4 - Using big data analytics to improve decision-making in apparel supply chains

Abstract

In the clothing and fashion industry, decisions must be made faster than in other industries because the accelerated pace of change in the consumer's life translates into the need for new apparel styles. It is important for managers to have the complete and correct opinions and feedback from their clients as soon as possible to make the right decisions. Big companies and even small and medium enterprises have their own information systems, which deliver sales reports, graphics, statistics, and forecasts. Also, they have an Internet portal for e-commerce and for communicating with their customers. But this is not enough. Data must be completed with the information circulating on social media, which could give the management another type of insight and would increase the competitiveness in the target field by improving the creative industry, the involvement of potential customers in style design, and in defining utility, quality, and comfort for new products. This chapter is structured into four sections to achieve our research objectives: first, an overview of the actual stage of Romanian clothing and fashion industry, and second, a study of competitiveness improvement in Romanian apparel using new information technology and communication technologies and a theoretical solution to explore social media information, considered as a significant factor in decision-making. In the third section is presented the Romanian clothing industry face-to-face with the economic crisis, as well as its slow but steady recovery since 2013. Also, this part is intended to provide several ways to increase the competitiveness in Romanian apparel and fashion on the international market, focusing on originality, quality, online commerce, and marketing. The fourth part includes the methodology and presents two evolving technologies, strongly connected, namely cloud computing and big data, and two important applications for social network analysis: Gephi and NodeXL. Also, in this section, we propose a model for integrating big data with an existing enterprise resource planning system, thus leading to a four-layer architecture based on a cloud-based Hadoop implementation. Finally, the chapter highlights the influence of big data on decision-making throughout the fashion supply chain and the points of view of all the actors involved.