The Problem
The company operates 13 regional distribution centers across the US, Canada, and Mexico, ships to 1.6 million customers with over 43,000 products, runs 1,000+ trucks daily with same-day shipping capability, and manages $50M in ocean freight spend alone. The procurement function managing that network was running entirely on spreadsheets. Each domestic LTL carrier analysis required 14 hours of manual work — building evaluation models in Excel, pulling historical shipment data, calculating cost scenarios, and assembling comparison outputs the procurement team could actually use to make a decision. With 45 scheduled carrier analyses per year plus 39 ad-hoc reviews triggered by new branch openings and network changes, that was 720-plus hours of senior procurement staff time consumed before any decision was made.
Ocean freight procurement had the same structural problem at larger scale. The annual ocean freight bid involved three rounds of negotiation across a carrier pool of 30-plus providers covering all major trade lanes. Each round required 11.5 hours of manual spreadsheet work per cycle — normalizing carrier bids in different formats, building scenario models, calculating total landed cost implications, and producing comparison outputs. The tools available were generic procurement software that pushed 90% of the analytical work into disconnected Excel workflows. By the time analysis was complete and a contract was ready to be awarded, the market had often moved. Three-week contract cycles meant the company was negotiating against rate data that was already stale when the award was finalized.
Carrier performance data was another gap. Lane allocation decisions were made without integrated historical performance metrics. On-time delivery rates, service quality, billing accuracy, and cost compliance existed in different systems and had to be assembled manually before they could inform a carrier evaluation. Freight commitments worth millions of dollars were being made with incomplete carrier performance information — relationships and historical familiarity filling in for data the company did not have in a system where it could be applied.
The scale of the problem was precisely quantifiable. 720 hours per year in LTL analysis. 84 hours per year in ocean bid analysis across three rounds. $50M in ocean spend managed through tools designed for a business one-tenth the size. The company needed a procurement platform that could compress the analytical cycle from days to minutes — not incrementally better, but categorically different.
What Freehand Did
Freehand’s AI Procurement Analyst automated the carrier analysis process from 14 hours per evaluation to 5 — a 64% reduction in the time required to build the analytical model, normalize historical shipment data, run cost scenarios, and produce a carrier comparison the procurement team can review and act on. Across 84 annual analyses, that reduction compounds to 720-plus hours of recovered procurement capacity per year. The team that had spent those hours in spreadsheets now reviews AI-generated outputs with supporting evidence assembled, anomalies flagged, and scenario comparisons modeled — not raw data requiring manual analysis.
Ocean freight procurement moved from a 3-round manual bid process consuming 11.5 hours per round to AI-managed event execution with automated bid ingestion, normalization, anomaly detection, and scenario modeling running continuously as bids arrive. The contract cycle that had taken 3 weeks now closes in days — capturing market rate windows that the prior process could not move quickly enough to exploit. Carrier engagement tripled: where the manual process limited how many carriers could be actively evaluated in a single event, the AI Procurement Analyst manages a 3x larger carrier pool with the same team bandwidth.
The Rate Manager Agent replaced the fragmented contract and rate management process with a centralized repository covering ocean, LTL, FTL, and intermodal — all modes, all carriers, version-controlled, with automated rate application and exception alerts when contracted rates expire or market conditions move significantly. The 3-week implementation cycle for contract rate updates dropped to days. When a new branch opens and requires ad-hoc carrier analysis, the AI Procurement Analyst completes the evaluation in hours rather than requiring a 14-hour manual project.
Carrier performance scoring now integrates historical on-time delivery rates, billing accuracy, dispute resolution speed, and service quality metrics directly into the procurement evaluation model. Lane allocation decisions are made with documented, data-backed carrier assessments rather than relationship-based familiarity. The 20% improvement in carrier performance evaluation translates into more defensible sourcing decisions and better carrier accountability in the lanes that matter most at the scale the company operates. The Spend Intelligence Agent provides real-time visibility across the full freight network — the analytical foundation the procurement team needs to operate at the scale of a $11B distributor without proportionally scaling the team.
