R&D Spending Is the Most Misleading Number in Business

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 does, the signal disappears into the average. Peanut butter across the portfolio. The model only got honest when it got specific. Research by platform and Development by platform, matched against the margin performance of those specific platforms years later. Which platforms were building future margin? Which ones were running on margin that past Research had already bought? We could see it because we were inside the company. The question is whether anyone on the outside could ever see the same thing. The R&D Data the Government Collects and Won't Release Outside the internal budget process, everyone sees the same thing: a single line on the income statement. The US government recognized decades ago that the combined R&D number was analytically useless. So they built a system to collect the real one. The National Science Foundation runs a survey called the Business Enterprise Research and Development survey. The BERD survey. Every year, roughly 47,500 US companies are required to report their R&D spending broken into three categories: basic research, applied research, and experimental development. The split that every board and every investor needs to see. Mandatory. Collected. Verified. And then locked away. The firm-level data is confidential under federal law. The NSF publishes only industry-level aggregates. So every company fills out this survey and reports its real R/D split to the government. That data sits in a federal database. And the boards, investors, and analysts who need it most cannot access it. Researchers at Northwestern and Boston University were given rare access to that confidential data. What they found is striking. When companies face financial pressure and cut R&D, they don't cut Development. They cut Research. Almost entirely. Development barely moves. Every earnings squeeze. Every activist campaign. Every cost optimization program. Systematically targeting the one part of R&D that builds future margin. And because the combined number barely moves, nobody on the outside sees it happening. That's not a coincidence. That's the accounting standard doing exactly what it was designed to do: produce one clean number for the income statement. It was never asked to protect the future. How to Estimate the Research-to-Development Split Without Inside Access So what can actually be done without access to the locked data? More than most people realize. Step 1. Find the industry baseline. The aggregate BERD data is public at the sector level. Ask an AI tool for the Research-to-Development ratio for the relevant industry. That's the benchmark. Everything else gets measured against it. A company spending 8% of its R&D on Research in an industry where the average is 25% is telling you something the combined number never would. Step 2. Look at the gross margin trend compared to peers. Gross margin over time is the most honest external signal of Research health. A company with a declining margin relative to peers, while reporting flat or growing R&D spend, is almost certainly shifting the mix toward Development. The math works in the other direction, too. An AI tool can pull this comparison for any public company in minutes. This is exactly the signal that was invisible at HP until it was too late. Step 3. Look at patent trends compared to peers over time. Patents are an imperfect but useful directional indicator. Not because more patents always means more Research. It doesn't. But a sustained decline in patent output relative to peers, alongside flat R&D spend, suggests the investment is maintaining existing products rather than creating new knowledge. Combined with the gross margin trend, it starts to triangulate where the split actually sits. None of these three steps requires access to an internal budget. All of them can be done in an afternoon with public data and an AI tool. Together, they produce a working picture of the R/D split that the income statement was never designed to reveal. What the R&D Split Revealed at HP That No One Outside Could See When Hurd took over in 2005, HP was spending $3.5 billion on R&D. Roughly 4% of revenue. By 2009, his last full year as CEO, that had dropped to $2.8 billion. Revenue had grown significantly over that period, so the percentage had fallen further still, to under 2.5%. Both the dollar amount and the ratio were declining simultaneously while the company got larger. Wall Street tracked the combined number. The board reviewed it. Nobody raised a structural alarm. The Research component within that total was well below the industry average for comparable technology companies. Not slightly. Significantly. The margin consequences arrived years later. They always do. What Happens When the Definition of Research Doesn't Exist The R/D split gave us a real predictive signal. We ran with it. The conversations were sharper. But the team kept pulling on a thread that nobody expected. When we looked closely at what was actually being called Research, project by project and budget line by budget line, things that didn't feel the same kept appearing. Work aimed at fundamental discovery. Work aimed at solving a specific defined problem using entirely new methods. Both labeled Research. Up close, they behaved differently, predicted different things, and when budgets got tight, got treated very differently. So we went looking for the agreed definition. The official standard that would tell exactly where to draw the lines inside Research. It didn't exist. Not the way we needed it to. And without it, everything we'd built was sitting on sand. How do you build a predictive model on a definition that doesn't exist? That's the next episode. If this helped you see something you might have missed, subscribe wherever you listen to podcasts. On YouTube, hit subscribe and the bell so you don't miss the next episode. And if you want to go deeper every Monday, join us at Studio Notes — free, at philmckinney.com. Until next time. See the pattern. Make the call.  

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/. 

