Spare parts optimization: how to reduce stockouts and inventory costs
Just a 20-minute read
Spare parts optimization is the discipline of stocking exactly what an operation needs to keep critical assets running, without tying up capital in parts that never move.
Done well, it lowers emergency procurement, protects uptime and frees warehouse space. Done badly, it produces the two failures maintenance teams know too well: the stockout on a Friday night and the shelf full of impellers nobody has touched since 2019.
Introduction
Every storeroom eventually splits into two populations of parts. A small group gets pulled constantly and everyone knows where it lives. A much larger group sits untouched, quietly aging on a shelf, purchased for a machine that was decommissioned two turnarounds ago or for a failure mode that has not repeated since. Industry reviews of manufacturing storerooms consistently find that somewhere between a fifth and two fifths of MRO inventory falls into this second, non-moving category, while a meaningful share of unplanned downtime traces directly back to a part that should have been on the shelf and was not. Both problems usually coexist in the same warehouse, which is why fixing one without the other rarely works.
The instinct to solve this by buying more, “just in case,” is understandable and almost always wrong. Excess stock does not eliminate stockout risk, because the parts that get overstocked are rarely the parts that fail. What actually reduces both problems at once is data discipline: knowing which parts protect which assets, how long they take to replace, and how often they are genuinely consumed. That data already exists in most plants. It is sitting in work order history, purchase records and technician memory. The rest of this article is about how to extract it and turn it into a stocking policy that a CMMS can enforce automatically, instead of one that depends on whoever has been at the plant the longest.
1. Why spare parts optimization is a reliability problem, not just a cost problem
Treating spare parts as a procurement line item misses the point. A stockout on a non-critical, redundant asset costs a purchase order and a delay. A stockout on the only bearing that fits the main extrusion line shuts down production, and the cost difference between those two events can be a factor of ten or more. Several industry reports put roughly a quarter of unplanned downtime events at plants down to a spare part that was simply not available when it was needed, and emergency procurement of the same part typically runs three to five times its normal purchase price once expediting fees, air freight and after hours vendor premiums are added.
Meanwhile, carrying cost never sleeps. Every part sitting in a bin accrues capital cost, insurance, warehousing space and obsolescence risk whether or not it is ever installed. Estimates of MRO carrying cost vary widely across sources, generally landing somewhere between 15 and 30 percent of average inventory value per year for typical industrial storerooms, higher for parts tied to legacy or soon to be retired equipment. Run that percentage against a storeroom carrying a few million dollars in stock and the annual bleed becomes obvious even before a single stockout occurs.
The two failure modes share a root cause: parts are stocked based on habit, purchasing convenience or fear, rather than on the actual criticality of the asset they support and the actual variability of their consumption. Fixing that requires classifying parts properly before deciding how many of each to hold, which is the subject of the next section.
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2. Core techniques for reducing stockouts without inflating inventory
Spare parts optimization is not one technique. It is a small set of disciplines that work together: classify parts by criticality and value, size stock levels against real demand and lead time, let the CMMS police reorder points instead of a spreadsheet, and periodically clean out what should never have been kept. Each of the four below addresses a different part of the problem.
1. ABC and criticality classification
ABC analysis ranks parts by annual consumption value, typically putting the top 10 to 20 percent of SKUs (Class A) into a tight control regime and letting low value Class C items run on simple, loose rules. Layering criticality on top, sometimes called VED analysis for vital, essential and desirable, corrects the biggest flaw in pure ABC ranking: a cheap seal that stops the only compressor on site is more important than an expensive part on a redundant, non critical line, regardless of what its purchase value suggests. Classification should be reviewed at least annually, since criticality shifts every time an asset is added, retired or reconfigured.
