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 7.55 risk score on its normalized 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 7.55 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 7.55 risk score on its normalized 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 7.55 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 2026-05-12.