With order fulfillment’s growing complexity, integrating AI into warehouse management is becoming a necessity. But how can companies truly harness AI’s power in their distribution centers?
To maximize AI’s impact, it’s crucial to understand how intelligent technologies integrate with the systems that drive warehouse operations: the Warehouse Management System (WMS) and the Warehouse Execution System (WES). These two systems work together to ensure smooth and efficient operations, each playing a unique yet complementary role. Understanding how WMS and WES interact is the key to unlocking the full potential of AI in your warehouse.
WMS: Defining the “What”
In simple terms, the Warehouse Management System (WMS) is the core system of warehouse operations, responsible for managing the ‘what’ of warehouse fulfillment. It acts as the central hub for various data points, answering key questions such as what orders need to go out, what SLA rules govern them, what inventory is on hand, and what resources are available to execute tasks.
The WMS sees beyond the warehouse walls, integrating with supply chain systems like ERP and TMS to coordinate activities such as supplier deliveries and transportation logistics. By sharing real-time data and aligning with customer demands, it manages vast amounts of information that touch on every aspect of order fulfillment.
However, while the WMS is excellent at defining what needs to be done, it does not dictate how these tasks should be executed. This is where the Warehouse Execution System (WES) comes into play.
WES: Optimizing the “How”
The WES takes the “what” from the WMS and focuses on how to fulfill orders as efficiently as possible. It processes data points about orders, inventory, and worker profiles, then plans, prioritizes, and prescribes workflows, effectively bringing the WMS’s strategic plans to life.
Traditionally, warehouse managers have relied on various systems, such as wave picking for order fulfillment and manual scheduling for task allocation. However, these methods often come with limitations that can lead to decreased productivity, unplanned downtime, and inefficiencies across different warehouse functions. Today, AI enhances this process by analyzing data to build tasks, place inventory, and manage every aspect of the warehouse with a focus on efficiency.
AI-Powered WES: The Foundation of Intelligent Warehouses
The ability to take all of the WMS data and build a decision plan requires exceptional capacity to process large amounts of information. This is where AI excels – it is particularly adept at analyzing complex datasets, allowing it to generate actionable insights for capacity planning and workflow optimization. Plus, the more AI is used, the smarter it gets. It learns and adapts through algorithms that analyze patterns within data, over time becoming even more efficient.
AI-powered WES systems, such as inVia Logic, are designed to handle these tasks with incredible efficiency. The inVia Logic WES software is powered by the inVia IQ AI engine, which collects data from the WMS and uses machine learning to optimize workflows and build effective decision plans. This continuous learning process allows the WES to adapt and improve over time, making predictive judgments that solve problems before they arise.
By leveraging AI, the WES can:
- Dynamically schedule and assign tasks: AI seamlessly matches order and inventory data, and SLAs demands with real-time resource availability. It ensures that the right tasks are assigned to the right workers at the right time. And by doing that, it virtually eliminates wasted time
- Maximize Hit-Per-Pick: AI-driven WES enhances the efficiency of picking operations by maximizing the number of items picked in each pick event, also known as “hit per pick.” By analyzing order patterns, inventory locations, and pick paths, AI can group orders strategically, allowing workers to pick multiple items in a single trip. This reduces the total number of pick events needed, minimizing travel time and labor costs, while increasing overall throughput. Maximizing hits per pick not only improves productivity but also optimizes the use of warehouse resources, ensuring that orders are fulfilled faster and with greater accuracy.
- Allocate inventory to support Just-In-Time (JIT) fulfillment: AI-driven WES dynamically manages inventory placement to meet JIT fulfillment needs, optimizing space utilization and ensuring timely deliveries.
- Optimize task execution: AI continuously monitors and adjusts workflows to ensure that all tasks are executed as efficiently as possible, adapting to changing conditions in real-time.
inVia Logic WES software is powered by inVia IQ AI engine that collects WMS data and uses machine learning to optimize workflows and build effective decision plans.
inVia Logic WES and WMS Process Flow:
