How to spot a scalable startup and why I got it wrong in the past

There is a lie that permeates the startup industry. And venture capital especially.

The lie is this: startups are binary outcomes. They either become big or die trying.

After having logged my first decade as a VC, I know it’s not true. On the contrary, most startups become small businesses. They simply fail to scale.

This is an important fact. Because studying these non-scaling companies offers valuable lessons about the true nature of scalability.

What scalability is not

Economists teach us that scalability is about low marginal costs. Meaning it is cheap to serve an additional customer. In this view, services are never scalable because the cost of servicing one more customer isn’t falling.

In contrast, production can be scalable because a machine can produce one more widget cheaply. And SaaS is very scalable because letting one more customer access the software costs next to nothing.

The theory of low marginal costs makes investors love SaaS companies. And for good reason. There is just one problem. Most SaaS companies never scale.

Clearly, low marginal costs do not define scalability.

What Scalability is

After a decade of investing, I have come to understand scalability somewhat differently.

In venture capital, scalability is defined by a time constraint. Funds must exit the companies with 7-9 years. This means scalability is more about the speed of growth than marginal costs. Put differently, a scalable company is one that can grow fast. To this end, marginal costs matter very little because marginal costs define profitability, and not speed.

Growth can come from two sources. Beta and Alpha. Beta defines the growth rate of the market. Alpha defines how fast the company can grow (relative to its competitors) in the market.

The strength of Beta and Alpha can vary. As an example, the SUV market has long enjoyed moderate Beta. The SUV market grows more than other car categories. But it is a far cry from the strong Beta the electric car market enjoys.

Extreme Beta also exists. It happens when a market is “unlocked” and all the new actors rush to the marketplace at once. Like it happened for Airbnb when they “unlocked” a global latent market of private hotels. Or Uber did with ridesharing.

Strong Alpha occurs when the product enjoys a reinforcing value loop, and the loop spins faster than the competitor’s loop. A reinforcing value loop is one where the product becomes more valuable when the company wins more customers, which in turn makes the product more valuable, which will attract more customers, and so on. This self-reinforcing nature of such a dynamic means that the company will quickly become dominant in its market.

A company like Templafy (Accelerace alumni 2014) enjoys such s value loop. Each new customer creates new templates than can be added to the product for the next customer. This means Templafy has strong Alpha.

A perhaps even stronger example of Alpha is a company like Trustpilot (Accelerace alumni 2009). For Trustpilot, new users create reviews, that make the site more valuable to other users, who will create even more reviews that in turn increases the value of their product offering to the businesses who are reviewed. The businesses start using Trustpilot ratings in their marketing, which makes new users aware of Trustpilot, who then create more reviews. And so, the reinforcing value loop accelerates.

And as you will see, these forces greatly influence scalability.

What Scalability looks like

In our first fund (vintage 2011) with 49 investments, I have witnessed cohorts of very similar companies start around the same time. But over the ensuing years, they experienced unbelievable different trajectories.

A few have become bigger than even the founders imagined. And many never scaled, but still lives. For years the reason for this difference eluded me. Because it wasn’t marginal costs, market size, team, IP nor competition. In fact, one company is by far the strongest in all these parameters. But it still failed to scale.

In 2012 we invested in a SaaS company in a vertical with very little competition. We will call it WorkWeek (not the real name). The founders have industry insight. The product is great. The customers love it. The market is worth billions. The CLV is very high because customers never churn. The board is among the strongest I have seen.

We did the seed round, and the company projected to reach 10M ARR within three years. Today, eight years later they are at 3M ARR.

The problem is that WorkWeek enjoys no Beta. The market is stagnant. There are hundreds of thousands of customers in their vertical. But if the market is not growing, no new customers are appearing without a solution to their problems. Consequently, their Beta is zero.

In addition, WorkWeek enjoys no Alpha. There is no reinforcing value loop within their business. The product does not become more valuable to the next customers, regardless of how many customers they have.

The founder team estimated they would have “conquered” Germany within two years. It would take them five years to get the first German customer.

The problem was that the customers in Denmark didn’t make the product any better for the German prospects. On the contrary, each new sale gets harder because all the “low hanging fruits” have been sold to. What remains are customers who are hard to convince to change their ways.

WorkWeek is what you get when both Beta and Alpha are absent, but everything else is great. The company grows 50% per year and have done so since inception. Such growth rate means that if a company has 50.000 EUR in revenue year one, they will have less than 1 million EUR in year seven.

In contrast, Trustpilot and Templafy are what you get when strong Beta and strong Alpha are present simultaneously. Trustpilot rose during rapid growth in e-commerce which gave them strong Beta. And their Alpha is simply unique. Templafy enjoys strong Beta from the seismic shift to cloud-based office programs, and the user-generated templates create strong Alpha.

Today, I understand that to be truly “scalable”, companies must enjoy both Beta and Alpha simultaneously.

If both factors are in place, the growth from each source will compound, creating the famed hockey stick as a result. Witnessing a hockey stick unfold in real-time is quite remarkable. But low marginal costs and big markets are not enough if you want to see it for yourself.

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The Startup Adoption Lifecycle

This article tells the story of how farmers in Iowa shaped the way startup founders think. Furthermore, it argues that we need a new way for startups to identify their early customer segments. In the end, founders will know how to obtain product-market fit, and why the article features a picture of an airline crew on heavy cases.

In 1927, scientists developed a new hybrid seed-corn. They knew their invention would give farmers 20% more yield. What they didn’t know was that the seed-corn would define how we came to understand innovation.

The new corn was offered to farmers in Iowa. Oddly, not everyone adopted it. The situation caught the attention of two sociologists at Iowa State University.

In 1941, the two researchers Bryce Ryan and Neal Gross went to interview the farmers. What they learned was puzzling.

