An electronics retailer was in need of assortment and space management upgrades, as the processes were defined manually and empirically for each category of products.
In spite of the ever-increasing business complexity and of the shorter products’ lifecycles, we found an opportunity to improve data analysis processes, underlying processes, and monitoring practices.
In order to succeed, we clustered stores based on their sales profile and predicted capabilities for new stores based on exogenous characteristics (e.g., income of potential customers). Regarding assortment, the forecast of the products’ sales potential was based on their attributes’ value (i.e., estimating, for example, the utility of each inch in a TV), and final product selection took into account sales potential and cannibalization effects.
As for space allocation, we based our strategy on an optimization of categories return, considering space elasticity.
By creating a tailored Decision Support System with monitoring dashboards, we successfully delivered new, leaner, and analytical-driven processes for assortment and space management.
Moreover, the overall reliability of the process was enhanced because it became less dependent on the planners preferences.
