The Greedy Trap
Why do highly successful organizations sometimes become trapped by the very capabilities that made them successful?
In Episode 76, Nic Encina closes Season 2 of UnNatural Selection by synthesizing insights from more than 70 conversations with innovators and leaders across industries.
Drawing on computer science, evolutionary thinking, and case studies spanning Kodak, NASA, MIT's Langer Lab, the FBI, and Aston Martin Formula One, Nic explores the distinction between optimizing today's position and building tomorrow's competitive advantage.
He introduces a five-dimensional framework for organizational competitive fitness: Adaptability, Cultural Resilience, Strategic Intent, Execution, and Temporal Optimization.
The executive takeaway: operational excellence is not enough. Sustainable competitiveness requires knowing when to improve the existing model, and when to accept short-term sacrifices to pursue a better future.
Evolution by Design.
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Nic (00:39)
Welcome to UnNatural Selection, a show about competition, innovation, and the strategies shaping tomorrow's frontiers. I'm Nick Encina. Each week we speak with pioneers shaping the future.
speaker-2 (00:50)
Welcome to the season two finale of Unnatural Selection. Over two seasons and more than 70 conversations, we've explored innovation and competition across an extraordinary range of industries, from Formula One garages and NASA missions to biotechnology labs, corporate boardrooms, and the frontiers of artificial intelligence. And to think, this entire investigation began with Nick staring at a roll of toilet paper. Apparently, some people see bathroom supplies. Nick sees the evolution of civilization.
Fortunately, we've expanded our research methods considerably since then. Today, we're connecting the discoveries from both seasons to explore a deceptively simple question: why can being exceptionally good at what you do today make you less capable of succeeding tomorrow? Here's Nic
Nic (01:36)
When I started on natural selection, the premise was to explore innovation and competition as forces shaping the evolution of human society. Not because businesses or institutions literally follow the laws of biology, but because ideas spread, capabilities accumulate, environments change, and success is never guaranteed to endure. Season one was about identifying the patterns. It was about finding invariant learnings that map across industries. And sure enough, we kept encountering the same underlying forces: adaptability, Organizational culture, asymmetric competition, and the ecosystems that determine whether innovation succeed or fail.
Kodak illustrated how an established business model can become a constraint. NASA showed us how shared purpose and institutional knowledge can sustain extraordinary ambitions across generations. And again and again we discovered that innovation depends on much more than having a good idea. It depends on whether an organization can recognize its potential, overcome resistance, and turn it into reality.
But that raised another question. If adaptability is so important, why do some organizations keep evolving while others become trapped by their own success? That's where season two came in. It was about understanding the mechanisms. We went deeper into how competition actually works, from the relentless optimization of Formula One and NASCAR to the changing economics of biotechnology, energy, and software. We examined how organizations make strategic choices, how culture influences execution.
And how new technologies can redefine the very basis of competition. And a distinction began to emerge. Being good at improving your current position is not the same as being good at reaching a better one. An organization can become faster, more efficient, and more profitable and still be moving toward that end. That's a paradox at the heart of today's episode. I call it the greedy trap. To understand why this happens, we'll connect three ideas: how human civilization accumulates capabilities.
how optimization can trap us in the present, and how we might assess whether an organization is genuinely equipped to compete in an uncertain future. And the first connection begins with a remarkable observation about human progress.
Aisha (03:48)
Act 2. How capability accumulates. Human progress is cumulative. Discoveries become tools, tools become infrastructure, and yesterday's breakthroughs become the foundation for tomorrow's innovations. But there's a paradox. The capabilities that allow us to advance can also become the assumptions that prevent us from changing. Nick explores how civilization accumulates knowledge and why every advance changes the landscape of competition.
Nic (04:14)
The mathematician and philosopher Alfred North Whitehead once wrote
Alfred North Whitehead (04:18)
"Civilization advances by extending the number of important operations which we can perform without thinking about."
Nic (04:27)
Think about what that means. A calculation that once required considerable effort becomes routine through mathematical notation. Navigation becomes easier through maps, instruments, and eventually GPS. We don't have to reinvent every capability from scratch. We inherit what previous generations have learned and build on top of it. This idea is an interesting parallel in biological evolution. Biological mutations don't arise because organisms anticipate a future need.
