Mitigating the Dwell Time Problem with Real-time Facilities Data

Dwell time – or the time drivers spend at facilities waiting to drop off or pick up loads – is one of the more vexing challenges for stakeholders across the supply chain. Everybody wants to reduce dwell time because everyone feels the negative effects when freight schedules go awry.

That’s why FourKites was so enthusiastic to join forces with the Trading Partner Alliance (TPA) and industry leaders Coca-Cola, Land O’Lakes, Giant Eagle and Wegmans in a pilot program designed to use real-time visibility to understand the root causes of dwell time at four real-world facilities, and devise strategies to minimize it. The pilot tangibly demonstrated how supply chain partners can leverage real-time data to reduce dwell time and capture additional capacity.

You can access the full report here, where we detail the pilot methodology, insights and recommendations. Here are some highlights.

Dwell Is Everyone’s Problem

According to the Owner-Operator Independent Drivers Association (OOIDA), in 2018, 78% of carriers lost the opportunity of at least one load per month due to detention times. Almost half lost more than one load per month. For shippers, excessive dwell times become detention fees; greater delays equal bigger losses for all, and put a real strain on business relationships – sometimes pushing them to the breaking point. 

And because dwell time is included in Hours of Service (HOS) maximums, it reduces the amount of time drivers can be on the road. Worse yet, dwell time is a real safety concern. A recent study by the U.S. Department of Transportation and the Federal Motor Carrier Safety Administration (FMCSA) found that for every 15-minute increase in average dwell time, average crash rates also climbed by 6.2% due to driver fatigue and related issues, increasing “the likelihood of truck crashes involving fatalities, significant injuries or vehicle towing”.

In short, it’s in everyone’s interest to reduce dwell time as much as possible.

Creating the “Dwell Dashboard” with Real-time Data

Working with a select group of supply chain managers and directors from Wegmans, Land O’Lakes, Giant Eagle, Inc., and Coca-Cola North America, along with several of their carrier partners, we developed a customer Dwell Dashboard based on real-time dwell data from their facilities. 

We analyzed several key metrics: number of loads and appointments; median dwell time; percentage of non-compliant loads and delayed carrier arrivals; and average delay of late arrival loads. We also looked at a number of “tier 2” metrics, including day of the week, time of day, inbound or outbound load, temperature class and type of product.

Every week we refreshed the dashboards to provide an updated, accurate snapshot of each facility’s dwell performance. Based on that data, Wegmans, Land O’Lakes, Giant Eagle, Inc., Coca-Cola North America and several carrier partners gathered to share insights and strategize on how to optimize dwell time performance. For instance, if the data highlighted that a certain type/concentration of loads was contributing to excessive dwell at a certain time during the week, these supply chain leaders were able to proactively adjust schedules to avoid such situations in subsequent weeks. 

These sessions clearly demonstrated how, when armed with the right data, decisions can be made swiftly and effectively across even the most complex supply chains.

Real-time Data + Collaboration = Dwell Time Reductions

Post-pilot, each facility observed improvements in dwell performance across the board. Here are some of the strategies and initiatives they adopted to drive those gains:

  • Coca-Cola Auburndale expedited the check-in process and brought down dwell time by moving the check-in and check-out process to a consolidated Guard Shack instead of a shipping and receiving office. 
  • Land O’Lakes’ digital check-in process at its Quakertown facility had the fastest check-ins throughout the pilot, demonstrating that automating check-in procedures is key to reducing driver on-site time. 
  • Giant Eagle Crafton and Land O’Lakes Quakertown found a direct correlation between high load volume and increased dwell. They are each working on a load-balancing initiative, attempting to reduce dwell times by balancing out inbound and outbound load volumes across the days of the week to reduce dwell. 
  • Wegmans Rochester identified issues with complex loads, such as mixed-pallet loads, and is working on an initiative to see if multiple purchase orders with the same item can be grouped into a single order to lower complexity and therefore reduce dwell.

Based on the positive results of the pilot, our general recommendations for reducing dwell time call for establishing a common understanding of root causes of high dwell times; launching an industry standard dwell time tracking app/interface; and defining measurement criteria for on-time-in-full (OTIF). You can read our detailed findings here.

The good news is that the successful reduction in dwell times throughout the transportation sector at large has the potential to create an additional 2-4% of transportation capacity. With an estimated two million trucks on U.S. roadways alone, this represents the potential for significant economic gains, as well as safer roadways.

The successful reduction in dwell times throughout the transportation sector at large has the potential to create an additional 2-4% of transportation capacity.

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As this important TPA-led pilot demonstrates, real-time supply chain data combined with ecosystem partner collaboration creates a powerful foundation for driving the improvements the supply chain needs to thrive. We learned a lot through this exciting initiative, and look forward to partnering with other innovative supply chain leaders on similar projects.

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