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Process mining is quickly emerging as a critical tool for manufacturers looking to make smarter, data-driven decisions – but many businesses are still at an early stage in understanding its full potential.

Speaking ahead of the upcoming Manufacturing Digitalisation Summit, Carl Milbourne, Group Operations Director at Sertec Group, highlighted that at its core, process mining is about establishing a “single source of truth.” In complex manufacturing environments, decisions are often made based on assumptions or incomplete information. Process mining challenges this by extracting clean, reliable data from systems to reveal what is actually happening across operations.

“The biggest risk,” he explained, “is when people think they know the answer without really going into the data.” Without accurate data, businesses can end up chasing the wrong problems or making decisions based on opinion rather than fact. For Carl, the priority is clear – before solving any issue, organisations must first ensure the data they are working with is both accurate and meaningful.

““If the data isn’t clean, you can start forming opinions of what’s happening - but that's not how you arrive at a single source of truth.””

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This focus on data integrity is shaping a broader shift in digital transformation. Rather than simply adopting new technologies, the emphasis is now on how effectively that data is used. At his organisation, this has led to a “level up” approach – moving beyond initial digital adoption towards more structured, evidence-based decision-making.

A key part of this shift involves changing how teams approach problem-solving. Drawing on frameworks like structured thinking models, the business is encouraging teams to separate fact from opinion and ensure that decisions are grounded in measurable evidence. It’s a cultural change as much as a technological one.

AI also plays an important role in this evolution, particularly in manufacturing environments where systems are becoming increasingly complex. While many companies have invested heavily in advanced machinery and digital platforms, Carl notes that much of the available data is still underutilised. In many cases, systems rely on operator input rather than machine-generated insights, raising questions about consistency and accuracy.

The real opportunity lies in moving from reactive to proactive operations. Instead of logging issues after they occur, manufacturers are beginning to explore how data and AI can predict problems before they happen – and even recommend solutions in real time. However, this capability is not always fully embedded in the equipment itself, often requiring additional investment or integration.

Ultimately, process mining represents a crucial step in this journey. By providing clarity and transparency, it enables manufacturers to better understand their operations, unlock the value of their data, and lay the foundations for more advanced, AI-driven capabilities.

Carl Milbourne

Head of SASB Operations, Sertec