The recent Corona virus needs no introduction. Its impact on supply chains caught everyone by surprise. In recent years we have had quite a few instances of unpredicted surprises in the supply chain. Amongst them: Spanish Flu, SARS, LA dock workers strike, Trade tariffs, hurricane Harvey and Irma, and of course Corona. Could we have taken any preventive measures to reduce the risk other than reacting to it? How fast did you react to any of these events and how much opportunity was lost due to slow reaction?
The answer is yes and yes. The impact of all these unpredicted events could be substantially reduced by having a system that
- Helps to find the weak points in the supply chain when an unexpected event occurs.
- Quickly find the alternatives and
- Can predict risk,
In a recent article on Corona and supply chains, Mackenzie & Co makes the following recommendations:
- Establish a supply chain risk function
- Digitalize process and tools to integrate demand, supply, and capacity planning
- Trigger the new supply network design for resilience
In order to find the magnitude of risk impact there needs to be a well-established methodology to figure out the “cost” if and when a link in the supply chain is broken or constrained. A breakage in the main artery can kill the operation. On the other hand, a small clog can be locally addressed and treated. By digitalizing your supply chain, you can very quickly identify the main arteries as well as the overall health of the system and its vulnerability to potential “attacks” from the outside. We refer to the digital representation of the supply chain as Digital Mirror© of the supply chain, Gartner’s terminology is Digital twin. Furthermore, when and if an undesired event occurs, the system can very quickly show you all the potential alternatives and their financial implications. You can think of the Digital Mirror like the simulator cockpit of an airplane. Any changes such as wind direction and speed or temperature is simulated and the exact behavior of the airplane is known and corrected either automatically or by the pilot (or planner in the world of supply chain).
With an accurate digitalization of this caliber, you are in a position to optimize sourcing, maximize cash, and accelerate supplier alternatives.
Finally, predictions of the events of such magnitude are not always possible. But their frequency is extremely low compared to many other events. Digitalization of the supply chain allows predicting most of the supply chain risks such as shortages, changes in demand patterns, supplier issues, and capacity problems amongst others. This is done by looking at past data as well as future (or planning) data using machine learning techniques. These advanced methods can pin point potential future risks as to what they are and when they might occur with very high degree of confidence and hence be able to prevent them. More importantly they can also identify the causes of such future risks! For more information on risk resiliency of supply chains go to Here.