Bulgari Demand Planner

Bulgari's demand planning process relied on Excel spreadsheets shared across teams, leading to version conflicts, formula errors, and delayed forecasting. As a luxury brand with long production lead times, inaccurate demand forecasts directly impacted inventory costs and missed revenue from stockouts.

Built a custom Demand Planner web application with React frontend and .NET Core backend. The system featured collaborative editing with conflict resolution, ML-assisted forecast suggestions based on historical sales data, and integration with their SAP inventory system. Led a team of 4 developers through the full product lifecycle.

Forecast accuracy improved 20%, inventory carrying costs dropped 15%, and manual adjustments decreased 40%. The collaborative editing feature alone saved the planning team an estimated 10 hours per week previously spent reconciling spreadsheet versions.