How to invest in startups at just the right time

In 1872, something strange took place in a small town in Pennsylvania. A seemingly mad man of Scottish origin was constructing a mysterious plant.

It turned out that the man was named Andrew, and that he was planning to produce steel in huge quantities.

The strange part was not the steel part. Steel had been around for thousands of years. The strange part was his ambition to make so much of it. Because at the time, steel was mostly used by artisans for jewelry. And they did not need much.

But Andrew was convinced that steel had superior properties. He imagined that steel could support buildings tall enough to scrape the sky, and bridges long enough to cross mighty rivers. To most people, it sounded like science fiction.

However, Andrew did not just make steel. He perfected it. Andrew refined the processes of steelmaking and broke new grounds in quality and cost.

Still, he produced more steel than was needed, and things looked bleak. In response, Andrew bet his future on a single audacious project. One that would either prove he was right or utterly humiliate him.

In 1874 Andrew revealed the world’s longest bridge (of its kind). The first bridge to cross the massive Mississippi River. Built entirely with his steel.

The immediate reaction was disbelief. Everyone knew that nothing sizable could be made with steel. And certainly not a bridge. But Andrew fetched an elephant he had borrowed and crossed the bridge with the enormous animal. This inspired confidence and hordes of people followed while newspaper photographers secured the frontpage.

Following the opening of Eads bridge, steel became a critical enabler of the Industrialization. At the time of Andrew Carnegie’s death in 1919, American cities had been utterly transformed. Iconic skyscrapers towered over Chicago and New York. Science fiction, indeed.

The real value of steel

Telling the story of magnificent steel skyscrapers paints an illustrious picture. However, it does not do steel justice. In fact, skyscrapers were one of the lesser impacts of steel.

The real benefit of steel was for machinery. The properties of steel made it uniquely suited for tools and machines that entrepreneurs could use to produce a wide variety of new innovative products.

In the years following the adoption of steel, a famous cohort of entrepreneurs used steel machines to make: Proctor and Gamble soaps, Levi’s jeans, Ford cars, Edison light bulbs and Heinz ketchup. Just to mention a few.

In other words, steel-based machinery served as infrastructure to produce new products. And as we will see, the distinction between infrastructure and product is key when timing investments.

Infrastructure before products

Entrepreneurs have limited resources. For this reason, their ideas need a mature infrastructure. A crafty entrepreneur prior to 1872 might have envisioned a skyscraper. But before Carnegie steel, eighty story buildings were not possible.

More than a century later, Reed Hastings of Netflix also had to wait for broadband internet to mature before he could realize his vision of streaming (until then he had to make do with enveloped DVDs).

Unfortunately, it is hard to know when infrastructure is mature. Those who invested in electric cars in the 1980s, webshops in the 1990s, and mobile applications in the first half of the 2000s learned exactly how hard.

In these cases, it turned out the investors were too early. But, why exactly do investors lose money when being too early? Because the products never get good enough before the companies run out of money. And why don’t the products get good enough? Because the technologies powering the products are neither powerful nor cheap enough to serve as effective infrastructure.

Electric cars in the 1980s did not have the lithium-ion batteries and AI that power a Tesla. Webshops from the 1990s did not have the payment processing and high-resolution imaging that power Shopify. Mobile apps before 2007 did not have touch navigation and GPS that power Pokemon Go.

The entrepreneurs behind electric cars, webshops, and apps need the infrastructure to reach maturity. Or more precisely, they need the many individual pieces of the infrastructure to converge and reach maturity in unison. This is an important detail because the infrastructure of most innovative applications are a mix of many individual innovations. A fact so important, it warrants the naming of a law.

The law of compound innovation

The story of Carnegie left out an important detail.

As you have already surmised, steel was not the only innovation required for Henry Ford to produce a car. Nor was it true for soap, ketchup, and jeans. In fact, the infrastructures were a mix of different innovations that converged and matured in unison. Besides steel, simultaneous advances in electricity, gasoline, and rubber were essential for car producers.

When products are built on infrastructure consisting of multiple innovations, two things happen. First, the timing of the maturity of the infrastructure becomes harder to predict. Two, the products that can be built, become harder to imagine. And as complexity theory teaches us, this effect is exponential. One might call it: the law of compound innovation.

