The Future of RFQ – How Automation is transforming quoting processes
In today’s competitive landscape, speed, accuracy, and efficiency are essential in winning new business - especially in industries like automotive, aerospace, and manufacturing. The Request for Quote (RFQ) process is pivotal in securing contracts, but traditional methods are often slow, manual, and prone to inefficiencies.
In this episode of the Connected Engineering Podcast, we sit down with Tobias, an engineer with over 20 years of experience, to explore how automation is transforming RFQ workflows, improving efficiency and increasing win rates
Breaking Down the RFQ Process
Tobias provides a step-by-step overview of the traditional RFQ process:
- Analyzing specifications – Understanding customer requirements and technical constraints.
- Creating initial designs – Developing feasible concepts that meet the specifications.
- Validating designs – Running simulations and ensuring compliance with performance requirements.
- Calculating costs – Estimating material, labor, and production costs to create a competitive bid.
With increasing pressure from global markets, particularly China, companies must optimize their RFQ processes to remain competitive. Automation offers a powerful solution.
How Automation is Revolutionizing RFQ Workflows
Tobias explains how automation can eliminate bottlenecks in the RFQ process by streamlining key tasks:
- Automating Simulations & Design Validation – Instead of manually running multiple simulations, automation allows for instant validation of design feasibility, drastically cutting down iteration cycles.
- Reducing Manual Errors – Automation ensures that calculations, compliance checks, and data transfers are executed flawlessly, minimizing risks and improving accuracy.
- Speeding Up Quoting Cycles – By leveraging AI-driven workflows, companies can generate complete RFQ responses in a fraction of the time, boosting their ability to secure high-value contracts.
Real-World Impact: A Case Study in Automotive RFQ Automation
Tobias shares a compelling use case from his experience with a tier-one automotive supplier facing major RFQ challenges—slow response times, complex validation requirements, and a low win rate.
By integrating automation into design simulations and cost calculations, the supplier achieved:
- 50% faster RFQ processing
- More accurate and high-quality proposals
- Higher win rates with faster, competitive quotes
This transformation enabled them to respond swiftly, improve precision, and win more business in a highly competitive market.
Overcoming Barriers to Automation in RFQ
Despite its benefits, automation adoption still faces resistance. Tobias highlights common objections:
- Fear of the "Black Box" – Engineers worry that automated decisions lack transparency. - Solution: Companies must provide clear documentation and validation processes to build trust.
- Resistance to Change – Traditional workflows are deeply ingrained. - Solution: Education and change management strategies are essential to ease the transition and showcase automation’s value.
- Integration with Legacy Systems – Many companies still rely on outdated infrastructure. - Solution: A step-by-step implementation roadmap ensures a smooth transition to automation.
The Future of RFQ: AI Agents and Fully Automated Workflows
Looking ahead, Tobias envisions a future where AI-powered agents will take RFQ automation even further:
- Intelligent task management – AI will coordinate tasks across departments, ensuring seamless collaboration.
- Data-driven decision-making – AI will analyze previous RFQs to recommend optimal pricing strategies.
- Instant proposal generation – AI-driven workflows will allow companies to deliver winning quotes within minutes, revolutionizing the industry.
As automation reshapes RFQ processes, companies that embrace these advancements will gain a competitive edge in speed, accuracy, and profitability.
