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How to Optimise Delivery Routes with Travel Time Data

by Victoria Akinsowon on Aug 25, 2021

When you have many deliveries to coordinate, planning delivery routes quickly becomes challenging. Unsurprisingly, the more delivery routes you have to plan, the greater the level of complexity. 

But how can you plan your delivery routes more efficiently? 

In this article, we'll explain what delivery route optimisation is and how you can plan the most cost-effective delivery routes with travel time data.

Contents

What is delivery route optimisation?
Why is delivery route optimisation important?
What are the challenges of delivery route optimisation?
How do you optimise a delivery route?
Public transport route optimisation example: Thomas Sanderson
Effective route planning with travel time data

What is delivery route optimisation?

Delivery route optimisation is the process of finding the most efficient and cost-effective routes for deliveries. By optimising your delivery routes, you can reduce the total amount of time that your team must travel when making multiple stops.

Just some of the industries that can benefit from delivery route optimisation are:

  • Food delivery: Plan food delivery routes and operations
  • E-commerce: Optimise last mile delivery routes
  • Field sales: Visit more customers and maximise sales
  • Post and courier services: Plan post and parcel deliveries
  • Logistics: Plan the most efficient routes to reduce operational costs

Why is delivery route optimisation important?

Whether your business offers direct-to-consumer deliveries or services where field employees visit clients in person, delivery route optimisation is crucial to maximising the efficiency of your operations. It helps you:

  1. Save costs and resources, including fuel
  2. Reduce the amount of time spent travelling
  3. Make deliveries with the most efficient use of resources
  4. Ensure that customers receive their deliveries at the scheduled time
  5. Reduce delivery time windows
  6. Plan in real time and react to last-minute changes

What are the challenges of delivery route optimisation? 

Imagine you have 10 delivery employees, each making 10 stops a day. There are potentially millions of possible permutations of how their routes could be allocated.

Additionally, there are other factors to consider, such as how stops are allocated to each driver and the sequence of stops they should follow to get the shortest possible route time. Depending on the location, you may also want to consider whether alternative modes of transport can be used to maximise efficiency. 

Processing all of these options requires a lot of calculation - this is often referred to as the travelling salesman problem.

Can you optimise delivery routes manually?

For the reasons explained above, manually finding the optimal delivery routes is virtually impossible. With just a handful of vehicles, there can be millions of different route options.

And because the calculations required to calculate the optimal delivery routes are incredibly complex, the human brain can't possibly compute all of the different parameters in a short timeframe. This makes manually planning routes both time-consuming and prone to human error.

How do you optimise a delivery route?

You can use delivery route algorithms to automatically calculate every possible delivery route in seconds. These algorithms can be accessed through a routing API.

For example, with the TravelTime API, you can plan and optimise delivery routes by using travel time data to determine the shortest possible routes for your drivers or field employees. Through the API, you can identify the quickest route for up to 100,000 origins and destinations within milliseconds.

How does travel time data help to optimise delivery routes?

Travel time data can process every possible route option by different transport modes and help select the most effective route for an entire fleet. 

The location in which your team is operating often determines the types of transport they will use to travel. For example, in cities, deliveries or visits may be done by car, bike or public transport.

The TravelTime API provides journey time data for any mode of transport. This means that you can use the API to calculate whether a route would be more efficient depending on the transport mode selected, such as driving vs. cycling. 

Thanks to the fast speed of the TravelTime API, it’s possible to run regular analyses to identify the most efficient route. This means you can adjust your delivery routes throughout the day. You can also specify time windows for deliveries. 

Public transport route optimisation example: Thomas Sanderson

Originally, Thomas Sanderson, a manufacturer of window shutters and blinds, had its 150+ field salespeople driving to client appointments because of the weight and size of its demonstration kits. 

However, after changing the type of equipment its employees needed to take with them on appointments, Thomas Sanderson team saw an opportunity to route their salespeople by public transport instead of driving. This would reduce the time spent in traffic and reduce operational costs. 

Thomas Sanderson decided to use the TravelTime API to route its salespeople to multi-stop appointments using public transport. TravelTime allocates calls efficiently amongst a sales team, then routes each team member around their allocated calls, by public transport (and all other modes).

“The [TravelTime API] helped us rethink how we plan sales appointments, plan the hiring new salespeople and plan how we travel to the customer," said Project Manager, Angela Mills. "These decisions have the potential to generate millions of pounds of additional sales each year.”

Effective route planning with travel time data

Delivery route optimisation is a complex process. There are many factors to consider, from which stops to allocate to the transport modes that can be used for maximum efficiency. 

To better plan and optimise your routes, the TravelTime API provides accurate and up-to-date journey time data for any transport mode. With the ability to calculate up to 100,000 routes in milliseconds, you can use the TravelTime API to help you determine the most efficient routes for your team.

To try the TravelTime API for yourself, start a free trial

Want to learn how to use TravelTime for route optimisation? Just contact us below. 

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Topics:
Location data Routing