Did The Lean Startup Cause a Fat Problem?

Do we dare even to ask that question?

EDIT: For any new readers, this was a free flow writing exercise. After reading, I’ve realized it may seem a bit confusing as I jump between views for a startup while also discussing from the view of a community that helps them. And it causes some contradictory points. Interestingly enough, what a startup needs to succeed and what a startup community needs to succeed is oftentimes very contradictory. I will come back to clean up this writing to make it more clear when I’m talking about one versus the other.

(~16 minute read)
It’s interesting. The concept of lean began to spread across the United States in the late 2000s. On the backend of The Great Recession, the economy was primed and ready for a B12 shot to the arm. A concept borrowed from Japan’s incredibly efficient automobile industry brought the idea to remove any inefficiencies from the production process for how startups work. Optimization. “To build a successful company, you to need to optimize with build, measure, learn.” Or said another way: develop, observe, research. This caught fire with Eric Ries’ writing, with collaborations from the likes of Steve Blank who was at Stanford and Alexander Osterwalder in London. But what would it mean to consider that it has possibly caused a decline in the quality of some of our companies? Is it weird to wonder if one of the most famous management methodologies created throughout history wasn’t as healthy as experts claimed for founders to be successful?

Circling back, Japan’s culture of optimization was essentially squeezing out the last bit of value from their matured economy. Their society had grown to a point of stagnation, which led to a 25+ year recession. Think of this in comparison with using a product life-cycle graph of Introduction, Growth, Maturity, and Decline. Japan’s economy was moving from maturity to declining and a business concept was taken from that culture.

Learn, the step in the lean process along with Ideas are the last items on the list; but they are much more effective being the first. We’ve allowed the concept of optimizing for time, to outweigh the benefits of growth. What if the management manifesto that influenced thousands of companies the past two decades has led to startup companies being less innovative?

But for startups to succeed, it’s not about optimizing. Optimizing for time is helpful, yes, but optimizing for time and the product so early could actually be counterintuitive of what a company needs. Using the product life-cycle graph analogy again, you would need to move from the Maturity > Declining phase and instead go from the Introduction > Growth phase. Think of symmetry. If you do that, then steps taken need to be done in reverse order. For startups, the inverse of what is taught with lean is actually more true: learn, measure, build. Or: Research, observe, develop. Is this why most high-growth companies have historically been next to research universities?

As odd as it sounds, if you optimize for build, measure, learn - you actually increase the likelihood of failure. More people that just start building more products fail. Whereas, the likes of Ash Maurya has taken the concepts in a much more meaningful direction. Which is the whole, “the problem has always existed”. And before we build anything, let’s truly understand the problem, behaviors, and a triggering event to cause for change.

There were “smartphones” before the iPhone. Steve Jobs just happened to see a nomadic communication device needed to solve additional similar problems that the other smart phones hadn’t considered. There were online social networks before Facebook, Zuck just timed the values of an exclusive social network. I could list other examples, but you get the point. The more you invest into knowledge gaps that align with the values of a growing society, the more likely you create a product that will succeed. While easy to fail with building, it’s much more difficult to fail at relentless inquiry. One you eventually run out of things, the other is potentially boundless.

So what I’m trying to say is lean as a whole concept can be flawed for startups. It is optimizing for time. Startups need to optimize for success, which is inefficient by nature. But that’s innovation: solving the same problem, just figuring out how to do it in a better way that aligns with society’s values now and into the future.

It seems pretty straightforward and harmless. “Build. Measure. Learn.” For someone to start something they have to begin by doing something. As subtle as it may seem (and acknowledging pillars of the framework have had revolutionary beneficial outcomes, such as Innovation Accounting), beginning with a minimum viable product (MVP) isn’t where most of the emergence of successful businesses begin. Unfortunately, that can easily all too often be the main takeaway from those who learn and adopt these principles. “I just thought of an idea, I need to hurry and build a product.”

