Among the fundamental misunderstandings that I try to tackle from time to time in these articles, many of them revolve around the fact that a startup is not « a smaller version of a larger company.» This single point is the source of the vast majority of the problems startups encounter when they have to do anything about their project. Whether they have to think strategically or react to an emergency, they activate neuronal pathways that have been formed whilst learning from — or working with — typical companies.
This shouldn’t be a biggie, actually. If you read about startups, you believe that startups die, but teams can regroup, reconfigure and relaunch new projects. This is a Darwinian process wherein the end serial entrepreneurs learn, evolve, and dominate the innovation food chain. Survival of the fittest and all that, right? That’s a lot of horse shit.
The Value of Battle Scars
No matter what, most innovation ecosystems are risk-averse. Some of them, like in Japan — or Latin countries like France — to extreme degrees. It’s not that there is no second chance; rather than in real life, you seldom get it. Obviously, if you’re an ex-engineer from Google and reading this from the Starbucks on Oxford Street near Berkley UC, well… disregard what I’m saying.
For the rest of us, check with a panel of your local investors when teams are pitching for an ambitious project. I’m thinking of a platform business that would have to go nationwide within one year… Then check what will be the first objections raised. Objections are good.
Objections are the most efficient way to profile an innovation ecosystem.
If the project is solid enough in its own right, when you’re in a favorable risk-taking ecosystem, investors will object with things like, “We’re not comfortable with you yet, because you don’t have enough battle scars yet to tackle such an ambitious endeavor.”
That would be a compelling thing.
It would mean that ambitious projects are OK in your ecosystem, but they require people who have already failed once or twice. Teams that have learned their lessons the hard way and got educated well enough on what a startup is deep down.
But you’ll seldom see that kind of feedback flying around.
Most of the time, the feedback you’ll get is about making baby steps toward your goal: make a proof of concept, start to have a few “real” customers, ramp up the business perimeter, and then maybe accelerate nationwide. One day you could even reach out to markets in different countries.
When I’m saying that objections profile your innovation ecosystem, you have it right there: if none of your interlocutors have worked abroad, sold products to foreign markets, or speak English, they will adjust to ambitions around which they can wrap their minds.
I do my best myself to be consistent with this logic. I was contacted a few months ago as a potential consultant for a French “scaleup” program. The program was designed in French, so I refused. This probably pissed off a few people, but what can I say? You’re just not going to help startups reach exponential growth corseted in a slow-going 65 million people market. I obviously can afford to hold my ground because I have no political commitment to bullshit startups in believing in magic ponies.
What is a Startup?
I’m not going to spend hours of your time advocating for the entrepreneur’s second chance and all that jazz. I don’t care about that so much either. I care about making innovation projects fly and connecting them as fast and with as much focus as possible on the market to transform it.
Going back to what a startup is and why it’s so poorly understood, I started a few days ago to write a comprehensive article on “what is a startup.” Then I realized I have a living to make and don’t have the time or the energy (yet?) to write a book on the subject.
So let me lay it down simply for you here: there are tons of definitions of “what is a startup.” Pick the one you like best. This now well-known definition from Steve Blank, I like:
A startup is an organization built to search for a repeatable and scalable business model.
I like it mainly because it’s short and centered on searching for a business model. My grip is that I’ve seen how this became (not through Blank’s fault, though) a bad excuse for not knowing how you’re going to monetize your project, and it further devolved into the poor’s man “lean startup” illusion (another topic to address someday).
I’m not pretending that defining a startup should be consensual, or for that matter, even easy. But when startups are in such hype and are sold as the only way left to innovate (even for multinational corporations), we’re long past the point it all became quite ridiculous. As for now, it seems that every single business project, even remotely connected to the web, or having a bloody engineer in it, is a startup. What’s next? Restaurants?
Well, guys, no. You are not reinventing the offline refreshment supply chain by a network of B2C interactions hot spots. You’re a fucking bar! That is quite a decent business (well, most of the time). There’s no reason to pamper it with innovation magic dust, not a single page of the startup playbook will help you out there.
When you go down the road where any business is a startup, you apply standard business know-how to startups. This is madness. Knowing “business” doesn’t make you legitimate to work with startups. Whoever you are with, whatever business knowledge you have, I respect it. I do.
It just doesn’t automatically apply to startups.
As a consultant, it should be expected that I’d be a tad defensive here. It doesn’t make me the arbiter of who should be legitimate or not to deal with startups. So do what you want with that. I’m just extremely ferocious and upset when I see smart businessmen that have been a successful building from scratch say a taxi company, resell it for a premium and then pass the time as business angels. I can admire them because they’ve demonstrated tremendous skills in their own right.
