The perfect forecast for cycling

This research aims to find the best way to improve the process of forecasting at Company X, which is a company specialized in the development of cycling accessories. Demand patterns at the company are highly dynamic, contain strong seasonality and show a clear trend. Moreover, during the previous years, the demand has risen since Company X has expanded its business to multiple other countries and numerous new retailers come to do business with Company X. These are some of the aspects that make forecasting at Company X a difficult task. With a lead time of four months, which became six months during the research, a more accurate forecast is desired in the future to minimize costs and maximize delivery reliability. In this research, multiple time-series models have been tested and evaluated based on the demand data of 2020 as well as 2019, since 2020 showed a remarkable demand pattern due to COVID-19. Also the innovations of using customer forecasts and pre-ordered products have been taken into consideration. With the chosen solution and the innovations, Company X could improve their process of forecasting.