Building the Self-Optimizing Warehouse Operation

In warehouse operations, managers are on a never-ending quest to drive greater productivity and throughput in the most efficient manner possible. Especially in lower-margin e-commerce categories such as fast-fashion apparel, electronics and books or media, the need to continually achieve process optimization is paramount.

Increasing labor costs and low unemployment, fluctuating demand, rising customer expectations and supply chain disruptions have created challenging conditions that tax the limits of traditional warehouse management system (WMS) technology. A lack of real-time data analytics constrains adaptability in order processing and tasking as conditions change, often throughout the day.

Companies need technology that not only improves order fulfillment metrics, but also helps them retain workers by making it easier for those workers to hit productivity targets, be accurate while doing so, and stay engaged with the task at hand.

The WMS “capability gap” has created a growing need to evolve traditional warehouse operations into self-optimizing, intelligent systems. Using artificial intelligence and machine learning, innovative warehouse optimization augments the performance of a legacy WMS, putting it on steroids. Companies can boost fulfillment efficiency through things like voice-directed processes, improved labor utilization, smarter tasking and mobile work execution.

Warehouse optimization technology also allows managers to create a dynamic fulfillment environment that automatically flexes as demand and priorities shift and change. For instance, associates can be automatically redirected by voice command from lower-priority to higher-priority orders — based on preset rules — along optimized pick paths. The system can also assign other tasks along the route, such as moving items to a more productive pick location.

This approach is bringing companies closer to the concept of the self-optimizing warehouse. It’s a world in which automated systems are continually learning and presenting new ways to improve productivity, reduce costs and keep workers happy — a trifecta and a flywheel effect at the same time.

Static vs. Dynamic Environments

In a standard WMS without warehouse optimization software, processes are much more static and inflexible. For instance, hard allocation of inventory requires constant manual oversight and intervention to adjust as priorities shift. This keeps managers shackled to their screens instead of doing what they were hired to do: managing workers out on the floor.

“When we go into a warehouse operation, we see a lot of supervisors doing administrative tasks instead of managing people, actually engaging with them,” says Simon Dunlop, head of solution consu…