The Innovators Studio with Phil McKinney

Every public company in the technology industry measures innovation spending the same way. R&D as a percentage of revenue.
Why? Because Wall Street tracks it. Boards benchmark it. CEOs get fired over it.
And it tells you almost nothing about whether the spending is working.
Bill Hewlett and Dave Packard knew that. From the very beginning, they measured something different. Something the rest of the industry has been ignoring for seventy years. And the proof was sitting in a paper that Chuck House pulled out and sent to me after a conversation at a Computer History Museum board meeting.
By the end of this episode, you'll know what that metric is, why it works, and why the one everyone else uses makes it nearly impossible to tell whether your innovation investment is building the future or just burning cash.
Here's how I found it.
The Question That Wouldn't Let Go
In the last episode, I talked about the argument with Mark Hurd. The question was over whether HP should cut R&D as a percentage of revenue to match Acer. I knew Mark was fundamentally wrong. But I couldn't prove it. The only metric on the table was R&D as a percentage of revenue. That was what Wall Street expected. It's what shareholders expected. It's what the board expected.
But I couldn't argue against it, because I didn't have the data.
I needed a better metric. So I decided to go back to the beginning. HP's complete financial records dating back to the 1940s. Division by division. R&D project by R&D project. The actual operating data. I got access to all of it. The HP archive team gave me direct access to Bill and Dave's original notebooks.
Now, data alone wasn't enough. It was mountains and mountains of data, and you're trying to extract the signal. What is the trigger in that data?
The conversation that cracked it open happened outside HP.
 
 
The Man with the Medal of Defiance
I was at a Computer History Museum board meeting, standing next to Chuck House, and I shared with him the struggle I was having.
A little context on Chuck. He spent twenty-nine years at HP. He was the Corporate Engineering Director and he helped launch dozens of products. He's also the recipient, from David Packard himself, of the Medal of Defiance.
The Medal of Defiance was given to him because David had told him at one point to kill a product line. Chuck went around that decision, put the product into the catalog, shipped it, and it turned into a phenomenal success. When David gave Chuck the medal, the citation was something along the lines of: "for going above and beyond the stupidity of management and doing what was right."
Chuck and Raymond Price co-authored a book called The HP Phenomenon, published by Stanford Press. It's the deep dive into the history of the innovation culture inside HP, all of the metrics used back in the Bill and Dave days that put in place the structure that allowed HP to be successful.
By the time I'm at HP, Chuck had long since moved on. He was running Media X at Stanford, the university's research program on innovation, media, and technology. But we both served on the Computer History Museum board.
At that board meeting, I shared the argument I'd had with Mark and the search for a better metric. I had a strong feeling there was something around gross margin. That R&D investment impacted gross margin. But a feeling isn't an argument. I needed data. I needed to correlate R&D spend to margin, and that's extraordinarily hard to do when you've got all these different product lines and divisions.
Chuck got this little smile on his face and said, "I need to send you something."
The Paper and the Whiteboard
What he sent me was a paper. A journal paper he and a few of his colleagues had written decades before. And it laid out the connection between research investment and margin performance. The correlation I suspected but couldn't prove was right there on the page.
I read it that night. The next morning I emailed Chuck, and I was just really excited. What they'd written decades ago matched what I was finding in the data.
That email exchange turned into an invitation. I asked Chuck to come to HP Labs. We met in a conference room in Building 3, the main building for HP Labs at the time. And I'll tell you, I look back on this and it makes me smile a little, because this conference room was just down the hall from Bill and Dave's offices. HP preserved those offices exactly as Bill and Dave left them. You can walk in there today, see their desks, see their offices, just as they were on their last day. There's something about being that close to where it all started that makes the history feel less like history and more like unfinished business.
Chuck walked up to the whiteboard and drew two things.
On the left side: R&D as a percentage of revenue. The metric every company reports. The metric Mark used to argue HP was overspending. Chuck's point was simple. That metric tells you how much you're spending. That's it. Nothing about whether your products are any good. Nothing about whether customers value what you built. It's an input metric pretending to be an output metric.
Two ways to improve the ratio: spend less on research, or sell more of what you've already got. Neither of those is innovation. You can manipulate R&D as a percentage of revenue by cutting your R&D spend, or you can cut prices to drive top-line revenue. But neither has any connection to measuring whether your innovation is actually working.
On the right side, he drew gross margin. The distance between the cost to make something and what the customer pays for it. Chuck said: that gap is a direct measure of differentiation. Solve a problem nobody else can solve, and customers will pay for that difference. Margin expands. Build a product that looks like everyone else's, and customers have no reason to pay more. They'll shop you. Margin compresses.
