Unpredictable spare-part demand, overstocked inventory, emergency procurement, and no linkage between maintenance cycles and stock planning.
$3.5M annual savings through optimized working capital and minimized unplanned downtime.
Inventory decisions driven by planner intuition; critical spares ran out while non-critical parts piled up.
Inventory reduced by 22%, stockouts dropped 35%, and procurement time fell 40%.
For this large industrial utilities operator, reliability wasn't just an operational goal — it was a contractual necessity. Every hour of downtime translated to revenue loss and penalty exposure. Yet despite investing heavily in ERP and CMMS tools, their spare parts management ran on guesswork. Procurement teams stocked excess quantities of low-value components 'just in case,' while critical, slow-moving items were frequently unavailable when needed most. Planners blamed suppliers for delays, suppliers blamed inaccurate forecasts — and the maintenance team blamed everyone. What the company truly lacked wasn't data. They had plenty. What they needed was insight — a way to connect the data dots between maintenance schedules, failure patterns, and procurement decisions.
With thousands of assets spread across substations and production sites, the utilities firm maintained over 10,000 unique spare SKUs — from motors and valves to specialized control boards. The ERP (SAP) contained purchase histories. The CMMS tracked maintenance tasks and breakdowns. But the two systems rarely 'talked.' As a result, spare parts were ordered based on outdated averages or personal judgment. Whenever breakdowns occurred outside the forecast window, the team scrambled with emergency orders, paying high freight and vendor surcharges. The irony: millions of dollars of stock sat untouched in warehouses — while critical machines waited for spares to arrive.
Still relying on spreadsheets for spare parts planning?
