Executive Summary
Procurement has become very good at seeing price. Spend analytics, supplier benchmarks, and competitive sourcing have given teams far more visibility into what they pay. But visibility alone doesn’t tell you whether that number reflects current market conditions or a supplier’s actual cost structure.
That distinction matters more as markets grow less predictable. Materials, labor, energy, freight, and policies can shift quickly, while supplier prices often lag. A quote can look competitive against historical or market benchmarks and still give procurement no real sense of whether there’s room to negotiate or whether costs are about to climb.
The white paper looks at the factors that influence supplier rates and why two suppliers quoting the same price can be facing very different cost pressures.
It also shows how breaking a price down into its individual drivers changes the conversation. Instead of simply asking for a lower number, procurement can point to specific factors and negotiate from a position backed by evidence, not guesswork.
The implications go beyond any single negotiation. A clearer view of cost helps category managers tell the difference between a temporary price blip and a real shift in a product or service’s underlying economics. It sharpens sourcing decisions by giving teams a better idea of how costs are likely to move over time.
Ultimately, this paper argues for building on price visibility with cost intelligence, giving procurement a more grounded way to read supplier rates, respond to shifting conditions, and negotiate with confidence.
Read the full report.
The is the first white paper in GEP’s six-part series, Creating Cost Intelligence Advantage With AI.
Frequently Asked Questions
Should-cost analysis breaks down the factors that drive supplier pricing, giving procurement a fact-based view of what a product or service should cost. That means teams can assess quotes objectively and negotiate around the real economics, not just what a supplier is asking for.
Materials, labor, logistics, and trade conditions can shift quickly, so the link between supplier price and underlying cost isn’t always stable. A quote might look competitive against a historical benchmark and still be built on outdated cost assumptions. Understanding what’s actually driving that price gives procurement far more context for evaluating an offer.
Cost intelligence lets sourcing teams track and understand what’s behind supplier pricing and how those factors are shifting over time. That can reveal where a supplier is genuinely under cost pressure, where there’s room to negotiate, and how today’s conditions are likely to shape tomorrow’s costs.
Should-cost analysis has traditionally been slow, manual and highly dependent on specialists, limiting how widely procurement could apply it.
AI changes that. It can read engineering drawings, identify cost drivers, and build detailed cost models in a fraction of the time, putting should-cost analysis within reach across a much broader spend base. Agentic AI takes this further still by continuously processing new data, updating cost intelligence, and flagging where procurement needs to act.