Developing Forecasting System with Zachman Approach

Abstract

Big data nowadays can provide unique insights into, market trends, demand and supply forecasting, stock retribution, sales scoring profile, stock redistribution with purpose benefit into lowering cost and enabling more efficient business decision. The article addressed the use of Zachman Framework to address challenges, and for successful implementation of Big Data Optimization. The article takes the case study in Astra International subsidiary such as Auto2000, an automotive dealer company that faced some challenges in inflexibility and complexity with handling stock and demand forecasting. The article applies the advantages of big data and combined with Zachman approach to address the transformation from business perspective into IT operation. The article addresses the role of brand principal to cut inefficient cost. The objective of this article to examine the use of Zachman approach with assistance of big data, and its analytic tools in the area of machine learning to investigate the user requirements how to predict the efficient the 3-month stock demand and allow stock planning optimisation at Country and Branch level through business flow understanding.