mvp #hardware #scipreneurs #techtransfer
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🔬 I have seen countless hardware-based university spin outs struggling defining and then building an MVP off the ground. And we all face the same question: outsource or build in-house.
The decision is a tricky one, and it will always depend on what your business strengths and weaknesses are.
Hardware minimum viable products are challenging because of their multi-dimensional requirements. They include mechanical, software, and electronics. Each one with a different skillset and different approaches to problem-solving.
What works extremely well for software, where delivery to customers is instantaneous, marginal costs are zero, and iteration cycles happen in days, may be much more challenging for hardware.
I strongly believe that one of the bottlenecks is lack of interactions across disciplines. Most engineering and design students are not exposed to scientific instruments or labs. On the other hand, most scientists are never exposed to engineering and design principles.
To add to the complexity, #scipreneurs must do all this in the highly uncertain context of what validating a business case means.
👀 I have seen startups face a decision that can put their very survival at risk: outsource the product development to a company and deplete their funding, or focus on validating the idea to justify a larger round of investment.
Endlessly validating an idea will only take you so far. At some point people need to experience your product. And for high complexity instruments, the user experience will never be as smooth as you thought, data will not be as reproducible as you claim.
Outsourcing and depleting your money is very risky. Without the famous product-market-fit, chances are you won't sell anything. It's a single-shot approach to all or nothing.
🏡 The intermediate path is to build the knowledge in-house.
Many mentors and coaches greatly oppose this approach. I simply think they over estimate the complexity and costs of building scientific instruments. They underestimate the risks of outsourcing, and they mostly miss the point: startups should focus on their strengths to overcome their weaknesses.
My advice: build knowledge and outsource smartly.
I have worked with, supervised, and coached many extremely talented students who can learn a lot from a startup's hands on approach, while they deliver immense value back. They need both guidance and creative freedom. Especially when working with people from fields which are not your own, there is plenty a founder can learn from the interactions with a student.
Founders come from many different walks of life, and they may have never built hardware before. Believe me, there's nothing more daunting than building a microscope for the first time.
The first step for a startup is, therefore, to define what their MVP is.
Customer knowledge will be partial, market knowledge will be incomplete. But those are the rules of the game for entrepreneurs: act on highly uncertain conditions. It is tempting to focus on making an MVP as cheap as possible, but you need to be mindful about the purpose of what you are building. Using more expensive components at the beginning is easy to correct when they are not needed. The other way around, however, is much more challenging.
There is no single path for building hardware MVP's. And that's when the value of a network comes into play.
The experience of other founders who have been building instruments for most of their careers can be crucial. Dare to ask for help, and be creative with the way to want solutions to be delivered. Maybe it's not just a one-off question, perhaps you need to engage someone on a more periodic basis to help you push through. Especially if you find someone who is not just technical, but who understands your struggles as a startup founder.
Now a days, creatively leveraging digital manufacturing, quick CNC prototyping, and open-hardware microcontrollers, can cut the development time from years to months. Dare to make mistakes, learn from them and move on. It's a challenging path, but a very rewarding one.
Outsourcing is tempting but unless you are sure which expertise is not crucial for your business model, it can put you in a dead-end path.
Joining the largest network of scipreneurs can help you make better decisions, faster: https://ck.scipreneurs.org
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