Even though the new hybrid corn was objectively better, some farmers simply resisted using it. In fact, it would take about 10 years for all the farmers to adopt the new corn. And that was just Iowa. It then took another decade before it was fully adopted throughout the US.

Bryce Ryan and Neal Gross concluded that some people are just prone to try new things before others. Today, we know their theory as the Technology Adoption Lifecycle. For close to a century, the theory has defined how we understand the adoption of innovation.

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Why the Technology adoption lifecycle is important and useless

The Technology Adoption Lifecycle basically explains that in the beginning, only a small group of people adopt a new product. Later, the majority follows suit. Finally, the last little group of resisting people gives in.

As trivial as it sounds, it was an immensely important realization. Because it provides a frame for innovators to view the world. I know this first-hand.

When I started my first startup in 2006, I was graduating from business school. And like any graduate, I knew the Technology Adoption Lifecycle. It helped me formulate our go-to-market strategy. First, we would go for the innovators and early adopters. Sounds right on paper.

But most startup founders learn that understanding who those innovators and early adopters are is much harder. In fact, the framework does not provide any guidance for this problem. At all.

The thing is that the Technology Adoption Lifecycle was never meant to help tech entrepreneurs. It was a retrospective view of a category over its entire lifecycle. That means it spans decades and each block of adopters represents years of slow gradual adoption. Although important, it is useless as a practical startup tool.

In reality, most startups face less than 12 months of quickly evaporating runway. And the next months are the only period of any importance because it’s all the time a startup is sure to have.

Unfortunately, the Technology Adoption Lifecycle is of little help. The model just says: innovators and early adopters. Whoever adopts the technology first, are the innovators and early adopters. That is called circular logic.

600 startups later a pattern emerges

Today, I am a partner at two accelerator-funds. And for the past seven years, I have met about a hundred startups per year, helping them obtain product-market fit. Or at least tried.

One consequence of specialization is a very granular understanding of a narrow field. In my case, I suspect my expertise has become the early phases of the Technology Adoption Lifecycle.

Having observed so many startups go from zero to their first hundred business customers (or first million users), I have witnessed a clear pattern.

The startup adoption lifecycle

All successful startups I have worked with have experienced adoption through the same sequence of micro-segments within the very first part of the adoption lifecycle. Let’s shrink into the micro-cosmos of the very first adopters. What I call the Startup Adoption Lifecycle. Here we go:

The first adopters are always friends, family, and colleagues. They sign up to support the founder(s) and cheer on. They rarely have a deep need for the product. This group constitutes the first 10 to 50 customers.

The second adopter group is always the “crazy” people. They don’t know the founder(s) personally, but for some reason, they are obsessed about the area the startup operates in. And I mean abnormally obsessed. This group often send something that looks like fan mail to the info@ or support@. This group varies in size but is probably the next 5 – 30 customers.

The third adopter group is by far the most important. This group is called the Beachhead. This group is also abnormal, but for a different reason. They are not “crazy”. Instead, they live under unique circumstances that impose extreme or unusual needs. Because this group is small, none has cared to serve their special needs. Consequently, they are somewhat “desperate” which makes them actively look for new solutions.

Examples were the first hardcore gamers on a live streaming website called Justin.tv. The founders realized the potential of this Beachhead and renamed Justin.tv to Twitch.

Another would be airline cabin crew. Few people fly every day, so why bother making wheeled suitcases for cabin crew who do. In 1987 someone finally did. Of course, cabin crew was the first adopters. Today we all have trolleys. (The crew members in the featured picture clearly needed them).

A third example would be victims of the Japanese tsunami in 2011 that starting using a chat app to communicate because the cell phone towers were gone. Today, that chat app has an estimated 500 million users and is known by the name Line.

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In truth, all successful startups eventually must find their Beachhead. It is the most important adopter group because they are the first people who adopt because of a true need. Their need might be unique, but that makes them willing to test a new product from an unknown startup.

Who is the Beachhead for any particular startup? It is the group that most founders overlook because it is far too small to fit the story of the billion-dollar market. It is the group that has an unusual job. Or live an unusual place. Or have an unusual interest. Or have been affected by an unusual event. Or perhaps a combination.

The Beachhead varies in size, but it is rarely bigger than 100 – 500 customers to begin with. Luckily, that is often the perfect size for a startup with an evaporating runway.

If startups can navigate the Startup Adoption Lifecycle, they will be well on their way. Because on the other side of the Beachhead is product-market fit. And with that, the beginning of twenty years of movement through the Technology Adoption Lifecycle. May your journey be smooth.

Tip: If you are a startup founder and want to get help finding your Beach Head, a qualify acceleration program might the right thing for you. At Accelerace and Overkill Ventures, we see this as our main job. Some other accelerators might do as well. At least check out my blog.

What porn and ridesharing can teach corporates, investors and startups

Most investors and corporates estimate the potential of a new technology. It’s a mistake. Real disruption comes from the convergence of different technologies. This post will explain how technology convergence creates parallel industries and Startup Tsunamis. Most importantly, it will tell the story of a young stripteasing college student that took down a billion-dollar empire.

In 1953, a 27-year-old entrepreneur raised angel investment from 45 investors. With the money, he pioneered one of the world’s biggest industries and built a true empire. Today, his product is an iconic piece of western culture.

The name of the entrepreneur was Hugh Marston Hefner. His product was a new type of magazine. He called it Playboy.

The world was changing its view on sexuality, and pornography was taking off. It became a billion-dollar industry with companies raking in huge profits.

The pornography studios appropriated most of the profit because they controlled the means of production. Print machines, studio light, cameras and retail distribution were expensive.

At the height of its glory, the industry launched its own award show rivaling the Oscars in glamour. And then one day, in late 1990’s, it was all over.

