By Juliana Davila-Suarez | Senior Manager, European Supply Chain Design | Chainalytics
Companies facing facility location decisions usually embark on supply chain network studies with misconceptions that can impact their long-term results: They often believe facility-related costs like property leases, direct and indirect labor and administrative expenses are the main drivers of site selection. In other words, they relegate transportation costs to a lower priority and are surprised when the cost relevance is indeed often the other way around. At Chainalytics we have compiled distribution costs from a variety of industries with different supply chain network sizes and levels of complexity (see Figure 1). For these sample industries, transportation accounts for more than 60 percent of the total distribution costs; indeed inbound and outbound transportation costs outweigh both fixed and variable facilities costs and inventory carrying costs.
Why Distance-Based Costs Don’t Work in Your Model We’ve seen time and again that modeling transportation in network studies with average cost-per-distance estimates at the national or regional level provides insufficient accuracy for investment-grade results. In fact, this approach can severely skew results and deliver poor answers — leaving savings on the table or worse putting a facility in the wrong place. Broad estimates like cost-per-kilometer ignore key factors like geography, equipment type, service levels, fuel and accessorial charges and are also limited to internal data, load board data, carrier quotes and third-party trends. For this specific example one could rephrase the very common expression–garbage in, garbage out–as average in, average out. How FMIC Fits into Successful Supply Chain Modeling In this instance and others, we’ve found that our customers benefit from Chainalytics’ Freight Market Intelligence Consortium (FMIC). FMIC provides an econometric benchmarking approach built on qualified input data with the goal of explaining cost differences that matter when buying transportation services. FMIC data reflect true transportation market dynamics including backhaul or origin and destination effects by geography, employing data that is otherwise difficult to capture. Figure 2 illustrates an ambient lane from Genk, Belgium to Bingen, Germany and vice versa that has very different costs in each direction, reflecting the market’s nature:
- Bingen is a wine-growing and tourist destination near the Rhine river with more residential than industrial traffic, which equates to a higher probability of empty miles and incorporates what the FMIC model defines as a higher “destination effect” variable (this variable accounts for the difference of supply and demand at every geographic point).
- Genk, however, is an industrial city in Flanders and a much more favorable destination for carriers because of the ease of finding loads out of the area. Therefore the FMIC transportation rate estimate reflects these market characteristics and the freight rate into Genk is lower by 11 percent, all else equal.
Chainalytics’ FMIC rates are available in the North American and European markets, providing various levels of FMIC data accessibility:
- Chainalytics’ network design clients (who are not necessarily FMIC consortium members) can employ FMIC market rates for the duration of their study and enjoy the benefits of modeling transportation accurately–a service that ensures they make their most efficient and cost-effective network design choices.
- FMIC consortium members can leverage FMIC data accessibility to not only benchmark their current transportation lanes, but also gain access to rate estimates for various types of analyses including supply chain design studies, further guaranteeing better results over time and business or network changes.
Juliana Davila-Suarez is Chainalytics’ Senior Manager, European Supply Chain Design. Over her 11-year tenure at Chainalytics, she has designed supply chain networks for clients in food and beverage, consumer goods, electronics and home and office durables, among other industries in the Americas and Europe. She employs deep expertise in supply chain design modeling to support clients’ fact-based decisions and help them achieve long-term strategic planning and supply chain results and savings.
