Supply chain control tower- a frequently used term that offers a lot of room for interpretation. In this article we want to highlight what exactly the supply chain control tower is, what typical forms it takes and what the control tower of the future might look like.
What is a supply chain control tower?
In general, the supply chain control tower is a concept that assumes central control and monitoring of logistics processes along with providing an overview of all data and processes. The core of the concept is to control all digital information within one platform. The control tower is often – hence its name – compared to an air traffic control tower, which keeps track of air traffic movements on the ground and in the air. You can also think of the control tower as a large monitor that records all processes along the supply chain. Among others, the aim is to identify problems and process bottlenecks at an early stage, thus enabling timely mitigation. In addition, weak points are identified and improved more quickly.
Centralization of data and visibility
The main pillar for a functioning control tower is centralization of data. This can be used as a basis for analysis purposes. It includes transport data, current data on delivery stocks and transport costs. Existing applications such as ERP, WMS and TMS systems are integrated via a central system, making it possible to synchronize the relevant information on a central platform. Moreover, suppliers, manufacturers and other cooperation partners can be integrated as well. In this way, the supply chain control tower develops into an information network that can provide end-to-end visibility across company boundaries and their respective IT systems. According to a study by the Fraunhofer Institute for Manufacturing Engineering and Automation IPA, 85 percent of the participants in the study see added value in potential data sharing.
An essential factor of the control tower is the recording of real-time data. Where is the order now? How much time is still needed until it reaches its destination? The control tower integrates track & trace solutions that record the entire transport process of the supply chain. This allows the entire transport process to be mapped transparently and allows for a more efficient root cause analysis of problems. Depending on the control tower, additional functions such as alarm functions and analysis tools can be supplemented to the basic functions.
Different types of control towers
As already explained at the beginning, the term “control tower” offers a lot of room for interpretation. Even analytical systems often refer to themselves as control towers. These often provide both a transparent overview of the supply chain and the necessary analytical tools as a basis for decision-making. In contrast to the operational control tower, however, there is no possibility of implementing solutions directly in the system.
In an operational control tower, end-to-end processes are monitored and controlled. Based on real-time data, they enable not only the identification of problems, but also support to solve them within the system and carry out operational processes.
Some control towers also differ in their focus. Some systems are more focused on transport, while others focus on the entire supply chain including areas such as order and inventory management.
The path to an intelligent control center
Artificial Intelligence and associated methods such as machine learning and predictive analytics offer the possibility of automated processes – even in the control tower. Experts assume that supply chains will be completely digitized in a few years’ time and will be able to operate increasingly autonomously and adaptively. AI technology goes beyond decision support. It includes decision making and autonomous control. Thus, it can automatically adapt to fluctuations in demand and supply.
How exactly does Machine Learning work?
Machine Learning, as a branch of Artificial Intelligence, can recognize patterns and algorithms in existing data sets and develop solutions. For the software to learn independently, however, it requires not only a data set but also previously defined rules. In this way, for example, required stock levels can be automatically adjusted to fluctuations in demand.
Predictive Analytics & Prescriptive Analytics
Statistical procedures and analyses can be used to highlight the inter-relationships of historical data and generate forecasts with the help of predictive analytics. On this basis, it is possible to identify opportunities and risks at an early stage and include them in the decision-making process. Prescriptive analytics goes one step further. Simulation models are used to compare decision options with each other and make recommendations for action. In the future, the control tower could use self-learning algorithms to continuously hone its understanding and become even more independent in solution implementation.