بِسْمِ اللَّهِ الرَّحْمَٰنِ الرَّحِيمِ
In the name of Allah, the Most Gracious, the Most Merciful
In 1990, Sears and IBM saw the future clearly. People would use the internet to shop, find information, and communicate. They were so confident they created a joint venture called Prodigy and invested $1 billion — $500 million each.
By 1992, they had 2 million subscribers. The technology worked. The vision was right. And their customers were telling them exactly what they wanted: email. Four million messages a month.
Prodigy's response? They charged $0.25 per email after the first 30. Their CEO said it was "outrageous" that anyone would expect unlimited messaging.
The money didn't just fail to help — it actively killed the opportunity. Because when you have $1 billion to implement a strategy, you implement it. You don't pivot.
- Every business goes through three phases — market creating, sustaining, and efficiency — and each phase needs a fundamentally different type of money and strategy.
- Good money is patient for growth but impatient for profit in early stages, then flips — becoming impatient for growth but patient for profit once the winning strategy is clear.
- The corporate death cycle traps companies in a loop: success creates a growth gap, bad money floods new initiatives, losses mount, new management cuts everything, and the cycle repeats.
This post covers the three phases of business growth and the good money/bad money theory from Clayton Christensen's Disruptive Strategy course — Module 5.
This post is for you if:
- You've watched a well-funded innovation initiative die while a scrappy side project quietly succeeded
- You've wondered why Netflix survived on almost nothing while Prodigy died with $1 billion
- You want to understand why companies keep repeating the same innovation mistakes decade after decade
- Builds on the strategy development process from Post 9 — now we apply it to business phases and funding
This is Post 10 of 11. Each builds on the last:
From Kindling to Blaze
Think about building a campfire. In the first stage, you're experimenting with kindling. You try different arrangements, blow gently on sparks, and learn what catches. You don't yet know what works -- you're discovering it in real time. Committing to a single arrangement too early means you might waste all your kindling on a spark that dies.
In the second stage, you've found a combination that works. The flame is alive. Now your job changes completely: feed it. Add the right fuel at the right rate. You know what works -- execute. Stop experimenting and start scaling.
In the third stage, you have a roaring blaze. Fuel is plentiful but expensive. Your job now is efficiency: keep the fire burning hot while using the least wood possible. And -- critically -- start gathering kindling again, because even the biggest blaze eventually needs new fuel.
Every successful business goes through exactly these three stages. And the strategy process that works in each stage is fundamentally different.
Phase 1: Market Creating Innovation
In the first phase, a company is doing something Christensen describes as "transforming products that are complicated and expensive into products that are so much more affordable and accessible that many more people can buy and use them."
This is the kindling stage. You're creating a market that didn't exist before. The product is new, the customers are unfamiliar, and nobody -- including you -- knows exactly what will work.
The strategy here must be emergent. You don't know what works yet, so you can't commit to a fixed plan. You need to try things, watch what customers actually do (not what they say), and be ready to pivot when the market teaches you something unexpected.
The danger? Picking a direction too early. If you pour all your resources into implementing a deliberate strategy before you've discovered the right one, you'll spend a fortune executing the wrong plan. And with limited resources, that's fatal.
Phase 2: Sustaining Innovation
Once you've found the strategy that works -- the product-market fit, the customer need, the business model -- everything flips. Now you're in the sustaining phase, where the job is to make good products better. You know your customers. You know your competition. The game shifts from discovery to execution.
The strategy here shifts to deliberate. You know the winning play -- now run it. Get everyone aligned. Scale aggressively. This is where effective execution spells the difference between becoming a market leader and becoming a footnote.
Christensen is clear: "Sustaining innovations make good products better." You're not finding new customers or new markets. You're serving existing customers more effectively and beating the competition at the game you've defined.
Phase 3: Efficiency Innovation
Eventually, the market matures. Growth slows. Competition intensifies. Now you enter the efficiency phase, which Christensen defines simply: "Making more with less."
In this phase, you're selling mature products to the same customers at lower prices. The business model is about squeezing more profit from every unit sold. Companies accomplish this by developing processes that reduce cost while maintaining quality.
The strategy here requires both deliberate and emergent processes. The core business needs deliberate management -- ruthless optimization, process improvement, cost reduction. But simultaneously, you must be scanning the periphery for the next growth wave. Because the efficiency phase is a signal: the current business has peaked. If you're not already building the next campfire, you're headed for cold ashes.
This is where most established companies fail. The resource allocation process becomes so deeply tuned to the core business that it automatically kills anything that doesn't fit the existing profit formula. The very efficiency that makes this phase successful becomes the barrier to finding the next phase of growth.
