What you can learn from best-in-class grocery distributors

Grocery distribution is characterized by a unique set of challenges that make it a valuable case study for other sectors.

Foremost among these is the handling of perishable goods, which necessitates an extraordinarily efficient and time-sensitive logistics network to ensure freshness and minimize waste.

Additionally, grocery distribution must contend with high variability in demand, influenced by factors like seasonal trends, consumer preferences, and promotional activities, making accurate forecasting and responsive supply chain management crucial.

Inventory management in this context becomes a complex balancing act, requiring sophisticated technology and processes to maintain optimal stock levels and labor productivity rates.

The grocery industry’s focus on customer satisfaction and retention, driven by the need to consistently deliver high-quality products in a highly competitive market, further underscores the importance of an agile and responsive distribution strategy.

A process that we talk about a lot on this blog is slotting optimization.  While every distribution operation will have a process for slotting new items, consistently evaluating slotting performance and proactively re-slotting items based on capacity constraints, sequencing, fluctuating demand, and other factors has traditionally been unique to grocery environments – although, this is quickly changing.

We recently conducted a Strategic Opportunity Assessment aimed at uncovering efficiency improvement opportunities for a specialized powersport accessory distributor.

This distributor was an industry leader, but labor costs were high (and increasing) and they were running out of storage space. 

While these two challenges are very common in most operations, regardless of the industry, this distributor was missing one extremely critical practice – fixed slotting.  

As many grocery distributors know, fixed slotting is a foundational practice that not only gives you better inventory control, but also is a prerequisite for true slotting optimization.

Although this was not a seasonal operation (like many in grocery), items were not being assigned a designated pick slot based on requirements.  They were being put away in variable locations within a specific area of the warehouse, ultimately resulting in items taking up multiple locations.  In fact, it was found that 12% of the operation’s active SKUs were being picked from up to 7 different slots on average.

Besides impacting productivity, having items being picked from multiple locations creates inventory accuracy challenges and potential order errors.

Although other areas of improvement were noticed, a strong recommendation to establish fixed slotting was our starting point as, not only did it allow for us to optimally slot items based on requirements, we were also able to set up popularity-based zones using a detailed order profile.

Next, we evaluated the operation’s footprint, considering existing pick paths – the average distance per order was found to be about 431 feet – and storage equipment.  The operation was largely conventional but did have a pick-to-belt module where about 50% of the orders were picked.

A conceptual model was built with optimized slotting, and it was found that the operation’s footprint could be shrunk by about 26%.   There were a few things affecting productivity (mostly on the outbound side) but it certainly doesn’t help when your selectors are walking 26% further than they have to for most orders.

Now, where this differs from most grocery operations is that, while some operations do have velocity-based slotting areas (mostly to shrink the footprint for slower moving items), items still must be sequenced properly throughout the pick path to enhance picking productivity and, more importantly, reduce product damage and unstable pallets.  In this case, because of the smaller order size and low hit rate, popularity-based zoning was a viable option.

After putting together the concept – keep in mind that our assessments are all done through our fulfillment optimization system and leverage 4-6 weeks of operational data – we were able to back our recommendations up with a detailed analysis and quantified (and conservative) expected results.

Off the bat, by shrinking the footprint, the resulting reduction in selection travel would raise the overall paid picking productivity rate by 47%.   After factoring in current hours spent picking, this boost in productivity would equate to nearly $200,000 in savings per year for the operation.

An important consideration when implementing fixed slotting is that it does mean an increase in replenishment tasks.  In this case, it meant an additional 36 hours per week.

Even with that factored in, however, the net blended fulfillment rate was still expected to increase by 30%, which meant about $150,000 per year in net productivity savings.

While this strategy would require a slight process change, as well as a change to the WMS settings (fully supported by their current system), aside from the dollars saved, the operation would benefit from better capacity utilization (only 74% of the current footprint was needed), an increase in inventory accuracy and a reduced margin for mispicks.  

In terms of maintenance, optimized slotting and popularity-based zones do require it.  A fulfillment optimization system – another secret weapon of sorts used by those in Grocery distribution – is a perfect tool to ensure the strategy stays in place and items remain optimally slotted year-round.

If you’re interested in finding out more information about our Strategic Opportunity Assessments, or skustream, our Fulfillment Optimization System, click the links below.

Free Opportunity Estimate – Compare your warehouse productivity to your industry peers

Strategic Opportunity Assessment – See exactly how much time, movement, space, equipment and resources you’re wasting, and what you can do to stop it.