How to Not Fail Innovating as a Startup

How to Not Fail Innovating as a Startup

20-Feb-2017 by Harry Wilson

This post is based on one section of the article co-authored by Aldo de Jong and Harry Wilson from Claro Partners and Pascal Bouvier, fintech venture capital investor. The starting and ending have been added by Harry Wilson for Startupbootcamp IoT & Data tech.

Let’s paint some broad strokes: a startup throws mud at the wall and see’s what sticks, with only 2% of them reaching ‘VC caliber’ and 0.2% of them ever reaching a size of $100 million. It’s a lot higher, but far from great, in corporations as 12.5% reach $100 million (according to a recent HBR article). Why is the failure rate so high?

Lean startup doesn’t stand up on its own

As with each in-vogue wave, there is preaching and swallowing without really understanding what it is, when to use it, and how to really do it rather than just redressing what was being done before. In the application of lean startup, the emphasis has been on ‘BUILD, measure, learn’, and this mantra has been used as justification to start with building on ‘unvalidated hypotheses’ (read: gut-feeling ideas not based on any customer insight in the worst cases, AKA mud). The focus is on ‘get shit done’ and ‘make shit happen’, while customer research and learning is often lost from sight.

When we start with ‘build’, we start with what we already know, and refine from there – but this restricts us to a narrow set of opportunities, that are not thought through. It’s the reason there are thousands of ‘startups that help startups start-up’ – they solve the problems in front of their nose. It’s the reason CES is filled with drones, robots and wearable devices which are fascinating, but have no indication of what real problem they are solving. It’s compounded by the view that developers and entrepreneurs think in a certain way, and incorrectly assume that their users will think and feel like them.

We find immersive research is the best way to uncover non-obvious, highly important customer needs. One of the classic lean startup fables is Airbnb’s experiment to hire professional photographers to shoot each listing, resulting in a 2-3X increase in bookings – but where did this hypothesis come from? Back when Airbnb was all air-mattresses and Obama-branded cereal, their cofounders travelled to New York City, met every single host, lived with them, and wrote their first reviews. Their ‘aha’ moment was seeing the mismatch of grainy photos compared to the real home; this insight gave life to what was, on paper, a mad experiment to run. As a human-centered designer, Brian Chesky lives this philosophy up to today (with guests on his couch every night). It’s this customer immersion that informs the lean experiments that have made Airbnb so different, and successful.

Lean startup experimentation is a hugely important way of working, predicated upon an important caveat: they have to be anchored in insights.

Of course, lean startup on its own works out just fine on an ecosystem level. As long as you have thousands and thousands of startups throwing mud at the wall cheaply, 1% of them will stumble or pivot their way into a non-obvious, important solution. But when you isolate that effect to one company, blindly testing hypotheses is not efficient. When a startup is your life, throwing out new propositions in the dark is a very expensive way to innovate. Darwinism doesn’t work, you need creationism. For lean startup to be effective, it needs a foundation in customer insight.

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Image: Where lean startup, done right, fits into the innovation process. Starting with customer insight helps identify non-obvious, important opportunities.

At Startupbootcamp IoT & Data Tech, the program broadly follows these 3 phases, with one month each. When startups arrive in the first month, it is important (and not easy!) for many of them to take a step back from their initial solution, and dive into customer understanding that they may not have done before in a deep way. This does take time, but it means that the revised value proposition they experiment with in the second month is more likely to land a lot closer to problem-solution fit.

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Image: Irakli and Denis, front, co-founders of Combine ( in a group discussion with digital nomads, their target users, at Claro Partners. In just 10 days after their user interviews, they were able to use this deeper understanding to create a much more targeted value proposition – and test if it was a good one with a lean startup experiment.

Come and see our startups next week at Demoday to see where this journey has taken them. If you see Startupbootcamp’s success statistics from the last years, you’ll know there is no mud flying, only sparks.

SBC IoT & Data Tech Demoday @ 4YFN / Mobile World Congress 2017

Senior Associate @ Claro Partners