Ron Johnson was one of the most successful retail executives in America. He'd made Target hip. He'd built the Apple Store from nothing into a retail phenomenon. So when J.C. Penney hired him as CEO in 2011, expectations were sky-high. Johnson moved fast. He killed the coupons. Eliminated the sales events. Redesigned the stores. When […]

Ron Johnson was one of the most successful retail executives in America. He'd made Target hip. He'd built the Apple Store from nothing into a retail phenomenon. So when J.C. Penney hired him as CEO in 2011, expectations were sky-high. Johnson moved fast. He killed the coupons. Eliminated the sales events. Redesigned the stores. When his team suggested testing the new pricing strategy in a few locations first, Johnson said five words that explain everything that happened next: "We didn't test at Apple." Within seventeen months, sales dropped twenty-five percent. He was fired. And here's the part nobody talks about: Johnson had access to all the data. Every week, the numbers told the same story. Customers were leaving. Revenue was collapsing. The board was getting nervous. He could see it all. He just couldn't act on it. Because changing course would mean he wasn't the visionary who reinvented retail. He wasn't making a business decision anymore. He was protecting who he believed he was. That's the identity trap. And it doesn't just happen to CEOs.  What if changing your mind didn't have to feel like losing yourself? Let's get into it. Why Identity Bias Looks Like Your Best Qualities The trap doesn't target bad thinkers. It targets good ones. Think about the entrepreneur who poured three years and her life savings into a startup. The data says it's failing. The metrics are clear. Her advisors are suggesting it's time to pivot or shut down. She has every analytical tool to evaluate this accurately. And she can't do it. She's plenty smart. The problem is that admitting failure would mean she's "a quitter." And she is not a quitter. That's not who she is. Johnson wasn't stupid either. He was brilliant. His identity as the retail visionary just happened to make him blind to the one thing that could save his company: the possibility that what worked at Apple wouldn't work at Penney's. He experienced his blindness as conviction. As leadership. And that's the disguise. Every other thinking error in this series, uncertainty, depletion, time pressure, social pressure, you can feel those happening. You know when you're tired. You know when you're rushed. But identity fusion is invisible from the inside. It disguises itself as your best qualities. The entrepreneur calls it perseverance. Johnson called it vision. The investor who won't sell a losing position? He calls it discipline. Your ego doesn't announce that it's taking over. It puts on a costume that looks exactly like your strengths. And your brain? Your brain is in on it. Why Changing Your Mind Feels Like a Threat When a belief becomes part of your identity, your brain defends it as it would defend your body. Challenge that belief, and your brain responds the same way it would to a physical threat. Not metaphorically. The same neural circuits that protect you from danger activate to protect you from being wrong. That's why arguments about strategy or direction can generate so much heat and so little light. You're not debating a position anymore. You're defending territory. And sometimes you defend it long past the point where the evidence says stop. A project you've poured months into. A strategy you championed. A hire you fought for. The data says cut your losses, but you keep going because walking away would mean all that time, all that effort, all that money was wasted. That's the sunk cost fallacy. And most people think it's about the money or the time. But it's not. Sunk cost is about identity. Think about that manager who spent eighteen months building a new system. The team knows it's not working. She knows it's not working. But scrapping it doesn't just waste eighteen months of budget. It means her judgment failed. It means she led her team down the wrong road for a year and a half. "I've invested too much to quit" sounds like a financial calculation. It's not. It's an identity statement. What she's really saying is: "If I quit, I'm the kind of person who wastes eighteen months of people's lives." The sunk cost isn't financial. It's existential. And suddenly you can see that every time you've held on too long, stayed in something past its expiration date, defended something you knew wasn't working, the force holding you there wasn't logic. It was your self-image refusing to absorb the hit. So how do you loosen the grip once you realize it's there? Three Warning Signs Your Ego Has Taken the Wheel Here's what to watch for. 1. Emotional Intensity That Doesn't Match the Stakes Someone suggests a different approach to a process you built. Not a criticism. Just an alternative. And you feel a flash of heat in your chest. Defensiveness. Maybe irritation. The reaction is way out of proportion to the suggestion. Pay attention to that gap. The intensity isn't about the process. It's about what being wrong would say about you. 2. How You Argue When someone pushes back on your position, watch what happens. If you find yourself attacking the person instead of engaging their argument, that's identity talking. "You don't understand our industry." "You haven't been doing this as long as I have." The moment you shift from "here's why the evidence supports my position" to "here's why you're not qualified to question it," you've stopped defending a conclusion and started defending yourself. The tell is subtle: you'll feel righteous, not curious. 