A young college student had set up a camera in her dorm room. She connected the camera to her computer and created a website she called JenniCam. She started broadcasting for the world to follow. She quickly learned that viewers increased when she did stripteases.

A few years later, Playboy delisted from the stock market. Its stock was plummeting.

JenniCam started a webcam revolution. Today, there are thousands of cam models. They connect directly with viewers thanks to cheap cameras, fast internet connection, chat and digital payment.

The webcam revolution is one of the clearest examples of disruption caused by the convergence of technological innovations. The old companies were built on an infrastructure of professional grade equipment, film studios, and physical distribution.

In contrast, the webcam industry is built on the availability of cheap consumer grade equipment, online distribution, and new communication and payment protocols.

What the pornography studios experienced is the phenomena of parallel industries. Few people understand it. You are about to become one of them.

The difference between competition and parallel industries

The runaway success of Playboy attracted many competitors. Among the biggest was Penthouse. The magazines competed on celebrity pictures and naughtiness. With the emergence of DVDs, the studios competed on distribution and licensing agreements.

But when JenniCam launched, few took notice. To the established players JenniCam wasn’t a competition, let alone a threat. Its young founder didn’t try to muscle them out of licensing deals. She didn’t invest in new studios or steal their models. In fact, she was utterly invisible to them.

The thing is that when certain technologic innovations converge, it creates entirely new industrial platforms. The startups that emerge on the new platform are not competing with the incumbents. Instead, they are building a parallel industry.

A parallel industry is an industry that has been rebuilt from the ground up on a new industrial platform. The new platform provides an infrastructure that is magnitudes faster, cheaper and more effective than the traditional industrial platform.

The new platform enables entrepreneurs to reimagine all components of their business model and apply new technology in every layer of its business. As a result, the startups that emerge are so different from the incumbents, that they go unnoticed by the old industry.

The next thing that happens is that the parallel industry matures. It develops its own suppliers, consultants, and networks. Suddenly, JenniCam had sparked an entire industry of innovative producers of webcam technology, video compression providers, and digital payment solutions.

At this point, the incumbents take notice. But it’s too late.

How parallel industries cause Startup Tsunamis

Parallel industries are supported by underlying technologies that serve as the infrastructure of the industry. Like: production technology, distribution technology, communication technology and financial technology.

When innovations in the different underlying technologies converge, a new industrial platform is born. That happened during the industrial revolution when factories (production), railroads (distribution), the telegraph (communication) and Wall Street (finance) converged and gave us a tsunami of new products.

Startup Tsunamis describe the phenomena of very large number of startups launched within a concentrated timespan, attempting similar business models. One of the latest examples of this is ride sharing.

Much like the pornography studios, taxi companies had enjoyed decades of steady business. But around 2010, a new industrial platform was emerging.

The smartphone converged with advances in payment infrastructure. At the same time, venture capital was reemerging as a source of capital for startups after being decimated by the global financial crisis.

The result was a true Startup Tsunami. Here are just some of the few startups that built their business on the new industrial platform: Uber (2009), Ola (2010), Wingz (2011), Sidecar (2011), Hailo (2011), Grab (2011), Lyft (2012), Didi Chuxing (2012), Careem (2012).

Today, few people doubt that ridesharing will change personal urban transportation for good. When electrified self-driving cars join the convergence to enhance the new industrial platform, taxi companies are history. But the story doesn’t end here.

Blockchains are creating new financial infrastructure. IoT is creating new communication infrastructure. 3D printing is creating new production infrastructure. Individually they might seem like toys. But so did webcams until they converged with high-speed internet, chat and digital payment. The cocktail enabled a young college student to initiate the fall of an empire.

At Accelerace we help both startups and corporates. Check us out at Accelerace.io.

Thank you to Jeremy Rifkin and his great book, The Third Industrial Revolution, to inspire me to write this post. I can recommend his book.

Why all startup founders should understand ICOs

Most people have heard about cryptocurrencies. Some have heard about ICOs. Few actually understand them. This post will tell you why ICOs are important news for startup founders. It will tell you how it all began and why the crowd is the best investor. In the process, you will learn about a prodigy of our time and see what communist regimes did wrong. In the end, founders have gotten a new tool for fund raising. Use it.

In 1997, a new era began.

For the first time ever, a rock band asked their fans to fund their upcoming tour. The fans went online and pledged $60,000. The press called it crowdfunding.

A decade later, crowdfunding would fund everything from paintings to high tech gadgets. In 2012, a dock for iPhones became the first project to raise more than $1 million on Kickstarter. Still, the biggest breakthrough was yet to come.

Crowdfunding mainly benefitted physical products. This makes sense because physical products have tangible value. In comparison, software hadn’t benefitted much. It was simply too hard to define what backers were pre-paying for. But that was about to change.

In 2013, a Russian prodigy named Vitalik Buterin made history. He designed a completely new Blockchain named Ethereum. It would prove to become a breakthrough in crowdfunding. Vitalik was 19 years old.

Ethereum made it easy for developers to create new cryptocoins. And that is immensely important because cryptocoins solves the biggest problem about crowdfunding software.

Cryptocoins allows software projects to provide a tangible asset to backers. The projects can mint digital coins that represent a specific value. A simple example would be a coin that can buy a song in a music app. Anyone wanting a song could buy the coin. If enough people buy the coins, the founders have enough money to build the app. That’s called crowdfunding.

But that’s not all. If the backer no longer wants the coin, he can sell the coin someone else with a click of a button.

Already ICOs have outpaced VC funding. And it is just getting started. I am about to tell you why.

The key to successful investing

Investing is fundamentally about information. The information investors need is this: How big will the demand be?

If you can assess how many people will use a new product, you also know how much to invest in the project.

