Revolutionizing Warehouse Management: Introducing New Inferred Case Count and Location Occupancy Capabilities

Introduction

Warehouse operators spend a significant percentage of their time trying to know the correct inventory levels in each location. This information is needed to ship on time and optimize space utilization. According to the Warehousing Education & Research Council (WERC) 2023 DC Measures Annual Survey & Report, the average warehouse meets shipping deadlines only 96% of the time,and uses just  81% of its cube utilization. 

Manually cycle counting cases requires someone to climb onto material handling equipment and go high up into the racks of a warehouse. Often cycle counters have to take down the pallets and restack cases to ensure the case count is correct. This heavily manual process makes it difficult to maintain accurate inventory and to ship on time.

We are introducing two new groundbreaking capabilities to help solve these challenges: 

• Inferred Case Count
  • Benefits:
    • Verify the cases on full and partial pallets 
    • Save labor and improve on-time fulfillment
    • Refocus labor on pallets when counts don’t match what’s in the warehouse management system (WMS)‍
  • ‍How it works:
    • Our AI estimates the maximum number of layers of cases on a pallet and combines it with Ti data in the WMS to infer the number of cases and display differences on your web dashboard. 

• Location Occupancy
  • Benefits:
    • Optimize your facility utilization
    • Strategically move and consolidate pallets to take advantage of available space
    • Improve your cube utilization
  • How it works:
    • Our AI estimates the percent occupancy of a pallet location

These capabilities leverage our world-class AI and computer vision.

Both capabilities are available with our current hardware. Count cases and report occupancy levels as part of normal drone missions, at a speed of up to 900 locations per hour.

How these capabilities will help you improve your operations

Inferred Case Count

Many warehouse operators are required to cycle count cases. Because the process is manual, it’s a struggle to have accurate counts in the WMS. If WMS data is inaccurate, teams don’t know when to replenish a location. Inaccurate case counts cause missed shipments and shipping delays. 

If you need to count cases, this capability will help you with:

Fulfilling Case Counting Requirements: Gather AI's inferred case counting capability enables operators to refocus manual counting on complex counting cases, accurately verifying pallet completeness without scissor lifts or other equipment. It can reduce the time spent on manual case counts by up to 90%.

Preventing Stockouts in Pick Areas: Stockouts disrupt operations and lead to missed shipments. Our technology alerts you to discrepancies between actual case counts on the floor and expected counts in the WMS, allowing for timely replenishment and WMS updates.

Identifying Replenishment Needs: Visibility into nearly depleted locations is significantly improved, enabling proactive replenishment actions.

Location Occupancy

Having insight into how much open space exists in each location within the warehouse can be used to consolidate pallets and see which pick locations are ripe for replenishment. If you struggle with finding space for inventory or have stockout issues, this capability can benefit you: 

Maximizing Space Utilization: Discover consolidation opportunities by identifying partially occupied locations with identical products. Optimize the available space.

Proactive Replenishment Alerts: See locations nearing depletion (with low occupancy), ensuring smooth operational flow through timely replenishment.

How It Works

Inferred Case Count

Our world-class computer vision and AI assess the number of cases on a pallet from an image taken by the drone. We can infer the number of cases on the front face based on what we detect in the image.

In its first version, our AI counts the maximum number of layers visible in a pallet location. We then use the Ti data (number of cartons on a layer) from the WMS to estimate the number of cases on the pallet.

This count is then compared with the expected count in the WMS. We highlight any variances for immediate attention. All of this data is available and exportable from the Gather AI dashboard, giving you a list of every location that needs your attention and why.

Location Occupancy

Our computer vision distinguishes between inventory and open space within a location and can calculate an occupancy percentage. This location occupancy data, combined with product information from the WMS, facilitates inventory consolidation opportunities. It identifies similar products in partially occupied spaces that could be moved to a single location. 

Taylor Logistics is 87% more efficient

Taylor Logistics, a leading 3PL, is required by some of its customers to count cases as part of their cycle counting program. "Using Gather AI's drone inventory monitoring and the inferred case count feature is 87% more efficient than having our team do physical cycle counting,” reported AJ Raaker, Director Of Warehouse Development at Taylor Logistics Inc. The efficiency gain enabled Taylor to move their cycle counters to higher value, revenue-generating activities.

Reach Out to Us to Learn More

With Inferred Case Count and Location Occupancy, you can now reallocate your labor to more value-added tasks, and improve on-time shipments and the utilization of your warehouse. Our AI and computer vision enable these insights and our solution will continue to evolve, promising even greater advancements. Discover how Gather AI can transform your warehouse management by speaking with one of our sales experts today.