The answer often lies not in technology, but in behavior. Therefore, the thesis of this article is: a good data solution influences human behavior. And that is exactly why it is crucial to take this into account when developing your solution. Because only when your behavior changes will the use of the data solution also change.
It happens more often than you think: you make something beautiful, the launch is a party, but then usage drops. Your product ends up on the digital shelf. Not because it was technically bad, but because it is not sufficiently embedded in people's daily work. The honeymoon period is over and a return to old behavior creeps in.A good data solution must therefore do more than just provide insight. It must facilitate, encourage or even provoke desired behavior. This requires a different way of thinking: from data as an end product, to data as a behavior changer. Take out your notepad.
Work from back to front
The first step? Work from back to front. Ask yourself not "What can we measure?" but "What do I want people to do differently?" Do you want a team to plan better, respond faster to risks or set priorities more sharply? Once you have that in focus, you can reason back to the information needed to do that. When will my user use this report? Not "at every month start," but take it a step further. This person needs to show that they have a grip on the business, that quality is in order, and that the course set fits with changes in the coming months. Show not the results, but the process.
This approach helps avoid building a technically sound dashboard that solves nothing. It ensures that you're not presenting nice-to-know info, but really contributing to behavior change. You raise the bar: don't just deliver, but activate. Provide insight into the knobs that can be turned.
Create personas: data for people, not for systems
A common mistake is that we design our products from roles or departments: 'management', 'team leader', 'procurement'. But people are more than their function. They have goals, frustrations, ways of working, experience, digital skills - and these vary greatly.
Personas help you make your data solution truly useful. Not for "the user" in the abstract sense, but for a concrete human being with specific needs. And that's exactly where behavior change begins. Is the data solution for a larger group of users? Then you still need to make sure those pain points are resolved.
Do an internship day: experience the practice
Want to really understand how your product will be used? Spend an internship day with the team you are building for. Sit with the department, watch consultations, listen to phone calls, and notice where people get frustrated or happy. Be a fly on the wall.
This often yields unexpected insights. Perhaps it turns out that the morning meeting in which your dashboard was supposed to be discussed is always rushed. People are late so the agenda is shortened. The result: your dashboard is not discussed. Or that people already use a self-created Excel sheet that better fits their rhythm. You discover the informal processes and unwritten rules - the very things you need to build a solution that does work.
Get representatives by job group
Behavior change rarely works top-down. If a manager says, "Use this dashboard," that doesn't automatically mean it will happen. People follow their peers, not their managers. That is why it is essential to involve a representative for each function or task group in the development and implementation.
Such a person acts as an ambassador, a bridge between practice and technology. They can provide feedback on what does and does not work, and convince their colleagues on the basis of content. This increases the acceptance and continued use of your product.
Changing needs? That's okay
And another important thing: it's not a big deal if your data solution stops being used after a while. That may feel like failure, but it's not. Sometimes the problem is solved, or the need has changed. Consider:
- A policy change that makes the old KPIs irrelevant.
- A market environment that requires different insights.
- A team that has matured and needs less direction.
We want a sustainable solution, long-term adoption, a return on investment. And of course: it's a shame if something falls into oblivion immediately after delivery. But that doesn't mean that every data product must continue to be actively used for years to be valuable . Data solutions are not there to last forever - they are there to solve a particular issue, provide insight or influence behavior. And once that goal is achieved, their use may decline. In such cases, it is precisely a sign that your product has done its job. Think of it as a bridge: once people get to the other side, it makes sense that they will walk further. Indeed, a good data product helps users become independent, so they are less dependent on you. The market is changing, the business direction has changed, and laws and regulations are interfering as well.
In short: a good data solution influences human behavior. And that doesn't happen by itself. It requires:
- Working from back to front: what behavior do you want to see?
- Creating personas: who are you really designing for?
- Run an internship day: experience how people really work.
- Representatives per group: provide ambassadors.
- And accept that sometimes goodbye is good: use is not an end in itself, but a means.