But why does the law affect investors? Because investors cannot be too late either. In fact, it is the very nature of venture capital to invest before everyone else sees the value. That was how Light Speed Venture Partners made 2345x return as the first investor in Snapchat.

Talking about Snapchat, let us apply the law of compound innovation. It is fair to say that no internet expert in the late 1990s had foreseen the disappearing picture sharing app. Why? Because Snapchat required more than the internet. In fact, it required several innovations to compound.

To create Snapchat the infrastructure had to become mature enough for a couple of youngsters with no budget to build the first version. It required 4G connectivity, high-resolution mobile cameras, and app store distribution.

And when did these underlying innovations converge and form the necessary infrastructure?

The app store came in 2008. High-resolution mobile cameras started appearing in 2010. 4G was rolled out globally during 2010. The result: Snapchat launched in 2011. And so did all its cousins: Line, Viber, and WeChat.

Projecting compound innovation. Timing the future.

Venture Capitalists bet on the future. And for investors, the future is synonymous with timing.

Consequently, investors must construct a thesis about the future. And not just about what will happen (we all know that). But when it will happen.

In order to construct a valid thesis on timing, one must first understand the innovations that are forming new infrastructure. And the law of compound innovation hints that this becomes exponentially harder the more complex the infrastructure is.

Consider an emerging infrastructure like VR. In 2012, Oculus revived the forgotten dream of virtual reality. Almost eight years have passed, and very few people use VR. To understand why one must first understand the infrastructure for virtual 3D immersion.

In order to deliver a quality experience, one could theorize that the following infrastructure is needed: Wireless lightweight headset with long battery life and a screen resolution of 8K with 180 degrees field of view. 5G to stream the content. And controllers with individual finger and joint sensors. All within a price point of a mid-range smartphone.

In this light, it has clearly been too early for investors (and entrepreneurs) to bet on products like VR games, software, and films. Instead, investors should have been focusing on pieces of the infrastructure. Like controller and screen technology. (A topic for a later post).

But the thesis also hints that successful VR products could be close. The Oculus Quest headset from 2019 is not too far from the headset described. And 5G is being rolled out this year.

Consider a more complex infrastructure. The convergence of Blockchain and VR. An infrastructure that could be called “Virtual Society”. Blockchain is an infrastructure that allows to track and manage ownership. For Blockchain infrastructure to reach maturity, one could theorize that it needs: the ability to handle millions of transactions per minute, wallets to be pre-installed in browsers, and non-technical vocabulary for normal people understand it.

When VR and Blockchain mature and converge, the combined infrastructure will lay outside our experience. Much like the convergence of 4G, high-resolution cameras, and app store distribution was an unprecedented infrastructure that gave birth to the equally alien apps.

Perhaps we are already witnessing the first of such products. In February 2020, Decentraland launched. It is an immersive social network with blockchain-based ownership. An early example of products based on the convergence of VR and Blockchain infrastructure.

It is fair to say that Decentraland would be very hard to imagine a decade ago. But looking at the infrastructure powering it, you might be wondering if it is too early. And if you are, you are asking exactly the right question.

Perhaps the law of compound innovation can help you. See my first crude attempt at depicting it below:

Law of compund innovation

At Accelerace and Overkill we are pondering these things, and if you have views of your own, we would love to discuss them with you.

Why founders should never build the one-stop-shop

Are you okay? The founder was reacting to my painful facial expression. The pain I felt wasn’t physical, but it was real, nonetheless. The unpleasant sensation stemmed from a proclamation the founder had just made. One I have heard too many times before.

We are going to build a one-stop-shop platform! the founder had stated seconds earlier.

Right then, I knew I had a long and difficult conversation in front of me.

I began (again): Look. Many startups founders get the idea of building the one-stop-shop. The logic is obvious. Each individual element to a platform has value. If the platform has a lot of elements, it has a lot of value. And if the platform has ALL elements possible, then it has the most value. Thus, it will be superior to competing products.

The founder nodded.

Unfortunately, the logic is wrong, I said. The founder looked a bit confused.

I continued: Imagine we do a startup. We decide to build an online room planner for private homes. Millions of people need to design their home when moving or renovating, and we know the pain from having moved our self.