This is the market creating phase in action. The company hasn't found its winning strategy yet -- the market is telling them through usage data. The 10x growth in messaging is an emergent signal screaming "this is the real opportunity." Committing to the document-sharing deliberate strategy would mean ignoring the market's clearest signal. Slack did exactly this -- pivoting from a gaming company to a messaging tool when they noticed their internal chat was more compelling than the game itself.
The company is still in the market creating phase -- they haven't found their winning strategy yet. The 10x growth in messaging is a powerful emergent signal. This isn't sustaining (the product-market fit hasn't been established for document-sharing) or efficiency (the market isn't mature). The right move is to follow the emergent signal and pivot toward what customers actually value.
The Joint Venture That Had Everything
In the early 1990s, the internet was a gold rush. Everyone sensed a transformational opportunity, but nobody knew exactly how the money would be made. Into this uncertainty walked two corporate giants: Sears, the retail powerhouse with the most recognized brand in American commerce, and IBM, the company that made the computer sitting in the customer's home.
Together, they created Prodigy -- and each invested approximately $500 million. That's $1 billion in 1990s dollars -- a staggering bet.
The vision was ambitious and broad. People could use the internet to shop online, access encyclopedias, trade securities, do banking, book travel, and exchange messages. The possibilities were overwhelming.
And that's exactly what happened: the possibilities overwhelmed them.
Picking Winners Too Early
Prodigy's executives looked at the landscape of potential features and made a fateful decision: they picked two. Online shopping and online information retrieval. These were the features they would build the entire technological foundation around. These would be Prodigy's deliberate strategy.
By 1992, they had 2 million subscribers -- a massive early-internet user base. The platform was working. But customers were using it in a way nobody expected.
Four Million Messages Nobody Wanted
Buried inside the Prodigy system was a messaging feature that let subscribers send messages to each other. It wasn't the point of the platform -- it was a side feature. But customers didn't get the memo. They started spending their time not shopping or searching for information, but sending messages to each other.
The volume was staggering: 4 million emails per month. Prodigy's architecture, built from the ground up to process shopping transactions, was overwhelmed. The system was architected to display product pages and handle purchases -- not to route millions of person-to-person messages.
The $0.25 Mistake
Instead of recognizing email as a massive emergent opportunity, Prodigy's leadership saw it as a cost problem. All these messages were clogging the system they'd built for shopping. So they made what seemed like a perfectly rational decision:
30 emails free per household per month. Every email after that: $0.25.
Theodore Papes, Prodigy's CEO, explained the reasoning with remarkable candor: "We never envisioned Prodigy for intensive use of one feature by a tiny fraction of the membership. It's outrageous on the face of it that anyone could think that they could send hundreds or thousands of messages for one low fee."
Outrageous. That's what the CEO called the behavior that would eventually define the entire internet.
Christensen's Diagnosis
Christensen's analysis of Prodigy cuts to the core: "They became very deliberate very quickly."
Prodigy's mistake wasn't that they targeted shopping and information -- both of those markets eventually became enormous. The mistake was choosing a deliberate strategy before the strategy's viability could be known. And Christensen emphasizes that this wasn't just unknown -- it was unknowable. Nobody could have predicted in 1990 what the internet would be used for. They had $1 billion, a blank canvas, and a market where nobody knew what would work. The correct approach was emergent: try everything, watch what customers do, and follow the signal.
Instead, they picked two features, built the entire technical architecture around them, and then -- when the market screamed "email!" -- they punished the very behavior that was trying to show them the winning strategy.
Every dollar they spent optimizing for shopping was a dollar that made it harder to pivot toward email. Every architectural decision reinforced the deliberate plan. By the time it was obvious that email was the future, Prodigy's foundation was wrong and their customers were already leaving.
Theodore Papes's quote deserves a closer look, because it reveals the mindset trap perfectly: "It's outrageous on the face of it that anyone could think that they could send hundreds or thousands of messages for one low fee."
From Papes's perspective, this made complete sense. Prodigy's architecture was built for transaction processing -- displaying product catalogs and processing purchases. Every email was a load on infrastructure that was never designed to route messages. Email wasn't generating revenue; it was consuming resources intended for the shopping and information features that were supposed to make money.
From inside Prodigy's profit formula, email was a cost center. A bug. A misuse of the platform by customers who didn't understand what the service was for.
But from outside the profit formula, email was the most powerful signal a company in the market creating phase could receive. Customers were telling Prodigy, with their behavior, exactly what the winning strategy was. Four million messages per month was the market screaming: "This. Build THIS."
The lesson is sharp: what looks "outrageous" from inside an existing business model might be the winning strategy trying to emerge. The word "outrageous" -- applied to customer behavior -- should always be a red flag. It means your model doesn't fit reality, not that reality is wrong.
The Two Switches
Christensen identifies two critical management switches that occur when building a new growth business. Most companies struggle with the first. Almost none get both right.