Then he drew the line connecting both sides. Research investment flows in. If the research produces differentiated products, gross margin expands. That expanded margin funds the next round of research. A virtuous cycle.
But only if you're watching margin. The moment you manage to the spending ratio instead, the cycle breaks. The boardroom conversation stops being about whether research is producing differentiation. It becomes about whether the spending number looks right compared to some peer.
That's what happened with Mark. HP's PC group margins were compressing toward commodity levels. The response, driven by that revenue-ratio metric, was to cut research spending to match the compression. Exactly backwards. Compressing margins are the alarm bell. Fix the research pipeline. Fix your innovation. Not just more innovation, but good innovation. Don't defund it.
Bill and Dave's First Product, and What It Actually Proved
Standing at that whiteboard, I could see it running through HP's entire history.
The HP 200A audio oscillator. 1939. HP's first commercial product. Competitors were selling oscillators for over $200. Bill and Dave were selling theirs for $89.40.
Now that's not because they undercut the market. What Bill figured out as part of his master's degree project at Stanford was that by using a light bulb inside the circuit as a self-regulating component, you could smooth the output in a way competitors couldn't match. Technically superior instrument. Radically cheaper to build. Walt Disney bought eight of them for Fantasia.
The founders tracked the gap. Cost versus what customers pay. Not total revenue. That gap is gross margin. And that gap funded everything that came after. A lower-priced product, a higher-quality product, and the margin it generated is what drove HP's ability to continue to reinvest.
David Packard codified it. He described what he called the six-to-one ratio. Products at HP were considered genuinely successful only when the profit from a product over time was six times the cost of developing it. If it was lower than that, it wasn't generating enough. And this is also how Bill and Dave decided which product lines to kill off. The ratio determined where research dollars were earning their return and where they weren't.
The products that crushed that ratio weren't the ones with the biggest R&D budgets or the most engineers. They were the ones earning the highest return on the research dollar, because customers paid a premium for what the research produced.
And here's what this enabled: self-financing. No debt. No banks. No Wall Street ninety-day pressure. That was back before HP was even public. It was the freedom to invest in research on a ten-year horizon, and that's only possible with healthy margins.
At HP's margins, spending landed at about eight to ten percent of revenue.
Why Eight to Ten Percent Is Not a Contradiction
Now you might hear "eight to ten percent of revenue" and think I'm contradicting myself. I just spent ten minutes telling you that R&D as a percentage of revenue is a useless metric.
Here's the difference.
Bill and Dave didn't start with the percentage and work backwards. They started with margin. They funded the research that kept margins healthy, and the spending that produced happened to land at eight to ten percent. The percentage was a byproduct, not a target. The moment you flip that and make the percentage the goal, you've lost the plot.
That's the distinction the entire industry missed.
Chuck drew all of this in about twenty minutes on a whiteboard. Decades of institutional knowledge, distilled into one diagram. And the thing that hit me hardest wasn't the analysis. It was the realization that HP had already figured this out. The knowledge was in a paper that had been sitting around for decades. The company had just forgotten.
What was old had become what was new. HP didn't need a breakthrough. It just needed to remember.
Confirming the Pattern: Art Fong and John Young
After the session with Chuck, I reached out to two other people who'd been there in the early days.
Art Fong. I've talked about Art many times on this show, and there's an interview with him in the archive. He was the sixth R&D engineer Bill Hewlett ever hired. At one point in the 1960s, twenty-seven percent of HP's total revenue came from Art Fong's innovations and projects.
And John Young. John was the first CEO after the founders stepped back, after Bill and Dave retired. He took HP from $1.3 billion in revenue to $16 billion.
I had the same discussion with both of them about R&D as a percentage of revenue, about margin. And they both confirmed it. They shared their own stories about margin priority, the six-to-one ratio, and their direct conversations with Bill and Dave. That series of conversations with Chuck, Art, and John, capturing all of that history, really drove me to refine the thinking on the R&D-to-margin connection.
So what did I do next? I back-cast against the entire HP history. Division by division. Is it predictive? Can you use a metric to actually predict? That's what turned an insight into something defensible in a boardroom.
But here's the thing. This isn't just an HP problem. Most companies never had the margin insight. They started with R&D as a percentage of revenue because that's what Wall Street asks for, and they've never questioned it.
