The Formula for a More Carbon-Efficient Supply Chain – Part 1

By Stephanie Judd, MBA/MS candidate, Erb Institute, University of Michigan, EDF Intern

As an MBA/MS student at the Erb Institute for Global Sustainable Enterprise, I have the distinct pleasure of working with Environmental Defense Fund this summer.  I’ve been tasked by the Goods Movement team to explore more alternatives for companies to improve supply chain transportation without compromising service levels or increasing inventory management costs.  The project focuses on the retail and consumer packaged goods (CPG) industries, because those industries have a high degree of transportation mode choice (air, ocean or rail) due to the value density of the products. Major appliances, like washing machines, will always come from China by ocean freight because they’re big, heavy and have a low value density (are not worth that much).  iPhones, on the other hand, are small, light and boast high enough margins to justify the cost of moving them by air.  But somewhere in between the packages of socks and the trendy summer shorts, a line is drawn, and a decision is made about what sails and what flies.  I’ll be exploring that line, trying to find ways to push a few more decisions toward the slower but more carbon-efficient transportation options.  Over the course of the next few months, I will check in periodically to discuss the development of the project and the lessons learned.

The Theory Behind the Project

In an ideal world, demand for products would be constant and predictable, and companies would produce for that demand, eliminating waste or lost sales in the system. Instead, demand is variable, and companies must try to predict fluctuations in consumer preferences and anticipate unpredictable demand schedules.  To buffer against this variability, companies have three tools at their disposal: Time, Inventory and Capacity.

Time: Companies can ask customers to wait.  This concept works in the case of highly specialized products or with particularly reputable suppliers.  A boutique guitar maker can wait to build a guitar until an order has been placed, and a customized luxury sports car will take several months to manufacture.  However, in the general retail market, buffering with time is not the competitive choice.  Customers will go elsewhere for the products they need or find suitable alternatives.

Inventory:  A better strategy for buffering against variability is to build inventory during periods of low demand.  Then, when demand soars, companies are prepared to meet it.  There are, however, risks to employing this strategy, since building inventory can be expensive.  Some associated costs include: the cost of capital tied up in inventory that might otherwise be invested to earn higher rate of return; warehousing fees; the risk of inventory loss due to theft, natural disasters, fires, etc.; and a sudden shift if consumer preferences, leaving warehouses full of unwanted goods.

Capacity: The last way to address demand variability is to increase response times.  For manufacturing firms, this means equipping machines with the capacity to run at high speeds when demand is up and slower speeds when demand drops.  For retailers, however, it means adjusting lead times between placing orders with suppliers and stocking the shelves.  Lead times are largely determined by the amount of time it takes to transport goods, and it is here where decisions are made about transportation modes.

My objective for the summer is to identify solutions for businesses to use slower, cheaper and more carbon-efficient shipping modes without asking them to buffer against demand variability with inventory or time. Stay tuned for updates on putting this theory to the test.