Grocers face a number of strategic decisions when considering the move from manual to automated e-grocery fulfillment. One that often doesn’t get enough attention is determining what products can be put into the automation system and what products are best picked manually. This may seem like a tactical rather than strategic decision, but how it is handled can have a huge impact on the productivity and efficiency of e-grocery fulfillment processes. Using decision criteria that leverages the strengths of the automation system can increase the number of products available for automated picking by 40%.
Establishing Decision Criteria
When we work with grocers early in the automation process, it’s not unusual for them to have already identified the product categories they want to automate and those they believe are best handled with manual picking. Their criteria for making this decision are generally based on how products are traditionally segregated in the warehouse for temperature control, safety or security reasons. Those products, they believe, should be kept out of the automation system in the same way they are segregated in the distribution center.
But, when we align individual SKUs to the categories they’ve identified, we find that up to half of all SKUs have been excluded from the automation system—often without good reason.
Instead of using broad product categories to decide what to automate, the best practice is to evaluate each SKU based on criteria specific to the automation system, not the layout of the traditional distribution center. These criteria include the size of the product, its temperature requirements and its cubic volume velocity.
Some products, such as a broom or a large bag of charcoal briquettes, simply won’t fit in the automation storage bins and these can be excluded quickly. Others, such as frozen foods, may require additional investment to automate and the business case for that investment can be evaluated based on the percent of basket of these products. Particularly in micro-fulfillment centers, it usually doesn’t make sense to automate frozen food picking.
However, beyond those two disqualifying factors, inclusion in the automation system should be based solely on a product’s cubic volume velocity—the combination of its size and sales velocity. Products with a high cubic volume velocity can be most efficiently picked manually while all other products should be considered for automation.
Here’s an example of how that can work. Rather than deciding that all fluid milk should be picked manually, a grocer and their automation partner should evaluate each SKU within the category based on cubic volume velocity. What they’ll likely find is that a large number of specialty milks can be most efficiently fulfilled through automation while the top sellers, such as gallons of whole and 2% milk, will have a sufficiently high cubic volume velocity to be picked manually. In this case, including the majority of products in this category not only increases efficiency but automates compliance with business rules around expiry or lot code date.
The same philosophy applies to alcoholic beverages. Are these products more secure waiting in an open aisle to be picked manually or within the automation system where they are inaccessible until ordered? As for household cleaners and similar products, which need to be isolated from food products, the automation system actually does this more effectively than store shelves. The AutoStore bins seal themselves in the stacking process and create a physical, impermeable barrier between these products and other products in the system. Even if spills or leaks were to occur, the damage would be limited to a single bin containing similar products.
Vendor-managed inventory may be excepted for an entirely different reason: established processes in which non-store personnel handle product stocking. But, if these products fit within the cubic volume velocity threshold identified for efficient automated picking, as most likely will, stores can work with their vendors to change these processes and have vendor-managed inventory delivered to the fulfillment center in the same way it would be delivered to the distribution center.
A final exception that should be evaluated is products sold by weight. Depending on the percent of basket these products represent, it may prove more economical to integrate weight capture into the design of the pick station rather than to pick these products manually. Of course, this doesn’t have to be an all-or-nothing decision; weight capture can be a part of both automated and manual picking.
Evaluating each SKU based on its size, temperature requirements and cubic volume velocity can have a major positive impact on the success of an automation project, regardless of the distribution architecture or automation technology being employed.
Using broad product categorizations to determine what products are “appropriate” for automation, a grocer may mistakenly find that half of all SKUs will be automated, and half picked manually.
When SKUs are individually analyzed based on automation-specific criteria described in this post, the percent of products being picked through automation can increase from 50% of SKUs to 70%. Considering that automation systems typically have pick rates 5-7 times higher than manual processes, the addition of 40% more SKUs to the system can dramatically impact productivity and order fulfillment times—and create a better foundation for future growth.
Learning From Experience
The lesson here is clear: don’t put up barriers to automation before you have to. Automated storage can provide safe, secure and date-managed fulfillment for a much broader range of products than many grocers realize and that can increase the return on your investment in automation technology. To learn more about our process for determining what to automate, contact Swisslog.
In the next post in our series, we’ll explore the upstream effects of micro-fulfillment centers on distribution centers and how to mitigate them.