Margin would have caught it. Margin starts telling you the truth years before the revenue line does. By the time you see revenue take a dip, the damage is done. That is the result of decisions made three, five, ten years prior. Margin compression is the early warning. Differentiation is fading. Research is not producing what it needs to produce.
Half the Answer, and a New Problem
Walking out of HP Labs that day, I thought I'd found the answer.
Track margin, not spending. Watch the output, not the input.
It took me another year to realize I'd only found half of it.
When I started tracing where HP's R&D dollars were actually going, division by division, I found a problem hiding inside two letters.
R and D.
We say it like it's one thing. It's how we report it in financial filings. It's how Wall Street looks at it. It's how the press views it. But it's not one thing. Research and development are two completely different activities, with completely different time horizons, different risk profiles, and different impacts on the business. The moment you combine them into a single line item, you can move money from one to the other, and nobody outside the building can tell.
That's what we're going to get into in the next episode. The split nobody sees.
 
 
Here's a question for you. If you've found a way to connect R&D spending to actual business outcomes in your company, how do you do it? What metric are you using with your leadership to make the difference? Drop it in the comments. I read every one of them, and the best answers end up shaping future episodes.
If this episode changed how you think about innovation investment, hit subscribe so you don't miss the next one. And share this with someone in your company who's fighting this fight right now. They'll thank you for it.
Two ways to keep going between episodes. Studio Notes comes out every Monday. That's where I take apart a real company's innovation decisions using public data. This week I dig into PayPal's innovation health. You want to check that out. Studio Sessions, what you're watching right now, drops every Wednesday. This is where the decisions happened. The real rooms, the real calls, what went right and what went wrong.
Show notes and the full analysis are at philmckinney.com.
The idea was never the hard part. It never is. The call is.

Twenty years. Nearly one thousand episodes on this show. And starting today, we're going to try something a little different this season.
Season 21 is about the decisions that actually determine whether innovation lives or dies inside any organization. The real calls. Not the fluff stuff we read in academic textbooks. I want to actually put you in the rooms where these decisions are happening. What went right. What went wrong.
My objective is to expose you to the patterns in innovation decisions so that you can recognize them. Recognize them in yourself, in the people you need to influence, long before you step into any landmines.
So let's get into it.
The Encounter on the Top Floor of Building 25
Making generational decisions on innovation investment can be a make-or-break moment. What I refer to as a CLM, a Career Limiting Move. In my case, it started with a chance conversation with Mark Hurd, HP's CEO.
Let me take you back to 2005. HP headquarters is on Page Mill Road in Palo Alto, referred to internally as Building 25. The top floor is where all of the executive offices are. That's where Mark's office was.
I was up there doing some meetings and got snagged by Mark. Now, Mark had a reputation. He was a big numbers guy. He believed in what he called extreme benchmarking. You tore into your competitors' numbers. You knew your own numbers in and out.1
Others had warned me about this. He had a famous quote that everybody shared: 
"Stare at the numbers long enough, and they will eventually confess."
Mark believed you could not lead a critical role at HP if you did not know your numbers cold, inside and out. Didn't matter whether it was sales, CTO, a function, or a division. It didn't matter. And Mark tested everyone on the leadership team. Not just the leadership team. He would randomly stop employees and ask them for their numbers based on what group they worked in. It was non-stop. It was constant. To where support staff was literally constantly preparing briefing books for managers, VPs, leaders, just in case they got nabbed by Mark.
In my case, I happened to be walking past his office. Mark waved me in. I sat down, and he immediately started drilling me on the CTO numbers.
The number he focused on was R&D as a percentage of revenue.
The Broken Benchmark: R&D as a Percentage of Revenue
Now, if you've been a regular listener of this show, you know my opinion of that metric. R&D as a percentage of revenue is a meaningless number.2 It is absolutely meaningless. But every public company CEO at an innovation-dependent company, all the tech companies, AI companies, even automotive, they live by this number. It's a number that Wall Street looks at. You have to report it as part of your quarterlies, and from there it's simple math.3
When Mark grilled me, he was focused specifically on the PC group at HP. HP's number at the time for the PC group was about one and a half percent. R&D as a percentage of the PC group's revenue. Acer, which was a key competitor, was at 0.8%. Less than one percent. Roughly half of HP's number.4
Apple was at four percent.5
Mark's question, and he was really pounding on this, was: How do we get our ratios in line with Acer? Basically, he was saying: how do we cut costs so that our R&D expense as a percentage of revenue equals Acer at 0.8%?
This is exactly the problem with choosing the wrong metric.
