Demand Sensing at the Fulfillment Edge: Algorithmic Retail Physics

The sportswear leader is the world's largest sportswear company, with consumer digital as the front door to the brand. The strategic engine is their direct-to-consumer channel flywheel — their main consumer app, their sneaker launch platform, their fitness app, connected retail, and a hybrid wholesale-plus-digital channel model — running on a microservices-and-event-stream commerce architecture (their GraphQL commerce gateway, their event-stream database), a membership-centered consumer-data stack with hundreds of millions of members, and a digital fulfillment supply chain that has compressed cost-to-serve through forward-deployed regional inventory and warehouse robotics. Taller's engagement at this client has run continuously since 2021. Sourced primarily from Argentina and Brazil, the work spans the web personalization squad (Adobe Target plus React and Next.js on AWS), the native mobile applications behind their fitness app, their running app, and the B2B platform, the Java and Spring Boot commerce backend on AWS, and Mobile QA inside the sportswear leader's production release pipeline. Engineers operate as members of named squads — various named squads within the engineering organization — with recognition inside the sportswear leader's own performance and bonus programs.

Inventory-to-demand matching is the unit economics that determines whether digital growth is profitable. Mismatched inventory produces split shipments, lower-margin clearance markdowns, and reverse-logistics drag; matched inventory produces full-price sell-through and lower cost-to-serve. The legacy retail model treats inventory as a static plan; the strategic problem is converting fulfillment into a continuous decisioning process where every unit becomes a decision object — size, color, demand heat, channel eligibility, margin, delivery promise, return risk, node capacity, labor availability — evaluated at the moment of order.

The sportswear leader's fulfillment model is digital-first: a third-party predictive analytics platform powers demand sensing; inventory is forward-deployed to regional service centers on both U.S. coasts; ship-from-store and buy-online-pickup-in-store turn stores into fulfillment nodes; warehouse robotics — thousands of robots across distribution centers, with their flagship distribution center — automate the operations layer. Taller's same-client touchpoint on the fulfillment side is the North America Capacity team, a named squad where Taller engineers participate inside the sportswear leader's broader supply-chain engineering function. The broader Backend and data-engineering substrate Taller contributes to elsewhere in the sportswear leader engagement feeds the upstream operational data the fulfillment decision layer consumes.

Same-client contributor presence on the North America Capacity team and on the broader Backend and data-engineering substrate that feeds the fulfillment decision layer.

The sportswear leader's published fulfillment outcomes — their digital revenue growth of 100%+ in North America in Q2 fiscal 2021 with digital fulfillment cost per unit falling year-over-year; reduced fulfillment cost per piece on West Coast shipments; thousands of robots added across distribution centers; more than 10M units handled by the flagship distribution center robots that would otherwise have required manual labor; improved full-price sell-through — are the sportswear leader's outcomes earned by the sportswear leader's supply-chain engineering function, a third-party predictive analytics platform predictive-analytics integration, and the warehouse-robotics investments at the Memphis digital DC and the regional service centers on both coasts. Capability fit at this client's broader backend and data-engineering layer is real; same-client deployment on the fulfillment decision layer specifically is not in Taller's documented scope.