Having principles where the major concept to start is with a product, unfortunately can have unintended consequences for founders and leaders who miss the importance of understanding a customer and their behavior. The most valuable thing to begin with is by first learning deeply about the triggering event of a potential customer who chooses to pay money for something they value more than how that current reality is. Too many startups blow this off, and then end up blowing a lot of time and funding. You don’t always, even most of the time, get the best intentions and motivations by shoving an early product or service in front of someone. At that point, you’re essentially just testing if your marketing and sales strategies are effective. And while customer development quietly got loosely tied into the lean movement, it has often been overlooked by many.

It seems silly to bring up what may be a nuance after so many years. Is it really that big of a deal? Haven’t the founders and companies overall benefitted from these activities? I’m not actually entirely certain. Since the dot-com boom, we’ve seen less and less people become entrepreneurs. Sure, a lot of historical shifts have happened within that time frame with the widespread adoption of smartphones, web2.0, globalization, new funding mechanisms, and geopolitics that could have also played a part in this. I’m not claiming that lean has caused there to be less entrepreneurs. After working with startups for the past decade, my experience has been that most early-stage companies who fail are tallied up as running out of funding, but the core issue has been they didn’t understand the problem and opportunity enough to build the right thing in the first place, or because of that lack of understanding, never have the capability to do so.

On language we use to describe the emergence of startups

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EDIT: This is where I move from talking from the view of startups to the view of communities who help them.
I think there needs to be a similar shift as there was with geocentrism and heliocentrism (more on centrism). We are not the center, the purpose, or even remotely close to the main driving force in our reality. Instead of focusing on how we (the proverbial “we” as in you, me, us) can provide all the answers, we serve founders much more successfully by focusing on shared experiences, and communities who help startups better with that approach.

The Rainforest by Greg Horowitt and Victor Hwang were influencers of Brad Feld’s The Startup Community Way who uses the term "Community" as in place. Both books were an influence to Chris Heivley’s Build the Fort. All of these books describe “ecosystems” (an ecological term) and “complex systems” which have similar themes in that the sum of the individual parts is greater than the individual parts acting alone. But this is only true when the parts are symbiotic. There are many more situations where this is not the case, and we should be open to discussing how to navigate them.

I picture The Rainforest and The Startup Community Way frameworks as paradise. The most healthy and picturesque versions of how people and things work together to help startups launch and grow. But there are a lot of circumstances where it’s not so glamorous, and by putting a framework in place for, “this is how you should be”, it can demotivate, derail, and even destroy opportunities to help startups.

With the book Rainforest using a biome as a metaphor, it doesn’t take into considerations other types of biomes, such as: Temperate Forest, Desert, Tundra, Boreal Forest, Grassland, Savanna, Freshwater, or Marine Ice. Replace the title of the book Rainforest with any other biome, and the descriptions on how to develop a startup ecosystem changes depending on the relevance of their interacting parts. The authors’ experiences are visiting businesses all around the world, so they view startup ecosystems as being highly dense and diverse, which is common in rainforests. So they claim emergence comes from many different things interacting. What about small towns and rural communities who aren’t densely populated, who don’t have all of the “staple” amenities, or don’t even have access to what some would consider the most basic of resources?

Let me be clear. They are describing the attributes of the most successful places they’ve been that drive an innovation economy. Where I think we have to be careful is that the characteristics to be helpful and successful in supporting startups and founders may look completely different at different times, in other places, with disparate circumstances.

Using the term "Community" has two issues. The definition  of Community is, “A group of people living in the same place or having a particular characteristic in common.” Brad mostly focuses on “place”, and his ideas were influenced by population density which is why he says startup communities can only thrive with 150k population or more. But in the definition of Community, if you emphasize the use of the word “characteristics” as the meaning instead of place, new ideas would be needed to make sense of a Startup Community. He claims emergence comes from people who are close by connecting with each other. It also explains why there was such an uproar when Techstars decided to uproot from Boulder.

