Data-informed decision making

Data-informed decision making is a balanced approach to using analytics. It's about using data as a tool to inform human judgment, not as a replacement for it. This is in contrast to being purely data-driven, which can lead to optimizing for local maxima at the expense of bigger opportunities.

The key idea is that humans and machines have different strengths. Humans are good at inspiration, creativity, and understanding the bigger picture. Machines are good at validation, optimization, and processing large amounts of data.

A data-informed approach combines these strengths. It uses data to test hypotheses, validate assumptions, and measure progress, but it relies on human intelligence to generate new ideas, set the overall strategy, and make the final call.

This approach avoids the pitfalls of both purely intuitive decision-making (which can be biased and unreliable) and purely data-driven decision-making (which can be short-sighted and lack context). It's a more robust and effective way to run a business, especially in a startup environment where the landscape is constantly changing.