Truckload budgets are at risk when pricing is set below the market price

Brief

Does paying higher rates to truckload carriers yield (1) better on time performance and (2) better load tender acceptance? This white paper explores the relationship between service and price in the U.S. truckload transportation sector.

You’ve heard the saying, “You get what you pay for.” It does seem to be the case that higher quality products and services that cost more often outperform the lower quality, cheaper versions. But does paying higher rates bring better carrier service?

Rates present a constant dilemma between shippers and carriers.¹ Shippers face continual pressures to reduce costs; carriers expect to be paid fairly for their services as their costs, maintenance, and equipment quality continue to increase. Other research projects have shown relationships between various aspects of transportation and final rate paid as a result of guide performance.² But when a shipper pays higher transportation rates per mile, do they really receive better on time performance and load tender acceptance patterns from their carriers?

We asked Nane Amiryan and Sharmistha Bhattacharjee, graduate students at MIT’s Center for Transportation & Logistics (MIT CTL), to find out. This white paper provides highlights of their findings about potential correlations between transportation carrier rates and performance.

How is OTD measured?

Does paying higher rates to truckload carriers yield better on-time performance?

1. Paying more does not result in better on- time pickup (OTP) percentage.
2. Paying significantly above market price does not provide notable improvement in on- time delivery (OTD).

There was no relationship found between OTP and freight rate. Rates had more impact on OTD than OTP, but the correlation was weak. However, when shippers paid below market average, there was a clear decrease in OTD performance (see Figure 1). An average drop of $50 below the market rate resulted in OTD performance below 40 percent. A rate of $20 below the market rate led to 40 percent to 70 percent OTD.

As Figure 1 shows, carriers with OTD percentages below 70 percent charge less for their services. This shows that shippers who always choose the lowest-cost carrier are most likely to get what they pay for. Shippers who had OTD in the 70 percent and 80 percent range paid market rates.

Those with OTD between 80 percent and 90 percent paid just over a $20 premium. On average, there was almost no additional premium to reach the 90 percent to 100 percent OTD range.

FIGURE 1: Effect of rates on OTD (on time delivery)

Does paying higher rates to truckload carriers yield better load tender acceptance?

No correlation was found between acceptance ratios and carrier pricing in a lane.

The data suggests consistency in shipment tender patterns leads to lower price paid. Freight consistency—tendering at least one load per week to a carrier in a given lane—is a measure that carriers increasingly seek.

In the case of truckload transportation, tender acceptance ratios of carriers rise when shippers offer consistent load volumes on a particular lane. No correlations were found between acceptance ratios and carrier pricing in a lane.

However, shippers that are highly inconsistent in their tenders in a lane over the course of a year (i.e., tendering less than one load per week more than 80 percent of the time) pay about $170 more per load or better than 11% higher per load per lane (see Figure 2).

The research also found shippers that are highly consistent—tendering at least one load per week more than 80 percent of the time—pay a slight premium of $10 per load. Or rather, their favorable discount was about $10 lower than the 60–80% lane tender consistency.

This suggests there is a plateau for consistency reward with some small additional opportunity between price and tender acceptance to get the highest possible primary carrier acceptance.

This data seems to reinforce other research conclusions on lane aggregation—that low volume, point-to-point lanes can be combined to improve consistency.

FIGURE 2: Shipper consistency ranges

Carriers need to optimize their networks

Consistently receiving loads on a particular lane allows carriers to develop a sustainable network plan and increase the utilization of the fleet. Previous research in lane aggregation supports this finding, showing that when lanes are aggregated—when low volume lanes are bundled within larger origin/destination pairs—the shipper sees better tender acceptance and more attractive pricing (meaning the demand/tender pattern is smoothed to the carrier).³

Shippers have the opportunity to benefit from lower pricing by offering a carrier consistent loads on a lane for 30 to 35 weeks in a year or more. There is value to the shipper to keep carriers engaged on a lane so they can scale up when needed.

This research supports using a ratio tendering strategy, awarding loads to a group of carriers, week in and week out, instead of using a primary carrier and a backup.

Finally, researchers found a relationship between consistent shipment tenders and a greater likelihood that the primary carrier would accept that tender.

Additional insights

The research did not ask specifically about the relationships between OTP and OTD, but the data showed an unexpected correlation.

First, 80 percent of loads that pick up late deliver on time as shown in Figure 3. (i.e., more than 80 percent of the time, carriers make up for delays in OTP and deliver on time).

There is usually some extra time built in between the time of the required pickup and delivery. The time between origin and destination cannot be planned too close to the actual time it takes to drive from one location to the other because there are too many factors that cannot be planned for: traffic and weather delays, equipment breakdowns, etc.

In addition, carriers use the buffer of time to maximize their drivers’ hours of service (HOS). Some carriers choose to be a little late at pickup because it enables them to more closely match the driver’s HOS and distance with delivery schedules to boost efficiency.

FIGURE 3: Relationship: late pickup to on time delivery

However, 50 percent of loads that delivered late also picked up late as shown in Figure 4. This points to a need for shippers to be aware of late pickups and to make sure carriers have an action plan to correct the situation.