2. Reorder point and safety stock calculation
A reorder point tells the CMMS when to trigger a purchase requisition, and it is only as good as the lead time and consumption data behind it. The basic formula is average daily usage multiplied by lead time in days, plus a safety stock buffer sized to the variability of both. For Class A critical parts, a safety stock equal to 50 to 100 percent of average lead time demand is a reasonable starting point; Class C items can often run with none at all. The mistake most plants make is setting reorder points once and never revisiting them, even as suppliers change lead times or a part’s failure frequency shifts after a reliability improvement.
3. Lead time and supplier risk mapping
Two parts with identical consumption histories deserve very different stocking policies if one ships from a regional distributor in two days and the other is a single sourced casting from overseas with a twelve week lead time. Mapping realistic, current lead times, including known seasonal or geopolitical disruption risk, against criticality tells you which long lead time parts justify holding stock regardless of low usage. This is where many storerooms get caught out: the part fails once every three years, looks unnecessary to stock by consumption value alone, but a stockout means three months of downtime while a replacement is manufactured.
4. CMMS-driven demand history and automated reordering
None of the above holds up if it is calculated once in a spreadsheet and then forgotten. A CMMS that ties parts consumption directly to work orders and asset records gives a live, accurate picture of actual usage, not the purchasing department’s best guess. That data feeds ABC reclassification, reorder point recalculation and dead stock identification automatically, and it lets the system generate purchase requisitions the moment stock crosses a threshold instead of waiting for a stores clerk to notice an empty bin during a routine round.
3. Frequently asked questions
Common questions maintenance teams ask when building a spare parts strategy
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1. What is spare parts optimization
Spare parts optimization is the process of determining which parts to stock, in what quantity and at what reorder point, based on asset criticality, consumption history and supplier lead time, so that critical equipment stays available without holding excess capital in slow moving inventory.
2. How do you calculate the right spare parts inventory level
Multiply average daily consumption by lead time in days to get base stock, then add safety stock sized to demand and lead time variability. Critical, long lead time parts justify higher safety stock even with low usage; low criticality, easily sourced parts often need none.
3. What causes most spare parts stockouts
Stockouts usually come from reorder points that were never recalculated after lead times or failure frequency changed, and from criticality being ignored in favor of raw consumption value, which underrates cheap but essential parts.
4. How much does excess spare parts inventory cost a plant
Carrying cost estimates for MRO inventory commonly range from 15 to 30 percent of average stock value annually, covering capital, warehousing, insurance and obsolescence, so a storeroom holding several million dollars in unnecessary stock can lose a substantial sum every year before any part is ever installed.
5. Is ABC analysis enough for spare parts classification
No. ABC analysis ranks by consumption value alone and will underrate cheap, critical parts. Combining it with a criticality or VED layer corrects for that and is considered standard practice in mature maintenance operations.
6. How does a CMMS help with spare parts optimization
A CMMS links parts consumption to actual work orders and asset criticality records, giving accurate, current data for reorder point calculation, automatic purchase requisitions when stock crosses a threshold, and ongoing identification of dead stock that no longer needs to be carried.
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Conclusion: Key takeaways and where ManWinWin fits
Spare parts optimization comes down to three disciplines applied consistently rather than once: classify parts by criticality and consumption, size reorder points against real lead time data, and let the system enforce those rules instead of relying on memory or habit. Plants that do this well tend to see fewer emergency purchase orders, materially lower carrying cost, and, most importantly, fewer situations where a production line sits idle waiting for a part that should have been on the shelf.
None of this works from static spreadsheets. It requires a system that connects asset records, work order history and stores data in one place, and updates the picture every time a technician closes a job.
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About the Author
José Fernandes is the Managing Partner at ManWinWin Software (Navaltik Management), leading company in maintenance management consultancy and CMMS (Computerized Maintenance Management System) solutions.
With a technical background in industrial organization, José Fernandes has been with Navaltik since the 1990s, progressing from consultant to strategic leader and a key figure in the development of the ManWinWin software.
Throughout his career, he has overseen hundreds of maintenance system implementations across more than 30 countries, including regions in Africa, Australia, the Middle East, and East Asia.