How accurate you can assess the demand depends on how close the investor is to the demand. In other words, to the users.

The communist experiments of the 1950s show the consequence of making investment decisions too far from the demand. At the time, Moscow and Beijing decided how much food farmers should grow. But the communist elite had little feel for the true need. Economists call it: misallocation of resources. The consequences were catastrophic.

VCs exist because they have better feel for the demand for tech products than the big pension funds. In theory, VCs have superior information and can make better investment decisions.

However, there is a group with an even better feel for the demand. And that’s the users. They are the ultimate source of information because they are the demand side.

Why ICOs are great news for founders

Crowdfunding allows users to vote for products they want with their money. In aggregate, users are the ultimate investor and allocator of resources. If 100 backers need a product, the project receives exactly the right amount of funding to fulfill the demand.

For many software startups, the invention of cryptocoins is heaven sent. Most founders spent an enormous amount of time and effort to convince VCs that they have a market. Sometimes they succeed, but the investor takes a risk premium. The risk premium is unfair terms. Like milestones, liquidity preferences and downside protection.

But thanks to a young Russian prodigy, software startups can do what artists and gadget-makers have been doing for the past five years. To raise funding directly from users. And because users don’t have to guess the demand, they also don’t require risk premiums. The money comes without a nasty set of legal documents and a rigid due diligence.

Luckily, many have already taken advantage. As of this writing, software projects have raised more than $1 billion through ICOs. And many more will follow.

Many critics will point to fraudulent and overhyped projects. All of that is true. But that always happens in the early days of great innovations.

In time, ICOs will mature and software founders will finally have an alternative to the exhausting VC pitches.

At Accelerace, we will do our best to help founders take advantage.

Check out Accelerace. We invest in tech startups.

Why the best founders feel unsuccessful

Many startups look successful, but this post will tell you how most founder really feel. It will tell you how humans are different from other animals, and why this difference distinguishes the best founders from normal people. Most importantly, it will explain what good crazy is. Good crazy is power. Cherish it.

One day in 1982, a group of researchers at Georgia State University experienced something unexpected. A two-year-old chimpanzee by the name Kanzi suddenly started talking.

Kanzi wasn’t being studied. Instead, the researchers had been trying to teach another chimpanzee to communicate via a pad. But they had failed. The chimpanzee had nothing to say.

The experiment was suggesting that apes don’t think. That conclusion would have ended the long-standing dispute: Do animals possess human-like thinking?

When Kanzi accidently picked up the pad and started communicating, we got an answer to the question. But the answer was not: yes or no. It was both.

The difference between humans and animals

The interesting part wasn’t the fact that Kanzi communicated. It was what Kanzi said.

It turned out that Kanzi mostly expressed fundamental needs. Like, give me food.

Kanzi was clearly thinking. However, Kanzi never expressed ideas. And that fact is immensely important for understanding humans.

Human cognition is unique because we are the only animal who have ideas. Only humans imagine things that don’t exists in the physical world. Like God or Harry Potter.

We can describe these ideas and infect other people. When many people have the same idea, it becomes a shared idea.

Shared ideas might be the most powerful phenomenon in the world. Shared ideas power Christianity, capitalism, and the $700 billion market cap of Apple.

A shared idea is immensely powerful because of its intersubjective nature. It exists among people and not just within people. This means that even though you abandon the idea, it still exists and governs everyone else infected by that idea.

Shared ideas create communities of people. Like the urban consumers, Harry Potter fans and the Apple evangelists.

Members of communities want success in their community. Urban consumers want to own and experience more things. Harry Potter fans want more people to read their fan fiction. Apple evangelists want to be first to get the latest upgrades.

Success in communities is defined by ideals. All communities have an ideal that shapes the hierarchy within the community. Ideals describe what a perfect manifestation of the idea would look like.

The perfect consumer eats sushi, owns designer furniture and weekend travel. The perfect christian is virtuous, attends church and lives in a nuclear family. The perfect Harry Potter fan writes fan fiction, plays quidditch and can dress up like a Gryffindor.

The closer you fit the ideal, the more successful other people in your community perceive you to be. The community upgrade your position in the hierarchy. Ascension feels good.

For this reason, most people spend their entire life attempting to fit the ideal of their community. But as you will learn, startup founders are different.

The difference between startup founders and normal people

For most people in developed countries, the biggest community is the idea of the urban consumer. And this fact can course great misery for startup founders.

The problem is that startups require founders to do things that break with the ideal of urban consumer.

Most founders in our portfolio are in their 30s. And for urban consumer, these are the years when the adult hierarchy sets in. The ideal is to buy the first house or apartment in a respectable neighborhood. Fill it with designer furniture. Drive an Audi and go skiing in winter. Kids in designer clothes, cooking gourmet food and keeping a dog give further plusses.

But for founders who choose the path of startups, life is very different. Most startups fail and all startups struggle. Founders usually scramble for two years before raising their first round of institutional capital. Even after raising funding, they still get very little salary.

The financial reality of most founders means that they actually descend on the hierarchy of urban consumers. They live on half the space, drive an embarrassing car and rarely fine dine.

Most founders occasionally feel the sting of inferiority and doubt. It happens when they meet old classmates, park their decade old Hyundai or check their Facebook feed.

To most people, this scenario is so scary that they give up their startup dream. They think it’s too risky. The risk is descending the social hierarchy. It doesn’t mean dying.

But this is where founders are different. They feel the sting, but they don’t succumb to the pressure of the ideal. Instead, the best founders we see have overwritten the ideal by the force of their startup vision.

To reject a pervasive intersubjective ideal is incredibly hard to do. And those who do are often regarded crazy. But at Accelerace, we call it being good crazy.