3. The Evidence Filter When you're evaluating something objectively, new information can move you in either direction. But when identity is involved, watch what happens. You accept supporting evidence quickly, uncritically, almost with relief. Contradicting evidence? You tear it apart. You find flaws in the methodology. You question the source. You say, "That's just one study." When you're applying completely different standards depending on which direction the evidence points, that's not critical thinking. That's identity protection wearing a lab coat. How To Loosen the Grip So what do you do once you recognize the grip? Early in my career, I championed a technology direction that I was convinced was right. The evidence started coming back that it wasn't working. And I was doing exactly what I just described. Scrutinizing the bad data, embracing the good data, and getting irritated when people questioned me. It wasn't until a colleague looked at me and said, "You're not evaluating this anymore. You're defending it," that I realized my identity had completely hijacked my judgment. What helped was a shift in language that sounds simple but changes everything. Stop holding beliefs as part of your identity. Start holding them as a working thesis. The Reframe Listen to the difference between these two statements. First: "I believe this company will succeed." Second: "My working thesis is that this company will succeed." The first version fuses the belief to you. If the company fails, you were wrong. You made a bad bet. The second version builds in the expectation that your thinking will evolve. New data doesn't make you wrong. It makes you better informed. The Proof That colleague I mentioned? After that conversation, I started framing every strong opinion as a working thesis in my own head. Not out loud at first. Just internally. And the effect was immediate. I stopped feeling attacked when contradicting data came in. I started treating it as an update instead of a threat. The position I was defending? I reversed it completely. And the thing I was most afraid of — looking like I'd wasted everyone's time — never happened. The team was relieved. The Practice Next time you find yourself defending a position with more heat than it deserves, pause and restate it starting with "My working thesis is..." Then ask yourself: "What would I need to see to change this?" If you can't answer that question, if there's literally no evidence that could change your mind, that belief has become part of your identity. And your brain will protect it like one. The Door The goal isn't to be wishy-washy. Commit fully to your working thesis. Act on it with confidence. The difference is that you've built a door in the wall, and you've given yourself permission to walk through it if the evidence changes. That door is the difference between updating when you're wrong and doubling down until it costs you. Why Identity Is the Amplifier The identity trap doesn't operate alone. It recruits every other force we've covered in Part Two of this series. Facing uncertainty? Identity says, "You're not the kind of person who hesitates." Someone manufactures a deadline to pressure you? "Leaders are decisive. Act now." The whole room disagrees with your position? Identity whispers "I'm a team player" — or digs in with "I'm the one who sees what others miss." Identity is the amplifier. It takes every vulnerability from Episodes 10 through 13 and cranks up the volume. That's why we saved it for last. Everything else we've covered in Part Two? Necessary. But not sufficient. Because if you haven't dealt with your identity's grip on your beliefs, those skills have a backdoor that ego walks right through. And this is exactly what mindjacking exploits. I go much deeper into an article I wrote and in my dedicated mindjacking episode, links below. But the core mechanism is this: mindjacking doesn't just offer you convenient conclusions. It attaches those conclusions to who you are. "People like us think this." "Smart people choose this." Once a belief becomes a badge of identity, you'll convince yourself. No external persuasion required. From Seeing the Trap to Building the Escape Here's your challenge this week. Pick one belief you hold that you've never seriously questioned. Something professional. Your management philosophy. Your investment thesis. Your view on how your industry works. Something you'd describe as "just who I am." Now find the strongest argument against it. Not a straw man. The real, best case the other side would make. Sit with it. See if you can engage with it without your threat response kicking in. If you can? You've just proven that your thinking is bigger than your identity. And that is the most important skill in this entire series. If this episode shifted something for you, share it with someone who needs to hear it. And in the comments, tell me: what's a belief you held that you later realized was more about identity than evidence? I think we can all learn from each other on this one. Episode 15 is about designing your decision environment. Not tips. Systems. Structures that protect your thinking, so willpower becomes optional. Now you can see the trap. Next, we build the escape route. Make sure you subscribe so you don't miss it, and I'll see you in the next one.   