This post describes a fast follow startup and the implication for how that startup learns. Define Startup A startup is a market hypothesis looking for validation. It’s an organization in search of a business. If they’ve accepted funding, then it’s a group of people looking for a liquidity event. Define Follow Follow means imitation. It means that an entrepreneur or a herd entrepreneurs have been observed pursuing a particular product-solution-market fit, or a hypothesis, and some founder wants to join the herd. Define Fast Fast means that the organization is imitating fast enough to nip at the heals of the lead innovator. It is imitating fast enough to be contention of overtaking the leader, or close enough to experience a[…]

It’s easier to link to this text than it is to repeat the intuition every time. Those who learn fastest win One of the core reasons why, as I write this in mid-2018, Silicon Civilization has the world in their teeth is because they figured out that it wasn’t just about learning. It was about learning quickly. Look at it from their perspective. A startup is a hypothesis looking for validation. Those startups that are able to learn fastest have a greatest chance of pulling up before the runway runs out. Those that learned survived takeoff. Those that really thrived never stopped learning. They win because they got really good at learning. It isn’t purely about data, it’s about how[…]

Data scientists spend so much time focused on learning: both machine learning and human learning. A machine can learn. A data scientist spends a lot of time just trying to persuade a machine to learn. It just takes a lot of labelled data. What about collections of people? Organizations can learn too. It’s just that the data isn’t all labelled well. Why Organizational Learning is Important I was so impressed with Carl Anderson’s synthesis two years ago, about Data Driven Cultures, that I unpacked it and¬†applied it to startups and strategy. Coming back to it now, in 2018, a lot of what he was saying is purely about learning. Carl Anderson, 2015, described a data driven culture as on that:[…]