It’s time to make weather forecasts part of your supply chain planning

Disruptions from extreme weather conditions seem to be accelerating – so, how can procurement pros build our supply chains – and thus ensure our supply chain planning is robust enough – to expect the unexpected?

If it feels like the weather is getting worse, it’s only because it is. 

In the past few years, extreme weather and natural phenomena have caused incalculable human suffering, ecological damage, and business disruptions. 

From historic droughts to unprecedented flooding, and temperature extremes, as well as wildfires, earthquakes and volcanic eruptions, the natural world continues to demonstrate its ability to impact the way we do business.

About half of the global CEOs in a recent Accenture survey named extreme weather events as one of the top causes of supply chain disruptions. They feel their current level of investment and preparation is not enough to protect the stability of their operations from climate-related risks.

Procurement professionals must develop strategies to build supply chains that expect the unexpected and use technology that makes predicting the weather more accurate.

Advanced weather analytics are helping businesses manage operating costs, create contingency plans, and prepare for recovery in the aftermath of a weather event. It’s essential for every sector, including food supply, manufacturing, retail, energy, and logistics.

With vastly improved weather sensors backed by powerful computers and increasingly accurate artificial intelligence, it may be time to make weather forecasts part of your supply chain planning.

Using smarter forecasts in supply chain planning

In the US, even the National Weather Service observes the Waffle House Index. 

Waffle House, a popular restaurant that serves breakfast around the clock, is known for staying open during severe weather when most other businesses close up shop or re-open very soon after the storm. The National Weather Service monitors the open or closed status of Waffle Houses to help gauge the severity of a storm.

With increased computing power, artificial intelligence, and machine learning, weather forecasting is growing beyond the Waffle House Index or your local meteorologist.

The US National Oceanic and Atmospheric Administration (NOAA) recently upgraded its ocean sensor network and Global Forecast System model, which provides a more accurate 16-day forecast for wind and waves. The supercharged forecasting system supports granular analysis and updates – for example, the wave forecast can be updated every five minutes vs. six hours previously.

In 2023, NOAA plans to update its hurricane forecasting system. The goal is to increase the time an accurate forecast can be delivered before a storm hits. Historically, it’s improved about a day per decade – today’s five-day forecasts are as precise as the three-day forecast 20 years ago.

In a twist on cloud computing, IBM bought the Weather Company in 2016 and introduced several weather information products. 

In 2022, IBM launched IBM Watson Advertising’s Weather Analytics service to use artificial intelligence to help analyse how weather affects consumer behaviour across different categories such as pharmaceuticals, apparel, consumer packaged goods, and indoor and outdoor activities. 

Hyper-localised weather could help shape campaigns, supply chains, and forecasting decisions. This data can even help uncover unique or non-obvious relationships between climate and consumer behaviour.

MetraWeather is working with major retailers in Australia to understand how weather affects consumer demand. By analysing store-level data on sales and weather, a predictive model is developed for specific product categories.

With this kind of information at your fingertips, you and your supply chain team have the ability to better match supply and demand planning for higher profitability through reduced waste, lower inventory holding costs, and avoiding stock outs. 

While local weather forecasting is valuable, insights into global conditions are also critical. Everything from volcanic eruptions to snow-covered highways could delay vital inbound products.

FourKites, a supply chain predictive analytics platform, has added predictive weather intelligence to its software. 

Shippers can plan around disruptive weather events before they can slow down freight in transit. With weather forecast data updated every 15 minutes, the predictive weather intelligence monitors shipments in transit, diagnosing the impact of real-time and forecast weather conditions along each shipment’s route. 

Condition updates every six minutes give supply chain execution teams the insights they need to plan with a broader geographic view by tracking major weather systems across North America. 

With a granular view, supply chain execution teams can see which routes to avoid and anticipate which regions of the country will experience the most disruptive weather events.

Weathering extreme weather events

Accurate, timely weather data can help re-reroute shipments around potential delays. 

Weather alerts can be created for types of events or specific events. If a load falls within the location’s event radius, the shipment could be affected due to this weather pattern or other external events. Supply chain managers can take action to revise the shipment’s path or check for alternate supply sources to avoid disruptions.

IBM shared this example: Say a shipment is moving from its origin point in Mumbai toward its destination in Chennai, and its current location is near Ratnagiri. The Weather Company service creates an external event for the location ‘Goa’ with an impact radius of 20 km. The shipment could get delayed due to the timing of the weather event. In this scenario, you could opt for an alternate route or delay the move to avoid disruption and ensure the on-time delivery of your shipment.

One response to supply chain disruption is developing dual supply chains or procuring products via two different suppliers or transportation routes. However, these kinds of solutions increase production and transportation costs and lead to expensive inventory buildup.

Severe weather events that disrupt the supply chain are often considered “force majeure” events that negate contractual obligations. 

While that clause provides some legal recourse, the evolving abilities of weather forecasting may call into question if weather events can be considered unforeseeable to the parties in the contract.

Will weather forecasts ever be 100 percent accurate? Scientists say not any time soon. 

The global movements of wind and water are too complex, and we don’t understand all the nuances yet. However, the short-term forecasts will improve, giving us more time to plan and react.

As predictive weather analytics continue to improve, it could significantly impact your procurement and supply chain management. Read more about improving your supply chain resiliency.

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