Customer insights aren’t set up for product impact over the long haul
Root causes of research waste in tech (1 of 3): Preparation
When it comes to managing their knowledge, researchers in tech have an isolation problem. Different researchers, from different disciplines and silos, keep delivering isolated reports. Generally speaking, they’re not connecting many dots across their work. It’s an unfortunate industry standard that some leading organizations are trying to change — and you can too.
In the conventional approach, reports typically cover only a self-contained set of samples from a single study. Related evidence may be abundant in other studies, but individual reports are often scoped to exclude that learning. Researchers effectively stick to their ‘own lane,’ favoring a highly cropped style of investigation. This cropping results in a less persuasive problem space for decision makers to consider.
When consuming these reporting outputs, it can feel as if prior research doesn’t exist — even earlier work by the same author. That ‘old’ project? Well, that’s in a different folder.
Individualistic reports also present research studies as sequential units of work. They cover a certain timeframe in the calendar. When a study is just a sequential unit, researchers mainly communicate and activate their new learning around a concluding date. Research projects move fast, and then it’s on to the next set of questions and the next report.
This approach can work fine for quick studies to inform narrow and time-sensitive decisions, such as checking in on a leader’s assumption about the market. The problem is that most studies aren’t actually so narrow.
Customers’ experiences reach out from microscopic questions to hint at adjacent and macroscopic insights. In effect, a lot of learning gets left on the table.
What’s more — even when an insight is directly within the scope that an owning team agreed to — those same teams may still deflect crucial insights around the time they’re delivered. Busy decision makers can perceive these insights as excess given their current workload. The influence of those deflected insights could land far outside of the study’s timeline, as part of future planning cycles.
Many researchers complain about the difficulty of informing larger-scale, future-oriented work in product development, especially as organizations grow. They want to shape the envisioning and prioritization of efforts by product, marketing, sales, customer success, and other owning teams.
They want to achieve overarching impacts that don’t fit within any one study’s timeline — but they haven’t prepared their outputs to deliver those impacts when they matter.
Research learning hasn’t been compiled, and it isn’t ready to be usefully plugged in.
It’s true that it’s no small task — but it’s crucial for activating research wealth.
Much more to come on these topics in forthcoming ‘Stop Wasting Research’ book for Rosenfeld Media.
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