Now I'm going to quote somebody who I think was probably one of the most insightful leaders in the business world. Charlie Munger. If you've ever watched any of his talks, he had a really strong opinion on certain metrics. Specifically EBITDA, earnings before interest, taxes, depreciation and amortization. Charlie referred to EBITDA as BS earnings. It was a metric Wall Street swore by, and Munger said it hid more than it revealed. His exact words: "Every time you see the word EBITDA, just substitute the word 'bullshit' earnings."6
R&D as a percentage of revenue is the same problem in a different disguise. It's the metric that makes every company look like it's investing when all it's doing is spending.
Mark was using a broken instrument to make a generational decision. If you make decisions based on R&D as a percentage of revenue, and then you do comparisons like "let's make our numbers look like Acer," what you are actually deciding to do is cut your R&D. That is generational. You will destroy a company's innovation capability over the next ten to twenty years before you can even have a hope of rebuilding it.7
"We Are Not Apple and We Never Will Be"
I looked at him and said: Why aren't we raising our R&D spend to match Apple?
Mark didn't hesitate. He said: "We are not Apple and we never will be."
I took offense at that. I was offended that he wouldn't even contemplate it. And I pushed back. I pushed back hard. I argued we could be Apple in areas where we had genuine advantage.
Here's one example. Go back to September 2004, about a year before my meeting with Mark. Carly Fiorina was still CEO. Carly had just handed Steve Jobs access to the retail shelf space HP spent thirty years building.8
At that time, HP controlled about nine, nine and a half percent of all retail shelf space for consumer electronics, the largest single entity holding in that category. Where did all that come from? It traces back to the calculator days in the 1970s. Those relationships, those stocking slots, that footprint: HP had spent three decades building that access.
Apple was launching the iPod.9 It had no retail distribution in consumer electronics. None. And rather than HP taking advantage of that for itself, it actually opened the door and allowed Apple to come in. That is how the iPod got its traction. It bought Apple the time to build out its own retail strategy, which is ultimately what allowed Apple to be where it is today.
That wasn't an accident of history. That was HP giving away a structural competitive asset.
When I tried to push back on Mark, saying we could be better with the right investment, it didn't land. Mark viewed the PC business as a commodity. And if it's a commodity, you manage expenses. You don't invest in capabilities.
Monthly Arguments and the Search for Better Metrics
There was no decision made that day. But something shifted in me.
That was the first of many monthly arguments I had with Mark. And they were non-stop.
What it drove me to do was start looking for better metrics. We had something most companies don't have: HP's complete financial history going all the way back to the 1940s. I had access to the numbers, division by division, for one of the founding companies of Silicon Valley.10
We were getting traction. I was actually getting Mark to align. I was getting the HP board to align. And then what happens? Mark gets removed as CEO and Leo comes in. Then Meg kicked Leo out and she took over. Then the split of HP into two companies.
Acer today? Still roughly 0.9% of revenue in R&D.11 Twenty years later, almost exactly where Mark wanted HP to get to.
What I Would Do Differently: Right Argument, Wrong Language
If I'm being honest about what I would do differently, I had the right argument. I had the wrong language.
The job wasn't to prove Mark wrong. Nobody changes their mind when they're being told they're wrong. I needed to stop speaking CTO and start speaking CEO. Meet him where he was. Make the case in the language of margin, risk, competitive position, the language he already trusted.
But that language didn't exist when it came to R&D and innovation. That's the reason I spent the rest of my career building something better.
And that is what this season is about.
What Comes Next: The Metrics That Tell the Truth
That conversation with Mark sent me looking. If R&D as a percentage of revenue was the wrong metric, and I believe to my core that it was, and is, then what's the right one?
We went back through HP's own numbers. We back-cast all the way to the 1940s, looking at the numbers by division, by the overall organization. And then something unexpected happened.
The archive team at HP gave me access to something nobody had looked at in decades: Bill Hewlett and Dave Packard's original notebooks.
What I found in there pointed me somewhere nobody had thought to look.
In the next episode, we're going to talk about the metrics that actually tell the truth when it comes to R&D and innovation.
 
 
If this episode gave you some insights, shifted something, share it with somebody who you think needs to hear it. Particularly if you're trying to fight senior leaders around R&D investment. And in the comments below, tell me: what's that one benchmark that you are required to hit, and yet you've never questioned? Is it the right benchmark? Have you really looked at it? I genuinely would like to know.
