Read this article and share your thoughts on: How is Data Analytics transforming Supply Chain? Share your thoughts in less than 600 words. Reference: The landscape of supply chain analytics Product design Supply chain design A. Sales, inventory, and operations planning Supplier risk management and Inventory projection and Forecasting accuracy incoming goods projection scenario planning evaluation and optimization B. Sourcing C. Production D. Warehousing E. Transportation F. Point-of-sale G. Consumer Cost modeling Scheduling of Picking zone/ Real-time routing Out-of-stock Credit rating to to identify energy-intensive warehouse space and ramp detection and define payment cost drivers production allocation allocation at prevention terms offered Quantification Statistical Worker to warehouses Shelt space . Retum projection of benefits from quality control picking zone Delivery optimization to calculate spend pooling and tolerance allocation based scheduling in line Channel/store outstanding Automatic optimization on efficiency with consumer allocation of inventory analysis of capabilities Automatic stock patterns goods maximizing Product . contract Lot sizing and relocation in high Cleansheet cost service recommendations compliance scheduling bay storage areas modeling Retail employee based on Aggregate considering Cleansheet cost Dynamic routing scheduling purchase history demand/supply cost, inventories modeling Fraud detection balancing and capacities Workload optimization McKinney Company Source: KLU research report "Supply Chain Analytics --Gaining value from data-based decision making