The UK courier and express delivery market is booming, due largely to the ever-increasing popularity of online shopping. The sector is currently experiencing double-digit year-on-year growth, which is expected to be maintained until at least 2023, with Brits sending a massive 3.65 billion packages last year.
But while the future of delivery services looks good, it is still a highly-competitive market with slim margins. Success depends on businesses continually improving their service while at the same time finding cost savings and efficiencies. Customers want to receive deliveries more quickly, or within highly-specific time slots, but aren’t necessarily willing to pay extra for the privilege. Integrating and analysing data using GeoSpock’s state-of-the-art spatial big data platform can help delivery companies achieve both service improvements and efficiencies in a variety of ways.
Driver route analysis
Traffic movements can be monitored using call and short message service (SMS) records if delivery drivers are issued with Internet of Things (IoT) SIM cards. Each driver can then be correlated to the road infrastructure using the SIM and global positioning system (GPS) coordinates, to gain a detailed picture of delivery routes. Moreover, because the SIM has a time sequence, analysis can also show when the driver leaves the depot or dispatch centre, and when they undertake drop-offs at residential or business locations.
Delivery companies can calculate key metrics to help them understand driver routes such as average drop times, distance between drops, and dwell time at each stop. When businesses understand what is happening, they can take action to improve. For instance, they might identify recurring traffic or road issues in specific locations or at certain times of day, enabling them to reroute drivers to avoid these.
Looking at the bigger picture, a delivery company can use data generated by IoT SIM cards to see how many delivery drivers are in a specific regional area – such as a cell tower catchment area – at any given time. They can identify overlaps where multiple drivers serve the same location or street during a set time frame and use the information to improve planning.
If depot locations are layered in as points of interest, companies can perform driver-to-depot density analysis over time, correlating the volume of drivers in a given area to the regional depot, which helps with resourcing. Additional data sets, such as retail customer information, can be combined with spatial data sets to analyse, for example, successful delivery attempts versus unsuccessful delivery attempts and identify patterns that can improve service levels moving forward.
Parcel locker monitoring
Not all deliveries are made to home or business addresses. Self-service delivery locations, or lockers, are frequently used to give customers the freedom to pick up their packages at a convenient time. Amazon has over 2,000 such locations in the UK and Hermes recently announced an agreement with InPost to use its network of around 1,000 lockers.
These drop-off locations can be added as points of interest to a geospatial data set to monitor patterns of use. Lockers can also be fitted with IoT SIMs for security purposes, to trigger an alert if they are moved outside of a geofenced area.
These are just a handful of the potential use cases for spatial data in the courier and delivery sector, helping businesses continue to achieve more with less.
To learn more about how the GeoSpock spatial big data platform can unlock insights in your data or to see a product demo, get in touch and a member of our team will contact you.