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How to Improve Your Inversion Thinking Skills

Most innovation tools teach you how to win. Inversion thinking teaches you how to lose on purpose, so you catch the failure while you can still change course.

Phil McKinney
Phil McKinney
6 min read
Image of inversion thinking - showing Phil McKinney inverted.

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.

... or listen to The Innovators Studio Podcast.

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.

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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.

  1. 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."
  2. Turn it into a failure question. Same goal, opposite direction. "How would we guarantee we lose the telepresence market?"
  3. 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.
  4. 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.

  1. Take your most serious irreversible failure mode. The one from Move One that would actually end the project.
  2. 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.
  3. Ask whether you tested that assumption or inherited it. Did you confirm it with evidence, or did it ride along with the idea because it felt obviously true? The Halo team inherited theirs. Quality felt like an objective good, so nobody checked whether the market agreed.
  4. If you can't point to the evidence, you've found your real risk. A plan resting on an untested load-bearing assumption is a bet wearing the costume of a strategy, however solid the rest of it looks.

Move Three: Decide What to Do With It

Once the assumption is exposed, you have three honest choices.

  1. Kill it. If the assumption is false and the failure is irreversible, stop now, while stopping is still cheap.
  2. Change the plan so the failure mode disappears. The Halo team had room to do this. A software tier on any network, at lower quality, to build the user base and the network effect, with the premium rooms kept for the customers who'd pay for them. They'd have owned both ends. The plan allowed it. The conviction didn't.
  3. Proceed, with the bet named out loud. Sometimes you take the risk on purpose, eyes open, because the upside justifies it. That's legitimate. Taking the same risk by accident, because nobody said the word "assumption" in the room, is not.

The one move you cannot make is to see the failure mode and proceed as though you hadn't. That isn't confidence. It's the most expensive form of hope there is.

Why You Can't Do This Alone

You know the three moves now. The hard part is running them on your own work.

You can't fully see your own assumptions. You built the plan. You believe in it. The assumption holding it up feels so obvious that questioning it never occurs to you. The Halo team wasn't careless. They were the best in the world at what they did, and that was the problem. The more expert you are, the more your assumptions feel like facts, and the less it occurs to you to test them.

Then there's the room. Even when someone can see the failure coming, the dynamics of a team work against saying it out loud. You earn standing by backing the plan, not by listing the ways it dies. Raise the failure scenario and you look like you lack conviction, or like you're not on board. So the failure half the room quietly senses stays unspoken until it's expensive. Culture rewards the loudest voice on the upside, not the person who turns out to be right about the risk.

Two walls. You can't see your own assumptions, and the people who might see them are discouraged from speaking.

AI has none of those problems. No ego in the plan, no career to protect, no boss to impress, no reason to soften the bad news to keep the room comfortable. Point it at your work, tell it to find the failure, and it will, without flinching and without politics. It won't make the call for you. It surfaces the failure modes you're too close to see, and then you do the judging.

That's how you practice this skill on your own. You sit down with a real decision and a partner that has no reason to spare your feelings. So I built the AI Prompts for Inversion Thinking for exactly that. One prompt makes the AI write the post-mortem of your project before you've even started. Another has it play a competitor designing your defeat. Then one walks you to the single assumption your whole plan is betting on. You bring the decision and the judgment. The prompts make sure nothing gets skipped just because it's uncomfortable to look at.

Here's your work this week. Take one real decision you're sitting on, something with actual stakes, and run it through the pack. It's free at innovation.tools, or use the link in the description.

The Long Game

The people who use inversion well aren't more negative than their peers. They're more honest about which risks they can walk back and which ones they can't. That single distinction, made early and acted on, is the difference between a project that fails fast and cheap and one that fails slowly, expensively, in year ten.

The failure that ends your project is usually the one plenty of people saw coming and nobody was willing to name.

Say it now, while it still costs you nothing.

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Phil McKinney is an innovator, podcaster, author, and speaker. He is the retired CTO of HP. Phil's book, Beyond The Obvious, shares his expertise and lessons learned on innovation and creativity.

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