Variation arises through biological processes. When a heritable variation improves reproductive success in a particular environment, natural selection can make it more common. Over generations, adaptations can make important functions more reliable or less costly. The capabilities that persist become part of the foundation on which subsequent evolution takes place. Human beings have developed another way to accumulate capability. We preserve discoveries outside our genes.
We transmit knowledge through language, mathematics, tools, education, and institutions. We can build what we've learned into machines and processes, allowing other people to use those capabilities without having to rediscover them. And unlike biological evolution, cultural and technological evolution can sometimes be deliberately directed. We can imagine alternatives, test them, and change the systems through which knowledge spreads. The mechanisms are different, but the broader connection is important.
What becomes routine today changes what becomes possible tomorrow. When an operation becomes easier, cheaper, or more reliable, we can direct effort toward the next challenge. When a capability becomes widely available, it may cease to be a meaningful source of competitive advantage. The basis of competition moves elsewhere. This pattern appears across industries. A technology can begin as a scarce specialized capability. It becomes more accessible, competitors adopt it.
But once differentiated one organization becomes an expectation shared by the market. The next advantage may come from how that technology is integrated, what new problems it makes possible to solve, or what parts of the value chain become more important as a result. Innovation doesn't just add new capabilities, it changes the landscape on which the next round of innovation takes place. And that brings us to a problem that appears in biology, algorithms, and business, although in different ways.
How do you move beyond a position that is already working?
Aisha (06:52)
3. The Greedy Trap. When the best next step is the wrong move.
Nic (06:58)
In computer science, a greedy algorithm makes a choice that looks best at each step according to a particular decision rule. That can be an excellent approach. For some problems, a greedy algorithm produces the optimal solution. But when decisions have consequences that unfold over time, the local best choice may not lead to the best overall outcome. Imagine you're hiking in a mountainous terrain. You've climbed to the top of a hill, you're standing at its summit, and the ground around you slopes downward. Every step toward the valley means losing elevation.
But across the valley stands a much taller mountain. To reach the higher peak, you first have to descend, you have to give up some of the height you've gained, cross the valley, and begin climbing all over again. If your only rule is to take the next step that increases your elevation, you'll never leave the hill. You'll keep improving your position relative to where you are while remaining unable to reach a better position somewhere else. That hill is a local optimum. A position that's better than the nearby alternatives.
But worse than a more distant position you could reach only by taking a different path. The danger isn't that the hill is worthless. You may have worked hard to get there. It may be a genuinely good position. The danger is that your decision rule makes it impossible to leave.
Aisha (08:10)
Congratulations! You've optimized your way to the top of a hill and made yourself incapable of reaching the mountain.
Nic (08:16)
Exactly. Now translate that into business. An organization has a successful product, established customers, skilled employees, efficient processes, and a business model that generates attractive returns. It knows how to improve that model, it can reduce costs, raise margins, increase output, and respond to customer feedback. Each improvement is measurable, each investment can be evaluated against a familiar baseline. But suppose the market is moving toward a different technology or business architecture.
Getting to the next competitive position may require investments that initially reduce margins. It may require new skills, new partnerships, and new ways of working. It may mean cannibalizing a successful product before the replacement is fully mature. The organization must accept a period in which the familiar measures of performance look worse. A decision rule that rewards immediate improvement will reject that move, even if the alternative offers a stronger long-term position. This is the greedy trap.
The organization doesn't necessarily lack intelligence, talent, or operational discipline. It may be exceptionally good at optimizing the business it already has. That company may actually even think it's innovating, it actually is. But there are different types of innovation, whether you're looking at something that's more routine or something that's architectural or disruptive. The problem is that it evaluates every move against a current position instead of evaluating the path toward a better one. Kodak offers a useful illustration.
The company had deep expertise in film photography, processing, distribution, and the broader photographic market. There were many ways to improve the system, and those improvements could create real value. But digital imaging changed the competitive landscape. Moving toward that landscape wasn't simply a matter of making the film business more efficient. It meant confronting different economics and developing capabilities that could challenge the value of the existing business. The point isn't that every legacy business should abandon its core as soon as a new technology appears.
