Thought 01 · Digitalization
A maturity framework for digitalization
There are no shortcuts in digitalization. There are a number of steps that must be climbed. You can try to jump several at a time, but only if you deeply understand those steps—and your processes.
This is a mental model I use to build a shared understanding with domain experts about the digital maturity of the tasks within the processes they want to improve.
One of the main challenges in my work is closing the gap between technical and business people. The framework is deliberately simple: its usefulness comes from giving everyone the same language for discussing where a process is today and what a sensible next step might be.
Just make it visible.
It won’t solve all your problems, but making data visible in the right place can make a huge difference. The hardest work here is breaking information silos and consolidating what’s relevant.
A screen showing stock levels in front of a machine. A dashboard that pulls from three systems that never talked to each other.
Data living in silos, requiring an analyst to extract, or only visible to someone who already knows where to look.
A nudge at the right moment.
No need to monitor dashboards: the system proactively notifies you when something needs attention.
Stock drops below a threshold. A delivery is late. An anomaly appears in production output. You find out immediately, not at the end of the week.
Dirty or incomplete data and noisy systems. Too many false alarms—and everyone ignoring them—is worse than no alerts at all.
A nudge with a plan.
The system doesn’t just notify you; it gives you context and a recommended action. It helps, but you still decide.
Stock is low. The system identifies the supplier, checks lead time, and drafts a purchase order for your approval.
Jumping here before Alert is reliable. If you don’t trust the diagnosis, you won’t trust the recommendation.
Let it do its thing (but keep an eye on it).
The previous stages have built the foundation. Now the system acts autonomously on well-defined, high-volume, low-ambiguity processes. Humans handle exceptions and set the boundaries.
Routine purchase orders below a threshold, with known suppliers and within budget, are processed without human intervention. Edge cases are escalated.
Automating when human input is essential. Skipping stages and automating bad processes. Sleeping at the wheel: it still needs monitoring.
The framework isn’t intended as a rigid sequence for an entire company. A single process can contain tasks at very different stages. The useful question is not “How digitally mature are we?” but “What would the next useful level look like for this particular task?”
Next thoughtWhere AI fits—and why I distrust giant black boxes