Turning Customer Insights Contributing to Vmi Based Decision Support System in Demand Chain Management

Thus Demand chain management (DCM) is emerging as an innovative concept of managing the supply chain. A typical business analytic service is expected to sense trends and insights from data, then model ‘what if’ scenarios to support better decision-making from the insights derived. It should also be able to deliver short term strategic engagements consistently for long term managed services. Rather than focusing merely on supply chain concept as a forward chaining approach, Demand-chain as a backward chaining strategy initiatives focus on better ways to capture the demand signal close to the source, analyze the demand to sense the latest and most accurate demand signal and shape the demand by executing and tracking promotional and pricing strategies to steer demand in line with business objectives. VMI is an efficient replenishment practice designed to enable the vendor to respond to demand without the distortive effect of purchasing decisions in the retail chain. Therefore the objective of this paper is to focus on how to turn customer insights into Vendor-Managed Inventory based Decision Support System in Demand Chain Management especially with the support of state-of-the-art information communication systems and technologies. It concludes by saying that there is a need of adopting innovative management methodologies such as CRASP management methodology and the need of working on adding semantics to big data analytics based decision support system to enable semantic decision making capability to better derive and realize the strategic value of the business.