Recently I came across a term that was new to me: “Data Experience.” And I’ve been enthusiastically thinking it through ever since.

In many organisations today, data infrastructure and data literacy are already in place. Dashboards, KPIs and reports are available in abundance. And yet most decisions are still made without any real engagement with data.

Why? Because we tend to think of data processing primarily as a technical process – whereas it is, above all, a process that people go through. Especially when it comes to strategic decisions, people have to (mentally) process the data and analyses. Technology is there to help – not the other way round.

But this intellectual process is not just about the classic tasks of searching for and analysing data, or presenting it and telling stories with it. It is also about uncertainty in dealing with data, about critically questioning data and analyses, and above all about mentally weighing different courses of action against what the analyses show. We do not want to reserve this only for trained data scientists, but to think of it much more broadly as a democratisation of data.

In this sense, “Data Experience” (DX) for me describes the human experience of using data to gain orientation, construct meaning, build trust and make responsible decisions.

And the challenge is to enable a positive experience here and now :-)

So what happens next with this topic?

At Impact Distillery, we want to develop a concrete consulting offering and a tool suite for “Data Experience”. As part of this, we are continuing the work on our tool “Graphite”, with which Larissa Wunderlich and I have been developing multi-layered data reports for years in order to enable a deeper engagement with analytical results.

With kaleidemoskop, Martin Manhembué and I are developing a platform for politics and public administration to integrate data and forecasts into socio-political decision-making processes – currently, for example, with the city of Rostock. Here we want to optimise DX for planning processes in public administration.

At DBU, I am currently developing a module on “Data Experience” for our Master’s programme “Data Science & Management”. And of course there is still more than enough need for research – for example on the question of how LLMs can support analyses and their interpretation as “research assistants”.

If this topic interests you too, I’d be delighted to hear from you – whether feedback, collaborators, projects, creative input, etc. :-)