Switch 1: You start with a deliberate plan, but you recognize that in all probability, the real winning strategy will emerge. So you flip your mindset: stop trying to execute the plan and start looking for emergent signals. Watch what customers do. Follow the unexpected usage patterns. Let the market teach you. Most companies never make this switch. They commit to their original plan and try to force the market to cooperate.
Switch 2: Once you've identified a growth opportunity that meets all the criteria -- it's disruptive, it's focused on a real job to be done -- you flip again. Now you go back to deliberate. The winning strategy is clear. Stop exploring. Focus every resource on growing this opportunity. Execute relentlessly.
Prodigy never made Switch 1. They went deliberate from day one and never flipped. The market tried to tell them about email, and they punished it.
AOL Gets the Job Right
AOL, led by Steve Case, approached the same market with a fundamentally different mindset. They watched what customers were actually doing on the internet and noticed the same signal Prodigy saw -- but interpreted it completely differently.
Christensen connects this directly to Jobs to Be Done: "If your proposition entails the customer needing to change jobs, it rarely works. Instead, if you help the customers do what they're already trying to do but better, that's when you can tell that a strategy has emerged that you can implement."
What were customers already trying to do? Stay in touch. That was the job. Not "browse an online encyclopedia." Not "shop from home." The job was simple, human, and universal: "I need to just stay in touch."
AOL built everything around that job. They created an architecture specifically designed for messaging -- not repurposed transaction infrastructure, but a system built from the ground up for person-to-person communication. They brought a purpose brand to it that captured the job perfectly: "You've Got Mail."
$23.90 and Unlimited
But the most revealing difference between Prodigy and AOL was the fee structure -- because it reveals which strategy process each company was following.
Prodigy charged $0.25 per email after 30/month. Their pricing punished the very behavior that was the winning strategy. Every message cost the user money. The implicit message: stop using our platform this way.
AOL offered a flat rate of $23.90/month with unlimited usage. No per-email charges. No caps. The implicit message: use our platform as much as you want. The more you use it, the more value you get.
The result? AOL exploded to 30 million users sending 194 million emails per day. "You've Got Mail" became a cultural phenomenon -- a phrase that captured the excitement of a new era of human connection.
Then AOL Lost
Here's the painful second half of the story. AOL won the market creating and sustaining phases brilliantly. They made Switch 1 (recognized email as the emergent winner) and Switch 2 (committed to deliberate execution around messaging). But they never made a third switch.
As the internet matured, the provision of internet access itself became commoditized. Standard protocols meant anyone could provide the same basic connectivity. The place in the value stack where money could be made shifted -- it moved to the layers above and below the access layer.
Google understood this. They deliberately accelerated the commoditization by offering Gmail for free -- destroying the ability to charge for email. Then they built an advertising business on top of the free platform. The money moved from access (AOL's business) to advertising (Google's business).
AOL's profit formula had become so hardened -- so deeply structured around monthly subscription revenue -- that they couldn't see the shift. Christensen warns: "There is so much momentum in the profit formula that you put into place that it is very hard to walk away from it."
AOL's subscription model was their greatest strength in the sustaining phase and their fatal weakness in the efficiency phase. They were the leader of a layer in the value stack that was being commoditized -- and they held on to it until they gradually disappeared.
The crucial lesson from AOL's decline: these big changes in strategy don't occur instantaneously. They're not events, they're processes. Day by day, the provision of internet access became less and less powerful, and more and more opportunities grew on top of it. But there was never a single moment where someone said, "Today, we've got to change." That's what makes these shifts so dangerous -- they happen too gradually for hardened profit formulas to notice.
The fee structure comparison is one of the clearest illustrations of emergent vs. deliberate strategy in action:
- 30 free emails/month, then $0.25 each
- Architecture built for shopping transactions
- Email = cost problem to suppress
- Implicit message: "Stop using it this way"
- $23.90/month flat rate, unlimited email
- Architecture built for messaging from scratch
- Email = the entire value proposition
- Implicit message: "Use it as much as you want"
Same technology. Same era. Same market opportunity. The difference: AOL recognized email as an emergent strategy worth following. Prodigy treated it as a distraction from their deliberate strategy.
This connects directly to Post 3 on Jobs to Be Done. AOL understood the job: "I need to just stay in touch." Prodigy was organized around its own internal job: "We need customers to shop online." When the customer's job and the company's job conflicted, Prodigy chose to punish the customer. AOL chose to serve them.
Resources don't determine outcomes -- strategy process does. Prodigy had more money, more subscribers, and more corporate backing. But they went deliberate before the winning strategy was clear, then punished the emergent signal. AOL made Switch 1 (recognized email), then Switch 2 (executed around it). They understood the job to be done -- "help me stay in touch" -- and built everything around it: architecture, pricing ($23.90 flat), and brand ("You've Got Mail"). Money and technology weren't the differentiator. The strategy development process was.
