What’s a deeptech startup in the first place, you might ask? Since this is the first part in a series of deeptech articles, here’s my own short and oversimplified definition:
A deeptech startup is a company that brings to market a superior solution, product, platform or service that’s 10x more effective than existing solutions. It must also solve an important SDG-related problem with novel, truly hard to copy, technology.
If you can tick that box, get in touch btw – I’d love to hear about it! So how is this different from building just any tech startup? Are there any special challenges for deeptech startups? You bet there is.
The important thing here is that the factor “10x superior” is enabled by a technological breakthrough. The factor 10x could in fact be 1.1x – as long as that’s enough to disrupt your target industry.
It’s already very hard to accomplish a technological breakthrough, of course, but using a technological breakthrough to sustainably create significant value for a large crowd of customers is typically much, much harder. This is also the reason for the 10x. If the technology doesn’t make a hell of a difference for the customer, then don’t even bother to build a startup around it.
What are the challenges then?
There are many, but the one I would like to highlight here is time.
Yes, time as in years, sometimes even decades.
If you are a tech nerd like me and born in the previous millennium, you may have read the book Gödel, Echer, Bach, by Douglas Hofstadter. One of my favorite passages from the book is the one about Hofstadter’s law which says: “Everything takes longer than you think – even if you take Hofstadter’s law into consideration”.
Yes, it’s worth a laugh, but when you’re building a deeptech startup, more often than not, this “law” feels like an understatement.
And it’s not just caused by all the hardships and negative surprises in product development and scaling your production, it’s also the time it takes to get your first customer to make the leap of faith to say yes.
Being the first customer to integrate an unproven, albeit 10x superior, and probably mission-critical component into their own offer takes a lot of guts.
This first, and super important step (especially when it comes to funding) takes much longer than your most pessimistic logical mind can imagine.
Regardless of your superior specs, you’re always selling to a human in the end and earning her trust in this new crazy thing takes 10x the number of meetings, 10x the amount of testing, and 10x the amount of legal loops to jump through. So long before you get there, your team, your investors and your customer champions lose faith in you.
Giving up, are you?
Despite this, there are actually deep tech startups that succeed. So, what are the tricks that make the journey smoother, shorter and increase your chances of success?
Sure, you are 200 percent convinced that your product and your business model is a total no brainer for the customer, and that if you build it they will come. That actually happens now and then in our universe, but on earth it almost never happens.
Instead, you better leave your ego at home and bring your most pessimistic glasses when you make your plans forward. Assume, in every step of your development, financing and go to market plans, that Murphy and Hofstadter are on the same team, and that team unfortunately isn’t your team.
Then multiply that estimate with a factor of pi every time. Now, maybe, you have something realistic. And the good news is that every time Murphy and Hofstadter happen to be busy elsewhere, you come with a positive surprise. If you have something as great as you say, i.e. 10x superior, the time required will probably be worthwhile for you and your stakeholders, anyway. Now coming from an underdog position you can start underselling and overperform.
- Remember that good enough is actually good enough
Yes, the potential of your technology perhaps allows for something even 50x superior. However, once you get to 10x or perhaps even 2x your offer may be good enough to make your first customers happy anyway. “Best” is often the enemy of good, and there are few things that steal more time than perfectionism.
Also, reality is too complex to just optimize in one dimension only. Very often 10x in one dimension means too late in a market context.
When a market is ready for a technology shift, it will not wait for the best technology, it will go for the one that is available and then shift again only once that technology is obviously obsolete.
- Stick to the plan…and don’t
Some say that the fastest learner is the one that wins in the end. This is true but only half the truth. Unless you transform your learnings into revisions of plans and actions accordingly, you will neither increase your speed nor shorten the time to success. So, what about your carefully devised plan. Should we just throw it in the bin every time we learn something? Yes, and no! There is an important balance to strike here.
Teams and organizations need plans with goals, milestones, KPIs, and so on. Not only because they perform better but also because most people feel safer when they know what’s expected from them. Many will leave the company if you change plans every week. Hence, you need a leadership and a process that puts every learning into context and determines if the learning really mandates a change of plans. Sometimes it’s many small changes, but once in a while it’s a pivotal change. Most of the time the conclusion will be to stick to the plan.
- Create a culture of taskforce operations
As I mentioned above, things never go completely according to plan. This is especially true when working with deeptech. Sometimes you even run into adversity so severe that it threatens to send your startup right into the graveyard of great ideas.
If this happens, you need all hands on deck! As a founder or leader you need to embrace the adversity as an opportunity and remind everyone that what doesn’t kill you makes you stronger. In the startup world this is in fact true.
Brainstorm possible solutions or workarounds and design an appropriate taskforce to execute on the best ideas. When you are through the crises, you’ll have a much tighter team and a higher valuation too. Setting up taskforces create the necessary sense-of-urgency and also a feeling that the company acts adamantly whenever hardships arise.
Also, at times, your creative and superbright team comes up with an even better solution than the one you are working on. At least it looks like it at first glance. This is a very dangerous situation that can easily create conflict and divide your team. Again, the solution here is to create a taskforce. Let a handful people prove that the new idea is in fact so much better and easier and faster to implement and that you should replace the old with the new. Otherwise stick to the plan.
Finally, find and engage with champions, EARLY. What we mean by a champion is a person, usually working at your favorite (ideal) customer who’s gladly willing to try out new solutions and, if the trial is reasonably successful, willing to push (yes, they have to push a lot) your solution, product, platform, or service further into the customer’s internal evaluation process.
Unfortunately, deep tech startups often refrain from meeting with potential customers early, either because they are not yet happy themselves with the performance of their product (perfectionism) or because they are afraid of being dismissed as naïve and immature.
This bad strategy (or rather lack of strategy) puts everything back to front. Unless you’ve been the customer yourself, it’s very unlikely that you’ll be able to suss out all the intricacies of the problem, what the problem costs, who owns the problem, what the implications are for the customer’s customer, what the budget is, etc. from the outside.
The devil is really in the details here. Instead, you should hook up with potential customers as early as possible. Try to identify a problem owner that can act as your champion on the inside. Make them your partner in crime. Give them chance to become heroes in their own organization. By having a champion on the inside, you can fine tune your understanding of the problem you’re solving. You’ll get incredibly valuable feedback about what’s missing and what things really matter to the customer. More often than not, you’ll be surprised how much faster you may reach a value proposition that is good enough to make your customer happy.
Imagine just how much time it will save to skip all the features that you where planning to include that turned out to be just nice-to-haves! Not to mention how much time it would have taken to fix it if you missed a must-have.
Should I always work closely with my future customers? There is one exception, but that we’ll dive into that in the next chapter of this series.
In summary: Building a deep tech-based startup takes time, period. By being focused, customer-centric, efficient, happy with good enough, and managing expectations, you can, however, make the journey faster and more likely to end successfully. Bon voyage!