Replenishment and demand forecasting in the fashion industry are fraught with many challenges - high volatility of trends, short product life cycles, long lead times, and more. Does this mean that applying artificial intelligence to these areas is a mission doomed to failure? No, although the path to achieving business goals through AI is not always clear.Download e-book
Key challenges in the fashion industry in the context of demand and sales forecasting
Among them are the volatility of fashion trends, seasonality, the problem of inter-store transfers and long lead times.
Ways to improve forecast quality while automating
Although predicting future business events in the fashion environment is not the easiest thing, it makes business sense. Artificial intelligence and Machine Learning can cope with frequent collection changes and upcoming fashion trends.
Replenishment strategies in the fashion industry
Thanks to advanced data analysis, it is possible to better predict demand in a given channel, as well as to dynamically allocate goods within different channels.
Click and download the e-book (PDF file) to learn more about how AI and ML are supporting the fashion industry in achieving a competitive advantage.