Show notes and this week's Studio Notes are over at philmckinney.com. Subscribe there. That's where the deeper analysis lives. Every Monday that we post, subscribe. You don't want to miss the next one.
I'll see you in the next episode.

The best decision-makers aren't better at deciding. They're better at controlling when, where, and how they decide. It took me twenty years to figure that out. Most people spend that time trying harder: more discipline, more willpower, more resolve to think clearly under pressure. It doesn't work. That's when mindjacking wins. Not through force. Through […]

The best decision-makers aren't better at deciding. They're better at controlling when, where, and how they decide. It took me twenty years to figure that out.
Most people spend that time trying harder: more discipline, more willpower, more resolve to think clearly under pressure. It doesn't work. That's when mindjacking wins. Not through force. Through the door you left unguarded.
The answer isn't trying harder. It's building systems that protect your thinking before the pressure hits. By the end of this episode, you'll have four concrete strategies for doing exactly that, and a one-page system you'll build before we're done. And I have something else to share at the end. Something I've been working toward for twenty years.
Let's get into it.
Why Willpower Fails and Design Works
Ulysses knew his ship would pass the island of the Sirens. He also knew the song was irresistible. Sailors who heard it became incapacitated and drove straight into the rocks.
He didn't try to be stronger than it. He had his crew fill their ears with wax and tie him to the mast, with strict orders not to release him, no matter what he said when the music reached him.
His calm self setting rules for his compromised self. That's the core of everything in this episode.
These are called commitment devices. The decision gets made early, when your thinking is clear, before you're tempted to take the wrong path. Studies tracking self-imposed contracts found that when people added meaningful stakes to their commitments, their follow-through nearly doubled. Not because they became more virtuous, but because they'd taken the choice off the table at the moment they were most likely to get it wrong.
Stop asking "How do I resist?" Start asking, "What can I decide now, so I don't have to decide under pressure?"
Before you can build the right commitments, you need to know exactly where your thinking breaks down. Not decision-making in general. Yours.
Finding Your Personal Vulnerability
Think back across the last few months. Where did your thinking most clearly cost you?
Some people stall. They keep researching past the point of useful information, using "I need more data" as cover for avoiding a commitment they know they need to make.
Others make their worst calls at the end of long days. Saying yes when they mean no, because no requires energy they've already spent.
Some get caught by urgency. A deadline appears, the pressure closes off their thinking, and they move fast. Only later do they discover the deadline was manufactured to do exactly that.
Others walk into a room with a clear position and walk out agreeing with the loudest voice, unable to explain exactly when they shifted.
And some defend decisions past the point where the evidence says stop, because stopping would mean admitting something about themselves they're not ready to face.
Identify yours. Write it down before we go further. Your primary vulnerability is a design target, not a character flaw. You can't build around something you haven't named.
Four Strategies for Protecting Your Judgment
Strategy 1: Control When You Decide
Every morning I put on the same thing: a black golf shirt, blue jeans, and cowboy boots. Same brands, same routine, no decisions. My wife tolerates it. I've stopped apologizing for it.
It's not a fashion choice. It's a cognitive load choice. Your brain has a finite amount of decision-making capacity each day. Every trivial choice draws from the same reserve you need for the decisions that actually matter. What to wear, what to eat, which route to take. Eliminating those choices doesn't just save time. It protects the mental fuel you'll need later.
Decision-making capacity isn't flat across the day. It peaks early, when you're rested and fresh. It degrades, measurably, as conditions erode. The same call made at 8 a.m. and at the end of your seventh consecutive meeting aren't equivalent. Same person, different machine.
Pull up your calendar from the last two weeks. Look at when your biggest decisions actually happened. For most people, it's not in a calm moment with a clear head. It's in the hallway, on a rushed call, in the last fifteen minutes of a meeting that ran over. That's not bad luck. That's the default you haven't changed yet.
Write a standing rule: no significant, hard-to-reverse commitments after a certain hour or after a certain number of back-to-back meetings without a mandatory pause. Hold it like a policy, not a preference. Because preferences are exactly what disappear under the conditions where you need them most.
Strategy 2: Build Your Kitchen Cabinet
One of the things I credit most for whatever success I've had in my career isn't a framework or a methodology. It's four people.
I call them my kitchen cabinet. They've seen my best decisions and my worst ones. They know when I'm rationalizing. They know when I'm avoiding. And they are not afraid to call me out when I'm off the tracks.
