Retailers and wholesalers invest heavily in technology, people, processes, and data to create relevant assortments across channels. While technology and vast amounts of data help localize assortments based on consumer preferences, product attributes, and store performance, it's impossible to complete the assortment planning process down to the most granular level of size. The ability to manage millions of size and store combinations is burdensome, not scalable, and not precise. Valuable time and effort is spent creating detailed, insightful assortments only to marginalize those assortments by applying corporate averages of size selling for the purchasing and distribution of sizes to locations. The result is missed opportunity: disappointed customers, lost revenue, and lost profitability due to missing sizes and markdowns on abundant sizes. This paper shows how retailers and wholesalers can transform historical sales data into true size demand and determine the optimal size demand profile to use in the purchasing and allocation of products. You do not need to be a data scientist, statistician, or hold a PhD to augment the business process with approachable analytics and optimization to yield game-changing results!