What Type of Data Helps in Last-Mile Delivery Scheduling?

How do companies break into the new and reinvented last-mile delivery economy? The data required to be relevant and effective has changed. New data characteristics now include urban planning, state of charge, fuel tank level, weather, designated delivery zones, weather, and more. All these types of data come together to form a plan of how goods and services can be scheduled.

Panelists from Geotab’s Mobi team and Deloitte discussed how to engage in new data for last mile delivery of goods and services during a session at the Data-Driven Fleet Experience last month.

Data can help determine what’s going on in the field and how to incorporate that into a company’s operations. This can help when choosing fleet vehicles. If a company is looking at adding electric vehicles to its fleet, it should consider what type of charge range would be needed to service its delivery route. By collecting a vehicle’s raw telematics data, you can better calculate the type of electric range required to make the required deliveries on one charge.

How do you ingest all the data that’s happening in the field and bring back that information to the routing software? Using driver knowledge and telematics data.

Telematics data helps a company keep track of preventative maintenance and what the vehicles are doing: When did the vehicle stop? Did it idle? Where did it park to make a delivery?

A company can take what its drivers are experiencing and capture that as data points. For instance, if drivers are making deliveries in a more congested place like New York City, it might take 10 to 15 minutes longer to make a delivery if they need to park in different locations or double park. That information can be captured and then used to plan for future routing.

Because companies are delivering different size packages at different locations, they aren’t doing the same runs every day, leading to different delivery patterns.

“If you are collecting data about your customers and their needs and about the supply and demand mix, then you can plug that information into a computer algorithmic tool,” said Darren Plested, future of mobility & transportation partner, consulting at Deloitte. “Then that can have a very dynamic change on your supply chain every day.”

Urban Planning

As cities look at future urban planning, this includes systems that need to be in place to regulate the flow of goods. If a company has access to its current vehicle and driver data, it can more accurately describe to city officials how urban planning might impact its operations.  

For example, if a company needs to move its warehouse farther from the city center because the property is now going to be used for other reasons, the company’s commute times are likely going to increase. If the company already has access to telematics data on its current routing times, it can get a sense of how its operations will be impacted.

Future Advancements

With autonomous fleets on the horizon, data is going to be even more important. How will companies get a package from point A to point B in the most efficient manner without human drivers? You might have a centralized control tower that’s managing the autonomous vehicles, but without a human driver, everything is going to be data driven. How will companies get the data needed to plan for future changes like zero emissions and autonomous vehicles?

“It’s accessing the current environment to be able to create a solution that’s more autonomous as far as reducing the decisions a driver needs to make to capture all elements from what you’re planning, what you’re seeing going on in the field, and then feeding that back into your routing,” said Ryan Hoover, AVP, strategic partnerships, sales at Geotab. “It’s working now to have an end-to-end solution that can route effectively with those data elements as well as create a cycle where you can take that data, put some machine learning data models against it, and factor that into your next generation routing for assessing future situations.”