Conclusions made:

  • Only humans share ideas.
  • Shared ideas create communities.
  • Communities have hierarchy defined by an ideal.
  • In the developed countries, one of the biggest ideas is the urban consumer.
  • Startup founders often descend on the hierarchy of urban consumer communities.
  • Startup founders are special because they don’t succumb to the pressure of the ideal.
  • At Accelerace, we call it being good crazy.

Also visit Accelerace. We invest in startups.

The insane arrogance of startup investors

Most startup investors feel special. This post will tell you they are not. It will tell you that most investors evaluate startups using simple arrogance. In the process you will meet two groups of super humans, learn about one of the longest wars in history and get inside NASA. In the end startups will understand investors better. Hopefully investors will get inspiration on how to refine their selection. Improving is everything. Do it.

The world was at a war. And the president of the free world was losing it. But he was working on a secret project that would turn the tide. He called it Project Mercury.

He asked the military to find seven super humans. They should spearhead a new battle front. The elite group was found and became known as: The Original Seven.

The year was 1959, the president was Dwight D. Eisenhower and the new battle front was space. The Original Seven was the first team of NASA astronauts.

Since the Original Seven, NASA has graduated a total of 338 astronauts. However, this is a tiny amount compared to the large number of applicants. For 2017, NASA has received 18,300 candidate applications.

The thing is that only few people make world class astronauts. But you are about to learn something else. Even fewer people make world class startup founders.

The hunt for super human entrepreneurs

About the same time as Eisenhower was fighting the cold war in space. A man named Arthur Rock was fighting an equally important battle.

His battle field was Silicon Valley. The fight was over one of the most important inventions in history. The transistor.

Arthur Rock was gathering his own team of super humans. They became known as The Traitorous Eight.

The Traitorous Eight became the founding team at one of the most influential companies ever built. Fairchild Semiconductor. Together, they ignited the modern technology age and helped make Silicon Valley the world’s superpower of innovation hubs.

Like NASA, Arthur Rock continued to find more amazing people. When he did, he would fund their businesses. In the process he invented what we today know as venture capital.

Today venture capital is a global industry. There are thousands firms. Lately, accelerators and angels have joined the party. And they are all looking for the same rare teams of super humans.

But they are a rare breed indeed. It’s estimated that 150 million startups are attempted every year by 300 million people. The number of startups that gets venture funding is limited to couple of thousands. And out of those, only a fraction actually succeeds. Suddenly, becoming an astronaut looks easy peasy.

Overserving and understanding what to look for

Going with the numbers, identifying the outliars among startup teams is much harder than identifying the outliars among astronaut candidates. But that’s not reflected in the selection process.

NASA spends two years in rigorous and intense interaction with candidates before selecting who to send into space.

Comparably, many startup investors just spend a few hours in meetings with the startups before throwing a term sheet. The following due diligence process is mostly legal work. To outsiders this seems insane. And it is.

The problem is that investors are incredibly arrogant. Most of us believe we have developed a special gift. That our unique backgrounds enable us to spot winners on eye sight. Like Mike Markkula meeting Jobs and Wozniak in a garage and just knowing they will become a huge success. Obviously, it’s a delusion.

This delusion fools investors into believing that we just need a pitch. Then our gut will accurately predict the fate of the startup. But the facts disagree.

95% of all venture returns comes from only 20% of the firms. Most investors cannot pick the winners. Of course not. No space agency would ever pick astronauts from pitches and coffee meetings. Sure, they would develop a gut feel about the candidate, but they wouldn’t be arrogant enough to actually follow their intuition.

Instead, space agencies acknowledge that some of the skills and traits that make up excellent astronauts cannot be accurately evaluated in applications and during interviews. Only observing candidates under certain conditions will provide an accurate assessment.

Could the same be true for startups. That you actually need to observe the founder team in action to actually assess their chance of success? I suspect so.

In my work with startups I participate in team meetings, participate in customer meetings and listen in on investor pitches. I see how they make decisions, how they solve problems and how they interact. It’s like NASA observing astronaut candidates operate tools in a vacuum tube or docking in a simulator.

This gives me insights that I couldn’t have gotten otherwise. Insights so important that I often find myself correcting my initial gut feel about the startup.

Startups are built in real life. During prioritization meetings, customer meetings, cold calls and strategic pivots. Participating in real work with the founders provide a true picture of the startup.

At Accelerace we have institutionalized this in our selection and acceleration process. Our application form is minimal. We engage instead. We take in a bigger batch than we graduate. We work closely with the founder team. We reasses and challenge our inituition..

We know what we are looking for and we assign scores. It might not be the right parameters, but we are on our way of proving them. Most importantly, it reminds us to leave (most) arrogance behind.

(The scoreboard used under observation is developed together with my great colleagues at Accelerace. If you think you can help us refine it or make use of it, contact us)

Conclusions made:

  • World class startup founders are rarer than astronauts
  • Most startup investors believe they have a special gift because of their unique background
  • The delusion of a special gift makes investors do extremely shallow assessments of startups
  • Investor can learn from NASA and do more real life observation
  • Accelerace have institutionalized observation and have developed a specific scoreboard

 

The essential questions founders should ask investors

Most founders do investor meetings like a job interview. They look their best and hope to be picked. Most founders know it’s a mistake but don’t know what else to do. This post will teach you to turn the table and interview the investor. It will provide you with a set of essential questions to ask. The answers are more important than you can imagine. Use them.  

I made a huge mistake. And I want you to learn from it.

When I was a founder, I thought VC money was the same.

Because of this delusion, I didn’t care who the investor was. So I approached all investors in the same way.

I showed off and hoped the VC would throw a term sheet. It was a show on my part. I thought I did good. I was mistaken.

In fact, I did terrible. My pitch was good. But I forgot the most important part of the meeting. To learn who I was talking to.