We launch, create some buzz, and a few hundred people start using it. However, the number of users is less than we have hoped for. And after a while, we realize that the hockey stick isn’t happening.

The scenario was exactly what the founder was currently experiencing. So, she was very attentive.

What do we do? I asked rhetorically.

Well, maybe there aren’t enough people who need a room planner for private homes, we might conclude. But if we add an office layout, then office managers could use it too. It is easy to add office furniture to the inventory library, so we do it.

What we hoped for happens. Offices are being designed on the platform. But it is still not a hockey stick. At the same time, we learn about multiple competitors that offer office planning. What to do? I asked again, rhetorically.

Well, we just learned that when we added the office elements, we broadened the scope of our product. This meant more people could use it. So, we decide to add more elements.

Factory planning! We add factory layouts and create 3D models of conveyor belts and machines. Now we have the only platform where users can plan homes, offices, and factories. We have no competition.

Still, the hockey stick eludes us. Worse still, we see a reduction in the number of private homes being planned. Maybe because we haven’t fixed all the bugs before we started focusing on the factory elements. Anyway, we have found a way to grow and escape competition, we think.

Next, we enable planning for yachts. Then restaurants. Then concert halls. With each element, we broaden the relevance of the product to even more people. Or so our logic goes.

Finally, we have built the ultimate room planner. The only place you can design any space regardless of function or size. We are the “standard”. The go-to-place. The one-stop-shop. Nobody else offers anything as complete as our software. And then God abandons us.

The founder looked a little confused. Maybe it was because I brought God into the picture. So, I elaborated:

What we would learn is what eBay learned when they added video conferencing (Skype) to its auction site. Or Burbn founders learned before they simplified their app and renamed it Instagram. Or Endomondo experienced when they added e-commerce and social networking to their running app. And these companies are among the surviving examples. The failed projects that have learned the same lesson are endless.

I looked directly at the founder and said: We would learn that the impressive breadth of use cases our software handles is utterly worthless to our customers. I continued:

The thing is that additional elements only provides value to the user if they are integral to the same problem. As an example, it’s valuable if a webshop also offers payment and delivery. The problem the user is trying to solve is to obtain a specific item. If users had to go to a third-party payment solution to transfer money. And to go to another service to arrange delivery, the friction would be unbearably high.

The question is: how integral must problems be to add value to the same platform? Well, more integral than you think, I said.

Take the running app Endomondo, I continued. Endomondo enables runners to track their runs. But runners also need running apparel. So, would Endomondo be a better product to runners if it also featured a shop with running apparel? I asked. The founder looked unsure. So, I continued: It turns out not. Endomono tried that, and it wasn’t a success. Why. Because tracking your run and buying apparel are very different problems. And no runners have these problems at the same time.

Our imagined room planner startup would suffer the same lesson. Nobody needs to design a home, an office and a factory at the same time. The section that supports office planning is worthless when you want to plan your bedroom. In fact, it’s confusing and adds clutter. The idea of the one-stop-shop is false.

Now, it was the founder who felt pain. And then came the inevitable question. But what about Amazon? The founder asked. I had expected it and said: Amazon is a perfect exampleAmazon sold only books for a long time. In fact, they decisively refrained from selling anything else before they had nailed the book problem. Amazon did not become successful because they sold everything. They became successful, exactly because they did not sell everything. Later, they added another element one by one. And so, should you, I said.

The founder was quiet, but slowly her painful facial expression lifted. Then she said: I guess Uber did the same thing. They started out offering expensive limousines, and not until later added cheap taxis and food delivery. Because….well none needs the same thing at the time. She let it sink in.

Then I could see her facial expression change into a very familiar one. Determination. Thank you, she said. I know what I must do. She got up and left. I looked out the window and thought about how often I have had this conversation. And then, I started writing this blog post.

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.

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.

The-technology-adoption-life-cycle-1024x336

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.

Billede2

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 corporates are terrible at assessing startups and how to do right

Many corporates are billion dollar entities in stagnation or decline. So they run startup programs to look for the next big thing. But big corporates need big ideas to move the needle. That is why most corporate selection committees focus on market size. They think big market is a prerequisite for big opportunity. They are mistaken. This post will explain why market size is irrelevant and how corporates should be evaluating startups.

