Never before have pharma companies had access to as much information as they do today. Production data, quality data, MES data, historical process data, real-time KPIs—plus dashboards for virtually every use case. This should actually make decision-making easier. In many organizations, however, the exact opposite is happening.

More data, less speed

With every new data source, transparency increases—but so does complexity, in most cases. In practice, more available information often means more coordination, more reports, and more metrics. These are then discussed in an increasing number of meetings before anything actually happens. In the end, the organization knows more, but it doesn’t necessarily make decisions faster or better.

Many companies are investing heavily in data platforms, data quality, analytics, reporting, and AI. Yet the biggest misconception underlying many transformation programs is that transparency is equated with impact. Transparency is important, definitely, but creating it is only the first step. Between insight and action lie other crucial levers: decision-making processes, governance, accountability, and prioritization. If these are missing, an almost critical situation arises: the organization recognizes its problems very clearly but still fails to solve them.

Four questions every organization should answer

1. Who prioritizes new use cases?

Not every idea should be implemented (immediately); the challenge lies in evaluating and prioritizing them.

2. Who makes decisions when goals conflict?

Production, Quality, IT, and Business often pursue different goals. Especially in regulated environments, Quality Assurance (QA) frequently has the final say. Ultimately, someone must be empowered to make decisions; otherwise, the conflict simply remains unresolved.

3. Who is responsible for the business value?

Responsibility for the platform alone isn’t enough. The business value also needs an owner—someone who takes ownership of it. We already asked this question in the first post of this series and see that it’s relevant in other contexts as well.

4. Who decides on the rollout?

Even the best solution is of little use if, in the end, no one makes the decision to scale it. This pattern may also be familiar to regular readers. In the second post of our series, we identified it as one of the most common scaling pitfalls.

What real maturity looks like

Anyone who wants to honestly assess the success of a digital transformation initiative should therefore look beyond just the technology. How quickly an organization makes decisions, how clearly it defines responsibilities, and how reliably it scales effective approaches often reveals more about its actual level of maturity than even the most detailed dashboard.

Today, data is rarely the scarce resource. Decision-making capability, on the other hand, certainly is. Those who develop this capability just as consistently as they do their own data platform gain a competitive edge that no rival can easily replicate: the ability to translate insights into better decisions and effective actions.

Meet Xenium at Pharma MES Europe 2026

How does data chaos turn into a decision, and how does that decision translate into measurable impact?

We’re dedicating a whole session to this question at Pharma MES Europe 2026 in Berlin: On October 1 at 4:45 p.m., our colleague Dr. Florian Werner will join our partner from cts to discuss why enablement is more important than technology alone when scaling industrial data—and why connected data alone simply doesn’t generate impact. Stop by!

Feel free to visit us at our booth and discuss successful transformation in regulated environments with our experts. We look forward to the discussion!