Why is decision-making quality so low among freight forwarders?

The logistics industry has historically relied on manual processes, fragmented systems, and point solutions rather than integrated platforms. Most forwarders lack real-time visibility into shipment status, carrier performance, and regulatory compliance requirements. Legacy systems cannot correlate data across multiple variables needed for optimal decisions. Additionally, many firms operate with small analytics teams or no dedicated data infrastructure, forcing decisions to be made on incomplete information or intuition rather than evidence.

What does 'excellent decision-making' mean in freight forwarding?

Excellent decision-making in this context refers to the ability to make informed, data-driven choices about routing, carrier selection, compliance strategies, and operational procedures. This includes leveraging predictive analytics to anticipate market changes, using real-time data to optimize shipments, and implementing systematic processes that reduce errors. Only 13% of respondents reported achieving this standard, suggesting most firms lack the tools, data governance, and analytical capabilities to support consistently good decisions.

How does poor decision-making impact supply chain costs?

Suboptimal decisions in freight forwarding directly increase costs through inefficient routing, poor carrier selection, compliance violations with associated fines, and redundant manual work. When forwarders cannot quickly analyze rate options, service level trade-offs, or inventory positioning, they default to expensive or inefficient solutions. Over time, these compounding inefficiencies create significant hidden costs that erode margins and reduce competitiveness.

What technologies could improve decision-making for freight forwarders?

Key technologies include integrated TMS (Transportation Management Systems), AI-powered rate optimization engines, real-time supply chain visibility platforms, predictive analytics for demand and compliance, and automated data integration across multiple systems. Blockchain and IoT can provide enhanced tracking data. Machine learning models can identify optimal carrier combinations and anticipate disruptions before they impact shipments. Integration of internal systems with external data (market rates, regulatory changes) enables truly data-driven decisions.

Is this a global problem or concentrated in specific regions?

The study, as reported by Logistics Management, indicates this is a global issue affecting the broader freight forwarding and customs brokerage industry. While the article does not break down results by region, the international scope of the publication and the universal nature of logistics challenges suggest this reflects a worldwide trend. Regional factors (regulation complexity, digitalization maturity) may create variance, but the fundamental issue—inadequate decision-making infrastructure—appears systemic across markets.

Technology & Innovation

Moderate

Only 13% of Freight Forwarders Rate Decision-Making Excellent

Jun 29, 2026

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The signal

A significant industry assessment reveals a stark capability gap among freight forwarders and customs brokers globally: only 13% rate their own decision-making processes as excellent. This finding underscores a widespread challenge in the logistics sector where operational decisions remain largely reactive rather than data-driven. For supply chain professionals, this statistic signals both a competitive vulnerability and an opportunity—those who invest in analytical tools and decision-support systems are likely to capture market share from competitors constrained by legacy processes. The low rating suggests that most forwarders and brokers are operating with incomplete visibility into shipment data, compliance requirements, and market conditions.

Without robust analytics platforms, decision-makers struggle to optimize routing, manage carrier relationships, forecast demand, or anticipate regulatory changes. This capability gap directly impacts service reliability, cost efficiency, and customer satisfaction—three pillars of competitive advantage in logistics. For supply chain teams, this industry-wide challenge presents a strategic imperative: audit your organization's decision-making infrastructure. The 87% of firms rating their decisions as anything less than excellent face structural disadvantages.

Investment in supply chain visibility platforms, predictive analytics, and integrated data governance is no longer optional but essential for competitive survival. Organizations that can demonstrate superior decision-making through better data will attract premium customers and build resilient operations.

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Frequently Asked Questions

What This Means for Your Supply Chain

Simulation Suggestion

this month

What if your organization invested in integrated supply chain visibility?

Simulate the business case for implementing a unified supply chain visibility and analytics platform. Model the reduction in decision cycle time (from hours/days to minutes), improvement in on-time delivery by 8-12%, reduction in compliance violations by 20-30%, and the payback period for such investment across different organization sizes.

Run this scenario

Simulation Suggestion

strategic

What if freight forwarders implemented AI-powered routing optimization?

Simulate the impact of 50% of freight forwarders adopting AI-driven route optimization tools that reduce transit time by 5-10% and carrier costs by 3-7% through better lane utilization and carrier matching. Model the competitive advantage gained by early adopters and the pressure on laggards.

Run this scenario

Simulation Suggestion

immediate

What if competitors improve decision-making faster than your organization?

Simulate competitive loss scenario where 30% of market competitors achieve 'excellent' decision-making status within 18 months through technology and process improvements. Model customer churn, price compression, and market share erosion for organizations that remain in the bottom 75% of decision-making capability.

Run this scenario

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Supply Chain Intelligence: The 2026 Buyer's Guide

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