Olivia: Blockbuster, at its peak, had over 9,000 stores. A physical empire. Netflix, in the beginning, had a website and a pile of DVDs in a warehouse. Jackson: I remember that! Getting the little red envelopes in the mail. It felt like a novelty, not a revolution. Olivia: Exactly. Yet by 2010, Blockbuster was bankrupt. And the weapon that killed this retail giant wasn't just the idea of streaming; it was a spreadsheet. It was the decision to measure what Blockbuster thought was immeasurable. Jackson: A spreadsheet. That’s a pretty humble giant-slayer. What are we getting into today? This sounds like a corporate thriller. Olivia: It kind of is! We're diving into a book that’s become a cult classic in the business and tech worlds: How to Measure Anything: Finding the Value of ‘Intangibles’ in Business by Douglas W. Hubbard. Jackson: How to Measure Anything. That’s a bold title. Olivia: It is, but Hubbard has the credentials to back it up. He’s not some motivational guru; he’s a decision scientist. He actually invented a method called Applied Information Economics, or AIE, which is a rigorous way for organizations to make huge, risky decisions. The book is his attempt to bring that powerful thinking to everyone. It’s highly rated for a reason—it fundamentally changes how you see the world. Jackson: Okay, but that Netflix example is, well, Netflix. They're a tech company built on data. For the rest of us, in normal businesses, there are things you just can't measure, right? Like brand reputation, or employee morale, or the value of innovation. You can’t put a number on those things. Olivia: That is the single biggest myth this book sets out to destroy. Hubbard argues that our belief in the "immeasurable" is an illusion. It's a comfortable excuse we use to avoid hard thinking and, ultimately, to make bad decisions based on gut feelings. As the famous saying goes, "Without data, you're just another person with an opinion." Jackson: Huh. I feel slightly attacked, but I'm listening. So how did Netflix prove that? What were they measuring that Blockbuster wasn't?

Olivia: Great question. It gets to the core of Hubbard's philosophy. He says if something is real—if it has any effect on the world at all—then it leaves behind observable traces. And if you can observe it, you can measure it. The trick is to stop trying to measure the fuzzy concept itself and start measuring the traces it leaves behind. Jackson: Okay, "traces." What does that mean in practice? What were the "traces" of customer happiness that Netflix was following? Olivia: Let's paint the picture. Blockbuster measured things that made sense for a retail business: foot traffic in their stores, inventory turnover, and, most famously, revenue from late fees. Their entire model was built around their physical locations. Jackson: Right, which was their biggest strength. Or so they thought. Olivia: Exactly. Netflix, on the other hand, had no stores. All they had was a website and a mailing list. So they started measuring completely different things. They tracked which movies you put in your queue. They measured how long you kept a DVD before sending it back. They analyzed the ratings you gave. They tracked what you clicked on but didn't rent. They were obsessed with every tiny signal of customer behavior. Jackson: Whoa. So they weren't trying to measure "customer satisfaction" with a five-star survey. They were measuring actions. They were measuring what people did, not what they said. Olivia: Precisely. And that led to their first breakthrough: the recommendation engine. By analyzing all those traces, they could predict what you'd want to watch next with startling accuracy. That created a sticky, personalized experience that Blockbuster, with its generic "New Releases" wall, could never compete with. They were measuring the value of personalization. Jackson: That makes so much sense. The personalized list is what kept you coming back. It felt like they knew you. Olivia: And it went deeper. They started doing A/B testing on everything. They'd offer one group of users a $15.99 subscription and another group a $14.99 subscription to see which one had better sign-up and retention rates. They were putting a precise dollar value on customer price sensitivity. Jackson: They were running real-time experiments on their entire business model. Olivia: Constantly. And this is the crucial part. All this measurement gave them an insight that Blockbuster completely missed. By tracking viewing patterns and seeing the growing demand for instant access, their data screamed that the future wasn't in physical DVDs. It was in streaming. They saw the trend years before it became obvious because they were measuring the right things. Jackson: And Blockbuster was still counting people walking through their doors. They were measuring the past, while Netflix was measuring the future. Olivia: You've got it. Blockbuster was so blinded by its old, comfortable metrics that it couldn't see the cliff it was driving towards. Their CEO famously laughed off Netflix as a "very small niche business." They had the data—they could have launched their own streaming service—but they weren't culturally prepared to measure what mattered. They were stuck in the illusion of their own success, defined by metrics that were about to become obsolete. Jackson: Wow. When you put it like that, it's not just about spreadsheets. It's a fundamental difference in philosophy. It's about having the courage to measure the things that make you uncomfortable because they might tell you your entire business is wrong. Olivia: That's the core of it. Hubbard argues that the things we label "intangible" are often the most important variables in a decision. And choosing not to measure them isn't a neutral act. It's an act of choosing to remain ignorant. Jackson: That Netflix story is incredible, but it also sounds incredibly expensive and complicated. I don't have a team of data scientists. This feels like it could lead to analysis paralysis, trying to measure every little thing. Where do you even start?

