How do you calculate a parts availability risk score?

Multiply customer downtime impact by stockout likelihood by recovery difficulty, each rated 1-10. With 9, 7, and 6 the calculator returns a 378 risk score on its multiplied 1-to-1,000 scale, flagging the part for action.

What is a good parts availability risk score?

Lower is better. Parts scoring in the top band, driven by high impact and stockout odds, need stock or sourcing action now; mid-range parts get periodic review; low scores can ride on standard lead times. The 378 here sits in the act-now zone.

Why multiply the three factors instead of adding them?

Multiplication mirrors FMEA RPN logic: a part is only truly dangerous when impact, likelihood, and recovery difficulty are all elevated together. Adding would let one mild factor mask two severe ones; multiplying makes compounding risk dominate the ranking.

What does recovery difficulty mean here?

It captures how hard it is to recover once you are short, long supplier lead times, single sourcing, no substitute, or no expedite path all raise it. A part you can air-freight overnight scores low; a custom casting with one foundry scores high.

How is this different from a simple stockout probability?

Stockout likelihood is just one of the three inputs. The score weighs that against how much customer downtime a stockout causes and how slowly you could recover, so a part that rarely stocks out but cripples a customer when it does still ranks high.

How often should I rescore service parts?

Rescore after demand shifts, supplier changes, or an actual stockout event, and at least quarterly for critical SKUs. Recovery difficulty in particular changes whenever a supplier consolidates or a substitute is qualified.

Aftermarket, Field Service & Service Parts calculator

Parts Availability Risk Score Calculator

The Parts Availability Risk Score ranks service parts by how badly a stockout would hurt, combining the customer downtime it causes, how likely you are to run out, and how hard recovery would be. Aftermarket and field-service planners use it to decide which SKUs deserve safety stock, dual sourcing, or an escalation playbook before a customer is ever affected. It matters because service-parts catalogs run to thousands of items and you cannot protect them all equally; an FMEA-style multiplicative score surfaces the few that combine high impact, high stockout odds, and slow recovery. Scoring forces an honest conversation about which parts are genuinely business-critical versus merely annoying when missing.

What this calculator does

Score service parts availability risk using customer impact, stockout likelihood, and detection or recovery difficulty.
a spare parts planner needs to rank parts that could disrupt field service or customer uptime
It multiplies three 1-10 ratings, customer downtime impact, stockout likelihood, and recovery difficulty, into a single prioritization score for a service part.

Formula used

Parts availability risk score = service impact severity × stockout likelihood × detection or recovery difficulty
Higher scores identify service parts risks that need inventory, supplier, or escalation action before customers are affected.

Inputs explained

Customer downtime impact: undefined
Stockout likelihood: undefined
Recovery difficulty: undefined

How to use the result

Use it during service-parts planning reviews to rank SKUs for stocking, sourcing, or escalation decisions before customers experience downtime.
The three ratings are subjective and the multiplicative scale is non-linear, so scores compare priority order well but are not a literal probability or cost.

Common questions

How do you calculate a parts availability risk score? Multiply customer downtime impact by stockout likelihood by recovery difficulty, each rated 1-10. With 9, 7, and 6 the calculator returns a 378 risk score on its multiplied 1-to-1,000 scale, flagging the part for action.
What is a good parts availability risk score? Lower is better. Parts scoring in the top band, driven by high impact and stockout odds, need stock or sourcing action now; mid-range parts get periodic review; low scores can ride on standard lead times. The 378 here sits in the act-now zone.
Why multiply the three factors instead of adding them? Multiplication mirrors FMEA RPN logic: a part is only truly dangerous when impact, likelihood, and recovery difficulty are all elevated together. Adding would let one mild factor mask two severe ones; multiplying makes compounding risk dominate the ranking.
What does recovery difficulty mean here? It captures how hard it is to recover once you are short, long supplier lead times, single sourcing, no substitute, or no expedite path all raise it. A part you can air-freight overnight scores low; a custom casting with one foundry scores high.
How is this different from a simple stockout probability? Stockout likelihood is just one of the three inputs. The score weighs that against how much customer downtime a stockout causes and how slowly you could recover, so a part that rarely stocks out but cripples a customer when it does still ranks high.

Last reviewed 2026-08-11.