Digital Transformation & Forecast Collaboration -- A Case Study on Fashion & Sports Industry

This thesis focuses on a company in the fashion and sports industry to examine how an AI-driven planning tool can facilitate digital transformation and improve collaborative demand planning in a complex supply chain. The study explores the challenges and results of moving from manual, Excel-based forecasting to an integrated, AI-supported planning system through a qualitative case study of a multinational corporation deploying ToolsGroup SO99+. The study relies on observations, interviews, and internal documents. It identifies both enabling factors like senior leadership support and cross-functional collaboration. It also discusses important organizational and technical barriers like data silos, lack of forecast ownership, and integration challenges. In order to improve service levels, forecast accuracy, and responsiveness, the study emphasizes the significance of probabilistic forecasting, real-time data integration, and structured demand collaboration. The adoption of SO99+ promoted cultural changes toward data-driven planning and shared accountability, despite partial automation and a continued reliance on manual overrides. In addition to providing a benefit-readiness framework to direct future digital transformation initiatives in environments that are similarly complex and multichannel the thesis ends with strategic recommendations for enhancing planning maturity.