Demand Forecasting in the Fashion Industry : The Shift to AI-Based Methods

Demand Forecasting plays a crucial role in the management of operations, especially in the Fast-Fashion Industry, in which demand can be very volatile and lumpy due to frequently changing customers tastes and the development of technology. However, demand forecasting is essential for optimizing the inventory levels efficiently, assisting with predictions of upcoming cash flow, and allowing business managers to know when they need to increase staff and/or other resources. Demand forecasting is a very popular research topic in the fashion industry which has recently undergone some major developments. As the world moves forward into the digital age, a trend in forecasting research in the fashion industry is noticed. Since many previous studies has been done in this area, this thesis will be an extended study to the previous research done. In my thesis, I aim to analyze and cluster demand forecasting methods and approaches in previous research which have been recently going through an obvious trend and direction towards a more digital supply chain and automated forecasting methods. Next, I aim to first address the developments in the fashion industry and link the previous forecasting methods to the current market features. Current existing challenges and barriers will be identified in order to be able to propose future research areas and framework in demand forecasting in the Fast Fashion Industry