Lean Reality Distortion
by Thomas L.
There is a misconception about the extent to which tools such as the lean methodology vis-à-vis product vision impact the success of a startup. Startup success cannot be engineered – the lean method does not overcome this principle. It can help to fail quicker and by that it creates valuable learning, however, it should not undermine the persistence around a bold product vision.
Empirically, premature scaling is the number one failure of startups. Reaching certainty around product-market-fit (PMF) is vital before hitting the gas pedal. It thus makes sense that a startup uses its limited resources to yield the biggest bang for its buck. The concepts around the lean methodology (MVP, rapid prototyping, etc.) can help achieving this, given that hypotheses are derived from a strong product vision. Fred Wilson described the lean methodology as a machine: “Garbage in, garbage out.” Without a great product vision, there is just not much you can expect to come out of that machine.
I recently had the chance to visit both Nest and Dropbox. Both companies have arguably achieved PMF (for now). Drew Houston is known for having applied lean principles in the early days of Dropbox. That said, both of these companies will likely look very different in 3 – 5 years. It’s not unlikely that Dropbox could evolve in some sort of cloud OS or move stronger into content; Nest could be anywhere among the lines of an Internet of things or demand response company, revolutionizing energy efficiency. These are both companies solving big problems and even at this stage, achieving their longer-term vision requires a huge entrepreneurial leap.
Both companies won’t get from where they are today to where they want to be by simply applying lean methodology. In the same way these entrepreneurs were able to see their vision through from MVP to today, they need to be able to see the next big step for their companies. In that, I disagree with the statement that companies need to be hunch driven in the early stage and data driven with regards to product at later stages. Companies at this stage can A/B test their products and generate lots of data around their product/device. This will allow them to perfect their existing products, but it does not help them to execute along their longer-term product vision. They need to be data AND hunch-driven.
While most entrepreneurship classes at HBS are based on the lean method, I think it is important to state that lean is not imperative for startup success. This is also the reason why Google, Twitter, Quora, YouTube etc. don't necessarily follow the lean pattern. The complexity of applying the lean method is immense, whereas dismissing the need for another search engine, another social status tool, another yahoo answers, etc. seems easy. With long enough testing, a slightly wrong built hypothesis, and by relying on customer feedback, I’m sure the respective founders could have come to the conclusion their ideas would fail in the market. Instead, they got their product vision right (and one million other things required in building a business).
So while “garbage in, garbage out" holds, there is just no machine (i.e. methodology) that can manufacture startup success. These tools can help one’s thinking in structuring a startup, but they really only make up a tiny fraction of a successful outcome.
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