Today most corporates have some kind of startup engagement activity. Like outplaced innovation teams, hackathons, innovation garages, and accelerators. And they should. Startups create much of the innovation today and corporates would be foolish not to attempt to leverage it.

The problem is that it’s not working. The initiatives do bring the sense of innovative spirit and fun for the employees involved, but the billion-dollar success stories keep eluding them.

The problem is that many corporates are terrible at assessing startups. And this problem is magnified because the consultants and service providers helping the corporates design and manage these programs are too focused on getting the contract to question anything. Sucking up rarely produce truth.

The fallacy of big markets

Corporates need billion-dollar ideas and this fact makes them focus on startups with big (adjacent) markets. And it makes sense. Big markets are the prerequisite for big business. Unfortunately, this logic is flawed.

The thing is that startups aren’t really businesses. Instead, they are problem-solving entities. And this fact is immensely important when assessing the potential of startups.

Businesses have markets. Startups have niche products that target niche customers with a problem no one has cared to solve before. Per definition, most startups have tiny or even non-existing markets. Like a young startup called Unity in 2005 that made it easy to create games for Apple devices. There was no market because none played games on an Apple device. That was until Apple launched the iPhone. Today Unity Technologies is a unicorn.

Or Trustpilot (an Accelerace alumni company from 2008), that made it easy to review webshops. Their market was non-existing because they had no customers. Only free users. Today Trustpilot has thousands of business customers and raised $150 million in funding.

The thing is that market size is not relevant because the product evolves and the market sentiment changes.

Still, in most selection committees I’m in, the corporate representatives will regard the current product pitched as a fixed value proposition and estimate the potential from that snapshot. It’s a mistake.

How markets emerge over time

The truth is that most startups radically change their product. It happens because startups are founder driven, and founders can enact radical changes at will. To a corporate, sudden and radical product changes is unthinkable. Thus, corporates tend to gravely underestimate the plasticity of startups products and business models.

When the product change, the potential market changes as well. Like when the high-end limousine ordering app Uber added non-luxury cars to their app and became a taxi killer. The limousine market is small. The taxi market is not.

Just like the product can change, so can the market sentiment. It happens if the product has network effects or product consumption is highly observable.

When products have network effects, the product becomes more valuable over time. In the beginning, the product is only valuable to a small group of people. Like the first computers or an early version of the crowdfunding platform Kickstarter. But as more and more people use the products the relevant market increases. And Metcalf law teaches us it can happen very quickly.

In other cases, the market sentiment changes because of trends. If the product is highly observable, it can initiate a change of perception among potential customers that suddenly redefine the market.  Like electric vehicles, café latte and CrossFit.

For reasons above, market size is a terrible proxy for potential. And corporates need to unlearn the importance of it.

How to do it right

Instead, corporates must learn to construct a thesis about the future of their industry. The thesis must regard how technologies and trends will influence, reshape or even replace their industry. Once in place, corporate must target ideas and startups within the thesis.

They must learn to resist the temptation of attempting to foresee the potential of the individual startup but instead focus on executing their thesis. In all practicality, this means betting on a lot of teams doing similar things but from different angles.

The selection committee must still regard the potential, but the potential is already built into the thesis. So instead of questioning the market size, the committee members should question how closely the startup fits the thesis.

If telcos had done this in 2011, they might have caught either Line, Snapchat, Viper or WeChat. They all launched their chat apps that year, but telcos were missing a valid thesis on the future of communication. This should be a lesson for all.

Conclusion

  • Most corporates look for billion dollar ideas.
  • When assessing startups, corporates question market size.
  • Market size is a bad proxy for potential.
  • Corporates need to create a valid thesis about the future of their industry and start targeting a large number of startups within this thesis.

 

My startup investment outlook for 2018

One year ago I felt uncertain about the future. I know because I wrote about it here.

The era of mobile internet was ending. The decade gave us causal gaming, on-demand services and chat. The successful strategy had been to bet on apps with network effects. But the next wave wasn’t obvious.

Going into 2018, my uncertainty is fading, and I start sensing the contour of the next decade. And it is cute kittens.

