Cost-effective ways to minimise supply shortages risks


Monday, 13 July, 2020



Cost-effective ways to minimise supply shortages risks

The coronavirus pandemic has hit the economy hard, and has prompted companies to consider how best to protect themselves against this kind of crisis in future. The Fraunhofer Institute for Industrial Mathematics ITWM has developed new mathematical methods that aim to calculate how the risks posed by supply shortages can be reduced at very little extra cost. The coronavirus pandemic has caused shortages of face masks and other personal protective equipment on multiple occasions. Previously, these supply chains had worked well, but necessary restrictions on the global flow of goods led them to collapse.

In many cases, for example, Chinese suppliers were unable to make deliveries even while factories in Germany were still working as normal, which had a knock-on effect on goods production in Germany. Viruses are also not the only potential risks; international suppliers can be affected by a range of unforeseen factors, such as tsunamis, earthquakes, storms and floods, to strikes or other unexpected political developments. If a company relies on a single supplier for its production needs in order to reduce costs, this can have devastating consequences that could bring production to a complete standstill. It can also take time for other suppliers to ramp up production and start delivering the required products. This is where the methods developed by Fraunhofer ITWM come into play.

“The algorithms analyse 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,” said Dr Heiner Ackermann, deputy head in the Department of Optimisation at Fraunhofer ITWM.

Companies must also 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 can procure a raw material from multiple suppliers at the same time, that risk decreases. Dr Ackermann believes that companies must consider how they can minimise the risk of supply shortfalls without incurring significant additional costs.

“And in this case, the difference in cost is much lower than the difference in risk,” Dr Ackermann said.

In other words, the risk decreases when a company increases its costs by just a few per cent; therefore, it is possible to eliminate much of the risk by raising the costs. Companies can use the algorithm to discover what would work best in their particular situation. According to Dr Ackermann, this method lets companies optimise their supply chains based on multiple criteria, helping them to find the optimal balance between costs and risks.

“The underlying algorithms work equally well whether you are dealing with supply shortages caused by an earthquake or a virus. So, unlike existing software solutions, we don’t try to make assumptions as to the likelihood of any particular scenario,” Dr Ackermann said.

With this method, a company starts by entering various parameters, such as areas in which they think disruption could be likely, and how long the 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. The algorithms also consider options such as storing critical products in order to cushion any temporary supply shortfalls.

Another option the algorithms take into account is whether a raw material could potentially be replaced by different materials in the event of a supply bottleneck. If so, this can be taken into consideration from the start. This method calculates the costs and risks of different courses that a company can follow in regard to their suppliers. Procter & Gamble is already using a software-based variant of this methodology, which has been tailored to its needs.

Image credit: ©stock.adobe.com/au/cacaroot

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