Tactics like interviews, paper prototypes, and simple landing pages help us cheaply and quickly evaluate whether or not we have a problem worth solving.Īs we collect data from doing those lightweight experiments, as we reduce our level of uncertainty about the product we are building and the market we will be selling to, we earn the right to move to gradually higher fidelity experiments, eventually evolving into a fully functional system. We start out using very lightweight methods to validate assumptions. In the beginning of any project our level of uncertainty is very high, and thus only a correspondingly low level of fidelity in our experiments is justified. This diagram shows how we approach experiments over the life of a project. At Neo, we like to point our clients to this graphic: Risk, The Lean Startup Wayīefore I outline the specific method I use, let’s look at how risk plays out in the life of a startup. But how can you know which one is really the riskiest? It turns out there is only one scientifically valid method to identify it quantitatively. Some you may have an intuitive sense of their risk level based on how uncertain you feel about them, or how impactful they will be on your overall business model. If you have done a business model canvas, and you should have, you’ve likely generated a dozen or more assumptions. You probably have a list of assumptions you’re making right now, as you stumble toward product-market fit, not sure which one is concealing the ticking time-bomb that will blow up in your face. Figuring out which it is can save you valuable time and money - and maybe mean the difference between the life and death of your company. And there is likely one that is disproportionately more responsible for your overall success than the others at any particular stage. Some assumptions are riskier than others. But very few actually walk the walk, actually use data to calculate risk in a way that is truly scientifically rigorous. It’s common these days for startup founders to talk of “lean”, of validating their assumptions with data. I am republishing it here so that Startup Patterns readers can have easy access to tools and tactics for small teams, Kanban being one of those tools. This post was originally published by Neo Innovation on their official blog. Being wrong in any one of these areas can take you out of the game. As a startup founder, you make assumptions about your customer, your product, and your market. Startups live and die on the validity of their assumptions. The Only Proven Method To Identify Your Riskiest Assumption
0 Comments
Leave a Reply. |