What Information Do I Need to Design My Warehouse?
Whether or not you work with a warehouse design consultant when you begin planning the design for a new warehouse distribution center, or a retrofit of an existing warehouse, there is certain data that you must have on hand if you are going to have a smooth design process.
This data informs both your internal team and any outside consultants about the products that you handle, as well as the rate at which you handle them—all of which will impact the amount of space required in your new facility, the technologies leveraged, and the general organization and flow of your finished warehouse.
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SKU Data
SKU data is an important driver in any warehouse design or retrofit, and for a simple reason: Your inventory dictates the size and capacity of your stock and forward pick areas, the general flow of your facility, and the layout of your order fulfillment and assembly areas within the warehouse. Four important pieces of SKU data to have on hand before beginning a warehouse design are:
- Number of active SKUs handled currently: This data will have a direct impact on space utilization. On its most basic level, it will inform how much physical space you must dedicate to storing inventory.
- Number of SKUs to be handled in the future: If your number of active SKUs is expected to increase or decrease in the future, having a working estimate on the impact of that expansion or shrinkage will allow you to plan a warehouse that accommodates your needs today as well as your needs tomorrow.
- Design specs of SKUs handled: Specs like size (length, width, height, weight, etc.) are critical, but equally as important are things relating to unit of measure of the saleable unit. More information on this in the Item Master Data section below.
- Storage requirements: Different kinds of SKUs are going to need to be stored in different ways—in a refrigerator, a freezer, a climate- or humidity-controlled environment, etc. If you handle multiple SKUs that require different storage types, this will obviously impact the design, layout, and flow of your warehouse, as well as your workflows.
Additionally, noting which SKUs are dead compared to which ones are currently active will help the warehouse design consultant have a better sense of your storage needs. If you don’t differentiate dead SKUs from active SKUs, the ultimate design won’t be reflective of your needs and will require additional rounds of design work to correct (which may add more to your project’s budget).
Item Master Data
Just as SKU data is important in designing your warehouse or DC, item master data plays a big role in ensuring that your new facility can adequately store and handle the items that you process.
If your internal team or warehouse design consultant does not have accurate item master data for your facility, then they will be designing based off of movement instead of physical items. A design consultant needs specifics if they are to understand how various systems within the facility will interact.
Item master data that you should have on hand before beginning a warehouse design process include:
- Description of each physical item
- Number of each item generally kept in stock
- The type or category for each item
- Dimensions (length, width, height, weight) for each item
- Unit of measurement (and conversion factors between UOMs, if possible)
- Ti (Cases per pallet level or tier)
- Hi (Number of levels on a pallet)
In addition to this, it is important to note whether or not certain items are fragile or have special wrapping, storage, or handling needs.
Order History
A warehouse design consultant needs accurate item master data to understand the capacity (physical storage, space, etc.) needs of your warehouse or facility, but they rely on accurate order history for volume and speed (average order, peak rates, seasonality, etc.).
Important order history data for you to provide to your warehouse design consultant for analysis will vary from industry to industry, but in general will include:
- Order number (so that your design consultant can see how many orders placed per day included a certain item, and how many lines need to be picked for the average order).
- Date and time up to an hour or minute that the order was picked. This will show when an item is picked compared to when it leaves the facility (system to door), which can help to point out inefficiencies in your processes. Knowing the baseline allows your consultant to find ways to increase efficiency so that you can handle more items and orders per day.
- Items in the order (to understand the lines picked).
- Quantity of items in each order (to have a better sense of the “average order”).
- When an order was placed (to see how it relates to pick time and ship time).
- Units of measurement in an order, if they differ from the data on the item master.
In the best case, you should provide data for the last year’s worth of orders. In many cases, 6 months’ worth of data will be sufficient. But this is just a quick rule of thumb: Depending on how much SKU turnover your facility experiences, more or less data may be better. (For example, if you turn over a lot of SKUs on a regular basis, a 6-month or 3-month window of data may be better. As always, though, it is better to have too much data and have to narrow it down than to have too little data.
Also worth noting are any exemptions or asterisks. If there is anything in your product handling, storage, or order fulfillment workflows that isn’t reflected in the data, but could impact design, it is good to know.
For example, we work with a client that sells health and beauty aids. Within their data set there was data about dentist chairs, which they sell. The thing is, they don’t store these chairs in their warehouse: The chairs are ordered, shipped to the warehouse, and then immediately shipped back out.
This is important to know, especially for large or bulky items, because this will impact the storage needs of the facility. Had we not known about this, we would have accommodated the chairs in the warehouse design—only to need to adjust the design later on when the mistake is spotted.
Conclusion
If you are working with a warehouse design consultant to plan the design of your new warehouse, having the above data on hand before your first sit down with them will help you put your business into perspective for them, which will only make the design process and ultimate implementation smoother.
Even if you choose to design your warehouse or DC in house, data analysis must play a role in your planning if you are to have a successful design build. By making sure you have the relevant data on hand, you ensure that you are one step closer to success than if you tried to begin without it.