Descriptive and Predictive Analysis

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Descriptive Analytics is about describing the historical performance. By applying these techniques to the level of performance, information can be very specific to product, customer, channel, supplier and other key operational areas of focus. This will help validate data to be organized and be used in a repeatable process, in order to have confidence in the information and to make it actionable. This will help companies to evolve from “standard cost to serve” approach to “total cost to serve” approach thus identifying immediate cost and revenue opportunities and take confidant action to utilize them. Prescriptive Analysis is about identification of optimum business outcomes by combining historical data, mathematical models, variables, business rules, constraints, anticipated customer requirements, machine-learning algorithms. It is also used when experimenting in the real world would be very expensive or overly risky, or require too much time. Many airline ticket pricing systems use this analytics to sort through complex combinations of travel factors, demand levels, Supply constraints and purchase timing to present potential passengers with prices designed to optimize profits at the same time maintaining the sales levels. Predictive Analysis is about predicting the future, unknown events, failure points based on statistical techniques. Predictive analytics enable Demand Driven Value Networks (DDVNs) through segmentation, demand sensing and shaping, and profitable response. This will help to transform the SCM model that was earlier based on aggregate information, averages and generalized models into a customized response based on the basis of unique characteristics of customers, products or suppliers or any other supply partners.... ... middle of paper ... ...services to market. The Digital Supply Network is connected to the end consumer. As companies sell products, information can be shared across the supply chain, helping retailers and manufacturers keep an eye on inventory. And as customers seek information about products or services they buy, companies can have information more readily at their fingertips to reassure the socially responsible consumer about how something was made and the raw materials that were sourced. Physical assets such as plant and equipment will remain central to manufacturing as of now but these can be intertwined in the Digital Supply Network, which is empowered by mobility solutions, the cloud, social media and analytics & big data. Following are few of the complex areas where digital supply chains can provide astonishing result and help organization overcome the persistent challenges.

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