Technology and timing played small roles, but the real difference was strategy process. Prodigy actually had superior infrastructure and a massive head start. AOL won because they recognized email as an emergent opportunity, pivoted their entire model around it (flat $23.90/month, unlimited usage), and built a purpose brand ("You've Got Mail") around the job to be done. Prodigy treated email as a cost problem. AOL treated it as their entire business. That's the difference between ignoring an emergent signal and building around it.
Reed Hastings' $40 Late Fee
In 1997, Reed Hastings returned a copy of Apollo 13 to his local video store. He was six weeks late. The late fee was $40.
On the drive home, Hastings was embarrassed. Not because of the $40 — but because he didn't want to tell his wife. And that embarrassment got him thinking. Around the same time, he heard about a new format called DVD. It was thin, light, and — critically — it might survive being mailed. So he tested it: he took a number of CDs, put them in envelopes, addressed them to himself, and dropped them in the mail. They came back in a few days, in perfect condition. VHS tapes couldn't survive shipping, but DVDs could.
That combination — the embarrassment of late fees and the discovery that DVDs could survive the mail — led to Netflix. Not as a grand strategic vision. Not as the result of a market analysis. As an experiment born from a $40 annoyance.
The Incremental Pivot Machine
Here's what makes Netflix remarkable from a strategy perspective. Hastings didn't sit in a room and design Netflix as we know it today. He constantly made incremental pivots as emergent opportunities arose. Each pivot was small. Each was a response to a specific problem or discovery. And none of them was planned in advance.
This is the emergent strategy process in action — not one bold bet, but a series of small moves that collectively transformed an entire industry.
Five Emergent Pivots
Netflix's evolution wasn't a single disruption. It was five separate pivots, each emerging from a problem nobody anticipated:
Pivot 1: DVD-by-mail for early adopters. The first customers weren't mainstream movie renters. They were tech enthusiasts who had just bought DVD players and wanted content. The mainstream market didn't care yet — most people didn't even own DVD players in 1997. Netflix started by serving a niche that Blockbuster couldn't see. But this original value proposition had a shelf life: as Hollywood realized how much money was to be made selling DVDs, they started pushing massive volumes through Walmart and Best Buy. With DVDs widely available at retail, Netflix's original proposition — convenient access to DVDs — became irrelevant.
Pivot 2: Flat monthly fee. Netflix first moved to a traditional rental model with per-rental fees and even late fees — the very thing that had inspired Hastings. The problem? They couldn't compete on a per-rental basis. Blockbuster had 5,200 stores — instant gratification. Waiting 2-3 days for a DVD by mail at the same price felt like a bad deal. So Netflix switched to a flat monthly subscription. Not because subscription was the grand plan — but because per-rental wasn't working against an incumbent with 5,200 locations.
Pivot 3: The recommendation engine. Netflix initially hired editors to curate and recommend movies — the same approach everyone used. But a problem emerged: when the editors recommended a title, everyone ordered it, and it went out of stock. Popular recommendations created stockouts. There was also a critical constraint: a movie had to be in stock to be recommended. If it wasn't in stock, Netflix wouldn't recommend it. So they built an algorithmic recommendation system based on each user's ratings and viewing patterns, pooling behavior from consumers who watched the same movies. The unexpected benefit? Customers made better choices. Demand spread across the entire catalog rather than clustering around the same 50 blockbusters. What started as a stockout fix became Netflix's greatest competitive advantage.
Pivot 4: 58 distribution centers. Netflix started in Sunnyvale, California, and discovered something crucial: areas with overnight delivery, like the San Francisco Bay Area, performed far better than places like New York, where a DVD might take a week to arrive and return. They even ran a Sacramento experiment — picking up returned DVDs at the Sacramento post office so that returns mailed during the day would be logged in Sunnyvale by evening, and customers would get a fresh DVD the next morning. This kind of obsessive, incremental logistics experimentation revealed that one-day delivery dramatically improved retention. So they built 58 distribution centers across the country by 2009 — not as a planned logistics strategy, but because the data showed that faster delivery meant lower churn.
Pivot 5: Streaming. Hastings always described Netflix as a "home entertainment company, not a DVD company." When broadband speeds made streaming viable, Netflix was positioned to make the transition — not because they had planned for streaming from day one, but because their subscription model, recommendation engine, and customer relationships transferred perfectly to the new medium. Original content like House of Cards, Stranger Things, and The Queen's Gambit removed the dependency on studio licensing — maintaining the balance of deliberate and emergent strategy even at massive scale.
Netflix's recommendation engine is now legendary — the backbone of their entire business. But it started as a fix for an embarrassing operational problem.
