Startups operate effectively with less data and more uncertainty because they plan to learn and adapt.
When you work at the juncture of startups and large corporates, one difference is stark. Large corporates need much greater certainty to make decisions. Startups make decisions at much lower confidence levels.
A large part of the slow response of large organisations is the demand for certainty in decision making. Large corporates always need more information. For example, you don’t need to demonstrate the potential for a positive return, you need to calculate that return exactly and defend every assumption and element of the plan to win support.
Startups realise that businesses are made in the market, not in ever greater piles of data and better spreadsheets. Startups deliberately make decisions with less information because they know the best information comes from experimenting, doing and adapting. Wait too long and your beautiful data will be wasted as the opportunity closes or the data is out of date.
Corporates make decisions on the basis it is a one and only chance to decide. It has to be perfect. Most decisions aren’t actually irreversible or final.
Startups know the decision is imperfect. It always will be. The point of the decision is to start the process to learn and adapt based on the lessons from doing. Nobody learns anything new around a board table.
Making decisions with less than perfect information is a big challenge when you are used to the model of decision making in large corporates. However, just like the transition from perfect messages to working out loud, the change to less certainty and adaptation is a liberating one.
We can all benefit from being a little less certain and more open to learn.