Second Largest US Restaurant Group Cuts Freight Procurement Cycle Time 50% with AI-Powered RFQ Automation
A second largest restaurant group in the US deployed Machine Learning & Predictive Analytics for Procurement Analytics in Food & Beverage Supply Chain. As reported by pando.ai: 50% reduction procurement cycle time.
Source-reported figures (cited source: pando.ai)
What the second largest restaurant group in the US was trying to fix
Operating over 32,000 restaurants across multiple brands with $32.5B in global sales, this restaurant group ran nearly 20 freight RFQ cycles annually — each requiring separate procurement templates for every brand, carrier type, and product category. Data collation meant manually extracting figures from disparate systems into spreadsheets before bids could begin, while all carrier negotiations happened entirely offline via email and phone. Manual landed cost estimation across brands consumed days of analyst time and produced pricing inconsistencies that buried true transportation costs within complex landed cost calculations, making it difficult to identify network optimization opportunities or accurately measure the impact of freight decisions on overall profitability.
What the second largest restaurant group in the US deployed
Pando deployed an AI-powered freight procurement platform to replace the company's fragmented manual workflows. Pre-configured digital RFQ templates with automated data population eliminated the multi-brand template maintenance burden, while a unified carrier collaboration portal replaced offline negotiations with structured real-time bid submissions. An AI-driven evaluation engine compared carrier offers simultaneously across lanes, rates, service levels, and historical performance — surfacing optimal choices faster than manual analysis. Automated landed cost calculations integrated transportation rates, handling fees, and product costs in real time, replacing spreadsheet-based estimation entirely. Pando's implementation team provided high-touch onboarding, configuring the platform to integrate with existing supply chain systems and delivering training that accelerated adoption across the procurement organization.
Results
The implementation delivered a 50% reduction in procurement cycle time, compressing the process into streamlined digital workflows. End-to-end RFQ-to-contracting reached 100% automation. Logistics team productivity improved 60%, with procurement specialists generating comprehensive RFQs in minutes rather than days.
Key outcomes:
- Real-time analytics delivered previously unavailable visibility into true transportation costs
- Automated landed cost estimation surfaced hidden savings opportunities that had been obscured inside manual spreadsheet workflows
- Centralized carrier communication eliminated fragmented offline negotiations, accelerating decision cycles across the full distributor network
Key Takeaways
- Multi-brand template standardization compounds over time: a single configurable framework scales across every brand-carrier-category combination without proportional maintenance overhead.
- Offline carrier communication causes delays; replacing it with a real-time digital portal keeps bids and negotiations in one place.
- Automated landed cost calculation is a prerequisite for identifying true freight savings; without it, transportation costs remain invisible inside consolidated cost lines.
- High-touch implementation support is as critical as the technology in complex multi-stakeholder supply chains where change management determines whether adoption actually takes hold.
Evidence for the second largest restaurant group in the US's Procurement Analytics deployment
- Reported outcome metrics
- 3 cited below
- Cited source
- pando.ai
- Last updated
- Source link checked
Limitation: The cited source does not identify the company.
Explore Related
Details
- Industry
- Food & Beverage Supply Chain
- Use Case
- Procurement Analytics
- AI Technology
- Machine Learning & Predictive Analytics
- Company Size
- Enterprise
- Company
- Second Largest Restaurant Group in the US
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