Accelerating Change in Dispatch Technology: Promise and Perils for Dispatchers

Dispatching is the heart of logistics. And for decades, it has also been an art. Traditionally, dispatchers used personal knowledge to plan delivery routes, turning their familiarity with the roads, the trucks and the drivers in their fleet into a map of stops that drivers could execute. While pencil and paper gradually yielded to spreadsheets, in less than a decade tools that use AI and machine learning to quickly analyze massive amounts of data have swept the industry, solving complex routing problems that once took hours—all in seconds. This is transforming logistics from an art into a data-driven science.

While this technology hasn’t replaced dispatchers, it has profoundly changed their jobs. Instead of manually plotting routes on a map, it allows them to focus on making strategic decisions, driving business efficiency and improving customer satisfaction. Unsurprisingly, adoption of this technology has been high (though not yet universal); equally unsurprising has been rapid advances in the technology bringing ever more powerful tools to dispatchers. This has created an arms race, so dispatch software that was cutting edge just a year or two ago may now be putting delivery organizations at a competitive disadvantage as their rivals adopted newer, more capable platforms.

A recent McKinsey study found that while both shippers and transport providers have invested heavily in logistics software (including dispatching/routing) there’s a gap, with shippers lagging behind providers in adopting basic technologies: 76% of providers have deployed at least dispatching/routing software while only 64% of shippers have—a 12 point gap. However, that also means that a quarter of transport providers do not yet have even basic transportation management software, a lack that McKinsey called out, saying “Companies that have not invested in these systems could be at risk of falling behind their competitors.”

In more direct language, they’re telling delivery organizations to get on the technology bus or get run over by that bus. When considering newer tools with advanced capabilities like route optimization, real-time visibility and telematics adoption rates plummet: Just 68% of providers and 56% of shippers have adopted those.

Why is deploying this tech—and making sure the technology deployed has the most advanced capabilities—so important? Because it reduces time and effort in route planning, increases efficiency by decreasing failed deliveries and miles driven, and has been shown to boost customer satisfaction. This is especially important in the last mile, which is the most difficult—and most expensive—part of the delivery process.

Highly Optimized Routing

The only way to fully optimize routing is by employing software with AI and machine learning built into its core, not added on as afterthought. AI and ML take in data from deliveries as they are executed—such as time differentials for deliveries made to similar locations but different customers—and use it to plan routes that make the best use of a fleet. This is an essential part of how dispatchers worked before the advent of routing software, but rather than forcing dispatchers to keep all of that knowledge in their heads, it now lives in the software, and the software can apply what it “knows” to hundreds or thousands of possible route combinations in seconds or minutes rather than hours or days.

This also makes routing scalable. In the past, to route more trucks required additional experienced dispatchers with specific knowledge of the delivery organization’s fleet and customers. The most advanced trucking dispatch software scales from a few dozen delivery units to thousands without slowing significantly, so dispatchers can spend their time monitoring executions and identifying greater operational efficiencies.

Real-Time Visibility

Without real-time tracking of deliveries, dispatchers are flying blind once the trucks leave the dock. While GPS allows vehicles to be located on a map, that alone doesn’t tell dispatchers what’s actually going on with their deliveries. Real-time visibility also means knowing whether a customer ahead on a route has canceled a delivery, whether there were problems with a delivery, when a delivery has been made and if the customer was satisfied with the goods delivered and their condition. GPS won’t tell you that. When combined with route optimization, the benefits of being able to head off problems before they occur—such as rerouting a unit to delay a postponed delivery without significantly increasing the length of a route—can save up to 10% on both miles and fuel cost.

Automated and 2-Way Communications

Seeing problems before they develop is not much use if your software doesn’t give you a way to communicate with the driver and the customer to create a solution—or better yet to prevent that problem in advance. Automating pre-routing and delivery day communications with the customer has enormous benefits in reducing failed deliveries. The best tools allow customers to self-schedule their deliveries into windows that are pre-optimized for your fleet and delivery queue. As that queue fills, the windows that are offered change, taking into account the delivery location and degree of difficulty as well as the preceding and following deliveries in that area.

Customers can be automatically contacted several days in advance, the day before delivery and again the day of delivery, at the route start, and when the driver is one stop away. If there is an issue—a customer has to cancel, or there’s a gate code required—the best tools support two-way communications between customer, driver, and dispatcher. Live tracking that allows customers to see updated ETAs and the location of their delivery on a map dramatically reduces where-is-my-order phone calls. The dispatcher, freed from the manual effort of routing with a spreadsheet and answering customer phone calls, can instead focus their efforts on making the daily execution go smoothly, boosting customer satisfaction while increasing operational efficiency.

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