SKUlike

SKUlike is a concept used in inventory management and data analytics to describe items that are treated as similar for planning and analysis, rather than requiring a separate stock-keeping unit for every variant. A SKUlike group combines products that share core attributes, such as category, supplier, price band, or functional similarities, so they can be analyzed collectively while still maintaining a link to underlying SKUs for traceability.

By aggregating around SKUlike groups, organizations can stabilize demand signals, reduce noise from sparse data, and improve forecasting, assortment planning, replenishment, and pricing decisions when SKU-level detail is impractical.

Implementation typically involves defining similarity criteria, choosing which attributes to group on, and establishing governance rules. Techniques range from rules-based groupings to automated clustering or machine learning models that assign SKUs to SKUlike clusters. It is important to preserve links to individual SKUs and maintain audit trails.

Benefits include improved statistical power, faster analysis, and more robust planning in markets with high SKU counts. Trade-offs include potential loss of product-specific nuance and the risk of overgeneralization leading to stockouts or mispricing if groups are too broad.

Examples include grouping fashion items by fabric and silhouette rather than by every color, or consolidating household goods into SKUlike families by function and size rather than by brand.

SKUlike relates to master data management, product information management, and demand planning methodologies that balance granularity with analytical stability.