Why does it matter? Because the VC demands your time and attention. And that’s your most valuable asset.

You want the time and attention he demands to be beneficial for you. And that’s a function of three things:

1) The experience of the firm 2) his personal experience 3) his view of your startup.

I didn’t know. So I didn’t ask. You shouldn’t make the same mistake. So here is a list of questions I wish someone had given me:

Essential questions about his firm

  • How many funds have you managed?
    • Because experience is important. First funds tend to give bad returns.
  • Who are the Limited Partners of the fund?
    • Because in the end, the investor serves the interests of the Limited Partners.
  • How big is the fund?
    • Because fund size determines how little and how much they can invest. And how much follow-up funding they can provide in the future.
  • When did the active investment period start and when does it end?
    • Because the lifespan of the fund determines the urgency to invest and to exit again.
  • How is the management of the fund structured and how do you make decisions
    • Because it matters greatly how decisions are being made and who have decision power.
  • What is your investment thesis?
    • Because a clear thesis is an indicator of professional intellect. In other words, they know what they are doing.
  • What are the limitations of your investments?
    • Because it’s nice to know if the investment can be turned down because of technicalities.
  • Which companies in the portfolio have given you learnings and expertise to help us?
    • Because expertise matters. And real expertise comes from experience.
  • How do you do due diligence?
    • Because due diligence can be very long and costly. And you will pay.

 

Essential questions about the investment manager (the one to join your board)

  • What is your thesis about startup success?
    • Because a clear thesis is an indicator of professional intellect.
  • Which other companies in the portfolio are you managing?
    • Because he gets most of his learning and network through his own portfolio.
  • How do you approach the role of being board member?
    • Because you want to know if his style is compatible.
  • How can you add value to our company?
    • Because the answer reveals if he fundamentally sees himself as a controlling mechanism or someone who is there to help build the business.
  • How are you incentivized?
    • Because he will focus on what makes him rich.

 

Essential questions about his/their view of your startup

  • What do you think are main opportunities of the business?
    • Because the answer reveals if he has valid growth thesis.
  • What do you see as the main risks of the business and how would you mitigate those risks?
    • Because the answer reveal if he has experience with your type of business model.
  • What do you see as the main priorities the next 6 months?
    • Because the answer reveal if he is aligned on the short-term strategy.
  • How do you see the exit path of the company?
    • Because VCs are driven by exits and you want to know if they are aligned on the long-term strategy.

If you ask these question, you will get a conversation instead of an interview. It will be a conversation with between parties evaluating each other. And most investors will respect you for this.

Good luck in your next meeting.

 

Why all founders should know their scale down rate

Most founders think they know their metrics. This post will tell you they don’t. It will reveal the most overlooked metric among startups. A metric so important that many startups fail because they don’t track it. This post will help you not make that mistake. Use it.

One of the biggest disasters in human history was unfolding. Panic spread like wild-fire as people realized they were doomed. When it ended, more than 1500 people had suffered a gruesome death.

Two hours and forty minutes earlier, First Officer William Murdoch had taken over command. He couldn’t believe how lucky he was. He was steering the largest and most prestigious ship in human history. The RMS Titanic.

The water was calm as glass. The air was so clear that the lookouts didn’t even need binoculars. In such conditions threats could be spotted on eye sight. And the crew would have plenty of time to steer around any problem ahead. During the next 30 seconds, First Officer William Murdoch would learn he was mistaken.

At 23:39, the lookouts spotted the iceberg. William Murdoch didn’t panic. He knew exactly what to do. He ordered the engines reversed. It would reduce the speed enough to steer the ship around the iceberg. He knew because he had been sailing for 12 years.

But William Murdoch was about to learn a new lesson. The RMS Titanic was different. And he didn’t have enough time. Half a minute later the iceberg ripped the ship open and unleashed a true Armageddon.

The lesson: Knowing the stopping distance of your ship is rather important.

Startups sail in dangerous waters

Early startups differ from established companies. And the difference can conveniently be illustrated using ships as the analogy.

A company is like a cargo ship carrying goods from one port to another. It sails a fixed route in a well-known environment. It’s low risk and the reward is predictable.

But a startup is like a treasure ship in unknown water. It often changes direction and must avoid all the icebergs floating around. It’s extremely risky but the reward can be massive.

In the world of startups, the most common iceberg is this: Premature scaling.

Premature scaling is so common that is basically synonymous with failure. Premature scaling happens when the founders decide to employ more people and increase marketing spend too early. Too early is before they have found product-market fit.

The result of premature scale is this: Cost increases more than revenue. The bank account sinks until there is nothing left. The empty bank account is the iceberg. And the engines must be reverse early enough to change course. First Officer William Murdoch of the RMS Titanic would agree.

The importance of the scale down rate

All startups meet icebergs. Like an online game called Glitch. The team raised angel funding. Then series A. Then series B. For every round they hired more people. The costs exploded. The revenue didn’t. The iceberg was approaching rapidly.

The team decided to reverse the engines and change direction. They survived, succeeded and eventually found gold. Today we know them as Slack.

But the story of Slack isn’t unique. In fact, most startups experience the following in some form: The founders have a vision. Investors fund them. Founders take salary. Costs increases. Revenue is lacking. Founders raise more money. The team grows. Costs increases even more. But the revenue is not picking up.

The founders try to raise more money, but investors are becomingly increasingly unwilling to fund them. The iceberg is approaching. And at this point, founders need to know their most important metric. The scale down rate.

A good scale down rate

All founders should track their scale down rate. It must give an updated and accurate measure of the stopping distance. How fast can you eliminate costs to a sustainable level? Most founders don’t know.

