Testing the future of transport at Coca-Cola European Partners in Swed ...
To the surprise of no one, most transportation companies hate making decisions in real-time. There are a number of reasons for this, of course. Transportation is a physical industry and when things are happening in the physical world, they take time, use resources and can be hard to manage overall.
If you look at a city during office hours you might find 1,000 trucks inside the city limit. None of them know what the other 999 trucks are doing, none of them are fully loaded, and all of them are waiting for the other trucks to get out of the way so that they can perform their deliveries. If you continue to observe the city for an hour, you will find hundreds of possible collaborations between the 1,000 clueless trucks. Collaborations that do not happen. Neither the carriers that own the trucks nor the companies that are responsible for the transportation have the time, the knowledge or the data needed to be able to act on these possibilities.
Instead the transportation system is based on rules of thumb, zip codes, predetermined milk runs, hard-coded patterns and other systems that do not need decision making in real-time to work. The planning is preferably made well in advance. No surprises please, we’re driving and have no time to adapt to changes.
All of the above absolutely screams for digital development, sensors, cloud computing and network optimization. That development is of course already underway, as is development of the algorithms that will make the transportation networks more efficient. In some aspects it will also push towards decarbonization in the sense that in an optimized system, the same transportation utility will be achieved with less resources. Fuller trucks, fewer empty trips, fewer vehicles needed, all leading to less energy used in the system over time. Alternative fuels will also push the decarbonization further. But the real difference is when we substitute the fuel that is combusted in the engine with green electricity.
Electric vehicles have the potential to decarbonize most of our transportation systems, reducing equivalent CO2 emissions by more than 90 percent. But if you try to just replace an internal combustion engine with a battery powered alternative you will soon realize that the two are not interchangeable. The combustion engine truck will have a large tank that enables it to travel longer distances and to fill up quickly when needed. The electric vehicle has a maximum range that is determined by the size of the battery, and the charging takes longer than filling a diesel tank (for now at least; chargers are getting faster all the time and battery technology is improving progressively).
The electric truck has the potential to be very cost effective compared to diesel trucks, but only if it is used wisely. The ideal usage pattern is to drive the same total distance every day, to charge at home during the night when electricity is less expensive and to maximize the uptime. If you do this, the electric truck will have a lower life cycle cost than a diesel truck, while performing the same work but at a fraction of the carbon footprint.
So why isn’t everyone doing this already?
The answer is that in most transportation networks, the consistency profile (driving the same distance every day etc.) has not been a deciding factor when planning delivery runs. The rewards are typically not large enough for combustion engines to be forced to new patterns. But when planning for an electric fleet, where consistency is crucial, new ways of optimizing become possible. And suddenly, we can not only reduce inefficiencies but also drastically reduce carbon footprint and also cost, even for the carrier who owns the truck. But this requires a new type of digital planning system that in turn allows for a new type of transportation system.
To just go digital or just go electric will never be enough. We need to do both, and we need to do it intelligently. Electric and digital is a match made in logistics heaven. Let’s make it happen already.