Manual work order prioritization, uneven workload distribution, missed production deadlines, and frequent rework due to scheduling errors.
$4.1M annualized benefit through optimized resource utilization, reduced idle time, and faster throughput.
Planners spent 3–4 hours daily reviewing hundreds of orders manually, often resulting in late deliveries.
Work order prioritization became automatic, planner effort dropped by 72%, and on-time completion rose 25%.
For a leading global manufacturer of industrial and construction equipment, every minute of production downtime equated to lost revenue. The problem wasn't broken machinery or delayed material — it was something far less visible but equally costly: manual planning inertia. Every morning, a team of experienced planners gathered around spreadsheets and printouts, trying to decide which jobs should take priority. Their decision-making was based on instinct, experience, and sometimes even pressure from sales teams. The result? High-value orders occasionally missed deadlines while low-impact ones consumed precious machine time. The leadership team recognized this bottleneck not as a workforce issue, but as an information orchestration problem — one that required intelligence, not just automation.
The manufacturer operated several assembly lines across multiple geographies. Each day, hundreds of work orders were released through SAP, covering everything from custom hydraulic assemblies to precision-milled engine components. Planners manually cross-referenced due dates, resource availability, and shift schedules — a time-consuming, error-prone process that left machines idle while urgent orders sat in queue. In an industry where clients measure reliability down to the hour, this manual dependency was unsustainable.
Still running your planning meetings in spreadsheets?