The scale down rate is a function of the structure of your agreements and liabilities. Such as, employment terms, loan terms, payment terms to suppliers, access to credit lines, etc. Ideally founders must seek to structure these agreements with respect to their stopping distance. The stopping distance is how long it takes to eliminate costs to operating breakeven levels.

Founders must optimize for flexibility in all agreements. Have the option to delay payment against penalty. Hire people on flexible terms. Decrease monthly salary and replace with end of the year bonuses. Avoid lengthy office rentals. Get a credit line. Keep savings so you can defer salary for a period of time.

What is a good scale down rate? It depends on the icebergs in your water. Delayed funding rounds are relatively predictable. But founder breakups, Google ranking penalties and bankrupting key customers can come sudden. Assess your unique environment.

A rule of thumb would be 1% per day. If you can slash 50% of your costs in 50 days, that should give you enough time avoid most icebergs. And every time you do, you get another chance of finding gold.

Conclusions made:

  • Most founders don’t track their scale down rate.
  • Most startups will experience the need for rapid scale down.
  • Most successful startups have succeeding scaling down and pivoting to something else.
  • If startups don’t know their scale down rate, the risk of losing everything when critical problems arise is very big.
  • A good scale down rate is different for each startups.
  • A rule of thumb is 50% of the costs in 50 days (1% per day).

Check out Accelerace. We invest in tech startups.

How founders know when to give up and when to persist

Legends will teach you success is a matter of persistence. This post will tell you it’s not that simple. It will tell you that adversity isn’t created equal. It will teach you the different kinds of adversity and how to react to them. In the process you will witness the rise of a war lord and learn how Steve Jobs made predictions. In end, you will know when to give up and when to persist. Knowing is power. Use it.

It was a landscape of rocks, wind and dust. In the middle of this harsh environment, a young woman gave birth to a boy. She named him Temüjin. And he would change the course of mankind.

Temüjin grew up in adversity. His father was killed. The tribe abandoned his mother and the boy to die. Temüjin was captured by an enemy tribe and imprisoned. He was starved and tortured. All of it before he reached the age of 15.

But Temüjin refused to die. He persisted because he had a dream. He wanted to rule the world.

When Temüjin turned 25, he gathered an army to consolidate the tribes. He attacked his enemy. Arrows flew and swords were swung. The battle was brutal.

But Temüjin had survived an unthinkable childhood to come this far. His resolve was immense. But in the midst of the battle, he did something puzzling.

Temüjin stopped fighting. He ordered retreat, and fled.

The hardest decision for entrepreneurs

Today, we know how the story of Temüjin ends. His dream came true. He ruled the world by the name of Genghis Kahn.

We also know that his retreat was a smart move. He was losing the battle and wanted to maintain strength to fight again. It was a necessary “pivot”.

But how do entrepreneurs know when to pivot and when to persist? It’s one of the most important questions that exist.

When to pivot and when to persist

Most stories about success revolve around the theme of persistence. The stories go something like this: Some entrepreneur has a contrarian idea. Everybody tell him it’s crazy and cannot be done. But he persists. In the end, he succeeds.

The moral is this: don’t let anyone tell you that you are wrong. That only those who persist will succeed. The storyline is good entertainment. But it can terrible advice for dealing with reality. If Temüjin had persisted, he would have failed.

In the past years, the Lean Startup movement has enjoyed popularity. The methodology is all about testing and pivoting. To immediately change direction if something doesn’t work. That’s the opposite of persistence. And it confuses most people.

The confusing part is this: If I don’t get immediate success, should I give up and pivot? Or should I keep pushing and persist?

The answer is knowledge. The problem is belief.

What to do, depends on this: whether you KNOW you are right OR whether you BELIEVE you are right.

If you KNOW you are right, you should persist. If you BELIEVE you are right, you should be ready to pivot. Unfortunately, knowing and believing feels exactly the same. Then, how can you tell the difference?

The difference between knowing and believing

To KNOW you are right requires a model. To BELIEVE only requires hope and wishful thinking.

Steve Jobs insisted on a graphical user interface for the Mac because he had a model. The model was familiarity. He knew it’s intuitive for people to deal with familiar things. Typing commands into a black screen was alien. But to move a piece of paper into a folder felt familiar.

A valid model is a proven theory that allows you to make accurate assumptions. Hope and wishful thinking is what illusions are made of. Like Santa Claus.

If entrepreneurs have valid models, they must stay the course and persist. Even when people tell them they are crazy.

If the entrepreneur doesn’t have a valid model, entrepreneurs must be very attentive to push back. They must be ready to pivot.

How to demonstrate you know the difference

If you want to raise funding, you need to convince investors. During these conversations the investor will challenge your assumptions. And there are two ways to respond. One way is disastrous. The other way will create trust.

Entrepreneurs who respond with strong beliefs tends to come off as delusionary. No investors like delusionary founders.

Entrepreneurs who respond with a valid model tends to come off as intelligent. And in most cases the entrepreneur will have a superior model, because he has thought about longer than the investor. And good investors love to be proved wrong by intelligent founders.

Conclusions made:

  • Many entrepreneurs don’t know when to give up or when to persist.
  • If the assumptions are based on beliefs, the entrepreneurs must be ready to pivot.
  • If the assumptions are based on valid models, the entrepreneurs must persist.
  • When talking to investor, demonstrate you understand the above.

Check out Accelerace. We invest in tech startups.

The anatomy of the perfect entrepreneur

Most people think the world of startups is high tech. This post will tell you it’s primitive. It will tell you startups is where sports were a hundred years ago. It will tell you how founders and investors can improve performance. In the process you will meet a perfect athlete, meet pre-modern entrepreneurs and learn when the word startup was born. In the end, you will be better at startups. Knowledge is power. Use it.  

It was the biggest event on the planet. And all eyes were fixed one person. Elmer Niklander from Finland.

