For retailers, peak holiday shopping season is like the Super Bowl of logistics, a high-stakes showdown of long-lead forecasts and rigid inventory bets.
Although retail sales are projected to grow as much as 3.7% in 2025 reaching $5.48 trillion, traditional peak season strategies anchored in static forecasting and planning are quickly becoming insufficient. Indeed, in a world defined by fluctuating markets, supply chain volatility, and rapidly shifting consumer expectations, retailers must rethink how they plan and execute their inventory management.
In today’s environment, agility is the new currency of success, and the top performers this coming peak season won’t be the best forecasters. It will be the dynamic retailers who can treat inventory as an ever-evolving variable – and react accordingly – who come out on top.
Static planning vs. dynamic demand
The traditional approach to peak season was to map out inventory for Q4 far in advance, as early as the summer. But a lot can change in 6 months. In reality, the old “forecast early, execute later” model leaves retailers at the whims of unpredictable factors – weather patterns, macroeconomic jitters, viral trends, and geopolitical disruptions can all reshape demand in real time.
Instead, modern peak season strategies must evolve from fixed plans to dynamic playbooks, not reliant solely on historical data but rather on real-time insights that inform allocation, replenishment, and fulfillment.
Foresight is still important, but the shelf life of plans is shorter than ever.
Inventory as a performance lever
Inventory is often thought of in terms of risk. Too much, and you’re sitting on dead stock and markdowns; too little, and you’re missing out on potential sales. This binary thinking overlooks a key point – it’s not just how much inventory you have; it’s how smartly you move it. In our work with global retailers, those who excel during peak seasons share one trait—they treat complexity as a catalyst, not a constraint. Their edge comes not from better guesses, but from faster, smarter responses driven by real-time data.
Rather than over-committing to static plans, retailers must be able to allocate stock not based on averages, but based on localized demand, promotional lift, and the shifting behavior of consumers both on and offline. When inventory becomes a fluid variable, it serves as a lever for performance by improving retailers’ ability to move stock between stores, warehouses, and customers in response to ongoing demand.
Today’s leading retailers are those who rely on systems that allow them to respond to dynamic market changes in hours, not weeks. It’s not about holding more inventory – it’s about removing the bottlenecks that prevent inventory from flowing to where it can perform best. Powered by connected data, intelligent automation, and cross-functional coordination, this level of agility is what can turn peak season from a gamble into a calculated advantage.
Post-peak hangover
Every January, retailers confront the fallout from their holiday strategy – often in the form of bad outcomes like overstocks, steep markdowns, and eroded margins.
With a dynamic approach, bad outcomes become avoidable.
Consider the practice of overbuying – an all-too common occurrence when retailers give in to the fear of missing out on demand and potential customers. In many cases, this reality is actually the symptom of a deeper problem: inflexible inventory systems that lack the feedback loops needed to correct course midstream.
Real-time execution doesn’t just improve in-season performance, it reduces the drag that often follows. When you’re allocating and replenishing based on what’s actually happening and not what you hoped would happen, you limit exposure and preserve margin into the following quarter.
AI as the enabler
So, how exactly can retailers make this critical shift to dynamic peak season performance?
AI is at the front line of this evolution. But it’s important for retailers to remember that AI alone is not the strategy: It’s the engine that powers a smarter, more adaptive one. Its promise is only realized when it enables better decisions at the ground level.
Accordingly, retailers should seek out AI systems that leverage micro-data to understand how demand fluctuates daily, across channels and by location. This allows for nuanced real-time decisions – such as allocating new inventory to stores with the highest probability of full-price sell-through or adjusting replenishment frequency based on traffic, not timelines.
Research shows that embedding AI in distribution can lead to 20–30% reductions in excess inventory, 5–20% lower logistics costs, and 5–15% savings in procurement spend.
The goal is to take planners' operations to the next level and augment plans with tools that turn overwhelming complexity into real-time clarity.
Fulfillment engine
As peak season traffic surges online and in person, brick-and-mortar stores are evolving from mere sales outlets into local fulfillment hubs – stocking, sorting, and shipping products directly to customers or neighboring locations to meet demand with greater speed and flexibility.
This adaptability allows retailers to localize inventory decisions, reduce dependency on centralized distribution centers, and meet demand with precision.
Adobe data predicts that buy-online/pick-up-in-store (BOPIS) purchases will peak at 30–35% of all orders on December 22nd and 23rd. But for stores to take on this role effectively, they need clear visibility into stock levels, rapid inventory updates, and the flexibility to allocate product dynamically – not just based on sales, but on proximity to demand and real-time availability.
All peaks, no valleys
The importance of peak season will never change, but that doesn’t mean retailers’ approach to it should stay the same. Static, top-down strategies are giving way to decentralized, data-informed execution, where inventory is no longer just a spreadsheet to manage – it’s a tool for success.
Retailers who embrace the shift to fast, flexible operations and real-time execution will not only weather the consumer expectations and demand of peak season, but will storm proof their operations well into the future.
