I am occupied with hierarchical demand forecasting (mainly about consumer packaged goods) and i have a question about the interpretation of its structure.
Let us assume that the hierarchy is as follows:
Total Demand for the Company --> Product Categories --> Products (SKU) --> Customers.
Let us assume that the product categories are chocolate, yogurt, and biscuits. The total demand for the company one time period could add up to e.g. 10,200 units of products that are not related e.g. 5000 units of yogurt 200gr 2%, plus 2000 units of yogurt 300gr 4%, plus 1000 chocolates 200gr, plus 1000 chocolates 80 gr, plus 500 units of chocolate biscuits 250 gr, plus 700 units of cocoa biscuits 300gr. In the top level of the hierarchy I end up adding irrelevant things and the aggregation does not make any sense. What is the business value of knowing that the demand is 10,200 units of irrelevant products?
In forecasting software the hierarchical facilities are very common and also a lot of vendors support reconciliation capabilities. What I don’t understand is the interpretation of aggregating different things in an upper level of the hierarchy.
In some cases aggregation makes sense. E.g. in a tourism forecasting application the hierarchy could be Europe --> Country --> Prefecture. If we assume that one unit=one tourist (person) then the aggregation makes sense. But what about in the case of consumer packaged goods?