Demand forecasting in the apparel industry
Moisanen, Jenni (2014)
Moisanen, Jenni
Metropolia Ammattikorkeakoulu
2014
All rights reserved
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2014052910961
https://urn.fi/URN:NBN:fi:amk-2014052910961
Tiivistelmä
The relatively recent trend of offshore sourcing in the apparel industry has led to long production lead times due to which companies operating in the field need to buy products months in advance their sale. This has increased the importance of demand forecasting in the apparel industry. The latest literature presents hundreds of forecasting methods and measures which leave companies with the difficulty of choosing the correct one and applying it in an appropriate manner.
The aim of this thesis is to investigate demand forecasting in the apparel industry through two parts. The theory section introduces the most relevant concepts comprehensively and the case study utilizes the findings in order to select and endorse the most valid forecasting measure and method.
The case study section of this thesis was conducted in co-operation with a global apparel company, which in the public version of the thesis will remain anonymous. The company’s demand forecasting method was evaluated and measured through weighted absolute percentage error calculations which indicated a need for improvement in forecasting. Two improvement suggestions were introduced: 1) standardize the existing judgmental forecast method which is most suitable for the company by applying the presented five principles, and 2) enhance the agility of the existing supply chain.
The aim of this thesis is to investigate demand forecasting in the apparel industry through two parts. The theory section introduces the most relevant concepts comprehensively and the case study utilizes the findings in order to select and endorse the most valid forecasting measure and method.
The case study section of this thesis was conducted in co-operation with a global apparel company, which in the public version of the thesis will remain anonymous. The company’s demand forecasting method was evaluated and measured through weighted absolute percentage error calculations which indicated a need for improvement in forecasting. Two improvement suggestions were introduced: 1) standardize the existing judgmental forecast method which is most suitable for the company by applying the presented five principles, and 2) enhance the agility of the existing supply chain.