Planning use
Feeds SKU-level signals back into a simpler category-level inventory model.
Method
A practical inventory planning note on SKU-level seasonality, seasonal buckets, and simpler category-level planning logic.
Planning use
Feeds SKU-level signals back into a simpler category-level inventory model.
Overview
In inventory planning, it is tempting to assign one seasonal pattern to an entire category. In practice, that can be too coarse. Products in the same category may follow different demand curves across the year.
That creates a planning problem: category-level seasonality is simple, but product-level behavior is often what actually drives inventory risk.
The method starts by calculating a seasonality index at the SKU level rather than relying only on category averages. Products can then be grouped into seasonal buckets based on similar patterns.
The point is not to create the most complex model. It is to keep the planning logic simple while making the seasonal signal more realistic.
Method
Estimate seasonality at the product level first so each SKU can reflect its own demand pattern across time.
Group products into a smaller set of seasonal buckets so the result stays usable for business planning instead of becoming too fragmented.
Map those patterns back into category-level planning logic so teams can use a cleaner operational framework without ignoring product differences.
Why it matters
This method is useful when you want a planning model that remains explainable but still captures real variation inside a category. It is a practical middle ground between one-size-fits-all averages and overly complex forecasting systems.
Teams can keep a clean planning framework without pretending that every product in a category behaves the same way.
I treat this as an example of a broader pattern in operations work: build a model that is simple enough to use, but structured enough to support better decisions.
Source
This page is a cleaned-up portfolio version of an earlier note.
View original markdownRelated
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