Allocation teams operate in one of the most decision-dense environments in retail. Thousands of SKU-store combinations, multiple inventory constraints, and constant demand shifts make it difficult to determine where attention will have the greatest impact.
Even with detailed forecasts and granular data, allocators often face a practical challenge: not every decision carries equal weight, but many tools treat them as if they do. The result is decision overload — time spent reviewing low-impact items while higher-risk issues remain buried
It raises the question: how can allocators quickly identify which decisions matter most for margin, sell-through, and inventory health? The answer begins with confronting the double-edged sword of modern data.
The challenge of acting on granular data
Modern allocation processes are highly detailed by necessity. Decisions are made at the SKU-store or size-location level, where small adjustments can significantly affect outcomes. But that same level of granularity can make it difficult to see broader patterns or prioritize effectively.
Common challenges include:
- Time pressure: Reviewing every recommendation in detail is impractical, especially during in-season execution.
- Limited visibility: Issues such as broken size curves or over-allocation risk can be hard to spot across thousands of combinations.
- Missed strategic signals: A focus on individual SKUs can obscure trends that span products, stores, or categories.
Without a way to distinguish high-impact decisions from routine ones, allocators are forced to rely on experience, intuition, or reactive firefighting. This is where a strategic shift in mindset becomes critical. Instead of attempting to give every detail equal attention, leading retailers are adopting a proven methodology for focusing on what truly matters.
Applying 80/20 logic to allocation decisions
Leading retailers increasingly apply 80/20 thinking to allocation workflows. Inspired by the Pareto Principle — the idea that a small subset of inputs often drives the majority of outcomes — this approach helps teams concentrate effort where it delivers the greatest return.
In an allocation context, this means identifying the subset of SKU-store decisions that are most likely to influence revenue, margin, or inventory risk. Instead of reviewing every recommendation equally, allocators can prioritize exceptions, patterns, and outliers that warrant attention.
How prioritizations are actually made
In a typical in-season cycle, allocators are responsible for thousands of SKU-store combinations, all requiring decisions at once. Reviewing each one manually isn't realistic, especially when inventory risk and margin exposure are highest.
Anaplan's Allocation and Replenishment Planning application applies an 80/20 approach by automatically surfacing the decisions that matter most. Instead of treating every inventory decision equally, the system flags a focused subset of allocations that drive disproportionate impact. These may include fast-moving items at risk of stockout, key sizes falling below service thresholds, stores deviating from plan, or products with growing markdown exposure.
This immediately shows allocators why an item is flagged and what action is recommended, allowing them to focus their time on high-impact exceptions while lower-risk decisions continue without manual intervention. Because these signals are consistent across products, locations, and time periods, broader patterns become easier to identify.
By applying this methodology, allocators spend less time reviewing low-value noise and more time applying judgment where it has the greatest financial and service-level impact, especially during peak periods when responding quickly to changes is most impactful.
Leveraging data trends for everyday execution
Beyond improving day-to-day efficiency, 80/20 prioritization helps allocators recognize larger patterns that would be difficult to see when reviewing recommendations one by one. Anaplan's Allocation and Replenishment Planning application allows prioritization to be applied across multiple levels of the inventory hierarchy, including:
- SKU-store level: Highlighting issues tied to specific products, sizes, or locations.
- Store or product level: Revealing broader patterns that affect multiple SKUs or stores.
- Category or network level: Surfacing systemic risks or opportunities that require coordinated action.
This layered visibility helps allocators more effectively determine whether an issue is isolated or part of a broader trend. Instead of reacting to individual exceptions, teams can make informed adjustments at the appropriate level — whether that means correcting a single allocation, recalibrating a store strategy, or revisiting category-level assumptions. This ability to move from granular fixes to strategic adjustments unlocks significant benefits for both individual allocators and the business as a whole.
The impact on allocator productivity and outcomes
When allocation teams can focus on the decisions that drive the majority of impact, several benefits follow:
- Reduced decision fatigue: Time and attention are directed toward high-value actions.
- Faster execution: Teams spend less time searching for issues and more time resolving them.
- Improved margin protection: Early identification of risk supports better inventory placement and fewer markdowns.
- Stronger alignment: Allocation decisions are easier to communicate and justify when priorities are clear.
Prioritization frameworks reinforce human judgment, allowing allocators to apply expertise where it matters most.
Looking ahead: Prioritization as a core planning capability
As assortments grow more complex and planning cycles accelerate, the ability to prioritize effectively will become even more critical. Retailers that treat all decisions equally will struggle to keep pace. Those who embed focus into their allocation workflows will be better positioned to respond to demand shifts and protect profitability.
80/20 prioritization is not a shortcut. It’s a recognition that in a complex retail environment, focus is a strategic advantage.