Until proven otherwise, I will consider them as terribly incompetent angels.
Startups being particular, business common sense does not translate:
If you build a restaurant, you don’t have time to learn about the best courses to deal with a taxi business. You want to focus on fresh food preparation (hopefully). In startup terms, focusing on your financial statements and cost structure is pretty dumb when you don’t even know your added value for your market (the problem you solve).
In that regard, a 25-year-old who has zero savings in her bank account, but spends years with three different startups, as a UX designer first, then a marketing team leader, and finally a co-founder, has acquired enough battle scars that she can be an invaluable mentor.
I’ve yet to see such specific battle scars in a chamber of commerce.
This also means that when first-time startuppers have to sort out what qualifies as educated perspectives from lucky guesses, their learning curve gets steeper.
Both Dead and Alive
Regarding all this, if I have to go back on what is a startup, I would rather adopt the longer, as a matter-of-factly, definition of Dave McClure:
A ‘startup’ is a company that is confused about — What its product is. Who its customers are. How to make money. As soon as it figures out all 3 things, it ceases being a startup and becomes a real business. Except most times, that doesn’t happen.
This definition may seem trivial. It actually oozes understanding of what it’s all about.
My way of putting it — because, hey, why not try to be smarter than Dave McClure on the subject of startups — is that a startup is a Schrödinger’s cat.
Or, if you prefer, a startup is in a state where it’s both dead and alive.
You may remember one of your teachers in high school that tried to explain the counter-intuitiveness of quantum physics? He probably used the Shrödinger (mock-up) experiment, where you trap a cat in a closed box with a quantum poison device.
The fictional device would release a poison gas by detecting the 50% chance that a radioactive isotope would emit a radioactive particle. If the isotope doesn’t emit a particle, the cat is safe. If the particle is emitted, the cat dies. With classic physics, whether you open the box, the particle will be emitted or won’t be, and the cat can only be alive or dead inside. If you could design such a small detection device that would work at the quantum level and still be somehow linked to the macroscopic vial of poison, the device would obey quantum laws. Until an observer checks it, the state of the particle is unresolved. It is both emitted and non-emitted; the poison is both released and not released… the cat is both dead and alive.
This doesn’t work for so many reasons (you probably can’t link quantum objects to macroscopic objects, the cat is an observer, …), but this is a fine way to introduce the weirdness of quantum physics. Most of the rules that we know and feel as intuitive enough about the world are absolutely disregarded by quantum physics.
Well, the same goes for startups. To the real enough laws that we accept as business common sense, they act as quantum objects.
This is basically what McClure is explaining: a startup is a business organism that lives for a while in multiple states of uncertainty. When they resolve, and they will resolve in conjunction, you’ll know if the project is dead or alive.
Among the many pretty inefficient things — just trying not to stay ‘stupid’ too often — while working with startups is to try to solve them in a step-by-step approach: first, we’ll do the product, then test it; if the market seems OK, we’ll try to monetize, and then maybe invest in ramping up the business.
Nope, not going to work.
You have to solve at the same time the added value/product/monetization/customers segment equation. The quantum physics term you want to use is ‘intricacy’ or ‘entanglement.’ You’re welcome.
The very startups trying to build quantum computers obey the laws of quantum business: until we know if what they do really work, they are well funded and appear alive, while maybe they are working on dead-end solutions. When we know, we’ll know if they were dead or alive.
Investors such as VCs don’t play the typical business game where they would analyze a company’s business plan to assess its investment value. They invest in a cloud of startups with various levels of risk and the best optionality possible.
Because optionality beats ‘intelligence’.
The Cat May Be the Last One to Know He’s Dead
My last point is that if you view all this from afar, it’s not that difficult to get educated and understand what a startup is at its core and not confuse them with other forms of business or even other forms of innovation.
But getting this perspective is easier when you’re working with many startups projects. To some extent, you’re avoiding the case-by-case approach of innovation: groups of startups are somehow easier to deal with because you can spread out uncertainty and risk around.
When you need to deliver results with every single startup, well… your cats are all in the same basket, if I may say so.
That’s what gets really tough and quite thrilling: to be able to work with every startup, in a way that you are yourself both extremely pessimistic and nearly paranoid, knowing that every bump on the road will kill them… While keeping extremely ambitious goals and seeing how they could deliver a hyperbolic ramp up in a few weeks.