Warehouses are not one size fits all. Too little warehouse capacity can restrict the volume of SKUs you can ship, inhibiting revenue and service levels, while too much warehouse capacity inflates your overhead expenditures and ties up working capital.
Unfortunately, unlike shopping for clothes, you cannot try on your new space before you buy it and there is no return policy. We all know the old adage: measure twice, cut once. The same fundamental principle applies to warehouse design. The capacity of your warehouse should satisfy both current and future business requirements, but also be flexible enough to accommodate unforeseen fluctuations.
If you are evaluating your current warehouse’s capacity, the best place to start is with your data – which hopefully is both available and trustworthy. Estimating the data that is used to calculate capacity requirements—no matter how educated those guesses are—is a surefire way to end up with a warehouse that doesn’t meet the current or future needs of your business.
The following data list is absolutely critical to capture and understand before you can right size your warehouse:
- Product dimensions and weight. Typically maintained in product item masters or provided by suppliers, this data consists of item attributes like length, width, height, depth, weight, stackability, etc. which determine the storage and handling requirements for each item—the largest drivers of capacity. This is the big kahuna. If you can get this one right, you’ve addressed approximately 80% of your space requirements.
- Product volumes. Inbound and outbound volumes are a critical component to identifying capacity requirements across nearly all functions inside of your warehouse. This data can be used to determine inventory turns and, when applied to the profile established for each item, storage media requirements and capacity can be calculated. When applied to productivity data, you can determine throughput requirements and headcount as well as the amount of space needed for inbound and outbound areas.
- Productivity data. When combined with product volumes, the number of items your material handlers can touch per hour for each function in your warehouse (i.e., unload, put-away, pick, stage, assemble, load, etc.) will help to determine the headcount required as well as the overarching material handling strategy for your facility. Once your headcount and material handling requirements are better understood, the capacity requirements for inbound and outbound areas, MHE storage and charging, as well as indirect space such as break rooms, parking, bathrooms, and other office space can be determined.
- Order profiles. What picking solution should you employ to meet the service levels expected by your customers? Do any items need to be pre-assembled? Should orders be staged or time-phase released? Can orders be consolidated? Are there any special material handling requirements? All of these questions can be answered by reviewing your order profiles which provide information such as lines per order, units per line, weight per order, cube per order, time of day, destination, shipment method, order type, etc. The selected material handling solution (e.g., order pickers, conveyors, etc.), picking strategy, order staging requirements, etc. will drive additional capacity requirements inside of your warehouse.
- Inventory snapshots. The history of where your inventory was stored within the warehouse at a given point in time (e.g., end of month or end of week) is important to determine the amount of storage capacity. Along with the product dimensions as well as median and peak inventory requirements, storage estimation will be a lot more accurate. The impact of increasing or decreasing inventory turns by different product groups can also be assessed.
There are a few other data sets that, while not crucial, are beneficial to determining and justifying the cost associated with a warehouse project, including:
- Operational cost data. If you need to develop a comprehensive business case for a new or retrofitted facility, this data is often necessary to justify and greenlight such a project. This requires an operational cost perspective that encompasses a robust knowledge of cost per unit, per function, per person, per hour, per square foot, material handling costs, equipment maintenance costs, as well as any other capital investment required for the project. Put together, this data can guide the analysis of alternatives for a facility design that meets operational and service level requirements while staying within financial bounds.
- Capital expenditure requirements. Unless you company is experimenting with on-demand storage, your warehouse is a long-term asset. You must work with your finance team to determine the financial criteria for building out a new space or renovating an existing one. If you cannot satisfy your internal rate of return, then you may want to consider outsourcing to a third party provider.
Collecting and analyzing this list of data is the first step in transforming your existing warehouse or planning for a new facility. While analyzing data and modeling different solutions may seem time consuming, it will pay off in spades throughout the lifecycle of the asset. Most warehouses are a long-term investment, so if you get it right, you’ll be operating efficiently for years to come and be aligned with your broader, long-term business strategy.
If you’re not sure where to start or want to validate your company’s current plans, let the experts at Chainalytics help you get it right the first time.
Kirk Waldrop is Vice President of the Supply Chain Operations practice at Chainalytics where he is responsible for leading engagements related to logistics and operations strategy, facility design and optimization, 3PL advisory and selection, warehouse technology advisory and selection, order-to-cash, procure-to-pay, customer segmentation, and transformation planning and implementation.
