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Use of Predictive Analytics in Supply Chain

Predictive analytics uses several techniques to analyze past events to make predictions about future. One of the areas where this technology can be applied is forecasting in supply chain management. The biggest challenge that companies today face is accurate demand forecasting. This can be determined to a certain extent if technology and analysis can help determine customer's usage, spending and behavior. For example, predictive technology can help determine the number of customers that would come to a coffee store based on the current temperature. This can be arrived at through data collected in the past where similar temperatures were recorded. Based on this analysis the number of staff can also be increased/decreased .  Apart from plain predictive models, predictive technology can be used to prepare decision models to take logical decisions based on a number of factors involving many variables. For example, in the case above, the other factors/variables that can contribute to the computing the number of customers arriving at the store could be the day of the week (weekday or weekend), the time (morning, afternoon, evening), current brand value of the products sold, type of customers etc.
One of the other challenges that companies face today is the customer retention. Today companies respond to customer attrition on a reactive basis and not on a proactive basis. With the proper use of predictive analytics, patterns can be obtained on reduced customer spending, usage and behavior that can help determine the probability of attrition of a particular customer. Such customers should be attended to and their grievances should be addressed. Additionally such customers could be offered some discounts and lucrative offers to retain them. Predictive technology can also help to increase in cross sales or sell additional products to customers. For example, notifications can be sent to customers to ask them if they want to repeat their orders close to festive occasions like Christmas, Valentine 's Day etc. based on their past orders.  Another challenge that companies are facing today is the increased competition with competing companies. Predictive analytics can help determine the correct product version and the timing of the product to be launched to have a competitive advantage over competitors. This can be done by analyzing the impact of a previous version upgrade and the new product version should be targeted at customers based on the customer responses to a competing brand upgrade/model.  I would further discuss on this technology and its application to supply chain in my subsequent blogs.

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