To improve performance scores, shippers must first understand OTP and OTD performance statistics and the relationship between them. A lane level analysis can show patterns of particular carriers, locations, or times of the day for pickup and delivery appointments to identify problem areas that can be corrected.

Findings from this sort of analysis might reveal that the performance of a facility is overall satisfactory except during certain times of the day or a certain day(s) of the week. Meaning, there may not be a wholesale issue, but rather a specific process or planning strategy that if amended, can improve performance where it is faltering and not negatively influence the broader facility performance.

FIGURE 4: Relationship: late delivery to on time pickup

Action items suggested by this research

1. Find the right carrier

The best carrier for a lane is neither the cheapest nor the most expensive, but the one whose service network complements the shipper's freight. This research suggests that paying market rate yields the best on time delivery. When shippers pay below market, they see a significant drop in OTD; those who paid just over a $20 premium had OTD between 80 percent and 90 percent.

2. Monitor performance for on time delivery

Good customer relationships depend on reliable carrier service levels. Shippers can use a transportation management system to obtain OTD levels for each carrier used and determine how often carriers perform as expected.

About the study

Two research projects have studied if paying a premium garners higher truckload performance:

• The first is the foundation of the content in this white paper based on shipment data from 2013–2015.⁴
• The second is from research using a shipment dataset from 2015–2019.5

The data for both projects comprised tender and shipment records for dry van truckload shipments from TMC, a division of C.H. Robinson, to control for economic cycles. Only single stop loads between 250 miles and 3,000 miles within the continental United States were considered.

The datasets included tender information from a large portfolio of shippers and nearly a thousand carriers, with millions of shipment tenders and executed truckload shipments.

“Performance” can include many criteria—transit times, technical competencies, flexibility during emergencies, willingness to share information, freight damage history, carrier financial stability, and so on.

For purposes of this study, the researchers defined performance this way:

• Timeliness factors—on-time pickup (OTP) and on-time delivery (OTD)
• Acceptance ratio (AR)—accepted loads to load tenders to a primary carrier (i.e., the number one and number two carriers in the routing guide)
• Consistency and volume of loads a shipper offers a carrier on a particular lane, and its effect on cost per load and acceptance ratios

NOTES

1. For purposes of this white paper, “carriers” is broadly defined as both asset-based motor carriers and non-asset-based carriers and brokers.
2. Julia Collins and Ryan Quinlan, “The Impact of Bidding Aggregation Levels on Truckload Rates,” MIT’s Master of Engineering in Logistics Program thesis; Erik Caldwell and Bryan Fisher, “Impact of Lead Time on Truckload Transportation Rates,” MIT’s Master of Engineering in Logistics Program thesis; Evan Armstrong and Dick Armstrong, “Carrier Procurement Insights: Trucking Company Volume, Cost, and Pricing Tradeoffs;” Bobby Martens, Ph.D., "Do Favored Shippers' Really Receive Better Pricing and Service?"
3. Bobby Martens, Ph.D., Kevin McCarthy, Chris Brady, and Steve Raetz, "Do ‘Favored Shippers' Really Receive Better Pricing and Service?" Iowa State University, TMC, and C.H. Robinson, 2016.
4. Relationship between Price and Performance: An Analysis of the US Trucking Market. Nane Amiryan and Sharmistha Bhattacharjee , MIT’s Center for Transportation & Logistics. Master’s in Supply Chain capstone project. Read the thesis here.
5. Elephants or Goldfish?: An Empirical Analysis of Carrier, Reciprocity in Dynamic Freight Markets. Angela Acocella. PhD Candidate, MIT- Center for Transportation & Logistics January 2020. Read the paper here.

Contributors

Nane Amiryan received her B.A and M.A. in Economics from Yerevan State University, Armenia. Before coming to MIT, she worked in a small manufacturing company and an auto transportation company in Pennsylvania.

Sharmistha Bhattacharjee received a B.E. in Electronics and Telecommunications Engineering and a Post Graduate Diploma in Industrial Management. Before the Supply Chain Management program at MIT, she worked for three years as supply chain manager with Unilever in India. Today, she is a senior program manager at Amazon.

Kevin McCarthy worked for C.H. Robinson as a director of Consulting Services. Kevin has an MBA from the University of Minnesota Carlson School of Business with an emphasis in Management Information Systems and an undergraduate business degree with an emphasis in Marketing.

Steve Raetz, director of supply chain integration at C.H. Robinson, has 26 years of logistics experience. He holds a B.S. in Mathematics and Teaching from Minnesota State University, Mankato, and serves on two university supply chain advisory boards.

Glenn Koepke, director of operations for TMC, a division of C.H. Robinson, has worked globally with shippers in Europe, the Middle East, and Africa (EMEA), responsible for both operational excellence and supply chain engineering. A graduate of the University of South Carolina in Columbia, Glenn also opened TMC’s EMEA global Control Tower in Amsterdam.