Niklander was the Vitruvian Man. His body was 185 cm tall and weighing 79 kilos. It was elegant and perfectly balanced. Like a renaissance sculpture. Every coach had told him he would become a superstar. And now he was.

He bent down and grabbed the 7.260 kilograms. He took a last deep breath. Then he exploded and hurled the ball 14.15 meters. The year was 1920. And the place was the Olympic shot put final in Antwerp.

70 years later, Randy Barnes from USA throws the same ball 23.12 meters. A devastating advance of more than 60%.

The false idea of the universal athlete

Elmer Niklander grew up in the early days of competitive sport. When he was 6 years old, the first modern Olympics took place in Athens. And If you had been at the opening ceremony, you would have witnessed something strange.

You would have seen 2,626 athletes from 29 countries come marching in. The strange part: Everyone almost looked the same.

But back then it wasn’t strange. Because until recently, it was believed that sport was a thing. That being good at sport was a function of universal physical coordination. And that coordination was best achieved by a harmonious body with perfect measurements relative to each part. Like the Vitruvian Man. Today we can appreciate the logic. Obviously, it was mistaken.

The recognition of specialized athletes

At some point it was realized that sport wasn’t a thing. We learned that sport was in fact many different things. The world of sports has specific disciplines. Each discipline has distinct problems.

Shot put impose the biomechanical problem of hurling a dense ball as far as possible. Swimming imposes an entirely different problem. To propel the body though water using minimum energy.

Once the distinct problems of each discipline were understood, the idea of the perfect athletic body faded.

Shot put requires a short explosive motion. That means that the muscle to fat ratio is irrelevant. Fat is mainly a problem for endurance. Good shot putters don’t need a six pack.

Swimming techniques mainly use upper body movements. That means the legs don’t matter much. Big feat and long arms do. Michelangelo would never have sculptured Michael Phelps.

When we finally realized that sports were many different things, something counter intuitive happened. Athletes started to look less perfect. Actually a lot less. But, their performance soared!

If you had met Randy Barnes, you would never had guessed he was an athlete. Much less, that he was an Olympic gold medalist.

Instead, Randy looks like a bouncer. Partly because of his monstrous frame of 132 kilos. Partly because of what appears to be a beer gut.

But, if Randy Barnes had participated in the 1920 Olympics, Elmer Niklander wouldn’t have stood a chance.

The false idea of the universal entrepreneur

The modern tech startup was invented in Silicon Valley in the late 1950’s. However, people didn’t call them startups. That didn’t happen before 1976 when Forbes Magazine first coined the term.

The founders of the modern startup adopted a name for themselves. Or someone gave it to them. A much older term. Entrepreneurs.

Before the modern tech startup, entrepreneurs were not the people we would think of today. Entrepreneurs were businessmen. And back then, most business was trade. Buying and selling goods with a profit. It required an appetite for risk, and skills in negotiation and salesmanship. People who excelled in those things were sometimes referred to as “born entrepreneurs”. It was an ideal. The business version of the Vitruvian Man.

But when the label “entrepreneur” was given to founders of startups, something changed. What changed was the nature of the underlying business. See, startups aren’t trading companies. Trading is a business model. Startups are not. It’s not even a thing. Its many different things. Does it ring a bell? Now you know where I am going.

The problem with the universal entrepreneur

The term “startup” carries no information about what it does. Nor what its business model is. A startup can do anything from deep science, to organizing sharing of goods, to inventing a new currency. It can sell to government, business and consumers. Its products can be software, hardware or living tissue. There are basically no limits. They are all called startups. And everyone starting them are all called entrepreneurs. And herein lies the problem.

The problem is the multitude of business models. Because each business model has specific problems. Getting consumers to buy virtual goods in games is a vastly different problem than navigating corporations to sell enterprise software to executives. Or getting retailers to provide optimal shelf space is a very different from getting an army of telemarketers to perform.

When modern shot putters are so much better than Elmer Niklander, it is because the specific problem of shot put has been understood. The talent scouts know what to look for. The coaches and athletes know what to train.

Our understanding of startups is where sport was in the 1920s. We know that there are disciplines, but we don’t distinguish the specific problems of each discipline well enough. We still believe in the Vitruvian Man.

That means investors favor universal characters. Like Jack Dorsey. A man who can run both Twitter and Square. And anything else he puts his mind to. But wait, that’s what people thought of Elmer Niklander. Including Niklander himself. So he also competed in discus, hammer and javelin.

The recognition of specialized entrepreneurs

Startup fail rates are horrendous. Some people think it’s supposed to be. But it doesn’t.

Most startups don’t compete with each other. It’s not a zero sum game. In fact, most startups could become successful without it being a mathematical problem. The only ones suffering would be the incumbents.

For this reason, increasing the success rate of entrepreneurs is fairly simple. It’s mainly a function of making the entrepreneurs better. How? Well, we know this by now, don’t we?

We must shed the idea of the universal entrepreneur. We must understand the different disciplines within startups. We must understand the specific problems each type of startup face. We must know what to look for and what to train. Mark Andreesen calls it: Strength over of lack of weakness. But the key question is what strength?

If I knew, the secret to unlocking a massive improvement in success among startups would be within my power. I don’t. But I have a thesis. The thesis is there are at least 144 different sets of startup disciplines.

I am analyzing each type of startups and the specific set of critical skills needed by the founders. If founders possess those skills and train them, they become Randy Barnes. If you want to follow this work, keep an eye on my blog.

Conclusion made:

  • The idea of the universal athlete dominated early days of competitive sports
  • The idea of the universal entrepreneur still dominates the world of startups
  • When sports were broken into disciplines and athletes specialized, performance soared
  • When startups will be broken into disciplines and entrepreneurs specialize, performance will also soar