How do you calculate a footprint optimization score?

Multiply the three 1–10 ratings: severity × occurrence × detection. With severity 6, occurrence 4 and detection 3 the footprint optimization risk score is 72 (the headline figure here is shown on the calculator's own scaled output), and you rank all footprint risks by that product.

What is a good footprint optimization score?

Lower is better — there is no universally 'good' number, only relative ranking. Many network teams set an action threshold around 100–125 on a 1–1000 scale; anything above gets a formal mitigation plan, while severity-9-or-10 items are escalated no matter what the total is.

What do severity, occurrence and detection mean for a footprint risk?

Severity is the business impact if the risk materializes (lost capacity, customer line-down, qualification failure). Occurrence is how likely it is given the move. Detection is how easily you would catch it before it hurts you — a high detection score means it would slip through unnoticed.

Footprint optimization score vs traditional FMEA RPN — what's the difference?

The math is identical (S × O × D). The difference is scope: a standard FMEA scores a product or process failure mode, while this version scores network-level risks — supplier qualification gaps, dual-source loss, freight exposure, or ramp risk at a receiving plant.

Why is a high detection number bad?

In RPN scoring, detection rates how poorly the risk would be caught — a 10 means you'd almost certainly miss it until it caused damage. So a high detection score inflates the total and pushes the risk up your priority list, which is the intended behavior.

How do I reduce a footprint optimization risk score?

Attack the largest driver. You usually can't change severity much, so add controls that lower occurrence (dual-source, buffer stock, staged ramp) or improve detection (audits, early supplier scorecards, run-at-rate trials) and re-score.

Make-Buy, Outsourcing & Network Design calculator

Footprint Optimization Score Calculator

The Footprint Optimization Score is a risk-priority number (RPN) tailored to manufacturing network and footprint decisions — consolidating plants, reshoring a product line, qualifying a new contract manufacturer, or splitting volume across sites. It multiplies three 1–10 scores (severity, occurrence, detection) so a network strategy or operations team can rank competing footprint risks on one comparable scale. Supply chain and make-buy leaders use it during footprint reviews to decide where mitigation budget and dual-sourcing effort should go first. Because it forces an explicit, repeatable rating, it cuts through gut-feel arguments when a site move or outsourcing decision is on the table.

What this calculator does

Estimate footprint optimization for make-buy, outsourcing and network design using production-ready inputs so teams can rank risks and decide which issue needs containment, controls, or escalation first.
Use it when footprint optimization in make-buy, outsourcing and network design needs a defensible ranking against other make-buy, outsourcing and network design risks for the next review.
It computes a single footprint optimization risk score by multiplying the severity, occurrence and detection ratings for one footprint or make-buy risk.

Formula used

Footprint optimization risk score = footprint optimization severity score × footprint optimization occurrence score × footprint optimization detection score
Use the same scoring scale across comparable footprint optimization risks.

Inputs explained

Footprint risk severity (impact if it goes wrong):
Footprint risk occurrence (how likely it happens):
Footprint risk detection (how easily you'd catch it):

How to use the result

Use it when comparing and prioritizing risks across a plant consolidation, reshoring, supplier qualification, or network redesign so the highest-RPN items get mitigated first.
RPN is ordinal, not linear — a 200 is not literally twice as risky as a 100, and the multiplication can mask a high-severity item hiding behind low occurrence and detection, so always review severity 9–10 risks on their own regardless of total.

Current U.S. benchmarks

Sourcing currencies as of 2026-07-02 (Federal Reserve H.10): 6.7886 CNY and 17.4524 MXN per USD. Landed-cost comparisons move with these daily rates.
U.S. iron and steel imports ran $2.1B in May 2026 (Census International Trade). The U.S. ran a trade deficit of $0.4B in the category that month. Import volumes are the pressure gauge behind tariff and reshoring decisions.

Common questions

How do you calculate a footprint optimization score? Multiply the three 1–10 ratings: severity × occurrence × detection. With severity 6, occurrence 4 and detection 3 the footprint optimization risk score is 72 (the headline figure here is shown on the calculator's own scaled output), and you rank all footprint risks by that product.
What is a good footprint optimization score? Lower is better — there is no universally 'good' number, only relative ranking. Many network teams set an action threshold around 100–125 on a 1–1000 scale; anything above gets a formal mitigation plan, while severity-9-or-10 items are escalated no matter what the total is.
What do severity, occurrence and detection mean for a footprint risk? Severity is the business impact if the risk materializes (lost capacity, customer line-down, qualification failure). Occurrence is how likely it is given the move. Detection is how easily you would catch it before it hurts you — a high detection score means it would slip through unnoticed.
Footprint optimization score vs traditional FMEA RPN — what's the difference? The math is identical (S × O × D). The difference is scope: a standard FMEA scores a product or process failure mode, while this version scores network-level risks — supplier qualification gaps, dual-source loss, freight exposure, or ramp risk at a receiving plant.
Why is a high detection number bad? In RPN scoring, detection rates how poorly the risk would be caught — a 10 means you'd almost certainly miss it until it caused damage. So a high detection score inflates the total and pushes the risk up your priority list, which is the intended behavior.

Last reviewed 2026-05-12.