Decision-making: driven by opinion vs driven by data

The two extremes of product decision-making

Out of all the cultures out there, I’ve had the luxury to experience (and survive) both extremes of the decision-making spectrum:

• Decision-making driven by opinion (mostly HiPPO) — a big boss decides what a team (department, company) is going to do, and good luck dealing with it if it doesn’t make any sense. Working in this environment isn’t very pleasant unless you’re the one making the decisions.
• On the opposite side of the scale, there is decision-making driven by data. Sounds great since supposedly anyone can propose a change given the right set of data (and very often they can). But this also results in the inability to make decisions when the data is not there (no, you don’t need to run an A/B test to decide whether you need a 2px or 4px border-radius)

With neither of them being exactly perfect, how do you find a balance between?

Here’s the magic formula:

Support your opinion with data whenever you can

This not only will increase buy-in from your colleagues but also, while looking for the data, you might discover your opinion was wrong in the first place.
Jedi-level: actually look for the data that proves you wrong.

Decide explicitly when to seek more data and when to learn by doing

You’ll never know everything you need to know. What are the risks you’re willing to take to learn later if you’re right, and which are the assumptions needed to be validated upfront?

Disagree and commit

One of the biggest blockers for the teams without data and HiPPO to tell what to do is striving for consensus. This is simply unproductive since:
1. They get incredibly slow
2. They get an average solution no one is happy about
3. No one is accountable because it was a shared decision

In reality, everyone has different experiences (designers don’t usually vote on Back-End architecture) and different stakes (a business owner should be able to overwrite whatever decision seems risky since they’ll be the one taking the downside) in the matter. So decisions should be made accordingly, and after they are done, everybody is committing to them.

This approach allows sticking with evidence-based decision-making while avoiding analysis paralysis. In the end, it’s good to be slightly data-obsessed, but only slightly. Where exactly the sweet spot sits depends on how risk-averse the company is — you probably willing to take more risks running an e-commerce site than a medical institution.

Read more on how to bring evidence to product development:

How to combine qualitative and quantitative insights for better design decisions

And decision-making in product teams

How to make complex decisions in product and dev teams

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