SaaS tool for retail range and shelf-space planning

A retail client needed a way to plan and adjust their product assortment across hundreds of stores, but the only tool available was a static, one-way Power BI proof of concept: numbers in, a single fixed output, no way to explore alternatives or see the trade-offs of a decision. This was my first engagement with Scalene, and the brief was to work out what a real product for this problem would need to look like.

I started by mapping the end-to-end business process across the store network and worked with the business and engineering teams to agree on a shared vocabulary for the model. From there I led the design of the ranking criteria and selection strategy logic driving the backend optimisation engine: how commercial and customer-relevance metrics combine into a ranking, and how rules like prioritising breadth, setting minimum requirements, or protecting specific nodes decide which items survive when a store can't fit the full range.

With the model logic defined, I captured the visualisation requirements at every level of the hierarchy (network, cluster, store and item) then explored and tested a wide range of visual concepts (tables, tile grids, lane views, bar charts, shelf diagrams, geographic maps) against those requirements to find the formats that actually worked. I mapped the detailed interactions the target user would need (adding, removing and comparing items against the existing range) then built high-fidelity wireframes and a clickable prototype, producing short demo clips to walk internal and external stakeholders through how the tool would work.