A single missed cost input or outdated volume assumption in an RFQ response can lock an automotive supplier into years of unprofitable business. Jason Versical, Vice President of Strategy and Transformation at Campfire Interactive, argues that legacy processes built on fragmented spreadsheets are the root cause, and that artificial intelligence offers a way to submit winning quotes without the last-minute scramble.
The spreadsheet problem in commercial management
When an automaker issues a request for quote, suppliers face intense deadline pressure. Volume assumptions, program timing, and cost data typically live in separate systems and unstructured datasets across the organization. Many suppliers still compile the final quote in spreadsheets, reentering and rechecking every assumption by hand each time a variable changes. That manual workflow makes it hard to run pricing and volume scenarios before the clock runs out, and change history is easy to lose.
"A quote submitted too low under deadline pressure can lock in years of unprofitable business, and a quote submitted too high can lose work that would have been profitable," Versical said. "The root cause is often the same: fragmented data and speed."
Where AI fits - and where it does not
Versical pointed to the repetitive, data-heavy parts of the RFQ process as a natural fit for AI. The technology can pull together volume signals, historical win-loss information, and cost and price data, then flag an outlier or risk the moment an assumption changes. It can also run dozens of pricing and volume scenarios in the time a person needs to build a single spreadsheet model.
The final quote decision, however, should remain with people. "AI is strong at surfacing patterns across large, messy datasets, but it can still make errors and should not be left alone to decide a quote submission," he said. The strongest outcomes come when sales and finance teams are freed from spreadsheet assembly and equipped with AI-driven insights to select programs that fit the supplier's strategy and use capital efficiently.
Investing ahead of the ERP data
Many suppliers have invested heavily in engineering, manufacturing floor, and supply chain software. Versical noted that those are important, but if the right programs are not awarded with a healthy financial profile, plant-floor optimization can only do so much for margins. Because OEM contracts span five to seven years or more, much of a supplier's profitability is decided one to two years before the data ever appears in ERP software.
That makes investment in software for sales, finance, and program management teams a direct lever on corporate profitability - one that is often overlooked. Large OEMs tend to run more sophisticated technology in their purchasing and launch operations than suppliers do in their commercial teams, which Versical sees as a real opportunity to improve margins and efficiency.
Moving beyond the spreadsheet
Suppliers get past spreadsheet dependency by treating commercial data as a shared system rather than a collection of individual files. The work can be approached by process area: moving program management and stage-gate reviews into a single system of record, tying cost and quote standards to design changes, or creating one consolidated view of program financial projections across current production, development, and upcoming targets.
The result is real-time visibility. A changed OEM volume, an SOP delay, or a cost increase becomes visible across the organization instead of sitting on one person's computer. Consistent definitions mean a unit or a dollar means the same thing across business units, plants, and regions. Spreadsheets still have a place for flexible, ad hoc analysis, but a supplier serious about improving results at the corporate level needs a commercial and profitability system of record it can trust.
Choosing a technology partner
Versical advised suppliers to look for a provider that understands automotive and manufacturing specifically, not a generalist AI vendor applying the same model to every industry. Depth of functionality matters because finance, sales, and program management teams need to trace how a number was produced and how it changed over time. The technology should integrate with systems already in place, such as ERP and PLM/PDM. As OEM requirements evolve, the right partner acts as an ongoing collaborator that keeps adapting the technology - a point Campfire Interactive emphasizes in its own AI offerings for suppliers.
Why this matters for executives and strategy
The commercial side of the business - quoting, program financials, and change management - often runs on the weakest technology stack in the organization, even as it locks in the profitability profile for years. Investing in a connected system of record for sales, finance, and program data, with AI handling scenario analysis and anomaly detection, shifts the conversation from last-minute spreadsheet reconciliation to strategic decisions about which programs to pursue and how to price them. For executives, the question is not whether to digitize the plant floor, but whether the commercial team has the tools to ensure the plant floor is building the right work at the right margin.
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