Here's what surprises people when I describe them. They're not senior executives. They're not peers from inside my industry. They don't work in any organization I've ever worked for. They're a deliberate mix: different backgrounds, different areas of expertise, different ways of seeing the world. One of them has been in my cabinet for nearly thirty years. I trust them completely, and everything we discuss stays between us.
That independence is the whole point. The people inside your organization have something at stake in your decisions. Your peers have their own agendas, even when they don't mean to. Your boss has a preferred outcome. None of that makes them bad advisors. It just means they can't give you the one thing you need most when a decision gets hard: a perspective with no skin in the game.
Your kitchen cabinet can. Because they have nothing to gain or lose from what you decide, they can ask the question everyone else in the room is avoiding. They can tell you what you don't want to hear. And they'll do it before you've committed, when it still matters, not after the fact, when all they can do is watch.
Build yours deliberately. Four to six people is enough. Prioritize independence over seniority. Look for people who will push back, not people who will reassure. And make the relationship reciprocal. You show up for their decisions too. The cabinet only works if the trust runs both ways and the conversations stay private.
You don't need them for every decision. You need them for the ones where you're most at risk of fooling yourself.
Strategy 3: Write Your Position Before the Room Fills Up
I've sat in enough rooms where I walked in with a clear position and walked out having said almost none of it. Not because I was wrong. Because by the time the senior voice spoke and the heads started nodding, my own analysis felt less certain than it did twenty minutes earlier. The brain doesn't just nudge your answer when social pressure arrives. It rewrites your perception. What you saw before entering the room changes to match what the room already believes, before you've consciously registered the pressure.
Before any consequential group decision, write down where you stand. Three sentences. What you believe. What evidence supports it. What would genuinely change your mind. A note on your phone is enough. It doesn't need to be formal. It needs to be external, because your memory will quietly revise itself once the social pressure arrives. Those three sentences are a record of what you actually concluded before the room had a chance to work on you.
When the discussion moves toward a position, you can then distinguish between "I'm updating because I heard something new" and "I'm caving because the silence is uncomfortable." Without that record, those two experiences feel identical in the moment, and one of them will reliably win.
Strategy 4: Assume the Failure Before You Commit
In August 2016, Delta Air Lines ran a routine scheduled test of the backup generator at their Atlanta data center. A transformer caught fire. Three hundred of Delta's 7,000 servers, improperly connected to a single power source, went dark. They couldn't fail over to backups. The servers that stayed online couldn't communicate with the ones that hadn't. The entire system collapsed: passenger check-in, baggage, websites, kiosks, and airport displays. Gone.
Delta cancelled 2,100 flights over three days. $150 million in losses. Thousands of passengers slept on airport floors.
The system had redundancy designed in. The backup had been tested. The specific failure mode, servers with no alternate power connection, was a known vulnerability that nobody had ever stopped to question.
A year before the fire, cognitive psychologist Gary Klein, the researcher who developed the pre-mortem, had written a thought experiment describing almost this exact scenario. Imagine, he wrote, that an airline CEO gathered top management and asked: "Every one of our flights around the world has been cancelled for two straight days. Why?" People would think terrorism first. The real progress, Klein said, would come from mundane answers: a reservation system down, a backup that didn't activate, a cascade nobody had traced in advance.
Delta built what Klein described. Without running the question that would have found it.
The pre-mortem is that question. Before you commit to a significant decision, assume it's six months later, and the decision failed. Not possibly, but definitely. Then ask: What went wrong? What did you know but not say? What did someone sense but find too awkward to raise in the room?
"What could go wrong?" produces hedged answers. People soften concerns to preserve harmony. "It failed. What happened?" changes the psychology entirely. You're not being negative. You're being forensic. The things that surface, the concerns that felt impolitic, the risks that seemed too small to mention, are frequently the ones that end up mattering most.
Each of these four strategies is a designed defense against the same thing: the systematic capture of your judgment before you notice it happening. That's mindjacking. And now you have four ways to make it harder.
But strategies only work if you remember to use them. And you won't remember. Not when you're depleted at 7pm, not when the room is staring at you, not when your identity is on the line. That's not a character flaw. That's just how it works.
So we're going to take everything you just learned and put it on one page. A page you'll sign. A page you'll keep somewhere you'll actually see it. Your calm self, right now, is building the system your future self will thank you for.
The people who shape outcomes consistently aren't necessarily the sharpest thinkers in the room. They're the ones whose judgment is still intact when everyone else's has degraded. That's a practice, not a talent.
The full video and written deep-dive on mindjacking are linked below at philmckinney.com/mindjacking.
