In the research program CoyPu we work on early detection of economic risks in global supply chains together with Siemens, Infineon and DATEV, among others, as well as strong partners from research, such as DIW, TIB and InfAI.

For early detection of economic risks on supply chains, trade sanctions are analyzed as part of economic sanctions.

Based on open data on trade sanctions, a graph between countries, products and trade sanctions was built. A distinction is made between countries that impose trade sanctions and those that are targeted by these sanctions. Each trade sanction has a start date so that a representation of when the sanction goes into effect is possible.

For a representation of what happened, an exemplary time series was determined and visualized using Gource. Since the complete visualization is very large, here is a small section:

On the left side of the visualization, there is a ranking that lists the most frequent pairs of countries that are linked due to trade sanctions. Further to the right, it shows which sanctions countries are imposing on certain products (e.g., export ban on certain metals).

It is noticeable that there are points in time with particularly high regulatory intensity. Without more detailed knowledge of simultaneous or preceding crises or political events, the time points are difficult to explain ex post. Beyond an explanation of the geo-political context of a sanction, knowledge of a sanction should be relevant for those actors whose supply of raw materials or intermediate products or export opportunities could be affected.

With the chosen treatment of trade sanctions as a network of the global economy, remote events can be determined on industries or even individual companies. Here, we are researching the propagation of events in networks to also predict ripple effects for specific industries or companies.

Potential applications for supply chain monitoring include:

  • Automated warning of newly detected import restrictions.
  • Automated warning of announced export restrictions
  • Prediction of direct supply restrictions
  • Prediction of indirect supply chain constraints due to ripple effects

With automated warnings and prediction of indirect impairments, risks can be sighted, evaluated and managed earlier in the future due to smart early detection, before supply bottlenecks or disruptions occur.

For further questions about the project and the application of analyses and data feel free to contact us at hello@implisense.com.