November 08, 2022 | Risk Management
As uncertainty continues to grow amid rising inflation, businesses must quickly adapt to a new normal.
And if there’s one thing that is likely to be constant in this new normal – it’s disruption.
The global pandemic—which disrupted activities across all spectrums of life—has highlighted major supply chain weaknesses, particularly those crucial for sectors like pharmaceuticals and medical supplies.
Lean global supply chains, widely implemented to cut costs through effective production allocation to low-cost regions, just-in-time manufacturing techniques, and holding lower inventory levels throughout the supply chain, have also contributed to the shortages during the pandemic. These tactics rely on predicting future trends using past data and often do not take any significant disruption into account.
A global call has gone up to develop specific risk scenarios and supply chain stress tests for essential products to ensure more resilient supply chains that are not disrupted by events like the pandemic.
With supply chain stress tests, firms can swiftly pinpoint potential financial exposure areas related to supply chain failure points, define the best mitigation plans, and compare their resilience to that of their competitors.
Stress tests can identify weak points in the supply chain and recommend mitigating measures.
A stress test is done by evaluating data from various supply chain nodes, building a digital twin/model of the supply chain, and putting the digital twin through simulating scenarios, including disruptions to one or more nodes.
A digital twin, also known as a virtual model, enables a company to comprehend its architecture and functioning and forecast process efficiency. It serves as a predictive "test bed," assisting businesses in lowering operational costs and boosting the lifespan of equipment and other tangible resources.
The digital copy mimics every aspect of the physical supply chain, including its assets, stocks and warehouses, logistical flows, transactions, and third-party interactions, and is like a parallel universe.
In today’s uncertain business landscape, companies must be aware of the threats to their supply chains and the risk-reduction techniques available. Given the complexities of modern supply chains, it is not surprising that many industries are prone to supply chain disruptions.
A digital twin allows a business to anticipate the effects of its strategy and future decisions. A new product's whole business cycle, from design to manufacture to logistics to retail to sales performance, can be modeled, and the complete process, including supplier supply chains, becomes visible. Digital twins can aid analysts in comprehending the behavior of a supply chain, forecasting improbable events, and offering a plan of action to cut costs and increase process efficiency.
A digital twin can aid firms in understanding trends and modeling the effects of changes to various processes for the following:
Supply chain digital twin models mitigate business continuity risks by predicting outcomes before they materialize. Before the process changes, the models allow for the calculation of advantages, savings, and prospective returns on investment. For instance, by simulating multiple scenarios with manufacturing, inventory, and distribution data, a company creates design test models to reconfigure its worldwide operations.
Digital twin enables supply chain firms to test and determine the best course of action for disruptions and attempts numerous scenarios in a simulated environment, dramatically enhancing organizational resilience.
With its continual, end-to-end view of the supply chain's processes and bottlenecks, digital twin enables more agile problem-solving with minimal human involvement. Digital twins assist in identifying possible flaws in all facets of delivery by gathering relevant data. To track efficiency and bottlenecks during transportation, a shipment digital twin, for instance, will rely on data collected from various sensors that update data while being shipped.
A supply chain digital twin inputs data from demand forecasting procedures for preventing stock-outs and saving total production and warehousing costs. As a result, it optimizes inventory across the entire supply chain network.
Digital twins can mirror package forms and packaging materials to test for defects before utilization, reducing both the economic and environmental costs of packaging.
Stress tests have many advantages, but they can have some drawbacks. For example, stress testing models depend on information; however, most businesses rarely know every supplier in their extended supply chains because suppliers frequently view their supplier's identity as "proprietary information."
As long as ambiguity surrounds specific supply chain components, stress testing's efficacy will be hampered. Therefore, businesses must recognize that stress testing is not a panacea that eliminates the need for other risk management techniques.