Management of supply chain: an alternative modelling technique for forecasting

Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in viewof the great strides made by research and the increasing abundance of data made possible by automatic identificationtechnologies, such as radio frequency identification (RFID). The relationship of various parametersthat may change and impact decisions are so abundant that any credible attempt to drive meaningful associationsare in demand to deliver the value from acquired data. This paper proposes some modifications to adaptan advanced forecasting technique (GARCH) with the aim to develop it as a decision support tool applicableto a wide variety of operations including supply chain management (SCM). We have made an attempt to coalescea few different ideas toward a ‘solutions’ approach aimed to model volatility and in the process, perhaps,better manage risk. It is possible that industry, governments, corporations, businesses, security organizations,consulting firms and academics with deep knowledge in one or more fields, may spend the next few decadesstriving to synthesize one or more models of effective modus operandi to combine these ideas with otheremerging concepts, tools, technologies and standards to collectively better understand, analyse and respondto uncertainty. However, the inclination to reject deep-rooted ideas based on inconclusive results from pilotprojects is a detrimental trend and begs to ask the question whether one can aspire to build an elephant usingmouse as a model.