Endnotes — Episode 14 How To Quit Defending Decisions You Know Are Wrong "He'd made Target hip. He'd built the Apple Store from nothing into a retail phenomenon": Brad Tuttle, "The 5 Big Mistakes That Led to Ron Johnson's Ouster at JC Penney," TIME, April 9, 2013, https://business.time.com/2013/04/09/the-5-big-mistakes-that-led-to-ron-johnsons-ouster-at-jc-penney/. Johnson is credited with creating Target's "cheap chic" brand positioning in the early 2000s and subsequently designing and launching Apple's retail stores, which became the highest-grossing retail outlets per square foot in America. "We didn't test at Apple": Tuttle, "The 5 Big Mistakes" (cited in note 1). When Johnson's team proposed testing the new pricing strategy on a limited basis before rolling it out chain-wide, Johnson reportedly shot down the idea with this statement. The quote has been widely attributed in retail industry reporting. See also James Surowiecki, "Why Ron Johnson Is Struggling at J.C. Penney," The New Yorker (The Financial Page), March 25, 2013. The article is archived under The New Yorker's legacy URL format; for a summary of Surowiecki's argument, see Derek Thompson's coverage in The Atlantic and Quartz: https://qz.com/58487/jc-penneys-ceo-wasnt-the-one-who-killed-it. "Within seventeen months, sales dropped twenty-five percent. He was fired.": Multiple sources confirm these figures. Sales fell $4.3 billion in 2012 — a 25 percent decline — and same-store sales dropped 31.7 percent in Q4 2012, which analysts called "the worst quarter in all retail history." Johnson was terminated on April 8, 2013, seventeen months after taking over. See Tuttle, "The 5 Big Mistakes" (cited in note 1); Sean Williams, "This May Be the Worst Quarter in Retail History," The Motley Fool, February 28, 2013, https://www.fool.com/investing/general/2013/02/28/this-may-be-the-worst-quarter-in-retail-history.aspx; and the Ron Johnson entry at Wikiwand, which aggregates and cites the primary financial reporting, https://www.wikiwand.com/en/articles/Ron_Johnson_(businessman). "When a belief becomes part of your identity, your brain defends it as it would defend your body": Jonas T. Kaplan, Sarah I. Gimbel, and Sam Harris, "Neural Correlates of Maintaining One's Political Beliefs in the Face of Counterevidence," Scientific Reports 6, 39589 (December 23, 2016), https://www.nature.com/articles/srep39589. doi:10.1038/srep39589. Using fMRI on 40 participants with strong political beliefs, the researchers found that challenges to identity-linked beliefs activated the amygdala and insular cortex — brain structures involved in threat detection and emotional processing — while also engaging the Default Mode Network, associated with self-referential thinking. Participants who resisted changing their minds showed the strongest activity in these areas. Lead author Kaplan noted: "The amygdala in particular is known to be especially involved in perceiving threat and anxiety." A 2026 replication by an independent European team confirmed these findings. See Kossowska, M., Szwed, P., Czarnek, G. et al., "Neural Correlates of Belief Change in Political and Non-Political Domains Among Left-Wing Individuals Confronted with Counterarguments," Scientific Reports 16, 4895 (January 8, 2026), https://www.nature.com/articles/s41598-026-35397-6. doi:10.1038/s41598-026-35397-6. "That's the sunk cost fallacy": Hal R. Arkes and Catherine Blumer, "The Psychology of Sunk Cost," Organizational Behavior and Human Decision Processes 35, no. 1 (February 1985): 124–140. doi:10.1016/0749-5978(85)90049-4. Available via ScienceDirect: https://doi.org/10.1016/0749-5978(85)90049-4. Arkes and Blumer defined the sunk cost effect as "a greater tendency to continue an endeavor once an investment in money, effort, or time has been made" and demonstrated across multiple experiments that the effect is driven by the desire not to appear wasteful — a fundamentally identity-protective motive rather than a financial calculation. "Sunk cost is about identity": The connection between sunk cost escalation and self-concept draws on Barry M. Staw, "Knee-Deep in the Big Muddy: A Study of Escalating Commitment to a Chosen Course of Action," Organizational Behavior and Human Performance 16, no. 1 (1976): 27–44. doi:10.1016/0030-5073(76)90005-2. Available via ScienceDirect: https://doi.org/10.1016/0030-5073(76)90005-2. Staw's central finding was that individuals committed the greatest resources to failing investments when they were personally responsible for the initial decision — an "intra-individual process in which people tend to act in ways to protect their own self-image." This reframes sunk cost escalation as identity protection rather than mere financial irrationality. See also Hal R. Arkes and Catherine Blumer, "The Psychology of Sunk Cost" (cited in note 5), whose findings complement Staw's by emphasizing the role of waste-avoidance norms tied to self-presentation. "To consider an alternative view, you would have to consider an alternative version of yourself": Jonas T. Kaplan, quoted in Emily Gersema, "Hardwired: The Brain's Circuitry for Political Belief," USC Press Room, December 23, 2016, https://pressroom.usc.edu/hardwired-the-brains-circuitry-for-political-belief/. This quote from the lead author of the fMRI study (cited in note 4) captures the identity-belief fusion mechanism described throughout this episode. Kaplan added: "Political beliefs are like religious beliefs in the respect that both are part of who you are and important for the social circle to which you belong."  

