Ask a sample group of people why startups fail, and, assuming they have a vague understanding of the modern world, they’ll give you a host of different reasons. Misfiring team. Poor product. No market. No business model. Delusional founder etc. And undoubtedly, they are all true depending on the circumstances in which the particular startup failed.
But there is a root problem to many of these problems. And it’s a simple one: a lack of tracked data, or perhaps simply a wilful ignorance of it. Data is the only means of empirically measuring the performance of your startup and building good practices upon proven foundations. In other words, tracked data gives you actionable insights where you would otherwise be guessing. Build upon what you already know to be true and your chances of avoiding ultimate failure will be much greater.
What this means is that failing on a low key level can be invaluable for the knowledge it provides; and as such, a failure can be considered a success if you properly understand and learn from the data you receive. Knowing what not to do can thus be as important as knowing what to do throughout the early stages of your venture.
This is the important point about success and failure. Micro-failures are useful stepping stones to ultimate success provided the data is tracked and learnt from after each attempt. As Elon Musk, CEO of SpaceX and Tesla Motors, puts it; “If things are not failing, you are not innovating enough.”
Here’s the article that got me thinking: Why do Startups Fail?