Introduction
When conducting analyses in the pre-project phase, one of the main problems is at what level the demand for storage space should be covered by a private warehouse, and from what level it should be covered by external space (colloquially: surface area).
The problem is not new, and several methodologies for solving it have already been developed.
The author focuses on one of them, presented for the first time in Polish sources by Prof. Danuta Kisperska-Moroń and Prof. Danuta Kempny, as well as by Prof. Stefan Abt.
In this study, it was decided to trace the methodology presented by the aforementioned authors on a more complex example. The complexity of the example lies in finding the optimal solution for a multi-year investment horizon. The added value for the reader will undoubtedly be certain guidelines that can be applied in a spreadsheet to find the optimal solution more quickly. This article is the second in a series of three articles. The financial aspect, which appears in the title, will be developed in the next article.
Procedure
STEP 1 Collection of historical data providing the basis for determining the trend forecast and determining seasonality indicators. It is important that there is sufficient data of adequate quality. Due to the secondary nature of the forecasting thread, the author does not focus on the correctness of the size and quality of the statistical sample itself. He only signals that such a step should start the entire procedure.
STEP 2 Breaking down annual forecasts regarding the demand for storage space using the seasonality coefficients calculated and presented in Tab. 2.
