Tier 1's Need To Fix Their RFQ Process
Why It Matters
The inefficiency directly cuts supplier profits and threatens OEM timelines, making AI‑driven RFQ automation a strategic imperative for the auto industry's competitiveness.
Key Takeaways
- •RFQ process hours have risen sharply since 2001.
- •Supplier win rates mask missed deadlines and lost revenue.
- •AI demos cut data compilation from months to minutes, yet adoption lags.
- •Tooling payments and data transparency remain major bottlenecks.
- •Consolidation and retirements threaten critical RFQ knowledge continuity.
Summary
The video features John Maroy with Ted Mabley and Edgar Fowler discussing persistent inefficiencies in automotive suppliers' request‑for‑quote (RFQ) process, noting that despite two decades of analysis little has improved.
They compare baseline data from 2001 to 2025, showing hours per RFQ rising, retirement of qualified staff, and up to 25% of quotes missing deadlines, directly eroding revenue and margins. Suppliers cite longer cycles—up to a year for multiple revision rounds—and a lack of visibility across finance, engineering, and sales.
Demonstrations of AI tools like Entra can compress month‑long data gathering into minutes, and analytics firms such as To‑Whom provide scenario modeling, yet adoption stalls because the process spans many functions and legacy data silos. A real‑world example highlighted a top‑tier supplier submitting an RFQ with zero SG&A, exposing quality control gaps.
The panel warns that without urgent digital transformation, the RFQ bottleneck will exacerbate cost pressures, tool‑funding delays, and supply‑chain security risks, especially as OEMs demand faster turn‑arounds and as the industry pivots toward EV volatility and onshoring.
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