In October, the first version of the game Cryptokitties was released. People breeding and trading digital cats. It became an instant success. Its demise will be equally swift. But something important will linger.

Cryptokitties paves the way for something truly groundbreaking. The assignment and trading of unique digital assets.

Bitcoin had long proved blockchain’s ability to assign and trade ownership over digital assets. But until October this year, the digital assets were fungible. Meaning my coin is no different from your coin. This property makes Bitcoin suitable as money. The thing is we already got money.

In contrast, we never really had unique digital assets. But we do now. And that matters because value stems from two properties. The first property is scarcity. The second property is uniqueness.IMG_6309

Bitcoin solved the scarcity problem. But the coins had no meaningful differentiation. Like oil, gold, and energy.

But the underlying blockchain to Cryptokitties added uniqueness as a property. Like art, companies, contracts, and land.

Uniqueness is immensely important because people are different. We like and need different things at different times. A rental contract might be favorable for one person but useless for someone else. A remix of a song might be enjoyed by one person, but disliked by another.

Furthermore, we are creative beings and we like to personalize our world. We develop recipes, produce art, write software and record tutorials.

The smartphone made it easy to create. In 2018, the innovations in blockchain technology will make it easy to own and sell whatever you create.

The combination will complete the economic ecosystem for digital products. The winners will be startups integrating and owning the biggest verticals, and thus benefitting from both economies of scale and network effects.

I would bet on startups with this aim.

Happy new year to everyone.

 

Startup tsunamis and how corporates face them

Most corporates think of startups as small businesses. Everyone knows that small businesses don’t matter. But startups move in waves. Sometimes waves are so big, we call them tsunamis. And tsunamis matter. This post will explain the nature of tsunamis. It will tell the story of a single earthquake that triggered two very different tsunamis. In the end, corporates know how to handle startup innovation. Do it.

In 2011, the most powerful earthquake in Japanese history triggered two devastating tsunamis.

The first tsunami hit the Japanese coast an hour later. A 40m tall mountain of water traveled 10 km inland demolishing everything in its path.

The second tsunami hit the global telco industry five years later. A cohort of chat apps reached maturity and shattered the future of telcos.

What happened was this: After the earthquake people wanted to call their loved ones, but the phone lines failed. Instead, people sought internet access and a group of developers developed a solution. They called it Line.

Line inspired entrepreneurs everywhere to build chat apps. Among these were: WeChat, Viber and Snapchat. All of them launched in 2011. A startup tsunami was in motion.

At this point, the telcos should have reacted. Today, we know they didn’t. The reason is the nature of tsunamis.

The nature of tsunamis

Tsunamis are always proceeded by an earthquake. Earthquakes are easy to read. The ground shakes and our needles move.

In contrast, tsunamis are hard to read. Only a fraction of earthquakes triggers one. When it happens, the tsunami is practically invisible. It travels underwater with the speed of a commercial jet. Just before the coast, it suddenly rises and darkens the horizon. At that point running is pointless.

The same happens in technology. Some big breakthrough occurs. Like an earthquake, the event is easy to read. Academics, research papers, and popular science media cover it in full.

In some cases, the technological breakthrough is practical enough for entrepreneurs to take advantage. In these cases, hordes of ambitious people found startups. The event has triggered a startup tsunami.

Like a normal tsunami, startups tsunamis also travel below eyesight. It moves through garages, co-working spaces, accelerators and obscure online forums. Places that are mostly invisible to corporates. But it moves fast, gain momentum and suddenly rises. At that point, innovation projects are meaningless.

Why corporates are paralyzed in face of startup tsunamis

Startups tsunamis travel for about 7 years before reaching shore. That means we get a rough picture about the future seven years in advance. If telcos had noticed the large cohort of chat apps launched in 2011, they could have saved themselves.

The problem is that most corporates don’t have proper sensors placed to detect these motions. And when they do, they don’t know what to do about the information.

Most corporates have no method to handle startups. Corporates normally have two defenses against competitors. They buy them or compete with them. But none of that works with startups.

Most M&A professionals would never consider buying a startup. It is simply too small. Why go through all the hassle to buy something small, when you can buy something big with the same amount of work.

Competing with startups seem equally silly. They have no market share.

