A stocked-out critical spare doesn't just delay a repair, it turns a two-hour job into a two-day one while the part gets expedited or fabricated on the fly. At the same time, most plants are also sitting on shelves of slow-moving parts that tie up cash and never get used. Both problems come from the same root cause, stock levels set by habit or gut feel instead of actual consumption data and criticality. Sign up to see what your own spare parts inventory could look like once it's data-driven.
-58% Stockouts
Reduction in critical spare part stockouts after moving to data-driven reorder points
+94% Inventory Accuracy
Stock record accuracy achieved once every issue and receipt was logged against a work order
-19% Capital Tied Up
Reduction in cash tied up in excess and slow-moving inventory after right-sizing stock levels
The Problem
Without consumption history tied to actual equipment and criticality, spare parts stocking tends to swing to extremes, some critical items sit at zero because nobody flagged them as high-risk, while low-criticality parts get over-ordered just to be safe. Stock counts also drift from reality when issues and receipts aren't logged consistently, so the number on the shelf and the number in the system stop matching, and planners lose confidence in both.
From Consumption Data To The Right Stock Level
Consumption History
Criticality Tagging
Min/Max Set
Reorder Alert
Stock Replenished
Without this chain, reorder decisions default to whoever last noticed a shelf running low. A CMMS runs it continuously, so min and max levels are based on how a part is actually used, not a guess made when it was first stocked.
Stock The Right Parts, Not Just More Parts
Oxmaint sets reorder points from actual consumption and criticality, then alerts before a critical spare ever hits zero. Sign up for a free trial to see it against your own parts data, or book a demo to walk through a cement plant rollout.
Spare Parts Inventory Before And After
| Metric |
Before |
After |
| Reorder point setting |
Set once, rarely revisited, based on habit |
Calculated from actual consumption and criticality |
| Critical part stockouts |
Discovered when a technician needs the part urgently |
Down 58% with reorder alerts ahead of demand |
| Stock record accuracy |
Drifted from shelf reality due to inconsistent logging |
94% accurate, tied to every work order issue |
| Capital tied up in stock |
High, driven by over-ordering low-use parts |
Down 19% with stock levels matched to real demand |
The Results
Fixing spare parts inventory isn't about stocking more, it's about stocking the right things. Once reorder points reflected real consumption and criticality, stockouts on the parts that actually matter dropped sharply, while cash stopped piling up on shelves of parts nobody was using, freeing up working capital without adding any risk to maintenance response time.
Frequently Asked Questions
Q
Why do plants end up both stocking out and overstocking spare parts at the same time?
Without consumption data tied to criticality, stock levels get set by habit, so high-risk parts that are rarely reviewed sit at zero while low-risk parts get over-ordered out of caution.
Q
How does criticality-based stocking differ from a standard min-max system?
A standard min-max only looks at usage rate, while criticality-based stocking also weighs how severe a stockout would be, so a rarely used but essential part still gets held at a safe buffer.
Q
Do we need a full physical inventory count before optimizing spare parts stocking?
A baseline count helps, but most plants start by tying every future issue and receipt to a work order, which corrects stock accuracy over the following weeks without a full manual recount.
Never Let A Critical Spare Hit Zero Again
Oxmaint sets reorder points from real consumption and criticality and alerts your team before stock runs out, so cash stops piling up on parts you don't need. Sign up for a free trial to see it against your own inventory, or book a demo to walk through a cement plant rollout.
