"Teaming involves a tentative, iterative approach to action that recognises the novelty and uncertainty inherent in every action between individuals." Amy Edmondson
To successfully innovate, companies need to experiment. That means creating an environment where employees’ curiosity is nurtured, where data trumps opinion, where anyone can conduct an experiment.
“In an increasingly digital world, if you don’t do large-scale experimentation, in the long term-and in many industries the short term—you’re dead.” — Mark Okerstrom, CEO of Expedia Group
If you value surprises, people will see failures not as costly mistakes but as opportunities for learning.
Don’t be too narrow in areas that merit experiments. Whenever there’s a high degree of uncertainty, conducting experiments is a cost effective way to test new ideas. This could be launching a new product or service or testing new approaches to working together.
Experimentation requires a data driven approach to making decisions. Empirical results must prevail when they clash with strong opinions, no matter whose opinions they are! This is hard because it goes against our natural biases. We tend to happily accept “good” results that confirm our biases but challenge and thoroughly investigate “bad” results that go against our assumptions.
When contemplating new experiments you must think carefully about the risks and ethics of the experiment. It’s great to test things out but it doesn't mean we can forget core codes of conduct or acting in accordance with our values.
Eric Reiss, author of the Lean Start-up, advocates experimentation or “validated learning.”
Validated learning is having testable hypotheses about the world, designing experiments to test those hypotheses, and analysing the data to evaluate your hypotheses.
The approach he suggests is Build-Measure-Learn:
Experimentation isn’t just a philosophy for how we launch products and services. We can and should adopt a similar open attitude to experimentation in how we work with colleagues. Creating carefully crafted experiments to see how it affects, for example, our levels of collaboration and well being.
If an experiment doesn’t work out, you stop or adjust, and little is lost. If it does work out, it’s a small win; over time these add up so that your overall efforts are focused increasingly on what and who matter most.