. The loud event, the launch, the lawsuit, the lost customer, is usually the visible end of something that started much earlier as a quiet shift somebody noticed and explained away. A weak signal is a small piece of information that doesn't fit the story you're already telling. A customer's casual comment that contradicts your data. A team member's evasive answer in a status meeting. A supplier missing a deadline they've never missed before. The reflex is to make it fit the story you already believe. The skill is to refuse. Go looking before you have one. Once a week, scan three places where weak signals live. Customer-facing teams. Data points that surprised you and got brushed off. Topics that smart people you respect are paying attention to, but you aren't. You're not looking for problems. You're looking for things that don't quite fit. Name the thing that doesn't fit. Be specific. "Their CFO made a comment about the budget that didn't match what we were told last quarter." Not "something feels off." The more specific the signal, the more useful it becomes. List the stories that would make the signal make sense. At least three. Force yourself to consider explanations that don't fit your current assumptions. Ask which of those stories you'd act on if it were true. If one of them would change a decision you're about to make, that's the signal you can't afford to ignore. Find one more data point before you decide. A single signal can mislead. Two signals pointing the same direction is usually real. The Cisco TelePresence launch was a weak signal about the partnership. The team read the product. I read the relationship. Neither of us pushed it far enough. Ask "Why Now" Before "What's Next" Most people jump straight to the future: what will the other party do next? That's the wrong starting question. Ask why now first. Why is this happening now, when it could have happened a year ago? The timing tells you what changed in their world, and that change tells you what they're likely to do next, often more reliably than asking the question directly. State the move that just happened. A competitor launched a product. A regulator opened an inquiry. A customer asked for a discount. Name it plainly. Ask what changed. What was true a year ago that isn't true now? What...
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    15 mins
  • How to Improve Your Inversion Thinking Skills

    How to Improve Your Inversion Thinking Skills
    Jun 3 2026
    Every playbook, every case study, every innovation workshop is built on the same question: how do you succeed? You map the path forward. You model the upside. Nobody teaches you to ask the harder question. How would you guarantee this fails? That's inversion thinking. Charlie Munger called it one of the most useful tools he had, and he used it for sixty years. Most innovators know the quote. Almost none of them actually use it. By the end of this episode, you'll know why that gap exists, what it costs, and the exact steps to close it. If you want to try this on a real decision right away, I've built a free tool for it. Link below. I'll come back to it later in the episode. What Is Inversion Thinking? Inversion thinking is the practice of reasoning backward from failure. Instead of starting with "what does success look like and how do I get there," you start with "what would guarantee this fails" and design those conditions out of the plan. You'll also hear it called thinking backwards, and when it's aimed at a project before launch, a pre-mortem. Munger's rule was three words: invert, always invert. Or, in his blunter version, "All I want to know is where I'm going to die, so I'll never go there." People hear this and think pessimism. It isn't. A pessimist names the failure and stops there. Inversion names the failure and uses it to redirect the plan, while the fix is still cheap. HP Invented the Category. Then Gave It Away. In 2005, HP built Halo. It was the best telepresence system in the world. You walked into a Halo room and the people on the other end looked like they were sitting across the table from you. Life-sized. Perfect audio. Nobody had built anything close. The team that made it was brilliant, and they believed one thing without question: quality wins. They built rooms that cost $500,000 each. They required customers to run those rooms on HP's proprietary network at a monthly cost that would make your eyes water. Every decision traced back to the same conviction. Make the experience extraordinary, and the market will come to you. Nobody in that room asked the one question that mattered. What if quality isn't what the market is buying? Because it wasn't. The market was buying access. Cisco, and then Zoom, came at the same opportunity from the opposite end. Good-enough quality, on any device, on any network, available to everyone. They understood what the Halo team never tested. In communications, reach beats quality. Every new user makes the service more valuable to everyone already on it, so the product that spreads to the most people wins, even when it looks worse. That network effect beat Halo so completely that Zoom became a verb. HP defined the category and then gave it away. In 2011, under quarterly pressure, HP sold Halo to Polycom for $89 million. In 2022, HP bought the business back, folded into Poly, for $3.3 billion. Thirty-seven times the price, to reacquire a category it had invented. The failure was visible the entire time. It lived inside one assumption nobody questioned: that quality was what the customer cared about most. An inversion exercise would have dragged it into the open. Ask "how do we guarantee Halo fails," and one honest answer was already the plan. Bet everything on quality. Price it for the few. Lock it to our own network. Leave the rest of the market wide open for a cheaper rival. No crystal ball required. Read the plan from the other side and the failure was sitting right there in it. The Three Moves Inversion runs in three moves. The first two are mechanical. The third is where the discipline lives, and where most people quit. Move One: Invert the Question Take the goal and flip it. Write your goal as one sentence. The way you'd say it to the board. "We will win the telepresence market with the best experience available." Turn it into a failure question. Same goal, opposite direction. "How would we guarantee we lose the telepresence market?" List every path to that failure. Don't rank them. Don't defend anything. Write down every way it could happen, including the ones that feel unlikely or embarrassing to say out loud. Price. Distribution. A competitor's move. A wrong read on the customer. Sort each one: recoverable, or not. A slow first year is recoverable. Letting a competitor own the network effect while you keep only the high end is not. The ones you can't undo are what matter here. Set the rest aside. Move Two: Find the Load-Bearing Assumption Behind every failure you can't recover from sits a single assumption holding the whole plan up. Find it. Take your most serious irreversible failure mode. The one from Move One that would actually end the project. Ask what would have to be true for that failure to never happen. For Halo: "Enough customers will pay a large premium for superior quality, and they'll do it fast enough to matter." That sentence is the load-bearing assumption. Ask whether you tested that assumption or inherited it. Did you ...
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    16 mins
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