The peak-season playbook for fewer out-of-stocks

Last month, we discussed why traditional resets don’t hold up the way they used to. December makes that problem impossible to ignore. Demand surges, picking increases, and a shelf that looked fine at 9 a.m. can be empty by lunch. In this issue, we’re breaking down what to fix first to prevent holiday stockouts, and the practical changes that protect on-shelf availability when everything is moving faster. Buy Online, Pick Up In Store (BOPIS) quietly turns a “normal” store into a hybrid showroom and fulfillment center, creating constant micro-resets and new pressure on assortments, labor, and space planning.

This month’s question is the one every retailer and supplier feels in their bones:

If BOPIS is pulling product off the shelf faster than ever, how do we protect on-shelf availability and keep out-of-stocks under control?

A shelf can look healthy at 9 a.m., then a burst of online orders hits, and by lunch, you’ve got holes, substitutions, and the classic “the system says it’s here… somewhere” scavenger hunt. Once you’re stuck in that cycle, micro-resets become micro-misses: missed sales, missed loyalty, missed labor hours.

So let’s break down what actually helps, starting with a simple reframe.

The new definition of “in stock”

In a BOPIS environment, “in stock” is no longer a single answer. It’s three separate truths (that may often disagree):

1. System Availability = What the inventory file says
2. Physical Availability = What’s actually in the building
3. On-Shelf Availability = What a shopper can actually grab right now

BOPIS stress-tests the gap between these. When they drift apart, out-of-stocks spike, substitutions rise, and store labor gets dragged into exception handling. The secret to staying ahead is early detection and fast correction, using better signals and smoother workflows.

5 strategies that reduce out-of-stocks

1. Improve inventory accuracy and visibility

Start with the basics, because they still move the needle:

• Centralize inventory across in-store, ecommerce, BOPIS, and ship-from-store so stock levels reconcile in real time.
• Use cycle counts (not just annual counts) to reduce drift between what’s in the system and what’s on the floor.
• Add RFID where it makes sense for faster, more accurate tracking.
• Turn on automated low-inventory alerts so teams discover issues before the shelf is already empty.

If inventory accuracy is shaky, planograms and shelf capacity planning become “best guesses” – which rarely survive store velocity.

2. Sharpen demand forecasting

Forecasting fails when it treats demand as a uniform entity. BOPIS demand functions differently than walk-in demand. Our previous issue emphasized the necessity for retailers to differentiate between customer types and their purchasing patterns.

Tactical improvements:

• Use historical sales and seasonality, but layer in omnichannel behavior shifts.
• Explicitly adjust for promotions, because stockout rates can spike when items go on sale.
• Use advanced forecasting and AI tooling where possible to reduce errors and lost sales from stockouts.

In general, improved demand forecasting leads to more proactive decisions regarding replenishment and safety stock.

3. Optimize fulfillment and logistics

If you are using stores as fulfillment nodes, then fulfillment processes directly affect shelf health.

• Maintain safety stock buffers for volatility, especially for items that swing hard with online order spikes.
• Improve store ops with a warehouse management (WMS) mindset, monitoring pick/packing, identifying bottlenecks, and reducing exceptions.
• Use omnichannel strategies like ship-from-store or curbside pickup thoughtfully to balance pressure between the backroom and the floor.

If staging areas and pick paths aren’t planned, they will “steal” space from high-performing categories, and then you get the worst of both worlds: worse shopping and worse fulfillment.

4. Strengthen supply chain management and planning

Traditional supply chain performance metrics were often “good enough” when stores primarily served walk-in shoppers, but peak-season demand exposes every weak link. Focus first on building resilient supplier relationships – communicating disruptions early, tracking and optimizing end-to-end lead times, and diversifying supply for key items to reduce single-point failure risk.

5. Turn supply updates into early action

The fastest way to reduce stockouts is to stop finding out too late. Delivery status signals can flag late or short shipments early, enabling teams to predict store-level risk, prioritize replenishment, and adjust labor to match what is actually arriving.

This is the difference between:

“We had an out-of-stock” (past tense) and “we’re going to have an out-of-stock unless we intervene” (actionable)

The best retailers connect the whole chain

There’s a bigger opportunity hiding in plain sight: if warehouse picking and truck building are aligned to common store layouts, you can create store-ready pallets or totes that speed replenishment and reduce in-store chaos. Even unloading sequences can be optimized so the store can move product to the floor with less wasted motion. This is the “end-to-end” view: macro space + planogram + warehouse operations + delivery + store execution, all pulling in the same direction.

Don’t forget in-store execution

Even with perfect forecasting and perfect trucks, the shelf still depends on humans doing the work at the right time.

The strongest approach is proactive tasking:

• Alerts based on inventory, shelf capacity, sales rate, and last stocking activity
• Predicting when a shelf hole is likely to appear
• Triggering restock tasks before a customer finds the gap

A simple checklist to bring to your next OSA conversation

If you want a quick gut-check on whether your organization is set up for BOPIS-driven OSA pressure, ask:

1. Do we measure on-shelf availability separately from inventory accuracy?
2. Can we distinguish walk-in demand vs BOPIS demand at store level?
3. Do we have leading indicators (delivery ETAs, partials, forecast deltas), not just lagging OOS reports?
4. Are store teams getting proactive tasks, or just reacting to holes?
5. Does our space planning reflect fulfillment realities, like staging, pick paths, or is it still designed for a pre-BOPIS world?

If you answered “no” to more than one, you’re not behind. You’re normal. But you’re also sitting on a lot of recoverable sales and labor hours.

BOPIS didn’t break the shelf. It revealed the shelf’s weak points.

BOPIS is reshaping what we know about retail space planning. It pushes retailers into constant micro-adjustments, and it forces a new standard for inventory truth, forecasting, and execution. Organizations that connect data signals to real workflows and connect supply chain reality to store-level space decisions can protect availability without burning out store teams. Let’s stop treating out-of-stocks as a surprise and start treating them as a solvable prediction problem. Let’s shift our perspective on out-of-stocks from viewing them as unexpected occurrences to recognizing them as a challenge we can address through effective forecasting and planning.