In today’s unpredictable global economy, ensuring resilient supply chains has become a top priority for businesses across industries. The logistics landscape is increasingly shaped by disruptive forces like economic volatility, geopolitical tension, and technological innovation. Amid this upheaval, industry experts Craig Fuller and Will O'Donnell shed light on two transformative tools driving change in logistics: artificial intelligence (AI) and freight data. This article unpacks their insights, explores practical applications, and offers actionable strategies for supply chain leaders to thrive in this complex environment.

Why Freight Data is the "Source of Truth" for the Goods Economy

According to Craig Fuller, CEO of FreightWaves, freight data holds unparalleled value in understanding the health and dynamics of the goods economy. From flatbed trucking that correlates with housing market trends to monitoring inventory replenishment at retail stores, freight movements provide real-time indicators of economic activity.

Unlike commodities like oil or wheat, freight cannot be "stored" or moved without a clear demand. Fuller explains, "People don’t move freight unless there’s demand on the other side." This unique characteristic makes freight data a leading economic indicator, offering businesses valuable insights into market trends.

Key Freight Metrics to Watch

Outbound Tender Volume Index (OTVI): This metric tracks the number of orders (or tenders) from shippers to carriers. It provides a real-time view of trucking demand and reflects fluctuations in the physical goods economy.
Tender Rejection Index: This measures how often carriers reject freight tenders, signaling whether they have better options in the market. High rejection rates suggest strong demand and healthy carrier conditions.

These indices enable companies to predict trends like housing starts, retail inventory replenishment, and sector-specific economic health, making them essential tools for decision-making.

The Role of AI in Supply Chain Optimization

AI is revolutionizing supply chains by streamlining processes, contextualizing data, and improving decision-making. While the technology has its limitations - such as struggles with time-series data - its potential to transform logistics operations is immense.

AI's Strengths in Supply Chains

Exception Management: Logistics professionals spend much of their time handling disruptions like damaged goods, misplaced shipments, or regulatory issues. AI excels at managing repeatable tasks, allowing humans to focus on complex problem-solving.
Data Contextualization: AI can turn raw freight data into actionable insights. Fuller notes that language models can personalize intelligence for specific industries, such as automotive supply chains or beverage manufacturing.
Faster Decision-Making: AI reduces the time spent collecting and categorizing information, enabling faster and more informed decisions. For instance, AI can analyze diverse data sources to predict inventory shortages or shipping delays.

The Challenges of AI

Despite its promise, AI has limitations when it comes to forecasting in highly unpredictable environments. Fuller cautions, "AI makes really bad decisions if it doesn’t have all the context." For instance, natural disasters or geopolitical disruptions - common in supply chains - often require human expertise and intuition to navigate effectively.

Freight as an Economic Barometer: Real-World Applications

Fuller provides a compelling example of how companies can leverage freight data to predict market trends. Flatbed trucking, often used to transport construction materials like steel and lumber, closely aligns with housing starts. By monitoring flatbed demand, businesses can anticipate shifts in the housing market and adjust their strategies accordingly.

Similarly, retail inventory replenishment provides another critical data point. Tracking freight movements ahead of sales figures allows businesses to project demand and avoid overstocking or stockouts.

The Importance of Experience in Supply Chain Disruption

One recurring theme in Fuller and O'Donnell's discussion is the value of experience in managing supply chains. As Fuller notes, "Experience really matters." Leaders with deep industry knowledge and on-the-ground expertise are better equipped to handle disruptions and implement contingency plans.

This principle extends to technology adoption as well. The most successful innovations often come from founders or teams with direct industry experience. Fuller highlights Jordan Graph of Highway, whose fraud-prevention solutions for freight stemmed from applying banking principles to logistics - an example of cross-industry learning driving transformative change.

Navigating Uncertainty: Advice for Supply Chain Leaders

In an era of constant disruption, Fuller offers several strategies for supply chain executives:

Expect More Disruption: The world is becoming more contested and unstable. Leaders should plan for continued supply chain disruptions caused by geopolitical issues, economic uncertainty, and global events.
Invest in Data: Real-time freight data provides the "source of truth" for supply chain operations. Companies must prioritize data investments to gain visibility and agility.
Build Diverse Teams: Surround yourself with people who have both industry expertise and diverse perspectives. This combination fosters innovative solutions to complex challenges.
Leverage AI for Repetitive Tasks: Use AI for exception management and routine operations, freeing up human resources for strategic decision-making.

Key Takeaways

Freight Data as an Economic Indicator: Freight volumes reflect real-time economic conditions and provide critical insights into market trends.
AI’s Value in Supply Chains: AI excels at streamlining processes, contextualizing data, and accelerating decision-making, but it struggles with complex forecasting.
Flatbed Trucking as a Housing Predictor: Monitoring flatbed demand offers actionable insights into the construction and housing markets.
Experience Matters: Leaders with deep industry knowledge are better equipped to manage disruptions and leverage technology effectively.
Plan for Continued Disruption: The geopolitical and economic landscape is increasingly unstable; resilience requires proactive planning and agile operations.

Conclusion

As businesses face a future marked by volatility and uncertainty, the integration of AI and freight data offers a path to resilience. By harnessing these tools, supply chain leaders can anticipate market shifts, optimize operations, and respond swiftly to disruptions. However, success requires more than just technology - experience, diverse perspectives, and strategic planning remain critical. By combining data-driven insights with human expertise, businesses can navigate the challenges ahead and build stronger, more adaptive supply chains.

Source: "Smart Freight: How AI and Data Are Reshaping Supply Chains" - Prologis, YouTube, Sep 2, 2025 - https://www.youtube.com/watch?v=6MiT-EfK1iU

How AI and Freight Data Improve Supply Chain Resilience