ARC Advisory Group does global market research on the warehouse management system market. We write about trends in this study. I am the author of this year’s study. One trend I believe is imminent is that the market appears to be poised to bifurcate in terms of functionality. There will increasingly be Tier 1 solutions with complex optimization. Low-cost solutions that can be implemented quickly will also be increasingly implemented. However, the need for Tier 2 solutions that include a moderate amount of functionality will diminish.
Why Will the Need for Tier 2 Solutions Diminish?
In short, because of intelligent automation. Autonomous mobile robot providers, like Locus Robotics, provide their own optimization. Warehouse workers work alongside autonomous mobile robots to fulfill orders. Warehouse execution systems emerged to optimize work across both the manual and more automated parts of the warehouse. Leading WMS providers – like Manhattan Associates, Blue Yonder, and Körber Supply Chain – offer WES.
Locus Robotics does not allow the WES to optimize the work it does. The warehouse mobile robot system downloads orders from the WMS for the work that will be done in its zone. The more orders it downloads, the greater the AMR system’s ability to intelligently group orders and increase throughput. Locus has introduced bots with larger payloads, and its value proposition now extends beyond each picking to include case picking.
In addition to warehouse robotic solutions taking over the task of optimizing work in the distribution center, vendors like Lucus Systems can layer optimization on top of legacy or Tier 3 WMS solutions. Lucus Systems is best known as a provider of voice AutoID solutions for the warehouse, but they are more.
What Does This Mean for Providers of Tier 1 Solutions?
They must focus on optimization and other functionality that drives labor productivity. Functionally, a Tier 1 solution should include the following:
A warehouse execution system – these solutions optimize work across the automated and manual activities in a warehouse.
Wave Planning involves batching several tasks into a wave of work. This minimizes travel for floor-level associates.
Task Interleaving—Picking is the most important activity in a warehouse. But when the need to get work out the door diminishes, it makes sense to interleave picking with other tasks. For example, if a worker is in an aisle making a pick, and they are next to a slot that has not been cycle counted for a while, the worker can count the number of items in that slot.
eCommerce order streaming—E-commerce orders are typically small, one or two items. Rather than batching these orders to gain labor efficiency, it often makes sense to drop them—or at least the orders that customers were promised would be delivered quickly—to the floor as soon as they are received. Thus, E-Commerce orders are fulfilled with something known as “order streaming” logic.
Route Optimization—Wave planning is a form of route optimization. By dropping a group of orders to an associate that all require work to be done in a particular zone, that associate does not have to travel as much. However, a zone typically involves several aisles. What is the best way to route a worker into and out of those aisles, particularly if the aisle is congested with other workers? Zebra has introduced location tags that attach to associates. Combining those tags with new optimization logic could take worker routing to the next level.
Engineered Labor Standards—The goal of a labor management system is to get employees to work at a steady pace consistently throughout the day. Engineered labor standards are developed to ensure that if a picker works efficiently and steadily, they can hit their goal for the day. Often, companies will give bonuses to workers if they can work faster than the standard pace. Labor productivity always goes up when an LMS is introduced, and these solutions provide quick payback.
Pack Optimization—Companies often use an excessive amount of packaging to ship items to customers. The extra boxes, bubble wrap, tissue paper, and other packaging materials have a negative impact on the environment and increases shipping costs. Pack optimization works to fill shipping containers efficiently.
Labor forecasting – Here, historical data is used to forecast how many workers will be required on a given day or week to complete the work that will hit the warehouse. This works even better if warehouse executives are included in the integrated business planning process. It works better still, if the DC has engineered labor standards in place. In many cases, a warehouse may have visibility to a significant proportion of the orders that will drop to the warehouse in the coming day or two. In this case, schedules can be adjusted so that the warehouse has neither too many nor too few workers.
A Warehouse Digital Twin – Currently, planner interfaces can show the layout of the warehouse, provide heat maps of SKUs about to expire, or show empty slots. But digital twins will be capable of more. The digital twin should include simulation capabilities.
The User Interface – Generative AI will be used to create highly intuitive user interfaces for warehouse planners.
When it comes to Tier 1 solutions, the architecture also matters. Ideally, the solution should be based on a public cloud architecture. The platform should include other supply chain applications sharing the same master data and database. The solution should be componentized. Components should not be inside the warehouse management or transportation system but rather independent, sharable, and composable. For example, if transportation plans can leverage pack logic components, typically used by a WMS, trucks can be filled more fully.
