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Usually manufacturers plan a lot of promotions during the festive season. As you all must have seen a lot of offers, occupying almost half your newspaper.


There is a lot of analysis which goes behind this and the manufacturers run what is called “Trade promotions”.

There is a planned budget for trade spends which include advertisements and other  promotional events. Discounts are announced as well.

The promotion, to be effective, should be planned in such a way that it should achieve the required sales volume and an overall planned profit aided by the above promotional strategies.


Here is where predictive analysis with HANA can do wonders. Using the historical sales data over a number of years for this product, we can predict the sales volumes for a location for this year. Using different forms of exponential smoothing predictive algorithms, prediction can be done based on time series. While predicting, the trend factor should also be considered to get an accurate prediction. The information from social media can be processed to arrive at a trend pattern for the product and an approximate percentage increase this year. HADOOP would be a preferred concept to work on this big data.

The next challenge will be whether the company can manufacture this kind of a volume within  a given time frame. Here is where project management solution with prediction makes a difference. To manufacture this product, several vendors will be supplying the raw materials and services to the manufacturer.  Applying predictive algorithms on historical records of purchase orders and Goods receipts, we can decide as to which of the vendors would be reliable and accordingly predict the best delivery time.

Manufacturers can have multiple plants producing the product. Using historical cost posting records and including the shipment costs, we can do prediction as to which plant will produce the product with least costs and within the stipulated time.

Thus, with predictive analytics, effective and efficient trade promotions can be planned end-to-end, right from planning to production.


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