At the Stamford Innovation Center, we’ve done a bunch of events, talks and meetups that focus on entrepreneurship – in fact you could say that startups are in our DNA. Woven into all of these activities is a set of assumptions about how startups should approach the insanely difficult task of building something from nothing: we assume that the best way to approach starting and growing a business is through the Lean Startup methodology.
Startup Weekend is a great example. Teams have a great time thinking up their product, working with design, strategy, marketing and finance, and there’s tons of value in that. However, the defining activity of Startup Weekend customer validation. We ask participants to get out of the building and talk to real people about their idea, their design and their business.
What Lean Means
At its heart, lean methodologies are data-driven, and assume you will spend the least amount of time, money & effort on each task as you can. Data is what determines how much you need to spend, which is why it is so important.
An American statistician and process control researcher, W. Edwards Deming started the whole thing back in the 50’s, was ignored in the US, and went to Japan, where his ideas were adopted and operationalized, most famously by Toyota. The world became aware of lean methods through the Toyota Production System (TPS), which revolutionized how we make everything from cars to electronics to paper clips. You hear this today with “Kanban” and sometimes “Kaizen,” possibly the only non-food related Japanese words most people know.
Throughout all of this development, asking questions, gathering and processing data were all central, and led to the ability to produce only what you need, when you need it.
Bob Dorf, co-author of “The Startup Owner’s Manual”, is fond of saying the first job of startups is to learn, not to market, not to produce, and not to fundraise. You don’t know if you’ve got a good product/market fit, don’t know what kinds of people to hire, you don’t usually even know if you’re using the right colors.
Startups are research operations until they get traction, and then they become research operations that make money. To compete in today’s marketplace, data and analysis must be central to every decision.
What’s Hard About That?
The problem with being research and data-driven is that you need to be ready to hear answers to the questions you’re asking. For many startup founders, the guiding, motivating vision is of their product smoothly being adopted by an accelerating number of users, leading to success, funding and fortune.
Nothing works that way.
Other people have other plans, priorities and preferences, and as your clean vision of the product hits the market, only honestly addressed feedback will allow you to make the corrections and pivots needed to find the magic formula.
The lesson of lean isn’t just that you should test everything, research as much as you can and the react appropriately.
The lesson is that you cannot afford not to.