Nor is the lesson that a particular investment in a new technology guarantees success.
The lesson is that the current business can be both valuable and constraining. The more successful an organization becomes at optimizing its existing model, the more it may have to lose by moving away from it. And the more its incentives reward immediate results, the harder that move becomes. This is why we need to distinguish two forms of performance. One is the ability to improve the current position.
The other is the ability to choose and pursue a trajectory toward a better position, even when the next step looks worse before it looks better. I'll call the first greedy optimization and the second dynamic optimization. Greedy optimization asks, what looks best right now? Dynamic optimization asks, which sequence of choices gives us the best outcome over time? And there's an important qualification. Not every valley leads to a mountain. Sometimes an investment destroys value.
A technology fails to mature or a market never develops as expected. Dynamic thinking isn't permission to pursue a grand vision regardless of the evidence. It means having a clear hypothesis about the destination, a credible route, and milestones that tell you whether the journey remains worthwhile. The challenge is to distinguish a necessary short-term sacrifice from a bad investment. That brings us to a framework that I've been developing over these conversations.
Aisha (11:33)
Act 4. The five dimensions of organizational competitive fitness. How can we distinguish organizations that are simply performing well today from those genuinely equipped to evolve? Nick introduces five dimensions of competitive fitness: adaptability, cultural resilience, strategic intent, execution, and temporal optimization. Together, they provide a way to examine not just how effectively an organization competes, but whether its decisions are preparing it for the future.
Nic (12:02)
Across two seasons, I've been collecting observations about how organizations innovate, compete, and respond to change. The industries differ enormously, but recurring questions keep appearing. Number one, can the organization recognize when its environment is changing? Number two, can people challenge established assumptions and learn from failure? Number three, can the organization decide where it wants to go rather than merely react to others? Number four, can it turn those decisions into action? And number five,
Can it make trade-offs across time instead of sacrificing its future to improve its present? I've organized those questions into a five-dimensional framework for assessing organizational competitive fitness. I think of it as a radar map. Each dimension captures a different capability. And the capabilities are, number one, adaptability. Adaptability is the ability to recognize meaningful change, learn from it, and alter behavior. It isn't simply moving quickly, it's closing the loop between information and action.
How quickly does information reach decision makers, and how willing is the system to stop doing something when evidence no longer supports it? Number two, cultural resilience. Cultural resilience is the ability to create an environment in which people can question assumptions, surface problems, explore alternatives, and take informed risks. Psychological safety isn't the absence of accountability. It is the ability to challenge established thinking and learn from disciplined experimentation without fear of arbitrary punishment.
Number three, Strategic Intent. Strategic intent is the ability to develop a deliberate point of view about where competition is heading and to act in ways that shape the future position the organization wants to occupy. Forecasting asks what might happen. Strategic intent asks what future we want to compete in and what assumptions we can change about how the game is played. 4. Execution. Execution is the ability to make decisions, establish ownership, resolve bottlenecks.
Coordinate people and deliver outcomes. If decisions are repeatedly reopened, accountability is fragmented, or essential resources remain trapped between departments, strategy never becomes operational reality. And number five, temporal optimization. Temporal optimization is the ability to balance current performance against future opportunity. It asks whether the organization can evaluate trade-offs across time horizons rather than allowing the immediate payoff to dominate every decision.
This is the vertex that directly combats the greedy trap.
Aisha (14:37)
Act 5. Stress testing the radar model. Six case applications. That framework gives us a theoretical vocabulary, but models are only as good as their ability to map real-world terrain. Let's stress test these five dimensions by examining five very different organizations through our radar model: Kodak, NASA, the Langer Lab, the FBI, and Aston Martin Formula One. Let's start with a classic example of corporate inertia.
Case one, Kodak, the complacent incumbent.
Nic (15:08)
Kodak presents a textbook complacent incumbent profile. They possess elite execution within their traditional chemical ecosystem. But when Steven Sassin presented the handheld digital camera in 1975, the company evaluated it using a collapsed time horizon of T equals zero.
Because digital couldn't match film's immediate profit margins, Kodak refused to descend into the performance valley. High traditional execution paired with non zero temporal optimization.
trapped him on a dying local hill.