When neuroscientists scanned the brains of people going along with a group, they expected to find lying. What they found instead was something far stranger. The group wasn't changing people's answers. It was changing what they actually saw. We'll get to that study in a minute. But first, I want you to remember the last […]

When neuroscientists scanned the brains of people going along with a group, they expected to find lying. What they found instead was something far stranger. The group wasn't changing people's answers. It was changing what they actually saw. We'll get to that study in a minute. But first, I want you to remember the last time you were in a meeting, and you knew something was wrong. The numbers didn't add up. The risk was being underestimated. And someone needed to say it. Then the most senior person in the room spoke first: "I think this is exactly what we need." Heads nodded. Finance agreed. Marketing agreed. The consultant agreed. And by the time it was your turn, you heard yourself saying, "I have some minor concerns, but overall I think it's solid." You're not alone. Research shows that roughly half of employees stay silent at work rather than voice a concern. And among those who stayed quiet, 40% estimated they wasted 2 weeks or more replaying what they didn't say. Two weeks. Mentally rehearsing the point they should have made in a meeting that's already over. That silence isn't a character flaw. It's your neurology working against you. And today I'm going to show you exactly why it happens and how to stop it.  It starts with what was happening inside your head during that meeting you just remembered. Why Your Brain Surrenders to the Group Most people know about the Asch conformity experiments from the 1950s. People were asked to match line lengths, and seventy-five percent went along with answers that were obviously wrong. That result gets cited everywhere. But the more important study came fifty years later, and it revealed something the Asch experiment never could. In 2005, neuroscientist Gregory Berns at Emory University put people inside an MRI machine and ran a similar conformity task, this time with three-dimensional shape rotation. Like Asch, he planted actors who gave wrong answers. But unlike Asch, he could watch what was happening inside people's brains while the conformity was occurring. Berns expected the MRI to show activity in the prefrontal cortex, the brain's decision-making center, when people went along with wrong answers. That would mean they were knowingly lying to fit in. Just a social calculation. That's not what the scans showed. People who conformed showed no increased activity in decision-making regions. Instead, the activity showed up in the parts of the brain that handle visual and spatial perception, the occipital and parietal areas. The group wasn't changing people's answers. It was changing what they actually saw. Their brains were rewriting their experience to match the room. And the people who resisted the group? Their scans told a different story. Heightened activity in the amygdala, the brain's threat detection center. The same circuitry that fires when you encounter physical danger lit up when someone disagreed with the group. Berns put it plainly. The fear of social isolation activates the same neural machinery as the fear of genuine threats to survival. When you caved in that meeting, your neurology wasn't malfunctioning. It was doing exactly what it was designed to do. Keep you safe inside the tribe. This is why what I call mindjacking works so well. Algorithms manufacture social proof by showing you what's trending, what your friends liked, and what similar people chose. Your wiring responds the same way it does at the conference table. You're fighting your own threat-detection system every time you try to hold an independent position within a group. You can't turn off the wiring. But you can learn to catch it in the act. And that starts with one critical distinction. The First Skill: Separating Updating from Caving Sometimes the people around you know something you don't. Changing your mind in a group isn't always a surrender. Sometimes it's the smartest move in the room. The real skill is knowing which one just happened. You can test this in real time. When you feel your position shifting in a group, ask yourself three questions. First: Did someone introduce information I didn't have before? If the CFO reveals a data point that genuinely changes the calculus, updating your view isn't a weakness. It's intelligence. That's new evidence. Second: Can I articulate why I changed my mind, in specific terms? If you can say, "I shifted because of the margin data in Q3 that I hadn't seen," that's a real update. If you can only say, "I don't know, everyone seemed to think it was fine," that's capitulation. Third: Would I have reached this same conclusion alone, with the same information? This is the killer question. If the answer is no, and you only arrived at this position because others were already there, you haven't updated. You've surrendered. Getting this wrong is costly. And not just the one time. When you capitulate and call it updating, you train yourself to stop trusting your own analysis. Do it enough times, and you won't even bother preparing, because you already know you're going to defer. That's how capable people slowly become passengers in rooms where they should be driving. Capture those three questions somewhere you'll see them. They're your real-time check on whether you're being open-minded or spineless. Those questions work when you're already in the meeting and the pressure is live. But what if you could protect your thinking before the pressure even starts? The Pre-Meeting Lock-In The most important thing you can do to protect your independent thinking doesn't happen during the meeting. It happens before. I call it the Pre-Meeting Lock-In, and it takes less than two minutes. Before any meeting where a decision will be made, write down three things:  Your position  Two or three key reasons supporting it What would it take to change your mind Put it on paper. Put it in a note on your phone. Just get it out of your head and into a form you can reference. Why does this work? Because once the discussion starts, your mind is going to quietly edit your memories of what you believed. You'll start thinking, "Well, I wasn't really sure about that point anyway." Your pre-meeting notes are an anchor against that self-deception. They're a record of what you actually thought before the social pressure arrived. You want to see what happens when someone has the analysis but doesn't lock it in?  