Data is not an asset until someone pays for it

Many hundreds of GP practices, live data, and almost unlimited technical possibilities.

So why is the real work somewhere else? Notes from building a healthcare data warehouse and analytical space – and what Big Pharma actually asked for.

Oscar Wilde wrote that a cynic is a man who knows the price of everything and the value of nothing.

The data business suffers from the opposite condition. Everybody knows the value of data – it has been “the new oil” for about fifteen years now. Hardly anybody knows its price. Or, more precisely: who would pay it, for what, and under which conditions.

For the past couple of months part of my work has been exactly this issue.

Together with a leading Hungarian medical software company, we have been building a data warehouse and analytics space on the live healthcare data of many hundreds of primary care practices.
Real patients, real prescriptions, real diagnoses – not a survey, not a sample, not a model.

Technically, our capabilities are close to limitless.
Warehouse, analytics layer, queries, dashboards: the engineers are not the bottleneck.
(Regular readers will recognize the pattern from my previous post. Technology is rarely the bottleneck.)

So what is it then?

Lesson one: Pharma doesn’t buy data. It buys answers.

We sat down with Big Pharma management several times. They appreciated how many records we had in our system. They liked how our system goes like clockwork.

Then came their questions – clinical and commercial at the same time, and always related to the business value of the concrete issue. The kind you can only answer if you understand the market.

I won’t list them here. Some things are better discussed across a table than on a blog.

But I can tell you what they had in common: every one of them was a product specification in disguise.
A data warehouse and analytical space becomes a product the moment it can answer the buyer’s question – not when it reaches a certain size or complexity.

After carefully listening to their challenges we have fine-tuned and delivered a sound concept.
We have agreed during several rounds of discussions on which gap-filling queries and analyses Big Pharma actually needs, and we have presented them the decisive part of what has already been developed. The pilot build is now in the planning phase.

Lesson two: The hard part is not technical. It is the system of consents.

Here is the part nobody puts on the pitch slide.

In parallel with the development, we have been designing – and now implementing – the legal architecture: primarily GDPR, and the professional consents that handling healthcare data requires.
It is slower than any code, and it cannot be skipped.

I will spare you the details – partly because they are long, partly because they are ours.
The principle, however, is simple: in healthcare data, the question is never only “can we do it?” It is “who may decide, who must agree, and who must know about it?”
And every answer has to hold up in front of a lawyer, a doctor and a patient at the same time. Not to mention authorities.

The direction in Europe is clear, too. Under the European Health Data Space regulation, the rules on secondary use of health data start to apply for most data categories from 2029, through permits issued by health data access bodies (European Commission). Whoever builds trust into the system now will not have to rebuild it later.

None of this is glamorous. All of it is what makes the data sellable – and defensible.

Lesson three: An asset needs three owners.

Data becomes an asset when three things meet:

1. a question someone is willing to pay to have answered,
2. a legal path that survives audits,
3. and the trust of the people who generated the data in the first place – doctors and patients.

Miss one, and what you have is not an asset. It is a liability with a nice dashboard.

Wilde’s cynic knew the price of everything. In health data, you have to earn the price – one consent, one specification, one honest answer at a time.

From technology to revenue: in this case the “through what” is not code. It is trust, put into a system.

You may have noticed that I have left out the details. That is deliberate.
The interesting part of this story does not fit into a blog post. It needs two coffee cups on the table.

So here is my reversal of the internet’s favourite tip jar.

Don’t buy me a coffee. If you are seriously interested in the details, let me buy you one.

Budapest, Tatabánya or a video call – in which case you bring your own cup, but the offer stands.
Write to me at priegl.gabor@gmail.com or through the contact page.

Gábor

I help owner-led tech companies turn advanced technology into revenue. If that’s you, write me: priegl.gabor@gmail.com