Forecasting Remaining Inventory and Seasonal Trends
Fabrice Decroo
Director of Consulting
August 17, 2026
End-of-season clearance sales are never a surprise: they are a sign of a missing or insufficiently reliable forecast of remaining inventory, prepared too late.
The combined cost of stockouts and excess inventory reached approximately 1,730 billion dollars worldwide in 2025 (IHL Group).
End-of-season inventory clearance comes as no surprise: it’s the visible result of a forecast that failed to anticipate, several months in advance, how much inventory would remain to be sold. Forecasting remaining inventory turns a decision made in a hurry into a well-prepared one.
Clearance sales begin months before the markdowns
When a category manager discovers at the end of the season that 30% of inventory remains to be sold, the problem didn't start that week—it began at the time of purchase or production, based on a sales forecast that turned out to be overly optimistic. Clearance sales are not the cause of the problem—they are a symptom of a missing or insufficiently reliable forecast of remaining inventory.
Forecasting remaining inventory essentially involves answering this question even before the sales season begins: If sales follow the expected trajectory, how much will remain to be sold by the deadline?
The Overall Cost of Poor Planning
The scale of the problem across the industry has been documented. According to IHL Group, an analytics firm specializing in retail inventory imbalances, the combined cost of stockouts and overstock reached approximately $1,730 billion globally in 2025, representing nearly 6.5% of global retail sales.
estimated annual global loss, resulting from a combination of stockouts and excess inventory —approximately 6.5% of global retail sales (IHL Group).
Excess inventory—half of this problem—is directly linked to inadequate forecasting of remaining inventory: without a reliable estimate of what will remain to be sold, end-of-season markdowns become deeper and occur later than they should have.
Seasonality: The Least Well-Accounted-For Variable
Seasonality isn't just about "it sells better in the summer." Three factors must be distinguished; otherwise, any forecast of remaining inventory will be skewed:
- Seasonality of the category: the expected sales pattern over the course of the year, specific to each product family.
- One-time events —such as sales, holidays, and unusual weather—that temporarily shift demand without changing the underlying trend.
- A trend shift: a lasting change in purchasing behavior, as distinct from a normal seasonal fluctuation.
Confusing these three dimensions is the most common mistake: treating a trend deviation as a simple seasonal variation delays the decision to write off inventory, until the remaining inventory becomes too large to be sold under favorable conditions.
How to Build a Reliable Forecast of Remaining Inventory
Start from the history, category by category
Develop a typical seasonal sales curve for each product family, covering several years if historical data allows.
Project the remaining sales pace
Based on sales already made at the start of the season, project the likely sales trend through the deadline.
Estimate the likely remaining inventory
Compare available inventory with the projected sales trend to estimate, several weeks in advance, how much inventory will remain to be sold.
Initiate markdowns proactively, not reactively
Use this forecast to activate the planned markdown schedule—see our article on the markdown schedule.
What This Means in Practice
A reliable forecast of remaining inventory does not eliminate the need for markdowns—it simply changes the timing of the decision. Instead of discovering a problem at the end of the season and rushing to correct it with the deepest possible markdowns, the retailer anticipates the shortfall several weeks in advance and can apply more measured markdowns, spread out over time, with a significantly less severe impact on margins.
Before the next end-of-season clearance sale
- Do I have a forecast for remaining inventory before the peak of the sales season?
- Can I distinguish between normal seasonality, a one-time event, and a trend deviation?
- Does this forecast trigger any action, or is it just a single number?
- Did I compare my residual forecast from last season with the actual results to adjust the method?
Frequently Asked Questions
The questions we're asked most often before getting started.
This is an estimate, prior to the end of the sales season, of the amount of inventory that will remain unsold by the deadline if sales continue on their projected trajectory.
Because it combines three distinct phenomena—normal seasonal patterns, one-time events, and sustained trend shifts—that are often confused with one another.
From the start of the sales season, using the first few weeks of actual sales to project the trend.
No, but it allows for a more gradual and evenly distributed price reduction over time, rather than a sudden, drastic discount later on.
Sources: IHL Group, study on global retail inventory distortion — ihlservices.com · Booper product data (GENIUS Predict module, sales forecasts, and seasonal scenarios).
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