predictive, and prescriptive ways of data analytics are introduced, and manual, automated, and autonomous decision making contrasted. Finally, key topics to get prepared such as data quality, organization, skills, and ecosystems are addressed. This is also summarized in Figure 3.1. The conclusion in the end highlights that logistics management in an IoT world will require managing new IoT ecosystem setups with new actors and new skill requirements.
Logistics Management in an IoT World
Get Connected
The defining element of IoT is connectivity. Therefore, the first aspects of setting up the supply chain and its management in an IoT style are to define what are the relevant Things that need to be connected, in what way data should be collected, and finally, which data needs to be collected. Simply collecting more and more data might just increase the amount of available data exponentially, but not necessarily lead to improved patterns of doing business.
When is a thing a Thing in the sense of logistics in an IoT world? Is a small component a Thing that needs to be monitored by sensors and always be online? Or does the Thing start with complex finished goods that are themselves composed of multiple components? Here, we need to distinguish between the user perspective and the logistics perspective. From the logistics perspective, i.e. the material and information flow point of view, everything is a Thing. From the classical user IoT point of view, the Thing is more related to machines and devices, such as finished products, components in a production line, transport vehicles, or whole warehouses. This chapter will examine Things from the logistics perspective.
Criteria for Defining the Right Things
Some examples of criteria based on which a Thing may be included in an IoT system or application would be as follows:
Requests from customers (e.g. to stay informed about the placed order).
The criticality of the Things to influence the supply chain performance (e.g. keeping a certain temperature or avoiding shocks during transport).
Requirements from the business model (e.g. provide services).
Depending on the needed information, the appropriate sensor and identification technology has to be selected. For instance, to keep customers informed about their delivery, it might be sufficient to collect information once the Thing is passing certain checkpoints, like a warehouse, cross‐dock, or the truck for the last mile, through simple scanning. Meanwhile, in case the Thing needs to be cooled or is sensitive to shocks, information on temperature or acceleration provided by sensors might always be necessary. Otherwise, the business model might require a continuous condition monitoring of a forklift or AGV through embedded sensors. In case deviations are detected, an alert can be triggered and then, for example, spare parts ordered.
Sensors and Identification
The level of monitoring and identification, thus the Thing itself, e.g. product, box, container, or transport device (see Figure 3.2), can vary according to the requirements. Although in a narrow sense the Thing is equal to the product, for example, for tracking a shipment from Europe to Asia by an ocean carrier, tracking the vessel itself during its way might be enough – knowing and trusting that the product was loaded onboard the ship. Thus, tracking information does not have to be sent from every single of the millions of products on a containership, but only from the ship itself. If the sensor data from individual products are requested, other solutions are required.
Figure 3.2 Levels of sensors and identification.
To define this level, the overall supply chain process and the intended business services have to be considered. Is a pure identification/localization2 enough, or are sensors needed to get certain data, such as condition monitoring? It could be necessary to use sensors implemented in the product to monitor certain conditions. At the same time, although the product itself might have some sensors inside, to optimize transport, handling, or warehousing of a mix of sensor and non‐sensor products, it might be needed to have additional sensors on container or transport device level. Furthermore, in case a sensor is needed, which conditions, such as temperature, humidity, or acceleration, do the sensor need to measure? Modern sensors are quite compact, small, and capable of measuring multiple of those.3
Means of Connection
Based on the application of the data, the means of connecting the Things can be done in an active or passive way. Active means that data is actively sent out from the Thing. This might be necessary if the condition of the Thing changes quickly, and the knowledge about these changes is decisive for the next step, such as the coordination of many transport devices in a warehouse to avoid collisions. To actively send out data, more technologies and especially energy supplies are necessary that might limit the device size and the usage lifetime and require additional services such as exchanging or charging of batteries. In contrast, if conditions are relatively stable or the intended application is purely identification, a passive mode might be sufficient. In a passive mode, the Thing reveals its data when it is triggered from the outside, just as when a box labeled with a barcode passes through a barcode reader.
Triggers
Data from the sensors to trigger specific actions or decisions enable new business models. For example, if the measured data of the sensors deviate from the target level, a truck driver gets an alert that the condition of the products on the truck needs to be checked or actions like adjusting the cooling function must be taken. Another use case can be machine monitoring. Based on information provided by the sensors on a machine, the next maintenance can be scheduled with minimum impact on downtime. A machine could even automatically order necessary spare parts preventively or once it breaks down. To gain full advantage of these actions, the logistics systems have to be prepared to quickly facilitate the transport of these necessary spare parts. In connected systems, the signal from the machine will already trigger the picking in the warehouse, prepare the necessary transport devices, and synchronize the material flow with the availability of the service technician.
Standards
As already well known in SCM, standards are important. With an increasing number of IoT devices involved, there is an exponentially large impact on the standards of the data format, the identification, and connecting technology that necessitates the use of middleware to connect different formats used throughout the whole supply chain. Everything is connected with everything, but based on which “language”? This issue can, for instance, be seen in the discussion about cables and connectors in the computer/mobile phone sector. It started with a lot of diverse single solutions and finally led to the USB solution as unified standard.
One well‐known and established standard for identification in the global retail business is the GS1 EPCIS standard and the Global Trade Item Number (GTIN). By scanning the GTIN number/barcode at defined “control points” in the supply chain, a track and trace function can be established from the source to the customer. Another common standard that is mainly
