Contract Manufacturing
You quoted 22% margin.You shipped at 14%.
Every run looks profitable on the quote. Then changeovers run long, a customer's tolerance spec gets missed, and the rework eats the margin nobody budgeted for. We embed with your team, map how jobs actually flow from quote to shipment, and deploy AI specialists that close the gap between what you quoted and what you earned. Not a new ERP module. Real operational change, measured in dollars per run.
The Problem
Where the money
is going.
Cost
Job Costing Inaccuracy
Your quoting tool says the run costs $8.40 per unit. Your actual cost is $9.70. The difference is changeover time that got estimated at 45 minutes but took 2 hours, a material yield assumption from 2019, and three quality holds nobody priced into the job. You find out the margin was wrong after the invoice goes out. By then, you've already committed to the next PO at the same price.
Knowledge
Customer Specs as Tribal Knowledge
Customer A needs a specific liner thickness. Customer B requires cold-seal packaging and a 72-hour cure time. Customer C's tolerance is plus-or-minus 0.002 inches, not the 0.005 your default setup assumes. These specs live in a binder on the floor, in a supervisor's head, or in an email chain from 2021. When that person is out sick, the line runs to the wrong spec and you eat the scrap.
Process
Scheduling Conflicts
Customer A calls on Tuesday and wants their Thursday run moved to Wednesday. Customer B's reorder came in early. Your biggest account just doubled their next PO. Line capacity is finite. Your scheduler juggles this in a spreadsheet, calling supervisors to figure out which changeovers can compress and which can't. Every reshuffle creates downstream risk nobody quantifies until a shipment misses its date.
Risk
Audit Readiness by Customer
Each customer has different quality documentation requirements. One wants full batch records with environmental logs. Another needs CoAs with specific test parameters your QMS doesn't track by default. A pharma customer audits annually and expects deviation reports in a format your quality manager rebuilds from scratch every time. You're one surprise audit away from a corrective action that ties up your team for weeks.
How We Work
Three steps. Hands on.
We embed with your team, map your operation, find what no one could see, and deploy specialists that fix it. You get a dedicated team, not a login.
Map
We start with a structured discovery across your operation. Our team interviews your plant manager, production scheduler, quality manager, account managers, and line supervisors. We connect to your ERP, MES, and quality management systems. The result is your Blueprint: a live, verified map of how jobs actually move from quote through setup, production, QC, and shipment. Not what the work order says. What actually happens on the floor.
Uncover
We analyze everything we mapped. Our platform finds the quoting assumptions that don't match reality, the changeover sequences that waste time between customer runs, the quality steps that get repeated because documentation didn't follow the job. We validate every finding with your team before acting on it. Not a one-time audit. Always running, always finding more.
Execute
Every finding comes with a concrete plan and a deploy button. We build AI specialists that handle the fix end to end. Recalibrate job cost estimates against actuals, sequence changeovers to minimize teardown, surface the right customer spec before a run starts. You approve, they run. We stay with you to make sure they deliver.
Example Findings
What Yield typically finds.
Based on a typical mid-market company with $20M–$50M in annual revenue.
Cost
Margin Erosion from Quoted-vs-Actual Gaps
$293K/yr
Cost
Changeover Waste Between Customer Runs
$127K/yr
Process
Rework from Misapplied Customer Specs
$64K/yr
Knowledge
Undocumented Customer-Specific Setups
34 procedures
Process
Manual Scheduling and Job Rescheduling
6 hrs/wk
In Practice
See it work.
From day one.
Week 1
Discovery
We talk to everyone who touches a job.
AI-led conversations with your plant manager, schedulers, line supervisors, quality team, and account managers. Not surveys. Real conversations that capture the quoting shortcuts, the customer-specific workarounds, and the changeover tricks that no system records.
Month 1
Blueprint + First Savings
Your Blueprint is live. Agents are saving money.
A complete, verified map of how jobs flow from quote to shipment, with every customer-specific requirement documented and every cost assumption tested against actuals. The first opportunities are identified, and AI specialists are already closing the gap between quoted and actual margin.
Ongoing
Continuous Returns
Quotes get sharper. Every quarter.
Yield keeps learning from every completed run. Job cost estimates get more accurate. Changeover sequences tighten. Customer specs stay current without anyone chasing binders. The platform pays for itself and keeps going.
FAQ
Common questions.
What happens when a customer audit exposes the gap between our quoted job cost and the actual production cost?
That gap is usually the first thing Yield quantifies. It pulls your quoting assumptions — labor hours, changeover estimates, material yield, scrap allowances — and compares them line by line against actual job data from your ERP and MES. You get a per-customer, per-product breakdown showing where estimates diverge from reality. When audit season comes, you already know the numbers and have the correction plan running.
We implemented IQMS two years ago specifically to improve job costing accuracy, but our quoted-vs-actual variance hasn't improved — why would this be different?
IQMS records what happens. It doesn't question the assumptions you fed it. If your standard changeover time is still the 45-minute estimate from 2019, IQMS will faithfully track actuals against that stale baseline. Yield compares every quoting input against real job history and flags the assumptions that have drifted. It then deploys specialists that update those inputs continuously, so your quotes reflect this month's floor reality, not last year's.
We run jobs for competing customers on the same lines — can Yield keep customer-specific IP and tolerance specs separated?
Every customer's specs, tolerances, and setup requirements are mapped and stored independently within your Blueprint. Access controls ensure that findings related to Customer A's proprietary tolerances are never surfaced in reporting for Customer B. Specialists pull the correct spec set before each run based on the work order, so there is no cross-contamination between accounts.
With over 200 active SKUs across 30 customers, where does Yield even start when margin is leaking everywhere?
Yield ranks every job family by the dollar gap between quoted and actual margin, then sorts by run frequency. A job you run weekly with a $4-per-unit margin leak matters more than a quarterly job leaking $12. The first specialists target the highest-volume, highest-leakage combinations. Most contract shops see the top five job families account for over half the total margin erosion.
Explore
Related industries.
Manufacturing
Multi-Site Manufacturing
Same product. Same spec. Different yield at every plant.
Manufacturing
Packaging Companies
Your presses run all day. Your trim waste tells a different story.
Logistics
Cold Chain Logistics
Your fleet runs 18 hours a day. Your data doesn't.
Real Estate
Commercial Real Estate
Your brokers closed $40M last year. You found out in January.
Real Estate
Construction Companies
You're winning more work. You're keeping less of it.
Regulated Industries
Pharmaceutical Distribution
Every pack is tracked. Every gap is invisible.
See what Yield finds in
your shop floor.
30 days. Real results. Or walk away.