When making product decisions, should you rely on your intuition or on data? I have previously written about how to become more data-driven, and I have also written about the perils of becoming data-driven. So, which is it? Naturally, both are important. A product without a vision guided by intuition will fail, as will one that does not observe how its users are behaving and use those insights to guide further development. So, you need both intuition and data in different contexts, but your life without data will be much harder. Here are some reasons why.
1. Data cuts arguments short
You can have endless arguments about opinions. Discussions about data are much shorter and more objective. Having data to back up your assumptions also levels out the playing field when you have particularly influential stakeholders that can be very aggressive in getting their points of view across into the product.
2. Data saves development time
Needless to say, building the wrong feature into your product is not an effective way of delivering value to your users. There is no better way to figure out what your users need than to gather data from them (through a variety of different channels) to make those decisions, rather than just to rely on intuition or anecdotal evidence. This idea applies to large projects, but also to smaller features in large projects. Should we rebuild our entire billing system? Do people need to keep multiple payment methods stored in their accounts? These are the kinds of questions at different granularities that we can answer by looking at data.
3. Data makes prioritisation easier
Knowing what your users really value in your product can make prioritisation decisions that much easier.
4. Your experts can be wrong
No matter how experienced the people you're collecting opinions from, people can be wrong. Or it just might be that their particular point of view on a certain topic is skewed by their experience on the subject and their decisions are being guided by projection bias. It might be that their proposed solution to a problem is the best for them, but might not be the best generic solution to a larger set of people. Different people perform the same tasks differently and solve the same problems differently. Trust your experts, but back up their opinions with data.
The opposite extreme can also be very bad. Products that are built exclusively on data, without an opinionated overarching vision, will likely be "lifeless" and that shows. Relying too much on optimisation also puts you at risk of reaching "local maxima" in your experiments, and the only way of climbing out of those is through exploring completely new paths that can only come from insights grounded in your product vision.
As with all things in life, the middle path is usually the best way to go. You need to have an opinionated vision to drive your product at the risk of it becoming lifeless, but at the same time, you should be relying on data to drive a lot of your product decisions and validating your insights.
In your experience, how do you handle these decisions when data is not available?