Your Decision Constitution
Remember the Ulysses insight from the beginning of this episode. Your calm self setting rules for your compromised self. That's exactly what this is.
A Decision Constitution is one page. Five commitments. Written when your thinking is clear, so the version of you under pressure has something to stand on. Not a to-do list. Not a productivity hack. A contract with yourself.
Here's what goes in it.
Your Timing Rule. You already know that your judgment degrades as the day runs long. So name it. What are the specific conditions (time of day, number of back-to-back meetings, hours of sleep) that disqualify you from making a high-stakes, hard-to-reverse call without a mandatory pause first? Write that line. Hold it like a policy.
Your Pre-Decision List. Think of the situations where you consistently make choices you later regret. The late-day request you said yes to when you meant no. The urgency that overrode your better judgment. Pick three. Write a standing rule for each, specific enough that you can invoke it without having to think. "I don't make new commitments without sleeping on it." That's a rule. "I'll try to be more careful" is not.
Your Pre-Meeting Anchor. Before any meeting where a significant decision will be made, you write down where you stand. Three sentences. What you believe, what evidence supports it, and what would genuinely change your mind. Not in the car on the way. Before. That record is what protects your thinking from the room.
Your Pre-Mortem Trigger. Name the threshold that makes a decision significant enough to require a pre-mortem. A dollar amount. An impact on more than a certain number of people. A commitment lasting longer than six months. Whatever your threshold is, write it down. Once a decision crosses it, the pre-mortem is non-negotiable.
Your Kitchen Cabinet Trigger. Your cabinet is only useful if you engage them before you've decided, not after. So name the conditions that require you to bring a decision to them first. A decision that's hard to reverse. A situation where you have significant personal stakes in the outcome. A moment where you notice everyone around you wants you to decide a certain way. A decision you find yourself avoiding thinking about clearly. Any one of those is enough. Two or more is non-negotiable.
Now print out your decision constitution. Sign it. Put it somewhere you'll actually see it before the moments that count. This is your Ulysses contract. Your clear-headed self, right now, is setting the terms your compromised self will have to honor when the pressure is real, and the easy path is pointing the wrong way.
Closing
That's Part 2 of the Thinking 101 series. Fifteen episodes. If you've been here from the beginning, you've built something real.
The series has been running for 21 weeks. The show behind it has been running for 20 years. And how we got here traces back to a single conversation.
Twenty years ago, a mentor of mine, Bob Davis, gave me a challenge I couldn't shake. I'd asked him how I could ever repay him for what he'd done for my career. He laughed and said I couldn't. The only option, he said, was to pay it forward.
That's why this show exists. That's why it has always existed.
The show was called Killer Innovations because that's what felt right in 2005. Bold, a little provocative, built for a moment when podcasting was brand new, and nobody knew what it was supposed to be. Tens of millions of downloads later, we're still here. We have regular listeners in more than 50 countries. Some of you are younger than the podcast itself.
But somewhere along the way, the show became something more specific. It stopped being about innovation tips and started being about the innovation decisions that actually shape outcomes. About the patterns underneath the decisions. About the skills that matter most when the pressure is real.
On March 23rd, the show's 20th anniversary, we're making major changes. The podcast. The YouTube channel. All of it.
And if you have thoughts about where we've been or where we're going, I want to hear them. There's a contact form at philmckinney.com. Send me a note.
I'll see you on the 23rd.
 
Endnotes 
"their follow-through nearly doubled": Gharad Bryan, Dean S. Karlan, and Scott Nelson, "Commitment Contracts," Yale Economics Department Working Paper No. 73 / Yale University Economic Growth Center Discussion Paper No. 980 (October 23, 2009). https://ssrn.com/abstract=1493378. The research draws on Karlan and co-founders' development of StickK.com, a commitment contract platform launched in 2008 at Yale. Platform data consistently shows that users who add meaningful stakes — financial or reputational — to their commitments achieve their goals at roughly double the rate of those who don't. The underlying mechanism was established in Karlan's earlier field research in the Philippines: Nava Ashraf, Dean Karlan, and Wesley Yin, "Tying Odysseus to the Mast: Evidence From a Commitment Savings Product in the Philippines," Quarterly Journal of Economics 121, no. 2 (May 2006): 635–672. doi:10.1162/qjec.2006.121.2.635. https://academic.oup.com/qje/article-abstract/121/2/635/1884028. Pre-commitment works not by increasing virtue but by removing the decision from the moment of temptation. For accessible application, see Ian Ayres, Carrots and Sticks: Unlock the Power of Incentives to Get Things Done (New York: Bantam, 2010), ISBN 978-0-553-80763-9. https://www.penguinrandomhouse.com/books/6794/carrots-and-sticks-by-ian-ayres/.  

