Vaughn Tan, an organizational researcher and author of The Uncertainty Mindset, argues that organizations routinely mistake uncertainty for risk. Targets, forecasts, and cost-benefit analysis assume the choices and their odds are already knowable. New ideas rarely arrive with that evidence attached.
It probably didn’t die because it was bad. Your organisation wanted something new, so it did what its machinery does: it made the new thing a big bet. Under uncertainty, big is the wrong move in two ways. A big bet on the new is not bold; it is necessarily blind, because you cannot know enough up front to justify it. And a big, visible bet is just what the parts of an organisation that want to keep things the same will move to get rid of. The better the idea, the bigger the bet you are tempted to make, and the bigger the target you paint on it.
The trouble with a flagship is that its visibility becomes part of its risk. Tan’s alternative is to make experimentation less dramatic and more routine:
The moves to make are the undramatic ones. Start small enough that no one sees a threat. Make tests cheap, fast, and numerous, so failure is survivable: a portfolio of small bets each placed to answer useful questions, instead of one big bet placed to create the impression of decisiveness. Disguise the innovation as an unremarkable update to standard procedure. The idea is to not fight the system head-on.
This is a useful distinction for design leaders. A large commitment tries to prove confidence before the team has learned enough to deserve it. A portfolio of reversible tests turns the same resources into evidence.
If this sounds like working behind the organisation’s back, consider what the alternative gambles with. The innovation big bet stakes public money and public trust on a guess, faking certainty about something genuinely uncertain. The small, quiet experiment spends almost nothing to buy real knowledge, and the public is never exposed to a large, irreversible downside. Being responsibly sneaky isn’t cheating. It’s how you take care of public resources in a world you cannot predict.
The responsible move under uncertainty is to keep failure cheap and learning continuous. In other words, get prototypes in front of customers as soon as you can.