The thing is this: startups are not competitors. In most cases, startups do not compete with the incumbents. Instead, they build a parallel industry that will eventually outperform the old industry.

Corporates have no answer to parallel industries. It’s not part of a standard MBA course. But there is a way.

Corporates must respond to startups by helping them build the parallel industry. Few founders want to disrupt. Most founders want to build. And when asked, an overwhelming majority of startups actually wants to collaborate with corporates.

If corporates help startups to build a new industry, the corporates will be a part of it. Luckily, new tools are available.

How to ride a startup tsunami

Corporates must take part in the startup tsunami. To do this, corporates need a dedicated interface towards startups. The interface can be an accelerator, incubator, VC arm or some other open innovation initiative. The most important thing is that the initiative follows these rules:

  1. It must scout startups globally. Innovation can arise anywhere.
  2. It must engage enough startups. The more exposure to the tsunami, the better you can react.
  3. It must have a value proposition that is attractive to startups. Startups don’t need you, so make them want to collaborate.
  4. It must include and incentivize all the relevant business units. To utilize synergies the startups must get access to operational decision makers.
  5. It must be rebranded. Even though your brand is a hundred years old and worth billions, startups don’t think it’s cool.

And most importantly….

  1. It must be run by people who know how to talk and deal with startup founders. Founders differ from the rest of humanity and disdain people who don’t get them.

Follow the rules above, and certain calamity becomes a possible future.

At Accelerace we help both startups and corporates.

My startup investment outlook for 2017

We are in times of transition. I never experienced it before, but I’m also young in this game.

I imagine it’s similar to the mid 1980ies when the personal computer wave faded. Or the early 2000s when the internet rush ended. Those too were times of transitions.

But history shows a new innovation will soon emerge and reach critical support. Certainty will return.

I experienced the latest of these waves. The mobile internet. I remember being absolutely certain about the future. The internet would go mobile.

Every website and application needed to be redesigned to the smartphone. I knew the change would be big enough for startups to battle the dot.com winners. At the same time, the mobile was cheap enough for new users to access the internet. Kids, teens and people in developing countries would want different applications. I knew it.

During the past year, it became increasingly clear to me that the mobile internet wave is fading. The big winners have been found. The pitches I see now are “the Uber of” some small segment.

Entering 2017, I don’t know anything for sure. There is no certain wave everyone is riding. But it’s exactly at times like this the biggest winners are made. Founders and investors who catch the next wave before it becomes obvious will make history.

Where we are going

My general belief about the future of the human race can be summed up in one word: Omnipotence. Humans have strived for the same ideal throughout history. The ideal has been called Zeus, Odin or modern superhero names. Their characteristics: They are all knowing, omnipresent, extremely powerful and immortal. Most telling of all, they look and behave as human beings. And this is where we are heading.

To a pre-modern human, we would already seem omnipotent. All knowing because we can seemingly access all of the world’s information though a screen in our pocket. Omnipresent because we are connected on social media and can move by car and airplane. Extremely powerful because can manage huge projects with software and turn of lights with our voice. Immortal because we can fix most diseases and live to be a hundred.

But modern humans know we still have far to go.

Approaching all knowing

The internet and mobilization of the internet basically made us all knowing. We managed to digitize information and transfer it via fiber and radio waves to everyone’s pockets. Sensors, cameras and peer generated content provided new sources of data. However, there is still a lot that we don’t know.

We don’t know what we are eating, the true state of our body or what a baby is thinking. We don’t know who would be our perfect spouse or how long we need to sleep.

What we need are new type of sensors and improved understanding of the existing data. I think those are big opportunities in the coming year.

Approaching omnipresence

Even though pre-modern humans would be amazed how quickly we can get around today, we are still far from true omnipresence. Food, medicine and people are still moved by relatively slow means of transportation.

In order to become truly omnipresent, we must turn physical objects instantly available. But because physical objects cannot be digitized, we only have three options. 1. Move them much more efficient, 2. Replicate them, 3. Substitute them with something else.

Drones and self-moving vehicles can move objects and people extremely efficiently. Alternatively, we could replicate the things we need. Aside from the potential dangers, having a medicine machine at home would make a lot of sense. In some cases, we could substitute people with humanoid robots, AI or avatars in VR.  I would bet on startups that did any of this.