In the early days, Netflix hired editors to write reviews and curate recommendations, just like a bookstore employee might suggest titles. The approach seemed natural. But it created a devastating problem: when an editor recommended a movie, everyone ordered it. Popular recommendations caused stockouts. Customers would see a recommendation, add it to their queue, and then wait weeks because every other customer had done the same thing.
The solution was algorithmic recommendations — a system that analyzed each customer's individual viewing history and preferences rather than giving everyone the same editorial picks. This spread demand across the entire catalog instead of concentrating it on a few titles.
But here's the unexpected benefit that nobody predicted: customers made better choices. The algorithm surfaced movies that matched each person's actual taste, not just whatever was popular that week. Customer satisfaction went up. Churn went down. And Netflix discovered that the long tail of their catalog — the thousands of lesser-known titles — was suddenly generating real demand.
What started as a stockout fix became the single greatest competitive advantage Netflix ever built. Blockbuster had 5,200 stores but no ability to personalize. Netflix had an algorithm that knew each customer better than any store clerk ever could. By the time competitors realized how powerful recommendation engines were, Netflix had years of data and refinement that couldn't be replicated.
5,200 Stores, 500,000 Copies
To understand why Blockbuster failed, you first have to understand why Blockbuster worked. And it worked spectacularly well.
At its peak, Blockbuster had 9,000 stores worldwide, 60,000 employees, and generated over $6 billion in annual revenue. Their model was built on a specific job-to-be-done: movie night. You're at home, it's Saturday evening, you want to watch something. You drive to Blockbuster, browse the shelves, pick up a movie, and take it home. Impulse. Immediate. Tangible.
The entire business was optimized for this moment. Prime retail locations for impulse visits. Massive inventory of new releases — sometimes 500,000 copies of a single blockbuster title across all stores. A 3-week exclusive window where most consumers watched their rental within three weeks, and then demand fell off sharply. Blockbuster then had to sell those copies on the used market. And late fees — which generated approximately $600 million per year in pure profit.
"Not a Sustainable Business Model"
In 2002, Blockbuster was asked about Netflix's online DVD-by-mail model. The response was dismissive: "We have not seen a business model that's financially viable long term... Online rental is serving a niche market." They added: "We don't believe there is enough demand for mail order. It is not a sustainable business model."
This wasn't arrogance. By Blockbuster's profit formula, it was objectively true. Netflix was small, unprofitable, and serving a tiny segment of tech-savvy early adopters. Blockbuster's cost structure required the massive revenue that came from 9,000 locations and $600 million in late fees. An online DVD service couldn't generate that kind of money — not with Blockbuster's overhead.
But the profit formula was doing exactly what it always does: filtering out small, low-margin opportunities. The same filter that made Blockbuster efficient at its core business made it blind to the disruption forming at the edges.
Blockbuster Online: Copying the Wrong Thing
By 2004, Blockbuster could no longer ignore Netflix. So they launched Blockbuster Online — a DVD-by-mail service that was, by many accounts, a perfect copy of Netflix's model. They even added something Netflix couldn't offer: the ability to return DVDs at any of their 5,200 remaining stores for instant exchanges.
On paper, it should have worked. Blockbuster had brand recognition, more customers, and the store advantage. But to fund the online service, Blockbuster made a fateful decision: they eliminated late fees. Overnight, $600 million in annual revenue vanished from their profit formula.
This is the classic trap. To compete with the disruptor, you have to destroy your own profit formula — without having a new one to replace it. Blockbuster eliminated the revenue that kept their stores profitable, but the online model couldn't generate enough revenue to compensate. They destroyed the old engine without building a new one.
Movie Night vs. Book on the Coffee Table
Here's the deeper problem that made copying impossible. Blockbuster and Netflix weren't competing for the same job-to-be-done.
Blockbuster = "movie night." You decide tonight that you want to watch something. You drive to the store. You browse. You rent. You watch. It's an impulse decision with immediate gratification.
Netflix = "book on the coffee table." You have DVDs from Netflix sitting in your living room at all times — always available, like a book on the coffee table. You watch whenever you feel like it. There's no decision to "go rent a movie." The movie is already there. It's always-available entertainment, not an impulse event.
These are fundamentally different jobs. A business model built for "movie night" — prime retail locations, massive new release inventory, impulse browsing — can't be retrofitted for "always available." The cost structures are different. The customer behaviors are different. The competitive advantages are different. You can't copy a model that was built for a different job-to-be-done. It probably would have made more sense for Blockbuster to do something that exploited their massive retail resource base — 9,000 locations in prime impulse-buying positions — rather than trying to be Netflix.