The night before the Challenger launch in January 1986, engineer Roger Boisjoly and his team at Morton Thiokol had the data. They knew the O-ring seals were dangerous in cold weather. They'd written memos. They'd run the numbers. They recommended against launching. But when NASA pushed back hard on the teleconference, Thiokol management called an off-line caucus and excluded the engineers from the room. When the call resumed, management reversed the recommendation. Boisjoly had the analysis. His managers had heard it. But under pressure from their biggest customer, the conclusion got edited in real time. Boisjoly later described it as an unethical forum driven by what he called "intense customer intimidation." He fought like hell, but the room won. That's the most extreme version of the problem. Life and death. But the mechanics are the same in every conference room. The analysis exists. The pressure arrives. And without something anchoring you to what you actually concluded, the room rewrites the story. There's a bonus effect to the Lock-In, too. When you've documented what it would take to change your mind, you've given yourself permission to be genuinely open. You're not being stubborn for the sake of it. You're saying, "Show me evidence that meets this threshold, and I'll update." That's intellectual honesty with a backbone. But you can know exactly what you think and still fail if you can't get anyone else to hear it. How to Dissent and Actually Be Heard Most dissent fails not because it's wrong, but because it's delivered badly.  Blurting out "I think this is a mistake" when the group is already aligned feels like an attack. People get defensive. Your point gets ignored, not because it lacked merit, but because your delivery threatened the group's cohesion. You triggered the same threat response in them that you've been learning to manage in yourself. Charlan Nemeth, a psychologist at UC Berkeley, has studied dissent for decades. You'd expect her research to show that dissent helps groups when the dissenter is right. When someone spots a flaw that everyone else missed. That makes intuitive sense. But that's not what she found. Nemeth discovered that when someone voices a genuine minority opinion, the entire group thinks more carefully. They consider more information, examine more alternatives, and reach better conclusions. And the group benefits even when the dissenter turns out to be wrong. Even when you're wrong, the act of dissenting makes the group smarter. Your disagreement forces everyone out of autopilot. Decades of research by Moscovici supports this. Minority voices don't just influence people in the moment. They shift perception afterward, in private, long after the meeting ends. That's the good news. The catch is in how the dissent happens. Nemeth tested what happens when dissent is assigned rather than authentic, when someone plays devil's advocate because they were told to. It doesn't produce the same effect. Groups can tell when disagreement is performative. The cognitive benefits only show up when the dissent is authentic. When someone actually believes what they're saying. That means the goal isn't just to voice disagreement. It's to voice it in a way that people can actually receive. And the hardest version of this isn't when you have a minor concern about an otherwise good plan. It's when the whole direction is wrong, and finding something to praise would be dishonest. In those moments, the move is to separate the people from the position. "I respect the work that went into this, and I know this isn't what anyone wants to hear, but I think we're solving the wrong problem." You're honoring the effort while challenging the direction. You're not attacking the tribe. You're trying to save it from a bad bet. When the stakes are lower, and you do see genuine merit, you can lead with that. "The market timing argument is strong, and I want to make sure we've stress-tested one thing before we commit." Same principle. You're working with their wiring instead of against it. Either way, your dissent has value beyond being right. Remember that. It's worth holding onto when your amygdala is screaming at you to stay quiet. Everything so far has assumed you're in a room with other people. Your amygdala can't tell the difference between a conference table and a phone screen. The Rooms You Can't See You're not just in meetings. You're in invisible rooms all day long. And most of the time, you don't even know you've walked into one. Every time you scroll past a post with ten thousand likes and think, "I guess that's the right take." Every time you read three articles with the same conclusion and stop questioning it. Every time an algorithm shows you what similar people chose, and you choose it too. Those are rooms full of nodding heads. And your amygdala responds to them the same way it responds to the conference table. Think about the last time you researched a major purchase. You probably started with some idea of what you wanted. Then you read reviews. Then you checked what was