Be Decision-Driven, Not Data-Driven
Seven points to consider in your collaborative decision-making process
The tech media is obsessed with data. But after eight years of measuring corporate data literacy, only 24% of companies report have reached data-driven nirvana. That’s fewer companies than last year.
Maybe being data-driven is the wrong goal.
Researchers Bart de Langhe and Stefano Puntoni think so. They advocate becoming decision-driven, not data-driven.
The distinction might seem small, but it’s not. It’s like communists versus capitalists, democrats versus republicans, or Red Sox versus Yankees fans.
Decision-making culture isn’t as cut-and-dry as saying Boston is a better sports town than New York. Data science is both creative and technical, like building a house — architects, designers, builders, and plumbers must work together. At first, the architect leads; during construction, the builder leads, in the finishing stages, design leads; the homeowner is the ultimate decision-maker.
Decision-driven thinking differs from the data-driven approach in seven ways:
- Start with questions, not data. Decision-driven thinking spends more time designing questions. Measure questions twice, cut data once!
- Decision-makers lead projects, not data scientists. The homeowner sets the tone, not the builder.
- Ponder unknowns more than knowns. In retail, a common data-driven project figures out how to optimize loyalty programs; decision-driven thinking explores what makes customers wobble in the first place.
- Look wide first, then dive deep. Data-driven teams often dive head-first into the pool of data they already have. Puntoni and de Lange suggest decision-first teams look “wide first, then narrow.”
- Build new data boxes. When you start with questions, you quickly find you’re missing data. Decision-centric teams more quickly identify the need for new surveys, simulations, or third-party data.
- Spot and reduce bias. By embracing a wider team upfront, decision-led teams tend to be more diverse. Diversity helps root out bias by questioning assumptions.
- Not rearview mirror. Data-driven thinking starts with historical data that accounts for what already happened. While the past might be prologue, pre-pandemic patterns might not still apply.
Pablo Picasso said, “the problem with computers is all they can do is provide answers.” His message is profound: don’t let tech lead; lead your tech. Be decision-driven, not data-driven.
