Smart data: the future of logistics

The Internet and containers are two obvious innovations that have revolutionized logistics over the past decades. They linked up the world, created new and bigger markets, and ultimately drove enormous growth in global trade. Thanks to them, the world has become smaller. They also expanded economic opportunities – although only for businesses that recognized the potential of these innovations early on and mastered the full repertoire of possibilities presented by this new age. This is why it is so important to know today what the state of the art will be tomorrow. To do that, however, we have to know what innovations are on the horizon.

 

So how will logistics develop from here? What technologies in manufacturing and transport will simplify processes? And how have businesses organized themselves to respond to the needs of their customers? Anyone who wants to answer these questions must know the trends that will define the market in the future. At the Fraunhofer Center for Applied Research on Supply Chain Services (SCS), we have spent more than 20 years observing developments in logistics. We recently produced an internal study that identified eight megatrends with the potential to fundamentally change the way supply chains will work over the coming years.
 

The eight megatrends in logistics

One trend is 3D printing, with its individual and often even personalized products with a batch size of one, and fundamentally different supply structures. Then there is autonomous driving, for instance on existing test tracks such as the A9 highway between Munich and Nürnberg. Robotics promises ever-smarter helpers for areas such as warehousing and production. The information society concerns rapid growth in global knowledge and an exponential increase in global data volumes. Diversification is about workforces becoming increasingly heterogeneous. Sustainability is in growing demand, including from customers, and the trend toward digitalization and servitization impacts the entire value chain.

All of these trends can pave the way for disruptive innovations or even become one themselves. The next few years will show us when exactly this will happen and what it will mean for logistics. At the moment, we are paying special attention to two trends in particular: increasing digitalization and the growing focus on service in everyday life and business. These trends affect the entire value chain, are not limited to any specific sector, and therefore possess the necessary force for disruptive innovations.
 

Focus on two megatrends: digitalization and servitization

The effects of digitalization and servitization on logistics and supply chain management are already visible and will only increase in the future. If new technologies, mobile computers, and the Internet of Things keep making objects smarter and more intelligent, there will be scope for developing new data-driven services around these smart objects in order to make products and processes more efficient. This transformation is also linked to fundamental changes in customer contact, in business models, and in collaborations between businesses. In addition, Germany is transforming from an industrial society into a service society. Customers no longer buy the product on its own – they also buy the associated services. These “hybrid products” allow businesses to increase their sales opportunities and boost customer loyalty.
 

How digitalization and servitization are changing intralogistics

In the field of intralogistics, transport processes and in particular tugger trains are playing an increasingly important role in making processes lean. A tugger train comprises a tow tractor and several trailers. It generally drives a predefined route and stops at certain points along the way. Material is offloaded at each stop, and more material is usually loaded on.

To ensure that tugger train systems continue operating efficiently once they have been introduced, and that they can adapt to what are sometimes subtle changes in their environment, operators need to record relevant key figures. With this in mind, we developed IKE, which is a system that can intelligently determine key figures and record detailed information about tugger train processes in a production or warehouse setting. A sensor box installed on the tow tractor records positioning data, driving and stationary times, and the load situation. These basic data make it possible to analyze the routes taken and the utilization of the tugger train, which means that weak spots in the processes can be reliably identified. This knowledge can then help to make transport in production and warehouse settings faster and more efficient.

“DATA WILL GAIN IMPORTANCE IN THE FUTURE – INCLUDING IN LOGISTICS.”

 

The key to digitalization: using data properly

Data use, however, is currently often limited to a very narrow field. Although most companies already have large volumes of data available, it is often contained in numerous “data silos,” i.e., in insular, non-networked data spaces that are only used for a clearly defined subject and task field, such as improving transport processes in the warehouse. Other business areas and even other businesses tend to have either limited or no access to this information; shared use does not occur.

Yet this is the key to actually exploiting the continual march of digitalization in manufacturing and its associated processes sustainably. Only by using and combining all relevant and existing data across businesses and functions is it possible to generate the necessary added value that justifies what is often an extensive investment in new technological solutions.

The future of logistics and supply chain management: the eight megatrends.

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.


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