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Category: Failure, Startup

Why Startups Must Fail

Nine out of ten startups are failing, and this puzzles someone who is not familiar with startups or businesses. Creating a business is a risky move in every sense. Can you attract enough customers, is the location right, is your service or product attractive enough to have customers come and come again?

The Product / Service

Traditional business know they can compare themselves to other businesses. If you start a barbershop, you know what the product is, you know that there are customers, and how much you can charge. And from that you can calculate the profit margin and all other business related metrics because this is a proven business.

With startups not so. A startup is – provocatively defined – an entity that doesn’t know what product or service it has, who the customers are, and how to make money. Take a look at Twitter. What really is the product? People sending out messages with 140 characters? Who is interested in doing so and reading those messages? And how can Twitter make money with it?

Often founders start out with an idea only to realize that they have to scrap it and do something completely different. They do a pivot. Instagram is such an example. This much beloved photo-filter-app started under a different name (Burbn) and was a check-in-app, similar to Foursquare. Only after analyzing the data, the founders realized that most app-users used just the photo-filter app. That’s when Burbn pivoted and changed its name to Instagram.

Google had for several years no business model and no revenue. It was also completely unclear whether a different way of ranking search results would be of value at all, after all with the likes of Yahoo! and others occupying the search engine market. It took some time to realize that users really appreciated the service and stayed loyal. And this is when a new business model could kick in.

The Execution

The best idea is worth much if the founder team isn’t executing well. Ideas are cheap, but the tough part is the execution. There were at least twenty other apps similar to Instagram, but they all lost out or moved into a niche. Facebook was not the first and best social network. There were at least Friendster, Myspace, or StudiVZ. They had a head-start, but Facebook executed much better and took it all. The other networks either disappeared or moved into a niche (like Myspace does for musicians, or VKontakte for Russian-speaking members).

Speed, reaction time, network, and willingness to take risks are some elements that can make or break a startup. The right combination is often difficult to find. One wrong step at the beginning can create insurmountable obstacles in a later stage. This could be technical debt that the team has accrued by taking shortcuts and not creating a stable framework at the beginning and once the rapid growth-phase starts, the system starts breaking.

Regulations and Conditions

Even with the best idea and founding team, a huge part of the success are the surrounding regulations and conditions that the startup encounters. Often similar ideas popup at the same time in different countries, but how the existing frameworks operate and are being dealt with can be crucial. Uber (US) and mytaxi (Germany) are from the most basic premise taxi-hailing apps. But Uber raised over $8bn so far and prepares for a large IPO, while mytaxi raised around $40mio and was acquired in 2013 by Daimler. Uber ‘outraised’ mytaxi by a factor of 200. While mytaxi played within the rules (it aims at cooperating with existing taxi-services), Uber plays with the rules and questions them.

Another example is LinkedIn (US) versus XING (Germany). Both are professional social networks, but XING never got out of the German-speaking market. One part of the problem are the strict data privacy laws in Germany that stifle the usage of data to create more services that LinkedIn could do unhinged.

Fundraising

While the $40mio that mytaxi raised is seen as great example in Germany, it totally pales to the $8bn that Uber raised. Certainly Uber is an extreme example, but the venture capital liquidity in the US market is just so much higher. And not because there is more money in the US. There is a lot of old money in Europe, but not much is used for venture capital. A reason for that is also that to do venture capital investments, you need a knowledgable and experienced class of investors. And that class is missing. Silicon Valley has a lot of experience with it, and it grew over decades organically.

Beating All Paths

In chemistry there are often multiple different ways to create a compound. You could start with simpler ingredients, and ‘cook’ the desired compound. Or it may be that you can break a larger structure apart and this way get the compound. Or you use more complex ingredients and use them to come to the desired result. In the end the path that is the most cost-effective gives you an advantage.

You could consider startups also as trying out alternative paths to a result. But there is a big difference: the target compound is often unclear, but still you need to try to go all paths.

Take Airbnb. This company lets people rent rooms, apartments, and houses to travelers. Could you apply this model to other physical objects as well? Like Airbnb for garages? Well, there are startups trying this: ParkatmyHouse and JustPark. Airbnb for storage places? There are at least three startups: Roost, StowThat, RovingBox. Airbnb for offices? Yes, this startup is called ShareDesk. And even the variation of Airbnb for hosting pets is out there: DogVacay, Holidog, Mad Paws. And the alternative model to rent a pet while you are on vacation at the vacation spot: Rent-a-pet.

Are there markets for those models? We don’t know, probably for most of them not, but if you haven’t tried, you will never know. The more is tried the higher the probability that the models that work will be found. If Thomas Edison had given up to experiment on the light bulb after hundred tries, we would have not had electric light. But he didn’t give up and statistics is in favor of this approach. The more you try, the likelier you’ll find a solution. It took Thomas Edison over 1,000 variations to find the one that created a working light-bulb. An ecosystem that encourages to try out even the wildest ideas, will find itself with more working solutions than one that is risk averse.

The Timing

Sometimes a startup is ahead of its time. A visionary solution where the market or the technology is not mature for it yet. Foursquare was not the first company that the founders had created. The same service came a few years ahead through SMS, but it failed miserably. With smartphone the idea suddenly worked. Mobile solutions for hospitals were available in 2000, but only with the advent of tablets, smartphones, and wireless services being ubiquitous people were conditioned to use them. The Apple Newton was 20 years ahead of its time as well. But being too late is also bad. The market may already be occupied by the first movers. Timing is crucial, and the window of opportunity may be short. But you should never say “We have tried that before and we failed”, because the timing may have not been right back then.

Conclusion

Starting a business on proven models is risky enough, and starting a startup on unproven models even more. To create future value, this needs to be tried out. As long as the few succeeding startups surpass the value of all the failed ones, this is a good strategy. The more can be tried, the more solutions will be found. The higher the number of startups, the more will die, the more working startups will be found.

This is why we need to help create many startups with many wild ideas and accept that many of them will die in the process.