Carrier Optimization with Lumi

‍Carrier optimization is a powerful strategy in supply chain management, helping businesses reduce freight costs, improve on-time performance, and build resilient transportation networks. In this guide, we’ll walk through Lumi's approach to carrier optimization using natural language and AI-powered insights.

Watch the Full Walkthrough‍

In this example, we demonstrate how Lumi enables fast, intuitive carrier optimization with real-time queries, high-volume lane analysis, and clear identification of best-performing carrier alternatives.

What is Carrier Optimization?

‍Carrier optimization is the process of selecting the right carriers for shipments based on performance, cost, and capacity data. Instead of relying on static routing guides or manual negotiations, businesses can use data-driven insights to match shipments with the best carriers. This helps reduce transportation costs, improve delivery reliability, and build more resilient supply chains.

Carrier Optimization allows businesses to:

• Reduce freight costs. By comparing carrier rates dynamically, businesses can allocate shipments to the most cost-effective carriers without sacrificing service quality.
• Improve service levels. Performance insights such as on-time delivery, damage rates, and geographic coverage help ensure carriers meet customer expectations.
• Increase flexibility. Optimizing across multiple carriers provides backup options during demand spikes, seasonal shifts, or unexpected disruptions.
• Enhance negotiations. Transparent performance data strengthens bargaining power when discussing contracts and volume discounts.

All of these strategies support the same outcome: lower costs, improved reliability, and more agility in transportation management.

Carrier Optimization with Lumi

‍Lumi makes carrier optimization simple by turning natural language questions into real-time insights. Here’s how it works, step-by-step:

Validating the Approach

The objective was to identify lanes where the most commonly used carrier underperforms the global average On Time % (across all carriers for that lane). By confirming this approach, it became clear that pinpointing lanes with a lower On Time % than the global average highlights opportunities to optimize carrier selection and improve delivery performance.

Focusing on High-Volume Lanes

Noticing that some of these lanes had low volume, the focus was then narrowed to only include lanes in the top 10% of shipment volume.

Adding Best-Performing Carriers

The analysis was further refined by adding two additional columns: the carrier with the highest on-time % and the name of that carrier.

This approach shows the lowest on time percentage carriers and other carrier options with the best performing carrier rate.  Lumi identified carriiers that consistently underperfors the global on-time percentage. In every high-volume lane analyzed, there is an alternative carrier with a significantly higher on-time percentage, compared to the most common carrier.

Discover how Lumi AI can streamline your carrier optimization processes with advanced AI-driven insights and automation. Book your demo today.

Frequently Asked Questions

Q1: What is carrier optimization in supply chain management?

Carrier optimization is the use of data and analytics to select the most efficient carriers for shipments based on cost, performance, and capacity, instead of relying on static routing guides.

Q2: How does carrier optimization reduce costs?

It enables businesses to dynamically compare rates and allocate shipments to the lowest-cost carriers that still meet service standards, cutting transportation spend.

Q3: How is carrier optimization different from freight consolidation?

Freight consolidation combines multiple shipments into one load to maximize efficiency. Carrier optimization, on the other hand, focuses on selecting the right carriers for each shipment. Both strategies can be complementary.

Q4: How does Lumi generate the SQL for these analyses?

Lumi understands your data schema and translates natural language into SQL queries automatically, runs them on your transportation data, and returns both results and explanations, along with assumptions made to generate the query.