Supply chain stress has become so intense that an index tracking it in the US recently reached heights never seen before. It’s true that the circumstances that led to these monumental bottlenecks have been extreme, once-in-a-generation events. But firms can’t know when or whether something will happen again, or whether a seemingly smaller event might still make consumers act unexpectedly.
During the coronavirus pandemic, US spending on durable goods shot up 32per cent compared to 9 per cent for non-durable goods, as consumers spent more on things and less on services for the first time in 60 years. While it’s likely that spending on services will continue to make up a significant share of disposable income, it is not yet clear exactly how spending on long-term(durable) versus short-term (non-durable) items will settle.
Accurately predicting consumer behaviour is notoriously difficult, but finance functions should be testing a range of financial scenarios to help them understand what measures they might be able to take when global trade stresses appear.
At the height of the supply chain issues in October last year, a record 100 cargo vessels were anchored outside the ports of Los Angeles and Long Beach alone, as the global logistics system struggled to keep up with the increased demand caused by economies opening up in the latter stages of the Covid-19 pandemic. While this is an extreme example, firms need to model how their finances could cope if such a situation arose again, as well as stress-testing more moderate scenarios.
Knowing which cost levers to pull could help a firm be better prepared for and understand the risk of extreme trade stresses, and constant dynamic forecasting could alleviate risks in an ever-changing market. Plans must consider how company finances might be impacted by a change in customer behaviour, and how the financial health of a firm could change if certain or multiple variables shift, such as cash flow challenges stemming from delays in purchasing. To do this, firms need reliable data sources and processes in place to transform data into meaningful insights in order to understand behavioural patterns.
Understanding what to do with the data available to them is one of the biggest challenges firms face, but Metapraxis’ Empower tool can help them visualise the most important information for their business.
Selecting a strategy
Dissecting data in the most relevant ways can help firms to expose hidden areas of weakness that may be masked at a high level by over performance in other areas.
Our dynamic planning tool can integrate multiple sets of data to help business leaders and their finance functions visualise how their firm might perform through a range of different scenarios. Companies can infer from these results the strategic decisions they need to take to redesign their supply chains for the post-pandemic world.
A trend that has become more prevalent since the pandemic is regionalisation, whereby firms have hubs in or near the countries where they trade. This strategy helps firms move away from low-cost labour countries; such locations are often far from firms’ customers, meaning the goods they produce have to be transported long distances, opening the supply chain up to disruption. Moreover, nearshoring strategies like this can also help to reduce the time to market, allowing firms to design, produce and ultimately sell their products faster than competitors who locate production in more distant locations. A survey by McKinsey showed that almost 90 per cent of respondents said they expected to pursue some degree of regionalisation during the next three years.
Regardless of which strategy is employed by the finance function and the wider business, it should never implement something it hasn’t tested.
Modelling real world scenarios
Finance leaders need to create a model of their business that can be stress-tested against real world challenges to their business, and a model which represents not just how these events could impact finance, but also other business functions such as operations and sales. They must also run multiple scenarios to determine what level of supplier diversification and stock are required to absorb different levels of shocks, and then ascertain how to boost their balance sheet under each set of circumstances.
Proactive businesses will constantly put their firm through its virtual paces to ensure they’re better prepared for when disaster really strikes, or an opportunity arises. The key is to have clear and readable data visualisations to allow companies to highlight key trends within markets and be able to update their forecasts to account for this in increasingly accurate ways.
Essentially, only firms with finance leaders that are constantly asking themselves ‘what if?’ will be in a strong position, but simply having the right information isn’t enough. Instead, these businesses must grasp this data and draw on its findings to prepare against future threats and help them navigate disruption on the horizon.
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