Any industrial engineer worth their salt starts a warehouse design (or distribution center or fulfillment operation) with detailed data analysis. This usually begins with gathering forensic information such as a 12-month sales history at line item (SKU, or Stock Keeping Unit) level, a fully populated item master file (including length, width, height, and weight), and inventory snapshots (peak and average). Typically, these transactional files contain millions of records, making a database or access project necessary. These data files are the fundamental building blocks to construct a base (as-is or current) mathematical model against which any alternative designs will be compared.
Many ancillary data points may also be needed, but this is the backbone of any re-engineering/optimization or new DC design initiative. In addition to the data collection, existing operations (processes, systems, infrastructure, and labor deployment) receiving through shipping must be documented. Existing operational challenges and opportunities, as well as any strategic/tactical goals, must be noted at this stage.
Once the historical model is created and validated (mapping and certifying all volumes and costs against current), forecast factors such as organic/acquisition growth, SKU proliferation, and market channel expansion are applied to the base volumetric model. This forward-looking exercise aims to define the ultimate design year (typically five years forward) operational requirements for the new or retrofitted facility, instilling a sense of optimism about the future design.
So, what does all that have to do with Cubic Velocity and Cubic Inventory by SKU, you ask? Cubic Inventory by SKU is the total number of cubic feet in stock (based on quantity x unit of measure – pallet, case, master pack, inner pack, and piece). So, if you have 20 cases of a particular SKU in inventory and each case is two (2) square feet, the total Cubic Inventory for that SKU is 40 cubic feet (approximately one pallet load). Average and peak calculations must be made. Cubic Velocity is computed by taking the cube characteristics of a particular SKU and determining how many were shipped over some period (aggregating the number of order lines and picks per line that the SKU moved during that timeframe). The result is the number of cubic feet that an item moved, providing practical insights into the movement of items in the warehouse.
Understanding the values of Cubic Inventory and Cubic Velocity by SKU is crucial in warehouse design and optimization. These values determine where items should be stored in the warehouse, both in storage and in a forward pick location (if applicable). For example, deep inventory items with slow movement characteristics may be best stored in dense storage modules such as floor stack lanes, drive-in/drive-thru racks, or double-deep racks. This can help reduce overall travel in the warehouse. On the other hand, small cube items with low velocities may be more efficient in shelving, decked racks, or carton flow racks. Some combinations of inventory and movement may be best served by automation, such as a goods-to-person system.
The combinations of process, systems, infrastructure, and labor approaches are exponential. An in-depth industrial engineering-based study is required to turn the Cubic Inventory and Cubic Velocity model into quantified alternatives with detailed capital cost, recurring cost (labor), capacity, throughput, flexibility, scalability, and risk characteristics. It is the only way to determine the best solution, achieve your service level objectives, and minimize operational costs. It all starts with the basic building blocks.
Download a free copy of our Pick Module Selection Matrix Tool to determine which alternatives are worth considering.