- Job: "Movie night" — impulse, immediate
- Model: 5,200 stores, prime locations
- Inventory: New releases, 3-week window
- Revenue: Late fees = $600M/year
- Behavior: Impulse browsing in-store
- Constraint: Physical locations, staff, real estate
- Job: "Entertainment whenever" — always available
- Model: DVD-by-mail, then streaming
- Inventory: Deep catalog, long tail
- Revenue: Flat monthly subscription
- Behavior: Algorithmic recommendation engine
- Constraint: None — no physical limits
Late fees generated $600M in pure profit — the engine that kept 5,200 stores running. Removing them didn't make Blockbuster more like Netflix. It made Blockbuster a broken version of itself. The online model couldn't generate enough revenue to fill the $600M gap, because Blockbuster's cost structure (stores, staff, real estate) was still intact. They destroyed the old profit formula without having a new one ready. This is bad money in action.
Addressing the complaint sounds logical, but the complaint existed because of the profit formula — late fees weren't a bug, they were the engine. Removing $600M in revenue without replacing it destroyed Blockbuster's ability to fund both its stores AND its online experiment. Closing stores wouldn't fix it either — the stores were what made Blockbuster, Blockbuster. The real issue: you can't fight a disruptor by dismantling your own profit formula. You need a separate unit with a fundamentally different cost structure.
Dwight Eisenhower — the 34th president of the United States and Supreme Allied Commander in Europe during World War II — once said: "Plans are useless, but planning is indispensable." The discipline of planning helps you recognize the features of a situation that matter. But in conditions of high uncertainty, you need the flexibility of an emergent approach. Netflix lived this principle. They always had a plan. But they held the plan loosely and adapted constantly.
Netflix's approach: Plan a small experiment. Test it in the market. Observe what actually happens. Adapt based on reality. Repeat.
Each pivot was small enough to be affordable if it failed, but meaningful enough to reveal something important about the market. The flat subscription fee was a small experiment. The recommendation engine was a fix for a specific problem. The 58 distribution centers were built one at a time, each justified by retention data.
Blockbuster's approach: Plan a massive response. Commit fully. Execute with heavy resources. No adaptation.
When Blockbuster finally responded, they launched Blockbuster Online as a full-scale initiative, eliminated $600M in late fees in one shot, and committed billions to competing head-to-head with Netflix. No small experiments. No incremental learning. One massive deliberate bet.
The cost difference is staggering. Netflix spent less on any single pivot than Blockbuster spent on its ONE competitive response. Netflix could afford to be wrong five times. Blockbuster couldn't afford to be wrong once — and they were.
The lesson: Emergent strategy at scale means making many small, cheap bets instead of a few big, expensive ones. Each bet teaches you something. The sum of those lessons becomes your actual strategy. This is what "patient for growth, impatient for profit" looks like in practice — which is exactly what we'll explore in the next section.
Type of Money > Amount of Money
Here's one of the most counterintuitive ideas in this entire series: the same money can be "good" or "bad" depending on what phase your business is in.
Most people think about money in one dimension: more is better. A startup that raises $50 million should be in better shape than one that raised $5 million. A company that invests $1 billion in innovation should innovate more than one that invests $10 million. But Christensen's research shows the opposite is often true. The type of money matters more than the amount.
Money comes with expectations. And those expectations determine whether the money helps you find the right strategy — or forces you to commit to the wrong one before you know what works.
Good Money When Strategy Is Uncertain
When you're in the early stages — when you haven't found product-market fit, when the right strategy isn't clear yet — good money is patient for growth, but impatient for profit.
What does that mean? It means the money doesn't demand rapid scaling. It doesn't require you to capture 30% market share in 18 months. Instead, it gives you time to experiment, pivot, and discover the right strategy through the emergent process. But it does demand that you prove the model works — that you can make money, even on a small scale. "Keep fixed costs low and get into the market."
This is exactly what Netflix did. In its early years, Netflix operated with modest capital. Each pivot was small and affordable. The flat subscription model was tested before it was scaled. The recommendation engine solved a real problem before it became a competitive moat. The 58 distribution centers were built incrementally, each justified by data. Netflix proved profitability at small scale before it ever tried to grow.
Good Money When Strategy Is Clear
Once you've found the right strategy — once the emergent process has revealed what works — the rules change completely. Now good money is impatient for growth, but patient for profit.
This is the moment to scale aggressively. You know the model works. You've proven unit economics. Now the risk isn't picking the wrong strategy — it's moving too slowly and letting competitors catch up. In this phase, you need big money that demands rapid growth, because speed matters more than short-term profitability.
Amazon is the clearest example. Once Bezos proved that online retail worked, he raised billions and sacrificed profitability for years to build scale. The money was impatient for growth (expand to every category, every country) but patient for profit (investors accepted losses for years). This was good money applied at the right phase.
Bad Money = Good Money in the Wrong Phase
Bad money isn't a different kind of money. It's good money applied at the wrong phase.