The words ecosystem and community are now widely used for programs, resources, and groups of people helping startups. Just look at the increase in number of academic articles and papers focused on “Entrepreneurial Ecosystem” or “Startup Ecosystem”. But using this specific terminology could mean completely different things based on who is reading it, where they’re from, and how they define those words themselves.

What they are essentially using, complex systems, is a subset of what is called “systems thinking.” And there are actually different categories of Systems Thinking:

• Closed and Open

• Hierarchal

• Dynamic

• Adaptive

• Cybernetic

• Ecological

The frameworks (from those shared for startup communities to society at-large), and measurement models such as factors and actors, are designed with different Systems in mind. This is why we hear things such as oftentimes flat organizations like startups have trouble working with hierarchal institutions such as governments. But I’d like to strip it down further where nothing can be implied; where what remains is that within Systems Thinking, it is a subset of… well, Thinking. And we have different types of Thinking that provide perspectives on understanding our reality:

• Reductive

• Critical

• Divergent

• Holistic

• Analytical

• Intuitive

• Metacognition

Complex Systems fits nicely under Holistic Thinking. And it seems rational, right? If we can see the broader picture and try to understand the interconnectedness of the subsets of something then we feel like we can better truly understand it. Economics brings in Reductive, Critical, and Analytical Thinking into the picture when we begin to measure for the purpose of analyzing identification, understanding, predictions, and making decisions from the data.

Here is the thing though. The #1 cause of the biggest breakthroughs with humanity have come from Divergent and Intuitive Thinking; which focuses on creativity and instinct. But those things are incredibly, if not impossibly hard, to both put an absolute definition on as well as measure and analyze. These things are significant pieces to the puzzle when it comes to understanding how startups and the programs, resources, and people who come together to help them are created, grow, and thrive. Emergence is a very difficult thing to nail down as the further you question, it moves from logic and reasoning to philosophical.

I’m not completely dismissing the work of Eric Ries and Brad Feld, who are giants of our industry. But conjecture is necessary for progress.

On measurements

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With Steve Blank’s thoughts that, “startups are not just smaller versions of large companies” and Brad’s thoughts on, “startup communities needing to be understood within society and the innovation and entrepreneurial ecosystems”, my argument is that small towns and rural communities are not just smaller versions of large metropolitans—they may need different forms of economic models—and my lasting point is the hope that we don’t leave out some of the most critical pieces to understanding.

Economics, a social science, often measures progress by examining human behavior and decision-making. Given the inherent volatility of human nature, efforts to analyze the emergence of startup activity have frequently been hampered by anthropomorphic biases. Throughout history—from pre-history to the agricultural revolution and the Enlightenment—humans have strived to explain the world around them. In this quest, three types of truths have emerged: objective, political, and personal.

A wealth of data, measurements, analytics, and narratives stems from these truths. However, when we employ anthropomorphic descriptors, we often rely on personal experiences to draw analogies about startups and their potential for growth. This approach is influenced by our contemporary worldview, shaped by the rapid rise of technology and innovation in our lifetime. Can we find better continuity?

With globalization, the rise of the internet, automation, covid, and the current views that higher education does not guarantee a job—all have contributed to people less likely in the future to move to urban areas or more likely to move back to someplace that they have a connection with: family, friends, school, sports, climate, culture, etc etc. Moving forward, emergence of tech companies more and more will not be bottlenecked to Silicon Valley or metro areas. The cause of emergence for entrepreneurship in these places is and will be quite different.

We need a new economic framework for describing how and to solve for the problems to increase the number of startup companies that generate wealth in small towns and rural communities. If we don’t solve for that, we will continue to see a decline in entrepreneurship. If we continue to see a decline in entrepreneurship, our country as a whole will need to continue to rely on imports for our basic needs. The velocity of our growth will stagger.