Aisha (15:39)
Now let's look at an organization operating on an entirely different time horizon. Case two, NASA, the generational pioneer.
Nic (15:46)
Dr. Ed Hoffman showed us that NASA is a generational deep tech pioneer. While administrative bureaucracy gives them moderate adaptability, their temporal optimization is unmatched. Launching Voyager in the 1970s with 1960s technology required designing a platform that could operate in interstellar space decades later. Their high cultural resilience, using storytelling and design disagreement to align distributed teams, allows them to sustain multi-generational bets.
without dissolving under short term political pressure.
Aisha (16:19)
What happens when scientific curiosity and commercial ambition reinforce each other over decades? Let's examine Robert Langer's lab at MIT. Case three, Langer Lab, the ecosystem incubator.
Nic (16:31)
Bob Langer's profile is almost perfectly balanced across all five vertices. Their defining strength is cultural resilience paired with temporal optimization. When experts claimed mRNA delivery was chemically impossible, Langer protected long-term curiosity and insulated his researchers from short-term market skepticism. That patients created the foundation for Moderna and mRNA medicine.
Aisha (16:54)
What happens when an established institution must confront threats that don't respect its traditional organizational boundaries? Let's turn to the FBI and Nick's conversation with Rajiv Raghavan. Case four, FBI, the institutional defender.
Nic (17:10)
Now, what happens when a massive century old institution faces borderless digital threats? The FBI profile illustrates a decentralized institutional defender. Traditionally, large government institutions struggle with adaptability due to rigid hierarchies. But as Rajiv Raghavan explained, cyber warfare forced the FBI to push decision making authority to the field office edge. Their strategic intent evolved from reacting to individual crimes.
Toward proactively building public-private trust to neutralize infrastructure before attacks occurred.
Aisha (17:44)
Finally, let's examine an environment where competitive advantage can be measured in thousandths of a second, and where the rules constrain nearly every engineering decision. Case 5, Aston Martin Formula One, the hyper-itterative competitor.
Nic (17:57)
An F1, strict cost caps and testing limits standardize a physical car. S and Martin thrives by maxing out adaptability and execution. They process gigabytes of real-time telemetry to alter race strategy on the fly. Their profile shows that when technical regulations equalize physical assets, competitive advantage migrates into execution velocity and learning loops.
Aisha (18:21)
6. Why Time Changes the Entire Map. Five organizations, five very different competitive environments. But their radar profiles reveal something important. Competitive fitness isn't simply about being strong across every dimension. It's about developing the capabilities that matter for your environment and understanding how their value changes over time. Nick brings these comparisons together to explain why temporal optimization can change the meaning of every other score.
Nic (18:51)
There's one final distinction I want to emphasize. The first four dimensions help us standardize an organization's capabilities, how it responds, how it learns, how it chooses a position, and how it delivers. Temporal optimization changes how we evaluate those capabilities. Without it, we can take a snapshot of a highly capable organization and miss the fact that it is moving toward a less competitive future. With it, we can ask whether today's choices preserve or expand tomorrow's options. Think back to the mountain.
If success is measured only by elevation at every step, descending into the valley looks like failure. But if the objective is to reach the higher peak, that descent may be a necessary part of the route. The same logic applies to a business investing in a new platform, a pharmaceutical company developing a feature pipeline, or a manufacturer preparing for a different production technology. The transition may involve lower near term returns, capabilities that take years to mature.
or products that initially underperform the established business. Those costs do not automatically make the strategy wise. The destination must be plausible, the route must be credible, and the organization needs evidence that the investment is working. But if every temporary decline is treated as unacceptable, the organization may rule out the very moves required to remain competitive. Temporal optimization is a capacity to make that distinction. It recognizes that some investments should be abandoned
Some should be accelerated, and some require patience because the value emerges only when multiple capabilities come together. It also recognizes that time cannot be separated from the other dimensions.
Adaptability supplies new information. Cultural resilience allows people to challenge the existing plan.
Strategic intent identifies a destination. Execution turns a plan into action. Temporal optimization evaluates the choices across the full trajectory.
