We use a structural model of unobserved components to perform modeling and seasonal adjustment of the Spanish sales time series. This model, complemented with a suitable dynamic-regression pre-processing, provides a flexible although parsimonious way to handle the complex nature of daily time series.

We will briefly present the modeling approach as well as the main results when applied to the total sales data as an example that represents its application to the breakdown of daily sales data (~25 supply-side components).