Olivia: And that is the perfect pivot to the second, and maybe even more practical, big idea in the book. Hubbard is not advocating for measuring everything to the ninth decimal place. The goal isn't perfection; it's simply to be less wrong. Jackson: To be less wrong. I like that. It feels more achievable than "be perfectly right." Olivia: It's a huge mental shift. He points out something he calls the "Risk Paradox." Organizations will spend thousands of dollars and countless hours creating detailed reports to analyze small, routine operational decisions. But when it comes to the biggest, most strategic, multi-million dollar decisions—like launching a new product line or acquiring a company—what do they rely on? Jackson: Gut feeling. A two-day offsite with some PowerPoints. A "strategic discussion." Olivia: Exactly. They revert to pure intuition for the decisions with the highest uncertainty and the biggest potential for loss. It's completely irrational. The point of measurement, Hubbard says, is to reduce your uncertainty about these big, important decisions. Jackson: Okay, so how do you do that without a giant budget? How do you measure something like, say, the potential success of a new product launch? Olivia: You start with what you already know, even if you think you know very little. This is where he introduces the concept of "calibrated estimates." It’s a skill, and he insists anyone can learn it. Jackson: Calibration. That sounds technical. Olivia: It's surprisingly simple. Instead of asking you, "How many units will we sell?"—which forces you to give one, probably wrong, number—a calibrated estimator asks, "Give me a range you are 90% confident the true number will fall into." Jackson: Ah, so it's like giving a lower and an upper bound. Like, "I'm 90% sure we'll sell between 10,000 and 50,000 units." Olivia: Precisely. And the book has these fascinating exercises to help you get better at this. They give you a series of trivia questions, like "What year was Martin Luther King Jr. born?" and you have to provide a 90% confidence range. Most people are terribly overconfident at first. Their ranges are way too narrow. But with practice and feedback, you can train yourself to become remarkably accurate in assessing your own uncertainty. Jackson: Okay, so it's less about being a psychic and more about being a good weather forecaster. You give a "70% chance of rain"—a probability range—not a definitive 'yes' or 'no.' You're quantifying your own ignorance. Olivia: You are quantifying your uncertainty! That's the perfect way to put it. And once you have these ranges for all the key variables in your decision—like the cost to produce, the market size, the potential price—you can do something really powerful. Jackson: This is where the scary math comes in, isn't it? Olivia: It sounds scary, but the concept is simple. He advocates for using tools like Monte Carlo simulations. Don't let the name fool you. All it is, is a computer program that takes your ranges—your calibrated estimates—and runs the scenario thousands of times. It randomly picks a number from your cost range, a number from your market size range, and so on, and calculates the outcome. After 10,000 runs, it gives you a probability distribution. Jackson: So it's basically a "what-if" machine on steroids. It tells you, "Based on your best guesses, there's a 60% chance you'll make a profit, a 25% chance you'll break even, and a 15% chance you'll lose your shirt." Olivia: That is exactly what it does. It transforms a bunch of fuzzy "what-ifs" into a clear, actionable probability of success. It doesn't give you a single answer, but it dramatically reduces your uncertainty about the range of possible outcomes. Jackson: That's a game-changer. But it brings me back to my earlier question: how do you know when you've measured 'just enough'? When do you stop analyzing and just make the call? Olivia: This is the most elegant part of the whole framework. You calculate the "Expected Value of Information," or EVI. You basically ask, "How much is it worth to me, in cold hard cash, to reduce the uncertainty on this variable?" If the cost of being wrong on a decision is a million dollars, and a measurement could reduce your chance of being wrong by 10%, then that measurement is worth up to $100,000. Jackson: Wow. Olivia: If you can conduct that measurement for less than $100,000, you do it. If it costs more, you don't. It's a simple cost-benefit analysis for information itself. You stop measuring when the cost of getting more data is higher than the economic value it provides in reducing your risk. It’s the ultimate defense against analysis paralysis.

Jackson: Okay, my head is spinning in the best possible way. So the big takeaway for me is that we're all walking around with this mental block, this "illusion of intangibles." And breaking through it doesn't require a PhD in statistics. It just requires asking two simple questions. Olivia: What are they? Jackson: First, "What observable thing, what trace, would reduce my uncertainty about this decision?" And second, "Is it worth the effort to go observe it?" It reframes measurement from this big, scary, academic thing into a simple, practical tool. Olivia: That's a perfect summary. It's about making a series of small, informed bets to reduce uncertainty, rather than one big, blind leap of faith. The book is full of examples—the Marine Corps using it to forecast fuel needs, government agencies using it to value IT security. It's been applied everywhere. Jackson: It feels like a superpower for thinking. It's not about eliminating risk, but about understanding it. About knowing the odds before you place your bet. Olivia: Exactly. And Hubbard's challenge to everyone is to try it on something small. Before your next big personal or professional decision, don't just go with your gut. Take five minutes. Write down what you're uncertain about and give a 90% confidence range for the potential outcome. He claims that just doing that one simple act fundamentally changes how you see the problem. Jackson: I'm going to try that. It feels both incredibly simple and profoundly difficult. It forces you to confront what you don't know. Olivia: And that's where real learning begins. We're curious what our listeners think is "immeasurable." Find us on our social channels and tell us the one thing in your work or life you've always been told you can't put a number on. Let's see if we can challenge that. Jackson: I have a feeling we're going to get some interesting answers. This was fantastic, Olivia. Olivia: This is Aibrary, signing off.