Welcome to the 12th edition of Q&A with Dr. Tompkins. Please be sure to write me any of the questions you may be having with regards to your own eCommerce supply chain operations.
QUESTION: What has MonarchFx helped you identify as the greatest weakness of Supply Chain Planning and Supply Chain Execution?
Supply Chain Planning
The greatest weakness of Supply Chain Planning has been the overall topic of network design. The current state of the art of network design is modeling a variety of networks in an attempt to define the network of facilities that allows for the satisfaction of customer service requirements at a minimal cost for transportation, inventory, investment, and operating costs.
The problems with this approach include:
- An objective function of minimizing cost as opposed to maximizing profits
- Constraining network alternatives to seller operated, 3PL operated, or a combination of seller/3PL and not considering distributed logistics ecosystems
- Customer service requirements not being consistent with future customer requirements
- Incorrect transportation costs
- Non-optimal inventory levels
- Wrong investment and operating costs
Allow me to briefly explain each of these factors:
- An objective function of minimizing cost as opposed to maximizing profits: Most network designs are done to minimize cost. This is an obsolete view of the supply chain. The objective of supply chains should be to assure profitable growth. The goal should be to maximize revenue, while minimize costs, to maximize profitability. Most network designs ignore the impact that improved fill rates and increased speed of delivery have on increasing revenue, thus missing the target of maximizing profitability.
- Constraining network alternatives to seller operated, 3PL operated, or a combination of seller/3PL and not considering distributed logistics ecosystems: Typical network designs look at the cost of either operating a network of owned facilities and/or of 3PL facilities, but not MonarchFx facilities. MonarchFx facilities are neither owned or 3PL facilities. They are multi-seller, automated facilities where the seller only pays for what they use. There is no capital cost and seller operating costs are based on the MonarchFx ecosystem unit rice This is established based on the seller order and storage profile. The facilities are flexible with one-year contracts. The MonarchFx solution can utilize the seller’s existing facilities and provide additional facilities as needed over time. MonarchFx provides the seller more distribution points closer to the customer at a lower price than the seller will be able to do on their own, even using 3Pls. MonarchFx facilities can provide for DTC, BOPIS, wholesale, store replenishment, and many other configurations.
- Customer service requirements not being consistent with future customer requirements: Network designs typically plan for a five year planning horizon and require the prediction of the volume by geography, fill rates, and order delivery times demanded by customers. The target is to develop a definition of orders over the planning horizon which is typically five years. Obtaining projections for the year ahead is difficult and trying to obtain these numbers for a five year planning horizon is even more difficult. The same challenge exists with the desired customer service levels. Do the customers want two-day delivery across the U.S. or do the requirements vary by the size of city they live in? Do all customers have the same requirements? Modeling anything beyond a year out cannot be justified. What is needed is a network, such as MonarchFx, that is flexible and modular enough to change on a yearly basis, while keeping capital and operating costs in check.
- Incorrect transportation costs: The most significant network modeling costs are transportation costs. Transportation costs include inbound, outbound, and trans-shipments. On inbound transportation costs, it is usually assumed that all sourcing stays the same for the five year planning horizon. On outbound, how do you handle the different requirements of two-day, next day, and same day? Also, how do you handle the evolution of BOPIS and DTC? On trans-shipment what assumptions can you make here? Lastly, how do you establish future transportation rates and assessorial charges especially given the fast evolution of final-mile delivery options?
- Non-optimal inventory levels: The square root law for the growth of distributed inventory safety stock as opposed to centralized inventory is well known and mathematically correct when stock is deployed by pushing inventory to locations. However, when deploying a demand-driven replenishment model the square root law is not applicable. Most network design exercises use the square root law, thus “optimizing” solutions by having too few stocking points. See the discussion below on supply chain execution to grasp why obsolete thinking on inventory can result in very poor network plans.
- Wrong investment and operating costs: This is not nearly as important as transportation costs and inventory levels, it is still a major factor impacting the “optimal” network design is the accuracy of the investment and operating costs going forward. It is not possible to accurately predict these costs over a five year horizon so when these costs are added to tremendous amount of uncertainty in the above four factors and the rapidly changing material handling technology used to fulfill orders, we find that mistakes are often made. There is a tremendous amount of shifting in networks over time and a tremendous amount of money wasted.
Doing network planning for the last 40 years (we began network modeling in 1978 on a Radio Shack TRS-80 computer) and understanding the huge level of disruptions and change occurring in today’s business environment, I am firmly of the opinion that what was once a great planning tool, network design, has become woefully obsolete given today’s dynamic environment and the existence of solutions like MonarchFx.
Supply Chain Execution
Planning and execution have been more blurred in recent years as technology has enabled near real-time visibility and data to be accessed and used. Users now have the opportunity to adjust plans to meet reality. One of the most important execution issues is the management of inventories, especially in the new world of demand-driven operations. Traditional execution inventories were “pushed” out to DCs and business customers with expectations that business customers would need them at some point in time. Deploying the “inventory push” to the network of DCs for customers has been the business objective. As business customers have become more sophisticated and consumers have demanded more personalization and online buying, demand-driven has required more “pull” inventory, meaning decentralizing only what will be sold in the short term ( “sell one, replace one”). Distributed inventories based on pull for order fulfillment or inventory “flow”, must complement the pull inventories at DCs for larger business customers. This new operating strategy has changed the business objective for the execution of product distribution.
Inventory optimization remains the goal of supply chain managers. Distributed logistics is the first step in reaching multi-echelon inventory optimization. The primary challenge then becomes short-term demand forecasting and minimizing weeks of supply to align with the demand pull. MonarchFx has developed a unique model for forecasting and replenishing based on “flow” that helps meet this challenge. Execution is now about what and when to replenish in order to sustain inventory optimization, minimize carrying costs, and reduce working capital
If you missed Part 11 of my Q&A series you can find it here and be sure to send me your questions!
James A. Tompkins, Ph.D.
Chairman and CEO, MonarchFx
Executive Assistant: Debbie Flynn, 919-855-5447