With limited budgets, tight margins, and declining foot traffic, it became increasingly difficult to understand why some locations significantly outperformed others and where the organization should open new stores.
We recognized that the organization needed a data-backed framework for validating location decisions. Our solution needed to account for the thousands of factors that impact sales as well as in-kind donations that serve as the pipeline of goods sold in the thrift stores. In other words, we needed to include data to inform both the supply and demand sides of the equation not only to understand past performance but also to predict future successes and failures.
Within the first month, over 300 reports were generated. Moreover, the tool aided in identifying underperforming stores and facilitated lease agreement negotiations with property managers for existing locations.