Fraunhofer ITWM scientists have developed new algorithms to help companies minimize supply shortfalls during crises like the current pandemic.
Supply chains have always run smoothly in the past, but the COVID-19 crisis has caught many of them off-guard.
In many cases, Chinese suppliers were unable to make deliveries even while factories in Germany were still working as normal – a situation that had a knock-on effect on goods production in Germany.
It isn’t just viruses that cause such damage; international suppliers can also be paralyzed by natural disasters such as tsunamis, earthquakes, storms and floods – as well as unexpected political developments too.
And if a company chooses to rely on just one supplier for its production needs in order to reduce costs, this can have devastating consequences.
The Fraunhofer ITWM team is hoping to contain this with their new algorithms, says deputy head Dr. Heiner Ackermann.
“The algorithms analyze how diversified the supply chains are in different areas of the company and thus how great the risk is of running into critical supply problems in an emergency, in other words in the event of regional or global disruption.”
Companies also have to get the right balance between risk and costs.
If a company chooses to rely solely on the cheapest supplier, they are taking a major risk. But if they procure a raw material from multiple suppliers at the same time, that risk drops significantly.
“And in this case the difference in cost is much lower than the difference in risk,” says Ackermann.
In other words, the risks fall dramatically even when a company increases its costs by just a few percent. So, it is possible to eliminate much of the risk by accepting just a slight rise in costs.
Companies can use the algorithm to discover what would work best in their particular situation, says Ackermann.
With this new method, a company starts by entering various parameters – for example areas in which they think disruption could be likely and how long that disruption might last.
The algorithms then calculate various cost/risk trade-offs for this exact raw material, including the possible allocations of suppliers that would correspond to each point on the scale.
They can even take into account options such as storing critical products in order to cushion any temporary supply shortfalls.
It can also ascertain if a raw material has to be replaced by different materials in the event of a supply bottleneck.
Image and content: Anna Shvets-Pexels/Fraunhofer ITWM