Replenishment Readiness Playbook
An operator playbook for size-level replenishment: the masking diagnostic, the allocation decision matrix by fleet profile, and the signal-hygiene rules.
What this playbook is
Most apparel planning teams have an allocation policy and a replenishment policy. Very few have a written, operator-grade playbook that connects them at the size level — the layer where full-price revenue is actually made or lost. This is that playbook.
It is designed for Planning Directors, VP Merch, and Allocation leads who are either (a) deploying AI-assisted replenishment for the first time and finding it surfaces inefficiencies they did not know they had, or (b) running size-level replenishment already and looking for a rigorous diagnostic, decision, and governance framework to codify it.
Everything below is operational. No abstractions, no reference architecture diagrams — frameworks you apply to your next receipt plan, decision matrices you use on your next allocation call, and a governance model you can stand up inside a single planning cycle.
Why size-level is the unit of analysis
Product-level KPIs are the default reporting layer for almost every apparel planning team. They are also where size-level demand problems go to hide. A style with a 70% sell-through, a sub-20% markdown rate, and a clean weekly sales curve can still be materially broken — if the core sizes stocked out on day two and the 70% sell-through was the composite of fast-moving core depletion followed by slow-moving fringe residual at full price.
The business cost of not surfacing this is threefold. First, next season's buy repeats the same size curve and reproduces the same ceiling. Second, replenishment decisions trained on the product-level signal over-replenish the residual fringe sizes and under-replenish the (already-empty) core. Third, the markdown provisioning at season end is calibrated to the wrong base case, so the finance partner is repeatedly surprised.
Every framework below sits on this foundation: size-level is the resolution at which apparel planning decisions are actually correct or incorrect. Everything aggregated up from there is a summary view, not a decision input.
Framework 1 — The 8-point size-level masking diagnostic
Run this diagnostic against any style flagged as a "healthy" performer. Each tell is independent; two or more firing on the same style indicates the product-level sell-through is masking a size-level problem.
Tell 1 — Day-2 or day-3 core-size stockout. A core size (typically the S/M/L block that carries the bulk of category demand) reaches zero on-hand within 72 hours of first receipt. On a correctly-curved buy, core sizes should sell through across roughly the same window as the full range, not ahead of it.
Tell 2 — Residual concentration in top and bottom sizes. At end of selling window, 80%+ of remaining units are in XS/S or XL/XXL. Fringe-size residual on a nominally successful style is the single most reliable size-curve error signal.
Read the full report.
Industry analysis for apparel brands — where planning processes break down, and the practical implications for your own planning process.
- How mid-market apparel brands typically structure OTB, assortment, and in-season planning
- Specific process gaps that drive markdown and inventory risk
- What high-performing planning operations do differently
- Practical implications you can apply to your own planning process
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