The most interesting thing about this is not the request itself, it is the silence that follows it. A student writing a dissertation on predictive analytics in product development cannot find a single professional willing to talk. That is a problem, and it says more about the field than about the student.
Predictive analytics is supposed to be the tool that helps teams stop guessing and start building with data. It promises to surface patterns, flag risks, and surface opportunities before they become obvious. Yet here is someone trying to study exactly that promise, and the people who work with it every day are not answering. That should make every product leader pause. If the people closest to this technology cannot spare thirty minutes to help shape the next generation of thinking about it, what does that say about how accessible or human-centered the practice actually is?
We think the reluctance is not about time. It is about comfort. Predictive analytics still feels like a black box to many teams. The models work, but the reasoning behind them stays hidden. Talking to a researcher means explaining that gap, and that is hard to do when you are not sure you fully understand it yourself. The student is not failing to find interviewees because the topic is irrelevant. They are failing because the industry has not yet made its own methods transparent enough to discuss openly. That is a miss. A field that cannot explain itself to an interested outsider is a field that will struggle to earn trust inside its own organizations.
For anyone reading this who works with predictive analytics in product development, consider what you lose by staying quiet. The student is not asking for trade secrets or proprietary formulas. They are asking for perspective. Your experience, the wins, the failures, the moments when the model surprised you, is exactly the kind of raw material that helps turn a technical capability into a practical discipline. If you want predictive analytics to become more than a buzzword in your own company, helping the next wave of practitioners understand it better is one of the most direct investments you can make.
Here is the concrete point: Reply to that post. Give the interview. The student's dissertation will cite you, your work will gain visibility, and the field will get a little more human. That is how you make a technology accessible, not by marketing it, but by talking about it.