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Ask five people why production was down last week and you might get five different answers. Take a fictional manufacturer: Midlands Precision. They make components for the automotive industry and run 30 CNC machines across two shifts. On Monday morning, the Operations Manager looks at the weekly figures. Output was 6% below target. He opens the ERP. Several orders were completed late. He asks Maintenance what happened. They point to 14 hours of machine downtime. He speaks to

One of the most expensive machines in your factory might be a spreadsheet. A production coordinator will often spend time every day pulling figures from ERP, getting information from colleagues, updating Excel reports, checking emails and sending the latest numbers to management. Lets be conservative and call it an hours work. An hour doesn't sound like much. But over 250 working days, that's 250 hours a year. At £25 an hour, that's more than £6,000 for one person, before acc

A dashboard can make bad data look very convincing. OEE for example is one of the most useful and high-level metrics in manufacturing. It's also surprisingly easy to make look more accurate than it really is. A factory might report an OEE of 82.4%. It looks precise. But how precise is it? Was every downtime event recorded? Were planned stops separated from unplanned downtime? Is the “ideal” cycle time still accurate? Were short micro-stops captured, or simply ignored? Were sc

In our last few insights, we've looked at data hiding across a factory, the cost of small manual tasks, and how basic KPIs can be misleading. There is a common thread between all three: Before improving something, understand what is actually happening. Yet when a company finds a slow manual process, the first questions are often: “How can we automate this? How can we make this faster?” etc A better question is: “Why does this process exist in the first place?” Consider a simp

When someone says “digital transformation”, it's easy to picture a very large project. A new ERP. An MES implementation. Robotics. AI. A digital twin. A team of consultants, a long project plan, and a six-figure budget. For a large organisation, that might make sense. For an SME, it often isn't the best place to start. A manufacturer might get more immediate value from fixing five much more ordinary problems. None particularly glamorous. But they can have a very real impact o