The Digital Transformation of Logistics. Группа авторов

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barcode label. Although such common identification systems exist, we can find additionally numerous labels of each logistics service provider for their specific operations or parts of the supply chain. The further development of the IoT in the future will show which identification and communication technology will prevail. The “Industrial Internet Consortium” (Object Management Group 2020) and the “Industry 4.0 platform” (Plattform Industrie 4.0 2018), for example, are working closely together to standardize and ensure interoperability in the industrial sector (Plattform Industrie 4.0 2019).

      Security

      To ensure trust and security in digital systems, Bosch has launched an initiative and invited different supply chain partners to the first Digital Trust Forum in Berlin on 16 May 2019. Representatives from leading international associations and organizations, including the Institute of Electrical and Electronics Engineers (IEEE), DigitalEurope, European Telecommunications Standards Institute (ETSI), the Eclipse Foundation, Trustable Technology, Plattform Industrie 4.0, the Industrial Internet Consortium (IIC), and the Trusted IoT Alliance, came together to discuss this topic.

      From a logistics management point of view, one major purpose of connecting Things and transferring, handling, and storing data in the IoT is to get decisions in a better (time, cost, quality) way than before. In general, we can separate into three different types of decision making: manual, automated, or autonomous.

      In the manual decision way, the collected data is analyzed or displayed by certain applications that help the decision maker to come to better decisions. The decision itself remains a task of the related person. For example, in a transport company, based on GPS tracking, all trucks are displayed on a screen showing the map of the road combined with traffic and weather information. In the case of a certain event such as a traffic jam, the “decider” must decide where and how to intervene to keep promised lead times.

      In case the decision process can be described in a standardized way, automated solution finding and decision making can be possible. Based on predefined checking and decision finding processes, the “application” (App) in use executes automatically the predefined solution process or gives a proposal to a human decider. Logistics management has to think about which kind of decision situations (e.g. data given by a Thing) can occur in which process and how the decision processes can be defined in a standardized way, including standardized answers. This is also discussed in Chapter 5.

      In a descriptive way, all selected information is gathered, and the monitored situation is described (e.g. condition, environment, process). Using the diagnostic way, the root causes of deviations between the set target value and the actual monitored value are analyzed. Hence, both the descriptive and diagnostic ways of analytics look back and explain what happened in the past. In a predictive way, the analyzed data is used to detect indications that signal impending events in the future. For example, if the system shows a certain number of Things in the inbound area of a warehouse while in parallel the internal data indicates that several workers are ill, it will most likely result in a delay or congestion in the goods receiving process – if no actions are taken. Lastly, the prescriptive form of data analytics strives for identifying measures to improve results or correct errors.

Schematic illustration of get decisions.

      In logistics management in an IoT world, the management of material and information flows in supply chains still has the same overall goals as before: to provide the right Thing, in the right quantity, at the right time, to the right place (Pfohl 2016, 2018). As outlined above, the IoT world provides new tools to realize these targets more effectively and efficiently. But this new IoT approach also demands new skills and a new way of thinking in logistics management. Aside from the new IoT‐related technologies, the prevailing characteristics of IoT and its management are the data.

      Data Quality

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