From process to new business model
The task is therefore to collect information, connect it in different ways, and use it to create added value. For the tugger train processes described above, for instance, this means that the data and information would no longer only be used to improve the organization of internal transport processes. They would also create new business for manufacturers of industrial trucks. For instance, the information could be used to develop more appropriate billing systems. Instead of buying a whole industrial truck, customers would then lease it and pay according to operating times or the distance travelled.
This type of approach would benefit both sides. Customers could reduce the size of their fleets and with it the amount of capital they have tied up. Manufacturers could increase the utilization rate of their fleets because they could flexibly lease and bill for vehicles according to requirements.
Manufacturing companies could also make additional use of the movement profiles of their industrial trucks. One example would involve linking the profiles to other information collected by sensors on, for example material stock and consumption, and using it to calculate reorder points. The information would be forwarded to the relevant offices inside and outside the company. As well as triggering repeat orders to suppliers from the company’s procurement department, this would also allow logistics service providers to efficiently plan full capacity utilization of their transportation systems in advance. This would create the foundations for sustainable logistics.
The future is smart
The increasing availability of internal and external data has enormous potential for the services of the future. The data can allow businesses to predict future customer needs, for instance when patterns in a machine’s usage data indicate that an outage is imminent, or when weather and traffic data suggest that a delivery might be late.
The ongoing optimization of the relevant basic technology also plays its part. In future, for instance, RFID tags will no longer only be used for simply identifying objects. Additional functions such as sensor technology and positioning systems will enter many different fields of application, including warehouse and container management. Multisensor labels will monitor aspects such as temperature, pressure, and moisture. They will reduce search times and help with inventories. This will also create new and additional potential for technology suppliers and users.
Data drive the megatrends
Data are the main drivers of all eight megatrends. The more networked, mobile, smart, automated, and therefore digital our world becomes, the more important these new raw materials will be. The term “raw materials” is fitting, as data alone are nowhere near capable of creating value for companies. It is not just a question of collecting data – they also have to be analyzed, interpreted, and potentially optimized before they can be used. Once that has happened, though, they open up entirely new worlds of application – with all the consequences for businesses, which have to learn how to handle new customer groups, payment models, technological infrastructures, cost structures, and collaborations.
Success and added value from data – including in logistics
Working with data like this is our core work at the Center for Applied Research on Supply Chain Services (SCS). We therefore know that, compared to physical products and pure services, data will gain more significance in the future – including and primarily in logistics which, as the “gateway to customers” in sales and production processes, is increasingly being confronted with the subject. On the one hand, this comes from shipping agents who expect better networking and communication, and more transparency for more agile processes. On the other hand, it comes from the industry itself, which is virtually obliged to profit from the digital transition so that it can master the future rather than be mastered by the future.
In the near future, the logistics industry will need to deploy data in their processes, service offerings, and business models in a way that adds value. Even if we cannot tell from this distance which trends will change logistics and at what intensity, one thing is sure: digitalization and the increasing focus on service in business and everyday life are advancing. Collecting, analyzing, optimizing, and exploiting data as key economic factors will therefore become essential in the future.