Relatively powerful

In pre-modern times, almost everyone was farming or hunting. Today, only a few percent create food to the rest of us. Machines and software coursed leapfrogs in what a single human can accomplish. I feel it when Google Maps navigate me places I never been before

However, I don’t feel very powerful when I need a key to open my door or don’t understand what a book is trying to teach me. To be powerful is to be in control. But to be in control requires tools. What we need are more tools.

IoT will help turn objects into tools and interactive interfaces and virtual environments will help me learn new skills. In this field, there is a lot to be done for startups.

Far from immortality

We will not achieve immortality any time soon. In fact, I believe we still got basic plummeting to do. Like just monitoring the state of our health or actually understanding the brain.

In the short term, the obvious task is to get everyone to wear a tracker. But no one likes to strap something bulky on and off all the time. Trackers must be tiny and permanent. Also they need to measure things that really matter. Things you currently need blood samples to get.

When we actually understand our body and what goes on, it will unleash a world of applications. But right now I look for startups that will do the ground work.

Happy new year everyone.

Visit us at www.accelerace.dk.

Why central banks hate startups

This is a useless blog post. It won’t help you succeed with a startup. Neither will it help you invest in startups. Instead it will make a connection most people haven’t seen. It will expose who really rules the world and how startups are changing everything we know about economics. In the end, you might see the world differently.

Nine years ago the world changed. We got a new ruler.

Regime changes happen when existing power structures break down. Like the French revolution and Arab Spring.

In 2008, the financial sector broke down. In the chaos following, the new ruler came to power. The central banks. And their leaders became household names. Today, most people know of Janet Yellen and Mario Draghi.

Like any new regime, the new rulers portrait themselves as saviors. And they were.

The world was headed for a 1930s like depression. Banks would freeze our accounts. Pensions would evaporate. Governments would have broken down.

Central banks emerged from obscurity. They stepped onto the world stage to shield us from chaos and anarchy. To restore order and confidence.

People embraced the new ruler. In return, central banks quickly and decisively saved banks, companies and governments. They did so by printing money at an unprecedented scale.

So far the ECB and the FED has printed more than $4 trillion in new money. Yes, that’s a lot.

Money printing is not bad in itself. It did save us. The problem is knowing when to stop. And if history has taught us anything, it’s that regimes never step back down. Central banks are no different.

The power of central banks

Central banks have stayed in power since 2008. They have declared state of emergency and taken control of our economy. The free market has been suspended. Prices of stocks and bonds are now under central bank control.

The price of stocks and houses are at historic highs. Not because the economy is better than ever. But because Janet Yellen and Mario Draghi keep printing money.

The reason why they keep printing so much money is because their instrument tells them so.

The instrument is a thermometer. It sits in every central bank. And it measures the temperature of the economy. Or so it’s believed.

The thermometer looks like this: high inflation – moderate inflation – deflation. High inflation is bad. Moderate inflation is good. Deflation is the really bad.

The thermometer tells central banks to aim for moderate inflation (around 2%). If the thermometer falls below their target, they print money.

And money printing always works. Except for the past eight years, it hasn’t.

Instead of inflation, we see clear signs of deflation. And Mario Draghi and Janet Yellen don’t know why. So they keep printing even more money. Sadly, it’s a futile act.

But to understand why, I will take you back in time to see when the misconception started.

Classic entrepreneurs made new products

In the late 1890s, there was a farmer named Henry. The thing about Henry was that he hated farm work. So he started dreaming about building a machine that could do his job.

Henry started to materialize his dream. After a long day of farm work, he would go to his small shed to work on his machine.

Then one day it was ready. He turned it on, and it worked. Henry had built a vehicle running on a gasoline engine. It marked the beginning of his later company. The Ford Motor Company.

But Henry Ford was just one of many entrepreneurs inventing new consumer products. In fact, the following decades would see a flood of new products. Like sewing machines, washing machines, personal computers and smartphones.

The new products provided vastly better solutions to our problems than the existing products did. Cars outperformed horses. Sewing machines outperformed handheld needle and thread. And the personal computer outperformed typewriters and calculators. The inventions created entirely new product categories that consumers were willing to pay premium prices for.

