Spare Parts Criticality Worksheet (Excel)
Not every spare deserves shelf space. This worksheet scores each part on what happens if it fails, how likely that is, how long it takes to get and how hard it is to source, so you can justify what to stock and what to buy when needed.
| Part | Asset | Consequence (1-5) | Likelihood (1-5) | Lead time (weeks) (weeks) | Sourcing risk (1-5) | Unit cost | Criticality score | Stock policy | |
|---|---|---|---|---|---|---|---|---|---|
16.6667 | |||||||||
12 | |||||||||
4 | |||||||||
18.3333 | |||||||||
4 |
Score is consequence multiplied by the average of likelihood, sourcing risk and a lead time score (1 for 2 weeks or less, up to 5 above 26 weeks). Scores range from about 1 to 25. As a starting rule, 15 and above are stock-on-site candidates, 8 to 14 are review, and below 8 are order-on-demand. Adjust the thresholds to your cost of downtime.
Review spares policy against ERP stock data
Optional: a short review of how criticality scores can drive min and max levels in your ERP.
Optional. The tool and every export work without this. No spam.
How to use the worksheet
List the spares for one asset or area at a time. Score consequence from 1 to 5 using your own production loss and safety scale, so a 5 means a stoppage or incident that costs more than the part ever will. Score likelihood from failure history or the maintenance team. Enter the real supplier lead time in weeks and rate sourcing risk. The sheet converts lead time to a 1 to 5 score and multiplies consequence by the average of the three risk factors. Sort by score and apply your stock policy.
Why these factors
Classic criticality analysis weighs consequence against probability, and spare parts add two supply side factors. Long lead time and a single source turn a modest failure into a long outage. A cheap sensor that is in stock next door scores low even if it fails often, while a rarely failing controller with a 30 week lead time scores high. This is why insurance spares, items held because failure is unlikely but intolerable, appear at the top of the list.
- High consequence and long lead time: stock on site
- High likelihood and low cost: min and max stock
- Low consequence and short lead: order on demand
- Sole source or obsolete: review for alternates
Using the result
Take the top scored items and compare the cost of holding them with the cost of downtime. If a one hour outage costs more than the part, stock it. For low scoring items, consider vendor managed inventory or consignment. Review the list annually and after any major failure. When items are in an ERP, link the score to the material master or stock policy field so replenishment logic follows the decision.
Common mistakes
Scoring parts instead of failure modes, copying OEM recommended spares lists without checking your duty, ignoring parts shared across several assets, and never revisiting scores after a design change. Also check that stocked critical spares are stored correctly and not cannibalized, otherwise the safety net is gone when you need it.
Frequently Asked Questions
What is an insurance spare?
It is a part with low failure probability but high consequence and long lead time, held only to avoid a long outage. Typical examples are large motors, main drives and control modules.
How should I score consequence?
Define the scale once, for example hours of lost production or safety and environmental impact, and apply it to every item. Agree it with operations so a 5 means the same thing to everyone.
Can I weight the factors differently?
Yes. Export to Excel and change the weights, for example doubling sourcing risk for imported parts. Keep the logic documented so other planners can follow it.
How often should I review criticality?
At least yearly, and after major failures, equipment changes or supplier changes. Lead times in particular can change quickly and move parts across your thresholds.
Netray can read your stock levels, consumption and lead times from the ERP and flag critical spares that are below their policy, in a private read-only view.
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