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Delivering every second washing machine ordered online to our customers the next day requires very precise demand forecasts. But deciding which of the nearly 12 million customers will buy one of the 10 million products defines a whole other level of complexity. My presentation will focus on the real challenges that come into play when implementing such a solution, while recalling basic limitations of forecasts and emphasizing important lessons learned.
As Senior Expert BI for Forecasting at OTTO, Gabriel Orsini is responsible for business services around automated demand forecasts, inventory management and stock projections. This includes requirements engineering, responsibility for the business architecture and the coordination of the implementation teams.
Gabriel has a background in distributed systems and machine learning, and has worked as a business analyst for nearly fifteen years designing and implementing planning and forecasting processes and solutions with a focus on the retail sector