The resilience of supply chains is being tested. There has been political disruption to trade flows and disruption from catastrophic events, notably the Covid 19 pandemic.

How COVID has impacted the supply chain

The most dramatically visible impact has been on container traffic, which carries a quarter of the world’s traded goods by volume and three-fifths by value. Capacity and demand had been in balance before Covid hit. The lockdowns imposed in response to the Covid pandemic constricted supply capacity while the compensatory stimulus packages gave a short-term boost to demand, particularly in the US, disrupting the status quo. The effect has been a near doubling of door-to-door delivery times- an overall quadrupling of freight rates and an unprecedented spiking of spot rates.
While the long-term impact on consumer prices is likely to be minor, the reliability issues most concern businesses. Firms are building inventories above pre-pandemic levels. In addition, the use of digital technologies has been accelerated in an industry that has previously been slow to adopt them. Data now provides performance visibility, showing which suppliers and shippers do a better or worse job of keeping to timetables.

How modern analytics and visualisation tools can help supply chain resilience

Modern tools such as Adobe Analytics, Power BI and Tableau make it easy to visualise the flow of material, components, and products from source to destination via nodes showing locations, facilities, and distribution points. The visualisations include inventory levels of components, spare parts at supply chain storage locations and depots. Additionally, the analyses are automatically refreshed from digital sources in the supply chain locations and are always up to date.

The tools make it easy to filter visualisations by the attributes of the flow, such as product categories, products, brands, component subsets, sub-assemblies, and SKUs. The visualisations allow the flows into, out of and through specific locations and facilities to be seen and understood by time-period.

Supply chain managers routinely use predictive analytics to increase inventory levels in the face of increasing risk and ensure that the supply chain is more resilient. But data and analytics can also help them recover more quickly from the rarer, higher-impact events against which it is harder to hedge. The visual analytics informs the rapid recovery actions that need to be taken. Trends such as climate change seem to be increasing the rate at which disruptive events occur. We can expect more frequent events with a high impact on supply chains, so tools that support the ability to recover from disruption and losses quickly have high utility.

Building supply chain analytics

The analytics visualisations are not out of the box but purpose-built to provide the filtering and drilling functionality required to understand potentially complex patterns of product and component flows. The calculations are also purpose-built to provide the appropriate calculations of inventory cover, supply chain velocity and working capital requirements reflecting the potential impact of disruptions on cash flows and cash requirements.

Such visualisations depend for their effectiveness on the quality of the data model design,and the functionality that permits drill throughof supply chain complexity. The visualisations are designed for use by supply chain professionals, who can fully use the ability to drill through the data, identify risks and cost-effective mitigations, and intervene as necessary to speed the recovery from disruption. The tools provide a means of engaging people and processes in the cost-effective improvement of supply chain resilience.

Increasing resilience vs fundamental change

The more resilient that supply chains can be made to disruption, the less likely we are to see fundamental changes in global trade patterns. Risk mitigation and improved flexibility might be achieved by localised changes to diversify supply chains and circumvent trade barriers, perhaps a tilt away from China to other low-cost countries and a limited amount of nearshoring and onshoring in specific sectors and specific technologies. It is possible also that the acceleration in the adoption of digital supply chain analytics prompted by the crisis will also make a significant contribution to the future resilience of global trade patterns.

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