A car was more expensive than a horse. A sewing machine more expensive than needle and threat. And a personal computer was more expensive than a typewriter and calculator combined. But that didn’t matter, because new categories have no existing price anchors. The inventor is free to set a high price.

In the age of product innovation, rising prices became synonymous with economic health. A healthy economic environment had rising prices. In large part due to the many new and better products being introduced on the market. In other words, the age of product innovation was a world of inflation.

New entrepreneurs disrupt industries

The evolution of entrepreneurship can roughly be summed up like this: The first generation of entrepreneurs created new products. The second generation created digital tools. But the third and current generation does something no generation of entrepreneurs have attempted before. They redefine established industries. And the change of focus matters greatly.

The highest valuated startups are currently Uber (2009) and Airbnb (2008). Both were founded in the aftermath of the great recession. And they have inspired and defined the new age of entrepreneurship.

These startups showed aspiring founders that startups can do more than just make tools. They can disrupt and redefine the very pillars of our society. Such as: transportation, housing, banking, legal processing, energy and even space exploration. These industries are so important that their institutions have (almost) become political establishments. Disrupting them is the most daunting task ever taking on by startup founders. And it’s also the most important.

But disrupting industries has a very different economic impact than creating new product categories and creating digital tools. New categories are inflationary. Digital tools increase productivity. But redefining existing industries have a very different effect. One that Janet Yellen and Mario Draghi fear the most. Deflation.

The age of deflation

When startups disrupt and redefine existing industries they are not inventing new product categories. They are reinventing the way existing product and services are being produced.

Uber fundamentally delivers the same service as taxi companies. But they have redefined the underlying infrastructure behind the service. They have applied technology and utilized excess car capacity. The result is transportation that costs half of a taxi.

Airbnb fundamentally delivers the same service as hotels. But they have also applied technology and utilized excess capacity. The result is overnight stays that costs half of hotels.

But these companies are merely the front runners of a seismic wave of startups attacking the very pillars of our economy. Startups like Impossible Foods is redefining the way we produce meat. The result will be high quality meat at a fraction of the current price. Robinhood is attacking the financial service industry and eliminating fees for trading stocks. All of these startups have one thing in common. They lower the price on things we already spend money on. And that has a name. It’s called deflation.

It’s the thing central banks fear the most. And they will fight it with everything they got. But what they fail to understand is that not all deflation is created equal.

Why deflation from disruption is different

Economic theory stipulates that deflation leads to deferred spending. If apples are cheaper tomorrow, we will wait buying them. That’s obviously bad for economic activity. But this theory builds on a critical assumption. The assumption is this: we can anticipate the price decline.

If we know that apples will be cheaper tomorrow, we will surely wait buying them. But deflation from disruption is fundamentally unpredictable.

No one saw Uber or Airbnb coming before they were actually here. No consumer thought: I will wait booking my vacation until some startup emerges that will utilize spare bedrooms to offer cheap stays.

This means that deflation from innovation won’t lead to deferred spending. And this also means that Janet Yellen and Mario Draghi are looking at an obsolete thermometer. In other words, they are dead wrong.

Disruptive startups will define our future

Central banks have pledged to keep printing money till they reach their inflation targets. But they are fighting the force of human innovation. A force consisting of entrepreneurs from across the globe hell-bent on disrupting the establishment. Janet Yellen and Mario Draghi have brought a knife to a gun fight. And they will lose.

What central banks will get instead is something worse than deflation. They will get bubbles. All the money flows into stocks and cheap housing loans. Prices on stocks and houses will detach from the true state of the economy. They will bubble up to levels so high, that central banks will have no choice but to keep them high.

Janet Yellen and Mario Draghi will find themselves in situation they cannot get out of. All of it because they don’t understand that the world has changed. That they actually aren’t in control. But that disruptive startups will define the future economy. And it will be deflationary.

Conclusion made:

  • Central banks rule the current economy by intervening with printed money
  • Central banks want inflation because inflation used to show economic health
  • The new generation of startups creates deflation
  • Deflation created by disrupting startups doesn’t lead to deferred spending
  • Money printing will only lead to bubbles
  • Startups will succeed disrupting industries and thus create deflation

 

Check out Accelerace. We invest in tech startups.