Supply chains have been rocked by wildly uncertain events precipitated by Covid and geopolitical storms. The resulting uncertainty in scheduling makes it challenging to implement just-in-time deliveries.
Simulating to respond quickly
Increasingly, supply chains are adapting to a fluid environment with demand and supply changing unexpectedly. As a result, simulations, common in the business world, have entered the world of supply chains to evaluate alternative options to cope as initial assumptions go awry. Businesses want to gain situational awareness with real-time data and analytics, visualize decision options with digital twins, and respond rapidly to disruptive events.
The turbulence in their markets has upended supply chains. Spot rates for shipping zoomed five to ten times, and shipping reliability dropped from 80 percent in 2019 to 30 percent post-Covid. The inventory to sales ratio dropped precipitously during Covid from a peak of 1.70 at the beginning of 2020 to a low of 1.25. There is no going back to normal as the disruptions during Covid have been aggravated by geopolitical events.
Renault is a typical case of a company that lost revenues from potential sales of hundreds of thousands of cars as the supply of integrated chips fell short. It has now entered into a collaboration with Google to build a digital twin of its supply chain with its Supply Chain pulse product.
The bullwhip effects
Supply chains have had chronic trials managing their sprawl with endemic imbalances in the demand and supply, even before the pandemic, which leads to stock-outs or inventory write-downs at retail stores. Costs of stock-outs alone are estimated to be 1.14 trillion dollars. At every stage of their journey, the lack of information on inventory flows and demand is the cause of bullwhip effects or wild swings in orders. Salespeople overestimate demand leading to a buildup of stocks and their sharp depletion. The remedy for such problems is visibility, or real-time data flows from every corner of the supply chain.
The data pool
Fortunately, supply chain operators recognize the need to share data from their facilities and create a pool of information for analytics purposes. IoT can help collect vast volumes of data on activities across the supply chain. Computer vision complements quantitative data collected from sensors. It is increasingly clear to supply chain managers that 5G telecommunications has the bandwidth and low latency to collect vast volumes of data in a timely manner.
Balancing demand and supply
The data can help remedy inefficiencies at multiple levels. Vehicles for the transportation of goods would be able to utilize spare capacity if they receive real-time information en route on goods available for pick up. The demand for goods can spike unexpectedly, especially during peak holiday seasons, weather fluctuations, fashion trends, etc. Logistics companies cannot plan with sufficient precision to match demand and supply.
The challenge of demand and supply balances extends to replenishment decisions across geographies and neighborhoods. As product variants multiply, it becomes harder to decide what to stock in which store. Local factors influence the demand volumes. Digital twins eventually can be designed to factor in demand and supply in individual regions and the stocking decisions. Furthermore, they could help make decisions on the volumes of goods to be transported and the mode of shipment that will work best for them.
TetraPak is an example of a company that uses digital twins and data to reduce the time lags in the supply chain. It uses data from its inventory stocks in warehouses to coordinate operations. For example, it can reduce wait time for trucks at warehouses by earmarking inventory that they will carry at a scheduled time rather than waiting until they arrive before retrieving the goods from warehouses. Accurate time schedules are determined based on data on the flow of goods across the supply chain.
Opportunities for optimization abound but have not been exploited due to obsolete practices. An example is air transportation; flight controllers are assigned a fixed air space regardless of the demand. As a result, some air spaces could get congested simply because of inefficient space allocation. Digital twins help keep track of the utilization of air spaces and flight controllers to reassign their duties as demand patterns evolve.
Conclusion
Supply chain disruptions seem alarming but are not beyond repair as they result from antiquated practices put in place when times were more stable. They have been hard to change in the absence of granular data on the obstacles to faster inventory movement. The Internet of Things and Digital Twins have altered the decision-making landscape for supply chains. Greater visibility into the sources of inefficiency across the supply chain and the ability to simulate alternative courses of action has prepared the ground for automation, optimization, routing changes, and technological innovation for making improvements.
Infographic: Supply Chains Change with 5G – Private 5G Networks (privatelteand5g.com)
