About 40% fewer backorders and up to 39% more output at critical steps

The challenge

The late backlog was an execution failure, and it touched everything leadership had promised: revenue in the quarter, delivery to customers and the credibility of the forecast. For every week an order stayed late, its revenue sat on the shop floor waiting to be invoiced.

Planning was unstable, and work orders went out late or out of step with capacity. Operators waited for material, people or instructions, and queues built up in front of a few machines while others stood idle. The floor had a long list of problems and no way of telling which one mattered most that week.

Opyflow's work

Opyflow started by measuring where the time went. Equipment effectiveness, a loss breakdown and a demand-versus-capacity view showed that the largest losses were flow losses: waiting, missing labour, missing material, setups and coordination. Machine speed came further down the list, so the first fix went to planning.

Planning got a daily review and firm rules for opening and releasing work orders, so starts matched capacity and the backlog priorities. On the floor, a dedicated water spider brought material to the line, so operators stayed at their stations. A structured shift handover carried priorities from one shift to the next, and a daily war room reviewed output, late orders and the day's constraint, with output reported by shift in view of the team.

Then the constraints came down one at a time: queue rules, layout and flow changes, work on breakdowns, and operators reassigned to machines where they were needed. What kept the gains from slipping back was a weekly KPI review, escalation by exception, and a named owner and due date for every action.

What changed

Backorders fell by about 40%, and backlog recovery became the measure the programme was run on. Daily output rose at the steps that mattered most, by 39% at a critical inspection step, 25% at a coating step and 15% at a core processing step, while production starts went up 13%. The extra output came from demand already on the order book, released by better flow, and it supported the quarterly revenue commitments leadership had made.

The longer-lasting change is in how the operation now runs. The constraint kept moving, from planning to starts, then to material, then to specific process steps, and each time it moved, the system found it and went after it.

Why does a late backlog grow when demand is strong?

Because work stops flowing. Late or badly timed releases, waiting and queues hold output down however strong demand is, so adding capacity alone would not have cleared this backlog. Here it came down once planning and starts were stable and each week's constraint was being removed.