And the results feed back into the system. New evidence may change the strategy, execution may reveal that the original route is infeasible, a shift in the market may require a new destination altogether. This is not a linear process that ends once a plan is written. It's a continuous diagnostic loop. The organization must detect, challenge, shape, deliver, and reassess, while making sure the immediate demands of the business do not consume the resources needed for its future.
speaker-2 (21:15)
7. The Executive Audit. A framework is only useful if it changes the questions we ask. In this section, Nick translates the five dimensions into a practical audit for leaders, innovators, and anyone responsible for building something that needs to endure. And if your strategy depends on a capability remaining difficult to replicate, what is your plan for the day it isn't?
Nic (21:38)
So how do we make this practical? I would start with five questions, one for each dimension. Number one, the adaptability test. What evidence would cause us to change our minds? How quickly does that evidence reach decision makers and how quickly can we alter course? If we keep discovering the same problems without changing our behavior, we aren't learning fast enough. 2. The Cultural Resilience Test. What important information are people afraid to tell us? Can employees challenge a senior leader's assumptions? Can a team report that a promising initiative isn't working? Our failure is examined for what they teach us or punished in ways that encourage concealment? 3. The strategic intent test. Are we deliberately shaping our future position or are we mainly reacting to what competitors do? What assumptions define our industry today? Which could change? And what could we do to influence the basis on which we compete? 4. The execution test.
Which important decisions are not turning into results? Where does ownership become unclear? Which bottlenecks keep recurring? What work remains stuck between departments, committees, or competing incentives? And number five, the temporal optimization test. Are we improving the position we're in or pursuing the trajectory we actually want? Which capabilities are we building that may not produce immediate returns? What short-term costs are we prepared to accept?
What milestones would justify continuing and what evidence would cause us to stop? Look at your most successful products, processes, and business models, which are still creating genuine value, which could become less valuable as the environment changes, and which of your current performance measures might discourage you from making a necessary transition? And if your strategy depends on a capability remaining difficult to replicate, what is your plan for the day it isn't? That's a threat connecting all five questions.
Adaptability without direction can become frantic activity. Culture without accountability can become complacency. Strategic intent without execution remains an aspiration. Execution without temporal optimization can make an organization exceptionally efficient at climbing the wrong hill. The framework is useful only if it helps us see those distinctions and identify which constraint is actually holding an organization back.
Aisha (24:01)
Act 8. What we've learned and what comes next.
Nic (24:06)
Looking back across two seasons, I'm struck by how often very different industries confront versions of the same underlying problems. How do you recognize that the environment has changed? How do you distinguish a temporary setback from a structural shift? How do you create a culture that can learn without becoming reckless? How do you build an advantage without assuming it will last forever? How do you turn a strategic idea into a coordinated action? And how do you make decisions today that preserve your ability to succeed tomorrow?
Our conversations have taken us from photography and biotechnology to professional sports, software, manufacturing, energy, government, education, and the science of human behavior. Whitehead's observation gives us one way to understand the accumulation of human capability. Civilization advances as important operations become routine, freeing people to do things that once seemed out of reach. Biological evolution offers a related story.
Variation arises, environments influence which variations persist, and adaptations change the possibilities available to future generations. Human innovation adds another layer. We can deliberately create, preserve, and transmit capabilities. We can build them into technologies and institutions, and we can sometimes redesign the systems through which further innovation occurs. But every advance changes the landscape. The challenge is not simply to improve, it is to recognize what is worth improving.
Decide where to go next, create the conditions for change, execute the transition, and make the trade-offs required to reach a better position. That's what I mean by unnatural selection: exploring how human ingenuity changes the systems we build, and how those systems in turn shape what becomes possible. The next question is becoming harder to ignore. What happens when artificial intelligence, biotechnology, autonomous systems, and human institutions begin changing one another's capabilities?
How do we understand innovation when the unit of change is no longer just a product, a company or an industry, but an entire ecosystem? That's where we take this investigation next season. Thank you and see you next year.
Aisha (26:14)
Thank you to everyone who has joined us across these two seasons. Our extraordinary guests, the teams behind the scenes, and especially you, our listeners. If this episode gave you a new way to think about innovation and competition, share it with someone building the future. Subscribe, leave a review, and explore the complete archive at unnaturalselection.net. Until season three, keep evolving.
