SCRC Meeting Part 2: DHL’s Advanced Analytical Team Models Logistics Challenges

In our second SCRC presentation, a team from DHL Supply Chain spoke about how digital issues are changing their business.

DHL is a global business that manages 3.6M tons of airfreight, but also operates as Deutsche Post in Germany.  It is more than 450,000 employees in 220 countries, with revenues ofEuro  57.3M in Germany, and millions of shipments.    The organization includes their Express business, Global Forwarding Freight of Air freight, ocean, and road, and Supply Chain, that is focused on Contract Logistics and Industry Solutions.  Each division is about the same size, and a bit more labor intensive in supply chain (150,000 employees).

Omer Rashid is a senior director of analytics, having worked about 20 years or more with DHL.  Omer spoke about some of the key industry insights and trends, and noted that the amount of change in the last five years is exponential compared to what has come before. The first trend is around what he called the Amazon Effect.  Cyber Monday next week was projected to be the largest online shopping day in history – 6.6M orders on Monday.  About half of these orders were with Amazon, which is also moving into other businesses and industries as well.  (Note the CVS/Aetna merger in response to hints that Amazon was getting into the pharma chain!) The second trend is around personalization of direct to consumer shipments including special operations like gift wrapping. Accelerating SKU counts which must be picked with this customization, which combined with the massive demographic shifts and massive growth in e-commerce, is having a MASSIVE impact on the supply chain.

In the past, companies typically used a single national distribution center, with a 3 day BIC delivery time, and 5 day average shipment time.  In 2014, many supply chains move to a two DC model, one in the West, and one in East, which facilitated a two day delivery window.  The future supply chain network is moving towards a metro orientation, with consumer proximity, to accommodate Amazon delivery in 1-4 hours, small pickup lot sizes, short haul, same-day or next day delivery, combined with new and emerging delivery models.  This is driving a lot of change in industry infrastructure.  There is also a move to final mile delivery models to go by traditional parcel carriers.

DHL Solutions Design works as a global community of 325 highly skilled and motivated experts supporting DHL customers.  The team focuses on Facilty design for warehouses, transportation routing and scheduling, assembly kitting/packaging, and network optimization.

Omer spoke about how DHL is focused on using data to drive results, and conducting operational analysis to drive down costs.  Deconstructing data analysis to understand business processes happens before modeling, in order to create a proper baseline, which is used to drive the right basis for decision-making.  There may be short-term opportunities, but also customer-specific business rules and modeling paramaters that need to be considered, to help avert or postpone investments by discovering capacity enhancements.  The team can also build out “what-if” analyses and models to help impact the changes.

Omer discussed two very interesting case studies that illustrated how these business models can improve decision-making.

Case 1:  Traditional CPG Network.  The first case involved a traditional CPG network to ship full pallet load, full truckload, and customer orders, and a changing landscape including different channels, SKU proliferation, and smaller orders, moving to a pull model to postpone deployment of inventory.  The goal was to develop a future state network to optimize service, cost, flexibility, and agility, and to provide a second set of eyes on input operational realities and provide a roadmap for implementation.   Step 1 was to collect detailed demand data, and build a model to vary growth scenarios, service levels, and trade off costs vs. service levels.   Step 2 involved building the models. Step 3 was an implementation roadmap, and Step 4 involved building out a future state cost model projection.

Case 2:  Carton Optimization – FedEx and UPS two years ago went to dimensional weight pricing, whereby customers are charged for cube utilized, not just weight.  In e-commerce, this was seen as a big challenge for controlling costs, and suddenly getting the carton filled with less “air” became more important.  Optimizing the sizes of shipping cartons and the new dimensional weight charges to reduce cost became a priority.  We tasked our team to create a decision-support tool around the number and size of cartons – and the operations we run involved WMS information, shipping, item master informaton, and other data.  We cube each order, and create a feasible carton size, the optimal number and size of cartons, and based on that establish the right cartons to take advantage of the tools.   We could change the size of a shipping order using optimal amount of 15 cartons, providing an annual savings of 2.1M of operating cost.

Data and analytics will continue to be critical, but so will the ability of students to learn how to model real-world and projected business situations using different analytical tools for decision-making.