If your strategy is still uncertain — you haven't found product-market fit — and you take money that is impatient for growth, you're forced to scale before you know what works. You commit massive resources to a deliberate strategy that hasn't been validated by the market. You build the factory before you know if anyone wants the product.
This is fatal. The 93% finding tells us that the winning strategy almost never comes from the original plan. But growth-impatient money demands that you execute the original plan — fast. It doesn't give you room for the emergent process. It demands execution when you need experimentation. Christensen is blunt about this: "You would rather have no money than bad money."
What makes this worse is that the very process of securing funding forces many potentially disruptive ideas to get shaped as sustaining innovations that target large and obvious markets. To get a big check, you have to promise a big market. And that promise locks you into a deliberate strategy before the right strategy has emerged. Thus, the funding received can send great ideas on a march toward failure.
And here's another thing to worry about: who is your banker? People think of bad money as coming from venture capitalists. But more often than not, your banker is the corporation itself — the parent company giving you money as an employee to innovate. Corporate money is almost always impatient for growth, because the parent company has its own growth gap to fill. That corporate expectation is often the most dangerous form of bad money.
Conversely, if your strategy IS clear and you take money that is patient for growth, you move too slowly. Competitors who have also found the winning formula will outscale you. Being patient for growth when you should be aggressive is how you lose a market you already understand.
This is the classic bad money trap. The startup doesn't know what works yet — the strategy is uncertain. But the $50M comes with growth expectations ($100M in 18 months) that force the company to scale a model that hasn't been validated. They'll burn through money building infrastructure for a strategy that has a 93% chance of being wrong. What they need is small money that demands profitability (proving the model) while being patient about scale.
The amount of money ($50M) isn't the issue — the expectations attached to it are. Demanding $100M revenue in 18 months forces the startup to execute a deliberate strategy at scale before validating it through the emergent process. The team's quality doesn't change this structural problem. Great people executing the wrong strategy still fail. What matters is whether the money gives room for experimentation (good) or demands premature scaling (bad).
The Pattern That Repeats Forever
There's a pattern in corporate innovation that repeats with eerie consistency. Once you see it, you'll recognize it everywhere — in companies you've worked for, companies you've read about, and companies that will make headlines next year.
It starts with success. A company's core business is growing. Margins are healthy. Everything is working. But eventually, growth slows. The market matures. Competition intensifies. The growth rate that investors and boards expect starts to exceed what the core business can deliver.
A gap opens between the growth the company needs and the growth the core business delivers. And that gap is where the death cycle begins.
The Six Steps
Step 1: "We need to be more aggressive about innovation." The board sees the growth gap and demands action. Management announces a bold initiative to pursue new markets, new technologies, new business models. Big speeches. Big plans.
Step 2: Big funding gets committed. The company allocates hundreds of millions — sometimes billions — to the innovation initiative. They hire aggressively, build new teams, launch new products. The money is impatient for growth: "We need this to move the needle NOW."
Step 3: The wrong deliberate bet. Because the money demands immediate growth, the team can't afford to experiment. They pick a big, deliberate strategy — the one that looks most promising in the boardroom presentation — and commit fully. No room for emergence. No small experiments. One big bet.
Step 4: Losses mount. The deliberate strategy doesn't work as planned — because the right strategy hasn't emerged yet. Revenue misses targets. Costs exceed budgets. The innovation initiative becomes a financial drain. Quarterly earnings calls become uncomfortable.
Step 5: Management gets fired. Cost cutting begins. The board blames the management team for poor execution. New leadership is brought in. Their first priority: stop the bleeding. They cut the innovation initiative, restructure the team, and refocus on the profitable core business.
Step 6: The growth gap returns. The core business continues to slow. Within 2-3 years, the same gap opens. The board again demands aggressive innovation. New management launches a new initiative with big funding. And the cycle repeats.
Why It Never Ends
The death cycle persists because each new management team makes the exact same mistake. They pour bad money (impatient for growth) into an uncertain situation (strategy not yet clear). They commit to a big deliberate bet when they need small emergent experiments. And when the bet fails, they blame the people instead of the process.
The new management team doesn't learn from the previous team's failure — because they diagnose the failure as "bad execution" rather than "wrong type of money." So they do the same thing with more conviction, more money, and more urgency. And they get the same result.
The death cycle breaks when leadership understands one thing: the type of money must match the phase of the strategy.
In the early phase (uncertain strategy): Use small money. Demand profitability at small scale. Give room for emergent experiments. Don't force premature scaling. This is patient-for-growth, impatient-for-profit money.
In the later phase (clear strategy): Use big money. Demand aggressive growth. Scale what's been validated. Move fast. This is impatient-for-growth, patient-for-profit money.