If you think about it, capitalism is driven by where the velocity of money is the highest. You have to remove transactional costs to keep velocity high. There was the gold rush in the 1880s and we pegged the US dollar to it because society trusted that is where progress was, until Nixon. Then the government began to back education which gave people more knowledge. So universities and lawyers saw big booms in the coming years. Then the dollar was pegged to the petrodollar, and eventually just backed by the Federal Reserve. All of these things are where people initially put most of their trust in. WW2 fought the ideology of eugenics, then we had a civil rights movement. You see religion spikes after each war we enter in other countries with radical religious beliefs because there is a lag effect. It's because it brings back or shakes the beliefs of their cultures to ours. So if dollars go to war with certain cultures, we can expect society’s volatility will shift to that in the coming years and they will enhance or disrupt existing institutions. 

Since most politicians are lawyers, the majority of money goes to protecting the laws of the government so that society has trust in it. This means we’re more likely to sue people than to just trust each other. It increases transactional costs. Regulation is focused on things that harm ourselves or harm the greater good, and businesses rise and fall with those willing to prosecute people for breaking such laws when the total return on investment for those lawsuits is likely to be larger than the investment to support its place in society.

The boom of Silicon Valley and tech was because people trusted each other. Once you lose trust, investment dries up. So to see infinite progress, it would be much better if we latched on to language, measurements, and values that aren't so close to human experience because those laws are more objectively true. Which should increase the velocity of money into successful startups.

So what does this all mean?

While the Enlightenment and scientific advancements have paved new paths for humanity, relying solely on empirical evidence can sometimes limit our understanding of what a more truthful and possible future might hold. It's akin to focusing on the wind from a small fan in front of you while ignoring the tornado surrounding you—your assumptions are more likely to be false if you don't broaden your perspective.

During the Enlightenment, we began to believe that the laws of nature could be applied to humans or that similar laws governed human behavior. Similarly, recent research on startup ecosystems has been anthropomorphic. The places where founders are more likely to launch and scale high-growth tech companies haven’t been planned—at least not until recently. This situation is analogous to the debate between organic foods and GMOs. Both have their pros and cons, and instead of arguing over these principles, we should simply acknowledge them.

With the recent massive influx of state and federal dollars supporting startup ecosystems, some programs, resources, people, and places may seem artificial or even "taste like plastic." This debate could become as subjective as choosing between soccer or football, chess or painting. As David Deutsch writes in “The Beginning of Infinity”, we don't need to explain where bubbles form in boiling water. Instead, we need to recognize what constitutes a good explanation and what is worth explaining.

As David Deutsch has critiqued different methods of providing explanations—such as reductionism and empiricism—we should be mindful of these limitations as we explore the best ways to support startups, founders, and the ecosystems that nurture them. We've often allowed ecological principles to "govern" startup ecosystems, but we must carefully select which principles we use to measure outputs and outcomes. Using inappropriate models can yield unhelpful data.

In “The Evolution of Everything”, Matt Ridley argues that humans mistakenly perceive top-down processes when dynamics are actually driven by bottom-up effects. He highlights how the Human Genome Project revealed, much to scientists' frustration, that most of our DNA serves no apparent purpose beyond simply existing.

The central point here is this: Are we measuring the things that matter?

As we continue to support and develop startup ecosystems, we must ensure that our metrics and models reflect the true drivers of success and innovation. This means recognizing the bottom-up effects that often drive these ecosystems and being cautious of over-reliance on top-down, empirical approaches that may not capture the full picture.

We’ve seen a decline in entrepreneurship across our nation for the past two decades, especially in small towns and rural communities. Coincidentally, at that time, our major institutions from within higher education to being incorporated throughout the entire federal government, industries were sensationally adopting a new framework for educating and training people to become entrepreneurs. While living and working to solve that problem for the past decade, I’ve asked what has been the cause of these continued declines in numbers and quality. I’ll share more on this topic and specific examples from a decade of experience working in the tech and startup-based economy. So hopefully you will stick around as we share questions that normally we would never even consider.

How should we question rural?