"a finite amount of decision-making capacity each day": Roy F. Baumeister, Ellen Bratslavsky, Mark Muraven, and Dianne M. Tice, "Ego Depletion: Is the Active Self a Limited Resource?" Journal of Personality and Social Psychology 74, no. 5 (1998): 1252–1265. doi:10.1037/0022-3514.74.5.1252. https://roybaumeister.com/1998/03/16/ego-depletion-is-the-active-self-a-limited-resource/. Also see Roy F. Baumeister and John Tierney, Willpower: Rediscovering the Greatest Human Strength (New York: Penguin, 2011). Baumeister's strength model of self-control proposes that willpower, decision-making, and self-regulation all draw from a single, depletable resource — what he termed "ego depletion." Subsequent work has debated the precise mechanism, with some researchers arguing the effect is motivational rather than metabolic. The practical implication, however, is consistent across studies: decision quality degrades as the day progresses, and the effect is most pronounced for complex, high-stakes choices. For a summary of the current scientific debate on the mechanism, see Michael Inzlicht and Brandon J. Schmeichel, "What Is Ego Depletion? Toward a Mechanistic Revision of the Resource Model of Self-Control," Perspectives on Psychological Science 7, no. 5 (2012): 450–463. doi:10.1177/1745691612454134. https://pubmed.ncbi.nlm.nih.gov/26168503/.  

"It rewrites your perception": Gregory S. Berns, Jonathan Chappelow, Caroline F. Zink, Giuseppe Pagnoni, Megan E. Martin-Skurski, and Jim Richards, "Neurobiological Correlates of Social Conformity and Independence During Mental Rotation," Biological Psychiatry 58, no. 3 (August 1, 2005): 245–253. doi:10.1016/j.biopsych.2005.04.012. https://pubmed.ncbi.nlm.nih.gov/15978553/.  This fMRI study at Emory University extended Solomon Asch's classic conformity experiments by imaging participants' brains as they conformed to or resisted incorrect group answers. The key finding: when participants went along with the group, the activity appeared not in the prefrontal cortex — the seat of conscious decision-making — but in the occipital-parietal network responsible for visual and spatial perception. In other words, participants who conformed weren't consciously deciding to lie; the group had altered what they actually perceived. Standing alone, by contrast, activated the amygdala, a region associated with emotional distress — consistent with the experience of social dissent as genuinely uncomfortable rather than merely inconvenient.  

"Three hundred of Delta's 7,000 servers": Yevgeniy Sverdlik, "Delta: Data Center Outage Cost Us $150M," Data Center Knowledge, September 8, 2016. https://www.datacenterknowledge.com/outages/delta-data-center-outage-cost-us-150m.  Also see W. H. Highleyman, "Delta Air Lines Cancels 2,100 Flights Due to Power Outage," Availability Digest (September 2016). https://availabilitydigest.com/public_articles/1109/delta.pdf. On the morning of August 8, 2016, a fire triggered during a routine backup generator test at Delta's Atlanta data center caused a transformer failure. Approximately 300 of Delta's 7,000 servers were improperly connected to a single power source with no alternate feed, and when that feed failed, those servers went dark. Because those servers couldn't communicate with the rest of the system, the entire network collapsed. Delta cancelled roughly 2,100 flights over three days, leaving an estimated 250,000 passengers stranded. Total losses reached $150 million.  

"cognitive psychologist Gary Klein, the researcher who developed the pre-mortem": Gary Klein, "Performing a Project Premortem," Harvard Business Review 85, no. 9 (September 2007): 18–19. https://hbr.org/2007/09/performing-a-project-premortem.  Klein developed the pre-mortem method over several decades of applied research in naturalistic decision-making. The technique asks teams to assume, before committing to a plan, that the plan has already failed — definitively, not possibly — and then work backward to identify causes. Klein's research found that this reframing dramatically increases the willingness of team members to surface concerns they would otherwise suppress to preserve group harmony. The method has since been endorsed by Nobel laureates Daniel Kahneman and Richard Thaler as a practical tool for reducing overconfidence in planning. For Klein's broader framework of naturalistic decision-making, see Gary Klein, Sources of Power: How People Make Decisions (Cambridge: MIT Press, 1998). https://mitpress.mit.edu/9780262343251/sources-of-power/.

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