The problem: Boards and investors are almost always impatient for growth — regardless of the phase. A board looking at a growth gap doesn't want to hear "we're running small experiments to discover the right strategy." They want to hear "we're investing $500M to capture this market." The pressure to look decisive overrides the need to be adaptive.
The structural solution: Create a structurally separate unit for the uncertain-strategy phase — with its own budget, its own timeline, its own board expectations, and its own definition of success. The separate unit gets good money (patient for growth, impatient for profit) while the parent gets to satisfy the board with the core business performance.
This is the same structural separation we explored in Post 6. A separate unit doesn't just solve the process problem — it solves the money problem. It's the only way to match the type of capital to the type of strategy without the parent company's profit formula and board expectations contaminating the innovation process.
The cycle isn't inevitable. But breaking it requires leaders who understand that the problem isn't bad people, bad strategy, or bad execution. The problem is bad money — the right money at the wrong time.
Jobs to Be Done as the Compass
We've seen how money type determines outcomes. How emergent and deliberate strategy each have their phase. How the death cycle traps companies that mismatch money to phase. But there's one question we haven't answered:
How do you know if your strategy is actually right?
The answer goes back to Module 2 — the Job to Be Done. If you don't understand the job your customer is trying to get done, then the probability of success is very low, regardless of how much money you have or how well you match it to the phase. You're navigating without a compass.
But if you DO understand the job — if you've identified what customers are actually trying to accomplish in their lives — then the probability that they will "pull" your product into their lives is very high. The job is the compass that tells you whether your emergent signals are worth following.
Think about Netflix. Every one of their five pivots was guided by a deeper understanding of the job: convenient entertainment on my terms. DVD-by-mail eliminated the Blockbuster trip. No late fees removed the anxiety. Streaming removed the wait. Original content removed the dependency. Each pivot was emergent, but the compass — the job — stayed constant.
Now think about Prodigy. They had the right product (email in 1984), but they never understood the job their users were trying to get done. They saw email as a feature of an information service. Users saw it as the entire reason to sign up. Without the compass, Prodigy couldn't recognize what the emergent signal was telling them.
The Complete Framework
Now we can see the full picture — how every module in this series connects into a single framework for building innovations that survive:
- Find the Job to Be Done (Module 2) — This is your compass. Without it, no amount of money or strategy process can save you. The job tells you what customers actually need, not what you think they need.
- Let strategy emerge, then make it deliberate (Posts 9 + 10) — Start emergent when the right strategy isn't clear. Watch for signals. When a pattern validates, switch to deliberate and execute with discipline.
- Fund with good money for the phase (This post) — Patient for growth and impatient for profit in the emergent phase. Impatient for growth and patient for profit once you've found the winning strategy.
- Organize correctly (Posts 5-6) — Sustaining innovations belong in the core organization. Disruptive innovations need a separate business unit with its own processes, priorities, and profit formula.
- Watch for modularity shifts (Posts 7-8) — As industries evolve from interdependent to modular architectures, the locus of profit shifts. Position yourself where performance gaps still exist, not where they've been solved.
Miss any one of these, and the innovation fails. Get them all right, and you have a systematic approach to building things that survive and scale.
Before investing in any new initiative, ask these four questions in order. If you can't answer "yes" to the first one, nothing else matters.
1. Do we know the winning strategy?
If yes: use deliberate strategy. Execute with discipline. If no: use emergent strategy. Stay flexible. Watch for signals.
2. Has the strategy been validated by the market?
If yes: you're ready for Switch 2 — lock in the deliberate strategy and scale. If no: keep experimenting. Don't commit resources to an unvalidated strategy, no matter how logical it seems.
3. Are we matching money to phase?
Emergent phase: patient for growth, impatient for profit. Deliberate phase: impatient for growth, patient for profit. If your money type doesn't match your phase, you're feeding the death cycle.
4. Is the Resource Allocation Process going to filter this out?
If the initiative doesn't fit your profit formula's criteria (cost structure, opportunity size, margin requirements), the RAP will kill it automatically — regardless of what the CEO says. The only solution is a separate unit with different criteria (Post 6).
- Three phases, three approaches — Market Creating (emergent, find the JTBD), Sustaining (deliberate, execute), Efficiency (both, optimize + prepare the next wave)
- Prodigy had everything right — and killed it — $1B budget, correct product (email in 1984), right timing. But bad money demanded growth before the strategy was validated
- Netflix is a pivot machine — five emergent pivots, none of them planned. Each one discovered by watching what customers actually did, not what the business plan said
- You can't copy a business model — Blockbuster destroyed $600M trying to replicate Netflix's model inside a sustaining organization. The RPP killed it
- Good money does not equal more money — good money matches the phase. Patient for growth when uncertain. Impatient for growth when validated
- The death cycle never ends — success creates a growth gap, which demands aggressive investment, which funds the wrong strategy, which fails. It only breaks when you match money to phase