Supply Chain Masterclass Series Part 2 Managing Products with Seasonality and Trend: Decomposition Analysis
Where datasets, as identified in Masterclass Part 1, are
highly trending and seasonal, it’s important to know how to Isolate the true randomness of the data, which is the art of decomposition. Find out how to do this in Masterclass Part 2.
About this Whitepaper
In the first Masterclass of this series entitled ‘3 Magic Numbers for Demystifying Demand Patterns’, we explored how the mean, gradient and standard deviation can reveal much about demand patterns. These statistics are the bedrock of a number of supply chain processes, such as safety stock calculations and relative performance measurement. However, the statistics cannot be taken at face value where datasets are highly trending or seasonal. In these instances we need to distinguish true randomness from identifiable seasonality and trend. Removing the trend and seasonality to isolate the true randomness is the art of decomposition
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