The situation I was solving
Uniform allocation caps made execution consistent but could not reflect differences in category demand, product depth, full-price performance, channel potential, stock cover, or broken-size risk. Historical share also risked reproducing the limits of past allocation.
Read the underlying principle: Inventory allocation is a decision product, not a fixed rule. →What becomes better
A governed decision product can improve availability and full-price sell-through while reducing avoidable markdown exposure. It gives operators a clearer basis for dynamic allocation and captures exceptions as evidence rather than hiding them outside the process.
How I work through it
I mapped the current allocation journey and terminology, identified data and decision gaps, and defined requirements across launch velocity, sell-through, full-price versus discounted demand, retail/e-commerce comparison, stock cover, dynamic caps, explanations, overrides, and outcome measurement.
Go deeper: A decision system beats another dashboard. →What I carry forward
Allocation intelligence should not replace commercial judgment. It should make the evidence, rule, uncertainty, and exception visible enough for judgment to improve the next decision.
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