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WMS Accelerators Bring Warehouses Into the 21st Century

Advanced technology simplifies planning and scheduling.

By: Keith Moore, Contributor

At a high level, managing a warehouse looks simple – inventory flows in and out, and you store a few things in the middle. In practice, managing a warehouse is akin to conducting a symphony. Each section, from inventory to labor, must play in harmony to produce the desired outcome: timely and accurate deliveries to every customer exactly when they need the product. To maximize service levels and reduce costs, companies often introduce automated warehouse technologies to manage some of the complexity in their warehouse. While these new technologies can often provide significant benefits in their functions, they can also create additional complexity due to the interchanges between automated and non-automated process flows.

The global warehouse automation market is estimated to grow at a compound annual growth rate (CAGR) of 15%, reaching a value of $41 billion by 2027, according to Logisticsiq, which creates a chart of 10 technologies and vendors that offer these technologies. Per Logisticsiq’s research, the top warehouse technologies include:

  • Autonomous Guided Vehicles (AGV) / Autonomous Mobile Robots (AMR)
  • Automated Storage Retrieval Systems (ASRS)
  • Conveyors
  • Sortation Devices
  • Order Picking Technologies
  • Automatic ID and Data Capture
  • Palletizing & Depalletizing
  • Gantry Robots
  • Overhead Systems
  • Warehouse Management Systems (WMS) / Warehouse Execution Systems (WES)/ Warehouse Control Systems (WCS)

Warehouses must adopt the combination of hardware and software technologies like those listed above to deal with supply chain complexities such as fluctuating consumer demand, fuel price increases, parts shortages and labor shortages. Addressing these challenges and meeting demand often requires sophisticated planning and scheduling solutions to integrate all the different technologies. Many companies think they can do all this using a warehouse management system (WMS).

A WMS accelerator can integrate data from across an enterprise, creating a unified view of the operations.
Image courtesy of AutoScheduler.AI


A WMS helps businesses meet customer demand and order fulfillment. However, many of these systems offer a one-size-fits-all solution focused on inventory management and hardware (i.e., scanner) integration, often overlooking the intricate details that make each warehouse unique. For instance, ensuring inventory is available for a shipment is just one piece of the puzzle. What if the stock hasn’t been unloaded, or there’s a sudden surge in orders (which originates from a system operating at the network level), and there isn’t enough staff scheduled to handle the load?

Today’s WMS needs more functionality for optimizing processes that incorporate current business constraints, such as labor, space, inventory and transportation availability.

This gap in existing WMS software to project optimal decisions into the future is filled by elbow grease and critical thinking at every site. Planners and administrative staff use all data available in every distribution center to manage shipping, receiving, dock schedules, inventory control and work release. This team reviews the list of complex tasks that need to be performed, the variety of constraints that each task entails, the available capacity and the tradeoffs that can be made to make decisions and get all the proper inventory out of the right door at the right time.


As technology introduces more complexity to buildings, the challenge becomes that there are often too many decisions to be made to optimize the labor and delivery to customers manually – the process needs to be automated. For example, a single order could look like the following: at a warehouse at a production facility that ships downstream to other distribution centers. An outbound due in the next three hours needs to have 39 pallets worth of product loaded onto it. Of those 39 pallets, 10 are in an automated storage and retrieval system, 12 are stored in racking elsewhere in the building, five are expected to be mixed-product case pick pallets, and 12 are not in the building. Of the 12 that aren’t in the building, five will be produced on a production line over the next two hours, and seven are sitting in the yard on two separate inbounds.

To deliver this single order on time, a planner would need to:

  • Immediately trigger both inbounds to be brought in and assign that work to two different people (because you can’t know where the product is in the truck, you must plan to load all of them).
  • Assign the best door to reduce travel between the racking, pick area, inbounds, ASRS and production spurs.
  • Simultaneously manage the workflow in the case pick area to ensure this order is appropriately prioritized to finish picking before the end of the production run. This will likely take more than two hours of picking, so multiple people may need to be dedicated to finish this in time.
  • Trigger the 10 pallets to be brought down in the ASRS and then have AGVs shuttle them to the assigned door.
  • Assign a picker to go and get the 12 pallets stored on conventional racking.
  • Ensure enough people are assigned to the production putaway team to deliver the five pallets needed to the outbound trailer before the product is stored.

On top of this, the planning team must ensure they deliver on all the other orders while meeting other warehouse demands, like reducing inbound detention and potentially supporting the production site.


This new complexity emphasizes the need for warehouses and distribution centers to adopt advanced technology, such as artificial intelligence (AI) and machine learning, to meet the growing deficiencies in today’s WMS. Warehouse executives benefit from using warehouse optimization technology that orchestrates activities within the warehouse so businesses can better meet customer deliveries on time and in full.

Using intelligent warehouse orchestration that works with a WMS, warehouse managers can look across the fragmented operations in a warehouse and optimize labor, touches and inventory to drive efficiency and create value. Often called WMS accelerators, these tools integrate data from across the enterprise, creating a unified view of the operations. The digital twin, AI and machine learning technologies can be applied to determine what must be done to meet schedules and create optimal plans. The whole example workflow identified above can be automatically created, adapted and altered as conditions continue to change throughout the building while accounting for all other building objectives.

WMS accelerators adapt and rebalance activities based on what happens inside a warehouse in near-real time. WMS accelerators rearrange schedules, review labor requirements, schedule replenishments, cross-dock orders, and ensure shipments arrive on time and in full. They ensure the right amount of labor shows up at the correct dock with the inventory needed to fill orders. With this technology, warehouses can be brought into the 21st century without constraining the personnel doing the planning today.


A WMS accelerator can automate planning and scheduling – in fact, our company identified the concept and jointly created the solution for P&G, which used many manual processes previously to schedule warehouse activity. Based on who was on shift and the need of the day, the planning process has many variabilities when sourcing loads. Beyond that, volatility in the production schedule and volume increased planning complexity. These factors often resulted in imperfect schedules requiring many bring-backs from the satellite warehouses to the plant to complete shipments.

AutoScheduler was deployed, and ingests data every 10-15 minutes, optimizes schedules, and then pushes optimized schedules back into systems of record for execution. As a result, workforce planning was reduced from 8 hours to 20 minutes per day, productivity improved by 5-15% depending on the site, and service levels (Controllable Fill) increased by 0.5-1%. WMHS

Keith Moore is CEO of AutoScheduler.AI, an intelligent warehouse resource planning and optimization platform that dynamically orchestrates all activities on top of an existing WMS in real-time. Learn more at

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