Our vision on the Logistics domain can be summarized in the following action lines:
- Ensure all actors share and receive relevant information and insights in real time;
Information is generally structured in a hierarchical fashion in most logistical networks, with a central planning department being in control of all information streams. In practice, this can lead to information overload. We believe that networks can benefit from structuring information as a network as well. This way, drivers can get insight into other trucks on or near their route, and packages themselves can continuously look for a more optimal path to their destination. For instance, a driver running behind on their delivery could share their burden with another driver who has an easier route, and is running out of packages.
- Solve planning locally, keeping as much leeway as possible;
The last step in a package’s journey – known as ‘last mile’ – is often the most difficult to plan, since a relatively large and uncertain amount of time is spent on finding the address, parking, unloading, and delivery, which makes it hard to give exact delivery estimates. However, by involving the customer themselves, this problem can be solved locally. Examples include delivering to the customer’s current location instead of a fixed address to ease the requirement of a fixed window when they have to be at home, or involving the customer’s social network or daily pattern to create more efficient delivery strategies.
- Transport capacity within the network should not go unused;
All too often, several parties have separate logistical channels even though their shipments have similar characteristics and modes of transport. This puts additional pressure on infrastructure such as roads and rail- and waterways, while each individual vehicle generally has transport capacity to spare. We believe that this can be optimized locally, taking advantage of excess capacity in parallel transport networks to achieve a more optimal solution, with less congestion and no reduction in lead times.