Supply Chain COST KPIs Use Case
Uncovering six decades of uncompetitive cost structure
A precision custom metal stamping and machined components manufacturer in Greenfield, Indiana, has been family-owned for nearly six decades. They have add-on plants in Columbus, Ohio, and Marietta, Georgia, completed in 18 months. A third acquisition is under due diligence.
Six decades in manufacturing had produced a belief that the cost structure was understood and well-managed. COGS as a percentage of revenue was stable. In a business that old, stability reads like optimization. What it actually meant was that nobody had looked hard enough at what was driving the number — and a datacenter customer's cost targets made that impossible to avoid.
Stability mistaken for optimization
Total Cost of Ownership | Realized Savings | Cost of Quality | Spend Under Management | % Strategic Supplier Spend
A Tier 1 datacenter contractor issued an RFQ for fixtures and assemblies supporting cooling equipment at the Columbus plant. Their cost targets on these sub-assemblies and custom hardware components — parts that had never been competitively challenged — were tighter than anything the business had quoted before. The internal read was that the customer didn't understand the market. The should-cost work said otherwise.
Should-cost modeling and TCO (Total Cost of Ownership) analysis are related but distinct tools, and both were absent.
Basing competitiveness on last year's cost
Should-cost models build the cost of a component from the ground up — materials, labor, overhead, reasonable margin — independent of what any supplier currently charges. It tells you what a part ought to cost given the manufacturing process it requires, and it identifies which cost elements are creating competitive disadvantage. When applied to the custom enclosure sub-assemblies and machined hardware in the datacenter RFQ, the model exposed gaps that six decades of institutional knowledge had never surfaced. The baseline simply hadn't been built.
TCO captures everything beyond unit price — inbound freight, quality escapes absorbed internally, and the inventory carrying cost generated by safety stock held to compensate for unreliable supplier lead times. Inventory management and logistics costs had never factored into a sourcing decision at all. The business had been managing line-item invoice price. The rest of the cost iceberg was underwater, and on complex components it was substantial.
Phantom quality issues blocking supplier consolidation
Two add-on plants in Columbus and Marietta had tripled the supplier base — similar components being sourced from multiple suppliers across three plants, managed independently with no consolidated volume and no leverage. Spend Under Management sat around 40%, and Realized Savings — barely tracked at all — hovered near 1%, more a reflection of supplier price increases working through than any deliberate cost action. Procurement had identified consolidation opportunities that would have recovered a meaningful portion of the synergy savings the acquisition thesis had assumed. The plants pushed back.
Each plant manager defended their incumbent suppliers on quality, service, and reliability grounds. The objections were consistent in their timing — they appeared whenever a preferred supplier was put up for evaluation and disappeared when the conversation moved elsewhere. Procurement started calling them phantom quality issues. The stalemate held until procurement sat down with Karen in Finance and put the synergy gap on paper. The savings assumed in the investment thesis weren't flowing through, and now there was a number attached to it. Data replaced preference, and consolidation moved forward.
Bob, the owner of one of the largest stamping suppliers, said it plainly when procurement finally called: "I was waiting for someone to discuss this with me. You just send POs." The most capable supplier relationships in the base had been operating transactionally for years because no one had asked them to be anything else.
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Technology considerations
No e-procurement platform was in place. Purchase requisitions were created in the ERP, but approvals happened offline — plant managers didn't have the time to navigate the system's complex interface, so approvals moved through email and spreadsheets instead. No contract repository existed across Greenfield, Columbus, or Marietta.
The priority before any platform decision was spend visibility — a classification exercise to understand what was actually being spent and where, and basic contract management to create a foundation for structured sourcing. AI-driven spend classification is a strong fit at that stage, once the data is clean enough to classify. The risk to avoid: deploying procurement technology into a fragmented spend picture doesn't fix the fragmentation. It makes it harder to see.
What moved
The should-cost model entered every sourcing event. Karen gained the ability to explain the activity inside the COGS line rather than just tracking the percentage.
Spend Under Management — the share of addressable spend running through a structured sourcing process — climbed from 40% to 70% as the supplier base was rationalized and contracts were put in place across all three plants, without adding headcount to procurement.
Realized Savings moved from roughly 1% to 4%, with negotiated inbound freight rates alone contributing a full point — the kind of savings that had been sitting in plain sight once TCO replaced invoice price as the basis for sourcing decisions. Phantom quality objections were replaced by a joint Finance and Procurement evaluation process with data behind it.
Bob's operation moved from transactional to strategic, with shared cost improvement targets and a multi-year agreement. The cost structure the business had assumed was optimized turned out to have meaningful room — once someone built the model to measure it.