From Gut to Data-Driven: Building Freight Procurement Decisions That Scale

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November 5, 2025
3
min Read
Aarthi Sudarsanam
Product Marketing
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Key takeaways

What You’ll Learn in 3 Minutes

  • Why most large forwarders get stuck after initial digitization
  • The real cost of fragmented rate intelligence
  • Where Procurement, Pricing, and Sales lose margin without realising
  • The three maturity stages of decision-making
  • The roadmap to shift from intuition → intelligence → orchestration

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Footnotes and Sources

[1] Gartner: The Cost of Poor Data Quality: $12.9 million annual data cost: https://www.gartner.com/en/articles/the-cost-of-poor-data-quality

[2] McKinsey & Company: Reimagining the back office with Gen AI25–35% time wasted on non-value-added activities: https://www.mckinsey.com/capabilities/operations/our-insights/reimagining-the-back-office-with-gen-ai

[3] McKinsey & Company: Harnessing the power of AI in distribution operations5% to 15% logistics cost reduction: https://www.mckinsey.com/industries/industrials-and-electronics/our-insights/distribution-blog/harnessing-the-power-of-ai-in-distribution-operations

Frequently Asked Questions

Q: What is data-driven decision-making in freight forwarding?

It’s the process of using centralized, structured data and AI insights to drive procurement, pricing, and quoting decisions across global teams.

Q: Why is it difficult for freight forwarders to become data-driven?

Because most use legacy TMS systems and Excel workarounds that trap information in silos, making collaboration and transparency difficult.

Q: What is decision intelligence in logistics?

Decision intelligence connects data, people, and AI systems to continuously learn from transactions—transforming experience into scalable foresight.

Q: How does AI improve freight pricing and procurement?

AI learns from historical contracts, quotes, and bookings to suggest optimal pricing, detect anomalies, and improve margin consistency.

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