The idea that perfect information is out there is an empty pursuit — it’s chasing the illusion of certainty.

“You can’t know that things will turn out all right. The struggle for certainty is an intrinsically hopeless one — which means you have permission to stop engaging in it.” – Oliver Burkeman, Four Thousand Weeks

Source: From Data-Driven to Decision-Driven

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You’ll rarely have all the data you want when making a decision. And the reality is that data isn’t usually conclusive. It can be interpreted in multiple ways. At some point, you’ll still have to make a decision.

The desire for more data is sometimes used to avoid making decisions. But it’s important to make the best decision you can with the data you have. And in the event more data comes along that changes your mind, then the work of figuring out how to iterate in that direction begins. Iterative innovation prevents analysis paralysis. 

Be mindful of chasing the illusion of certainty as you conduct research.

Certainty is an emotional state that we crave — the alternative, of course, is uncertainty and ambiguity, which is viscerally uncomfortable to stomach.

Source: From Data-Driven to Decision-Driven

Or, as the ever-wise Cameron Moll said:

There should always be some level of subjectivity in choosing the best design outcomes.

We can throw as much data, research, and strong narratives at decision-making as we want. But the best decision is often "I feel we should go this direction" by experienced practitioners & leaders who are informed by — but not entirely driven by — objective inputs.

Research and design validation? Essential. But data is just one piece of the puzzle. It’s still important to consider other inputs like feedback from stakeholders and even your intuition. The advantage of software is that corrections can almost always be made later. So don’t get stuck in analysis paralysis - especially for things that are low-risk and can be easily changed later.

This matrix nails how I think about research:

Source: A Framework for Prioritizing User Research

I’ve grown to prefer the phrase “data-informed” over “data-driven.” Sometimes, we’re afraid to decide because we don’t have a full academic-level research summary. But rigorous research isn’t required for every decision. Calibrate the research to the level of risk and problem clarity at hand.

Jeff Bezos coined the “70 percent rule” at Amazon.

"Most decisions should probably be made with somewhere around 70 percent of the information you wish you had. If you wait for 90 percent, in most cases, you're probably being slow."

Research is about reducing risk, not guaranteeing success. We’ll inevitably get it wrong sometimes. Success comes through iteration and quickly making improvements.

As my friend Brandon used to say, “Make mistakes of boldness, not timidity.” Waiting until you have every last data point is a mistake of timidity. As long as we’re going to make mistakes, let’s err on the side of boldness and have a bias for action.