Using Environmental Data to Design Smarter Supply Chains

Texas License Plate half Buried in Snow

Ten years ago, “What’s an environmental scientist doing in supply chain analysis?” would have been a good question. I might have even asked it myself before I took that exact step across the two industries.

These days, however, news items regularly illustrate the links between climate events and supply chain disruption: From sourcing and production to logistics and distribution, no aspect of the modern supply chain is immune to the effects of environmental extremes, and supply chain managers are constantly reminded of the need to incorporate environment and climate-related risk into their supply chain strategies.

Most of them simply don’t know how to make the best use of the tools and information available – and that’s exactly where we come in.

 

Expertise and Information: The One-Two Punch

Incorporating agility and resilience into your supply chain requires much more than just a piece of technology: The best tools and design solutions can’t deliver optimization if they’re not paired with a team of people who have the experience and know-how to address a range of challenges from expected highly seasonal demand to globe-spanning rapid changes in consumer behavior.

I’ve worked with satellite data that provides an unprecedented picture of regional changes in wildfire risk, crop yields, and flooding already occurring. Temperature, greenness, sea level, emissions, reflectance: All of these can be measured from orbit, and each dataset can be used as a proxy for conditions that can affect supply chain operations.

And while data gathering becomes more comprehensive and granular, the science of climate modeling has become sufficiently mature that data products summarizing predictions of regional changes in flooding, growing season, storms, sea level and other disruptions are now widely available and increasingly reliable.

 

Environmental Data Makes the Difference

It’s not just theoretical. Let’s look at some real-world examples of environmental information used as business intelligence that can make a difference:

  • Longer dry seasons driven by shifts in temperature and the timing of precipitation will affect global Arabica coffee crops in coming decades. By linking changes in growing season with supply, coffee companies can modify procurement plans and be prepared for changes in distribution routes – and that’s resilience in sourcing.
  • In February 2021, ice storms cut off power and transportation across Texas beyond anyone’s expectations of timing and extent. Companies that were able to divert inventory or draw from safety stock saw their business impact minimized due to their agile response to disruption in logistics.
  • COVID-related backups at ports and the 2021 Suez Canal blockage disrupted supply chains worldwide and highlighted our reliance on the global shipping industry. Environmental data can help us prepare supply chain vulnerabilities against the effects of storm surges on offshore operations, or the impact of sea level changes on coastal facilities, reducing risk during infrastructure shutdown.
  • Safety stock allocation buffers the effect of variability in supply and demand – but inventory policies based on historic supply data are only truly effective when the future resembles the past. Use of modern environmental data products as part of your inventory strategy can improve predictions of variability in raw material supply and transportation lead times, offering built-in resilience against disruption.

 

Data Drives Decisions

Unilever’s Chief Supply Chain Officer recently commented that “At the end of the day, every dollar we spent on agility has probably got a 10x return on every dollar spent on forecasting or scenario planning.”

So why wouldn’t you want to incorporate environmental data into your supply chain planning? Its value isn’t going away: It can increase your visibility into risk of supply chain disruption at the tactical, operational, and strategic levels, enabling us to work with your company to identify how the risks may affect your ability to deliver finished goods and where increased flexibility and agility are required.

We can also link these risks to network model inputs, be they external supplier costs, raw material availability, warehousing needs, or logistics to quantify costs of disruption and remediation.

Whether we help you incorporate risk into your supply chain models from the ground up or use a digital twin of your existing network model, Profit Point can show you how to use environmental data to help mitigate at-risk components of your supply chain.

About Rina Schumer

Rina has 25 years of experience in the formulation and solution of data-driven models and optimization problems. She has a Master’s degree in Applied Mathematics and a PhD in Hydrogeology.

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