You need one piece of data to know if your startup will fly: How many customers' eyes dilate when they hear your idea?
In a presentation Wednesday before an engineer-dense crowd at MIT, Steve Blank spent most of his time talking to people about talking to people. Blank is the serial entrepreneur who birthed the lean startup methodology, which he teaches in popular classes at Stanford, Berkeley, and elsewhere. Chatting with Roman Lubynsky, a senior advisor to MIT's Venture Mentoring Service, Blank returned repeatedly to the dangers of entrepreneurial myopia. Cool though your product may be, if customers don't love it like you do, then it's just a lab experiment.
Imagine visiting a potential customer--no prototype required--and sketching your idea on a whiteboard, Blank enjoined the audience. "They, go 'you are not leaving until we figure out how to do a deal,'" he said. "While you think that is a joke, I would say if you don't have any of that indication early on, you don't have a business."
Lean methodology is essentially the scientific method applied to entrepreneurship (an observation Blank attributed to an official at the National Science Foundation). Put simply, it is a series of experiments and observations. Lean begins with a set of hypotheses: an apt word that reminds founders they cannot plan--only guess. What is your value proposition? Who are your customers? How will you make money? What resources do you need? The answers to those and other foundational questions, said Blank, lie "outside the building."
"You are the smartest person in your building," said Blank. "But there is no way that you are smarter than the collective intelligence of your potential customers."
Students in Blank's Lean Launchpad classes must talk to 10 to 15 customers a week, for 10 weeks. "You are asking, 'do you have this problem?'" said Blank. "Eighty percent of the time, the answer is 'no. But too bad you are not solving this other problem over here.'"
The goal of talking to customers is not to validate the founder's vision--by getting as many people as possible to agree--but rather to inform it. Blank told the story of a student team working on an app that set the price at $9.99 because that's what 47 out of 50 people said they would pay. They didn't bother to log data from the remaining three people, whom they deemed "outliers." When Blank questioned team members in front of the class, they explained that the outliers had said they would pay $25,000 for the product if it were an enterprise solution. "And that's what they eventually turned it into," said Blank. "In fact the product is not now sold for $25,000. It is sold for $250,000."
Blank offered another student example to illustrate the concept of minimal viable product (MVP), which he defined as "whatever gets us the maximum amount of learning on our hypotheses." Not long ago, a team that had taken his class approached him about investing $500,000 to help build a prototype drone equipped with hyperspectral scanning technology. Their idea was to survey croplands and collect data about water and nutrient levels. Blank told them they needed just $500. "They weren't in the drone business or the hyperspectral scanning business," said Blank. "Their business was selling data to farmers."
All they needed, said Blank, was to "show the farmers a spreadsheet and say, 'if we can give you this data on a weekly or daily or hourly basis, would you buy it?'" The team later realized that crop dusters were already flying over farms, potentially rendering drones superfluous.
Toward the end of his session, Blank expressed optimism that Boston could develop an entrepreneurial ecosystem--including plentiful risk capital--to rival Silicon Valley's. There is a "giant sucking sound of talent going to the west coast. I don't think should be the case," said Blank. "Smart scientists and entrepreneurs should not be thinking about how to leave but how to stay."