trending. Then you asked friends. By the time you decided, how much of that decision was yours? How much of it was the room? Or think about how you form opinions on topics you haven't studied deeply. You read a few articles. They mostly agree. You adopt the consensus. That feels like research. But Berns' scans tell us what's actually happening. Your brain isn't independently weighing the evidence. It's detecting a consensus and rewriting your perception to match. The same process that happens at the conference table is happening every time you open your phone. Mindjacking doesn't need to override your thinking. It just needs to make sure you never finish thinking for yourself before the crowd's answer arrives. And once it arrives, your neurology does the rest. The group doesn't just influence your answer; it shapes it. It rewrites your perception. The Lock-In works for these invisible rooms, too. Before you research a major purchase, write down what you actually want and what you're willing to pay. Before you dive into reviews and opinions, commit your criteria to paper. Before you ask friends what they think about a decision you've already analyzed, record your conclusion. Give yourself the same protection from algorithmic conformity that you'd want before walking into a boardroom. The skill isn't being contrarian. It's being first. First, to your own conclusion, before the room, any room, gets a vote. This is your challenge for the week. Think of one meeting you have coming up where a decision will be made. Before you walk in, open your notes app and type three lines. Line one: what you think. Line two: why. Line three: what would change your mind. That's it. Then sit in that meeting and watch what happens to your thinking when the room pushes back. I think you'll surprise yourself. What if the person you can't resist isn't your boss, your colleagues, or the algorithm? What if it's you? What happens when the decision you need to make threatens something deeper, when being wrong would mean something unbearable about who you are? That's where we're headed next. Closing If this episode gave you something useful, hit that subscribe button. I'm building a complete thinking toolkit here in the Thinking 101 series. If you got value today, share it with someone who could use it, especially anyone heading into a big meeting this week. Drop a comment and tell me: what's the hardest group you've ever had to disagree with? I read every comment and reply. Thanks for watching, and I'll see you in the next episode. Endnotes/References "roughly half of employees stay silent at work rather than voice a concern" / "forty percent estimated they wasted two weeks or more": VitalSmarts, Costly Conversations: Why The Way Employees Communicate Will Make or Break Your Bottom Line (Provo, UT: VitalSmarts, December 2016). In a study of 1,025 employees, 70 percent reported instances where they or others failed to speak up effectively when a peer did not pull their weight. Half wasted seven days or more avoiding crucial conversations. Forty percent estimated they wasted two weeks or more ruminating about the problem. A 2021 follow-up study by Crucial Learning (formerly VitalSmarts) of 1,100 people found the rumination figure had risen to 43 percent. The script's "roughly half" is drawn from the VitalSmarts finding that the majority of the workforce reported conversation failures, with half losing seven or more days to avoidance behaviors. Primary source: https://www.vitalsmarts.com/press/2016/12/costly-conversations-why-the-way-employees-communicate-will-make-or-break-your-bottom-line/. Follow-up study: https://cruciallearning.com/press/costly-conversations-how-lack-of-communication-is-costing-organizations-thousands-in-revenue/ "the Asch conformity experiments from the 1950s": Solomon E. Asch, "Effects of Group Pressure upon the Modification and Distortion of Judgments," in Groups, Leadership and Men, ed. Harold Guetzkow (Pittsburgh: Carnegie Press, 1951), 177–190. The expanded report was published as Solomon E. Asch, "Studies of Independence and Conformity: I. A Minority of One Against a Unanimous Majority," Psychological Monographs: General and Applied 70, no. 9 (1956): 1–70. Asch conducted the line-judgment experiments at Swarthmore College. Participants judged which of three comparison lines matched a standard line, with confederates unanimously giving incorrect answers on critical trials. Across conditions, approximately 75 percent of participants conformed at least once, and the mean conformity rate was approximately one-third of critical trials. Group sizes varied across experiments, typically with 6–8 confederates and one real participant. https://psycnet.apa.org/record/1952-00803-001 "neuroscientist Gregory Berns at Emory University put people inside an MRI machine": 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. The study used functional magnetic resonance imaging with a mental rotation task. Participants (n=32, ages 19–41) judged whether three-dimensional shapes were rotated versions of each other while four confederates provided answers. Conformity was associated with functional changes in the occipital-parietal network (visual and spatial perception regions), not the prefrontal cortex. Independence was associated with heightened activity in the right amygdala and right caudate nucleus, regions linked to emotional salience and threat detection. https://pubmed.ncbi.nlm.nih.gov/15978553/ "The group wasn't changing people's answers. It was changing what they actually saw": Berns et al., "Neurobiological Correlates of Social Conformity," 245–253. The researchers isolated the specifically social element of conformity by comparing brain activation when wrong answers came from a group of people versus when they came from computers. Conformity to group-sourced wrong answers produced