This might sound extreme, but it’s exactly where we are today in supply chain. Agility and rapid fulfillment no longer fall into the “buzzword” category—they’re the expectations of your customers. The key to delivering next-day or same-day fulfillment effectively and profitably is cut differently for every business. But, moving inventory from Point A to Point B is (and will always be) critical to the speed of order fulfillment. And now more than ever, customers have a need for speed.
Shaking up traditional slotting and material flow, we’re seeing dynamic inventory slotting grow in popularity in many industries. Businesses effectively using this model reduce fulfillment time and optimize labor by rethinking their slotting and taking a demand-based approach.
Slotting – Then and Now
In the good old days when companies had a few days to fulfill an order, pallets and slots sat in static locations. Slot replenishment occurred as orders consumed inventory. It’s a model that favors large, bulk orders. But, the trends we’re seeing and the future of supply chain don’t fit this strategy.
The growing popularity of eCommerce’s low unit, high volume orders isn’t going away. On top of this, consumers are more unpredictable than ever. An item could be hot today, cold tomorrow—throwing a wrench in traditional demand and forecasting models. Also, many companies offer a broader range of SKUs than ever before. This proliferation in inventory typically results in a pick face that can’t accommodate every SKU.
To solve these challenges, we’re seeing companies look to their greatest asset: data. Vital information, such as real-time order trends and predictive demand, allow warehouses to prepare and optimize their pick operations. This affords optimizations such as:
- Allocating inventory to slots based on oncoming demand
- Prioritizing slots based on demand
- “Batching” SKUs in proximity based on shopping cart trends
This model, dynamic slotting, puts purpose and a strategy behind picking and replenishment. Categorizing pick faces and slots based on “hot” seasonal items and lower-demand SKUs also reduces traffic jams on the pick line and helps pickers move quickly through orders.
Applying dynamic slotting starts with great data from your warehouse management system (WMS). The system pieces together real-time demand, analyzes order trends and seasonality, and manages replenishment queues simultaneously. By assigning a smart, data-driven SKU to a slot, the WMS monitors consumption and restocks as needed. When orders fall below a threshold, it’s time to reassign that slot for a more popular item—factoring seasonality, promotions, and other trends into your slots.
Dynamic slotting goes beyond replenishment. We see companies like Amazon place suggestions on product pages based on items frequently ordered together. So, why not apply this to your pick face by batching frequently purchased items in adjacent slots? The data shows the trends for slot optimization, and your pickers reduce hunting and pecking to fulfill orders.
We’ve seen a few dynamic slotting models, and they generally fall into one of three categories:
- Basic: Warehouses with more traditional inventory management and pick lines assign a fixed slot for everything. But, the key difference here is that a warehouse will use dynamic slotting for ‘slow mover’ SKUs. An area of the pick face may be designated to low-demand SKUs and replenishment occurs on an infrequent, as-needed basis. There are marginal operational and time-saving benefits, but this model can preserve space on cramped pick lines.
- Mid-Level: A mid-level dynamic slotting model incorporates low- and high-demand SKUs. Designated areas of the pick face allow materials to flow based on real-time demand. For example, if 500 orders for a certain SKU recently hit the system, multiple dynamic slots will be assigned and inventory allocated. As inventory depletes from these slots, the dynamics are “self-cleaning” and the system reassigns those slots dynamically for future demand. This strategy helps with managing seasonal spikes and other high-demand events by flexing the pick face to accommodate consumer appetites while minimizing inventory allocation of low-demand SKUs.
- Advanced: A truly dynamic model performs slotting only based on demand. It’s all about staying one step ahead. This requires more than real-time data, as the WMS needs to provide trending and predictive data that anticipates material flow. This system requires an agile rules engine that constantly reprioritizes the pick queues based on order types and fulfillment requirements. Often, we see warehouse automation systems at play in these warehouses as the WMS, material handling equipment (MHE) and pickers act as one. Higher efficiency trickles out to the pickers and other warehouse workers as they’re not “replenishing for the sake of replenishing.” They move inventory strategically, and the data keeps operations flowing at a smooth clip.
A great example is Fox Racing, a motorsports manufacturer and retailer. Fox implemented dynamic slotting and designed its entire warehouse to streamline this model. By assigning types of items to an area of the warehouse, it relies on its WMS to figure out replenishment and prioritization. The WMS analyzes the pool of orders and compares it with the inventory allocated to the pick face. If the pick face inventory falls short of demand, a replenishment order goes into motion. Real –time prioritization is critical. The WMS continually reevaluates material flow and orders to ensure that replenishment always beats the pickers. This keeps all the ducks in a row to meet same-day or next-day delivery.
“We’re 100% dynamic now. Our operations and customers call for it,” says John Romero, Fox Racing Global Director of Distribution. “With a dynamic pick face and slotting, we cut replenishment labor by 10% and improved labor 15%.”
A Dynamic Future
The pursuit of perfection never ends; the rules keep changing. To keep up, it’s critical to look for innovations, process improvements and efficiencies wherever possible. With systems that encourage flexibility and adaptability, there aren’t enough Kardashians on the planet to put your supply chain on tilt.
It’s not always about making a multi-million dollar investment. Sometimes, it’s finding creative solutions. We believe that continuous process improvement (CPI) keeps the warehouse current and vital. Dynamic slotting is a proven strategy helping warehouses move faster and put purpose into picking and replenishing.
Richard Stewart is vice president of professional services at HighJump, a provider of supply chain management solutions. For more than 18 years, he has focused on helping customers across a variety of industries design and implement supply chain systems. Prior to HighJump, he was a principal of Vitech Business Group Inc.