IOTA offers a way to store data in an immutable way and can therefore be used to establish trust and transparency in a logistics network with multiple participants. Especially when there is no dominating partner, this fact becomes more and more important. In this article we present a proof-of-concept implementation for a real-world use case, based on IOTA Masked Authenticated Messaging (MAM).

The main characteristics of a supply chain is that there are handover points, where a good is given from one to another participant. And it’s not only the good which is transferred but also the ownership and risk. Therefore, data about the current and past ownership is important to answer questions, such as “Who is responsible for a damage of the goods?” or “Is the seller of the product the rightful owner?” or “Who was the first owner respectively manufacturer, so that the true origin of the product can be identified?”.

Figure 1: Handover point at which a product changes ownership

Besides the ownership question, there are additional points of interest when it comes to supply chains. To better address these points, it is also common to speak about “value chains”. While at the beginning of the supply chain there are only raw materials, these materials are combined in every further step and processed until they become a final good. Thus, value is added through every step of every partner in the supply chain. So next to ownership data, it is important to get additional information about the processing and production. The data should reflect the actions like certain production steps, machine parameters and times and so on to give background information about the good delivered.

Figure 2: Production information about a specific product

To illustrate the importance of the described data, the example of a quality error can be given. A simple example is a broken axis of a car. It is not only of interest who manufactured the axis, but also where the failure occurred. When base materials like steel are used in production, there will always be batch numbers to track back material issues. So, the whole production of axis based on this batch can be called-back, when the steel is identified as being the origin of the quality issue.

Therefore, a perfect supply chain documentation should identify every production step and crucial parameters or material inputs to trace back quality issues and numerous other questions.

Supply Chain Example

To transform the given requirements into an IOTA based supply chain documentation, an appropriate real-life example was used. The example is in the domain of construction of flood protection barriers. The process is made up of a geotextile manufacturer, a middleman/ retailer and the construction company which finally builds up the barrier.

The rather short supply chain offers all the described characteristics of supply chain data. Also, there are multiple participants involved, making a trusted data storage worthwhile. An illustration of the supply chain can be found in figure 3.