greater activation bilaterally in visual cortex and right intraparietal sulcus, overlapping the baseline mental rotation network. Berns interpreted this as evidence that social conformity operates at a perceptual level rather than merely at a decision-making level. Full text PDF: https://pdodds.w3.uvm.edu/files/papers/others/2005/berns2005.pdf "Heightened activity in the amygdala": Berns et al., "Neurobiological Correlates of Social Conformity," 245–253. Participants who gave independent (correct) answers when the group was wrong showed significantly increased activation in the right amygdala and right caudate nucleus. The amygdala is associated with processing emotionally salient stimuli and threats. Berns described these findings as "consistent with the assumptions of social norm theory about the behavioral saliency of standing alone." The script's characterization that "the fear of social isolation activates the same neural machinery as the fear of genuine threats to survival" is an accessible paraphrase of this finding, consistent with the broader social pain literature (e.g., Eisenberger, Lieberman, & Williams, 2003), though Berns' paper does not use that exact language. https://pubmed.ncbi.nlm.nih.gov/15978553/ "engineer Roger Boisjoly and his team at Morton Thiokol had the data": Roger M. Boisjoly, "Ethical Decisions — Morton Thiokol and the Space Shuttle Challenger Disaster" (paper presented at the American Society of Mechanical Engineers Annual Meeting, December 13–18, 1987). First presented as a talk at MIT in January 1987. Boisjoly, a specialist in O-ring seals and rocket joints at Morton Thiokol, documented how engineers recommended against the January 28, 1986 launch based on concerns about O-ring performance in cold temperatures. During the pre-launch teleconference, Thiokol management called an off-line caucus, excluded the engineers, and reversed the no-launch recommendation under pressure from NASA. Boisjoly described the forum as constituting "the unethical decision-making forum" driven by customer pressure. He was awarded the Prize for Scientific Freedom and Responsibility by the American Association for the Advancement of Science. The Online Ethics Center at the National Academy of Engineering hosts Boisjoly's full account: https://onlineethics.org/cases/ethical-decisions-morton-thiokol-and-space-shuttle-challenger-disaster-introduction. See also Russell P. Boisjoly, Ellen Foster Curtis, and Eugene Mellican, "Roger Boisjoly and the Challenger Disaster: The Ethical Dimensions," Journal of Business Ethics 8, no. 4 (April 1989): 217–230. doi:10.1007/BF00383335. https://link.springer.com/article/10.1007/BF00383335 "Nemeth discovered that when someone voices a genuine minority opinion, the entire group thinks more carefully": Charlan J. Nemeth, In Defense of Troublemakers: The Power of Dissent in Life and Business (New York: Basic Books, 2018). Nemeth's research program at UC Berkeley, spanning four decades, demonstrated that exposure to minority dissent stimulates divergent thinking, broader information search, consideration of more alternatives, and higher-quality group decisions. The finding that dissent improves group performance even when the dissenter turns out to be wrong is documented across multiple studies. See also Charlan J. Nemeth, "Minority Influence Theory," IRLE Working Paper No. 218-10 (Berkeley: Institute for Research on Labor and Employment, May 2010). https://escholarship.org/uc/item/1pz676t7 "Decades of research by Moscovici": Serge Moscovici, Elisabeth Lage, and Martine Naffrechoux, "Influence of a Consistent Minority on the Responses of a Majority in a Color Perception Task," Sociometry 32, no. 4 (December 1969): 365–380. In the original experiment, participants viewed blue slides while two confederates consistently called them green. The consistent minority condition produced a shift in approximately 8 percent of majority judgments toward the minority position, and roughly one-third of participants conformed at least once. In the inconsistent minority condition, the effect was negligible (approximately 1.25 percent). The script's claim that "minority voices don't just influence people in the moment — they shift perception afterward, in private" draws on Moscovici's subsequent conversion theory and research on the delayed and private effects of minority influence, including afterimage studies showing genuine perceptual shifts. https://www.jstor.org/stable/2786541 "Nemeth tested what happens when dissent is assigned rather than authentic": Charlan J. Nemeth, Joanie B. Connell, John D. Rogers, and Keith S. Brown, "Improving Decision Making by Means of Dissent," Journal of Applied Social Psychology 31, no. 1 (2001): 48–58. doi:10.1111/j.1559-1816.2001.tb02481.x. Groups deliberated a personal injury case under three conditions: authentic dissent (a genuine minority viewpoint), assigned devil's advocate (a member told to argue the opposing side), and no dissent. Authentic dissent was superior in stimulating consideration of opposing positions, original thought, and direct attitude change. The devil's advocate condition did not produce the same cognitive benefits, suggesting that groups detect and discount performative disagreement. https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1559-1816.2001.tb02481.x. See also Charlan Nemeth, Keith Brown, and John Rogers, "Devil's Advocate versus Authentic Dissent: Stimulating Quantity and Quality," European Journal of Social Psychology 31, no. 6 (2001): 707–720. doi:10.1002/ejsp.58.

“We need an answer by the end of the day.” Ten words. And the moment you hear them, something shifts inside your chest. Your pulse ticks up. Your focus narrows. Careful thinking stops. The clock starts. You probably haven't even asked the most important question yet. Is that deadline real? Most of the urgency you […]