Utilising Big Data Analytics for Enhancing Retail Sales Forecasting and Supply Chain Management

Author:

Mavutha Winiswa1,Buthelezi Makhosazane2ORCID,Mabotja Tshepo Phuti3ORCID

Affiliation:

1. Durban Univeristy of Technology, South Africa

2. Durban University of Technology, South Africa

3. Vaal University of Technology, South Africa

Abstract

Retail sales forecasting is challenging for demand planners, thus it's important to understand product and store predictions. Forecasts help establish a strategy to incorporate demand signals and start upstream supply chain actions. Retailers often have unique strategic orientations and managerial decision-making processes. Autonomy in demand forecasting can lead to biases and errors, especially when store promotional efforts are poorly communicated. Poor retail sales forecasting strains the distribution system, requiring an evaluation of infrastructure, automation, transportation capacity, and manpower. In a changing economy and technological advances, merchants must use new data to stay competitive. This chapter provides a big data analytics platform for manufacturers, distributors, retailers, and third-party logistics providers. The system will simplify supply chain management automated operating cost evaluation and optimization between distribution facilities and retailers.

Publisher

IGI Global

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