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Demand forecasting in textiles to reduce overstock - a case study

Updated : October 2020

Stakeholders

  • Marketing or sales professionals
  • Retailers or wholesalers
  • Textile industry sustainability professionals

Predicting sales accurately is challenging in the textiles industry, however, it is crucial for brands to offer sustainable customer services, manage the supply chain activities and prevent overstock. This case study discusses the key concepts of demand forecasting, challenges involved and recommends some sustainable measures to implement the same.

It involved a detailed literature review to understand some of the prominent ideas followed by the brands and a case study to enable a footwear brand implement similar sustainable measures. Some of the prominent techniques for forecasting include qualitative, time series, causal and quantitative methods. For the case study, a detailed primary discussion was carried out to analyse the present forecasting methods, their benefits and challenges and suggest suitable measures from the literature study.

Results showed that qualitative forecasting methods need to be well-structured to minimize challenges involved and techniques like quick response systems should be developed to ensure sustainable supply chain practices.


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Topics

Demand forecasting in textiles

Textile sales prediction for overstock reduction

Qualitative forecasting in textiles

Time series forecasting in apparel

Causal techniques for textile demand forecasting

Quantitative apparel sales forecast

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  1. Demand forecasting in textiles to reduce overstock - a case study
Geography
| Global
Year

2014

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