In Zeean project we aim to develop a tool that models and predicts the indirect impacts attributed to local production failures on the supply chain, as even a comprehensive monitoring of one’s own supply chain network wouldn’t be of much aid when it comes to predicting e.g. whether a flood in Missouri or a strike in Shenzhen would influence the production of goods in Baden-Württemberg 18 days later due to supply bottlenecks in the network. The supply chain network in a globally interconnected world is simply too multilayered and complex for this purpose. In our understanding, this ambitious goal is only achievable with an N-tier analysis that takes into account all the relevant interdependencies within the global network. And it’s for precisely this reason that we are developing Zeean.
A Global Merchandise Network Model
Zeean is based on the global model Acclimate, which has been developed at Potsdam Institute for Climate Impact Research (PIK) as the fruit of a multi-year research project. The fundamentum of the model is to divide the production, import, export and consumption of all relevant regions worldwide into as many different sectors as possible. This allows us to build a simplified and aggregated model for the world economy and its complicated interconnected network system. In a subsequent step, an imbalance will be brought into this representation of the global economy to reflect events occurring that are relevant for the production or the transportation network, such as natural disasters, strikes and so forth. Starting from the initial imbalance in the model, Acclimate simulates the potential propagation of individual damages through the global merchandise network up until when a new equilibrium is reached or when the simulation run is stopped. In this way, we are able to monitor the impacts of events along the supply chains for weeks or months and thus to point out potentially affected locations and warn of risks very much in advance, before the companies could realize whether a certain event would be relevant for them or not.
Therefore, Zeean can identify potential risks in the supply chain beforehand and as extensive as possible. This enables the companies to be much more readily prepared in their day-to-day operations than otherwise and to take appropriate measures preemptively.
Since Acclimate estimates the price development in the modeled product groups as well, Investors and Asset Managers could also benefit greatly from the process by obtaining notice early on regarding potential profitable short-term investments, much earlier, before prices actually change as a consequence of a certain event.
Early Warning System and Scenario Analysis
Currently we at Zeean are working on two essential modules. The first module is an Early Warning System that delivers information on risks in the supply chain network on a daily basis. Zeean searches worldwide for relevant events with regard to production failures by monitoring pertinent information sources (such as Newsfeeds), which then serves as input parameters for the model simulation.
The second module is Scenario Analysis, which takes hypothetical events as input parameters. Here we can make assumptions about possible production failures and simulate the reaction of the global supply chain network to these events with help of Acclimate. For instance, it would be possible to simulate the impacts of, say, the escalation of a trade dispute, the blocking of an important transport route (e.g. the Panama Canal) or the occurrence of a natural disaster (e.g. an earthquake in Japan), on a specific supplier network. We could utilize hypotheses of these sorts in order to support strategic decision making in management or purchasing and thus make the supplier network more resilient in the long term.
This type of analysis makes it also possible to assess the indirect vulnerability of economic sectors or individual corporations in a scientifically accountable manner. The insights acquired by our model will create significant added value for (re)insurers and also for state institutions, notably (but by no means exclusively) considering the increasing frequency and intensity of extreme weather events resulting from climate change.