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February 7, 2025 · The Bloomfield Team

The Complete Guide to Shop Floor Metrics That Actually Matter

An ERP system with 200 report options and a shop owner who checks three of them. That is the reality in most manufacturing operations. The data exists. The problem is knowing which numbers actually move the business and which ones create noise.

After working with dozens of manufacturers, the pattern is consistent: seven metrics cover 90% of what a shop needs to monitor daily and weekly to run a healthy operation. Everything else is either a derivative of these seven or a vanity metric that feels useful and changes nothing.

The Seven Metrics

On-Time Delivery

OTD is the single metric your customers care about most. A 2023 survey by the Precision Machined Products Association found that 67% of purchasing managers rank delivery reliability above price when selecting repeat vendors. The math is straightforward: count the jobs shipped by their committed date, divide by total jobs shipped, express as a percentage.

The trap is in how you define "committed date." Many shops quietly adjust delivery dates when schedules slip, which inflates OTD without improving actual performance. The honest measurement uses the original date promised to the customer. Shops running below 90% typically have a scheduling problem, a capacity problem, or both. For a deeper look at what causes late shipments, see how late shipments actually start.

First Pass Yield

FPY measures production quality at the point of creation. A part that needs rework passed through the process once and came out wrong. That consumes machine time, operator time, inspection time, and material, all of which went into producing something that required a second pass. Shops with FPY below 90% are essentially running a hidden factory inside their operation, consuming resources to fix what should have been right the first time.

Track FPY by work center, by operator, and by part type. The patterns will tell you where your process needs attention. A specific machine producing consistently lower FPY might need maintenance or tooling upgrades. A specific part geometry causing repeated failures might need a process review or better work instructions.

Quote Win Rate

Most job shops win between 15% and 35% of the quotes they submit. Knowing your win rate matters, but knowing why you win and lose matters more. Track win rate by customer, by part type, by dollar value, and by response time. The shops that see the clearest patterns are the ones that track how quote turnaround time correlates with win rate.

A win rate below 15% usually means you are quoting work that does not fit your capabilities, your pricing is too high for the market segment, or you are responding too slowly. A win rate above 40% often means you are leaving money on the table and could price higher without losing volume.

Machine Utilization

Utilization gets misunderstood more than any other metric. High utilization is not always good. A machine running at 95% utilization has almost zero buffer for unexpected jobs, rush orders, or rework. Queueing theory shows that as utilization approaches 100%, lead times increase exponentially. The sweet spot for most job shops is 65 to 80%. That provides enough throughput to cover overhead while maintaining the flexibility that job shop customers require.

Measure utilization as spindle-running time divided by available time. Available time excludes planned maintenance, holidays, and scheduled downtime. Unplanned downtime, changeovers, and idle time all reduce utilization and deserve separate tracking to identify root causes.

Setup Time Ratio

Setup is the tax on every job changeover. In a high-mix job shop running short lots, setup time can consume 20 to 35% of total available machine time. That means a third of your capacity is spent preparing to make parts rather than making them. Tracking setup time as a ratio of total production time shows how much capacity you are spending on changeovers, and whether initiatives like quick-change tooling, preset fixtures, or better scheduling are actually reducing it.

Revenue Per Employee

This metric tells you whether your operation is scaling efficiently. The average American job shop generates between $150,000 and $200,000 in revenue per employee. Shops above $250,000 per employee typically have higher automation, better process efficiency, or a favorable mix of high-value work. Shops below $120,000 are carrying overhead that the revenue base cannot support.

Revenue per employee is a lagging indicator. You cannot improve it directly. But watching it over time reveals whether your investments in equipment, training, and process improvement are translating to operational leverage.

Quote Turnaround Time

The time between receiving an RFQ and submitting a quote predicts win rate better than almost any other variable. Shops that respond within two days win at roughly triple the rate of shops that take five or more days. Track this metric religiously and investigate every quote that takes longer than your target. The quoting process is where most shops have the largest single opportunity to improve revenue without adding capacity.

What to Ignore

Machine hours sold as a standalone metric. Pounds of material consumed. Total quotes submitted. Number of customers. These metrics feel productive to track and offer almost no actionable insight. They measure activity without measuring outcomes. If a metric does not connect directly to revenue, quality, delivery, or efficiency, it belongs in a reference report, not on the daily dashboard.

The shops that grow consistently are the ones where every person on the floor knows the three numbers that matter this week and can explain how their work connects to those numbers. Seven metrics, reviewed honestly, acted on consistently. That is the system.