# Petrol Case

1128 words 5 pages
MC1-009-I

PETROL
Original written by professor Pablo Pedro Melero Perlado at IE Business School. Original version, 14 January 1998. Last revised, 27 May 2008. Published by IE Business Publishing, María de Molina 13, 28006 – Madrid, Spain. ©1998 IE. Total or partial publication of this document without the express, written consent of IE is prohibited.

A company specializing in the distribution and sale of petroleum products is studying opening up a branch in Taraland, a new emerging market located in the antipodes. Given the significant investment required in ports, pipelines and service stations, the Board of Directors believes that a better understanding of future demand in the market and the variables affecting it is essential before
By the way, in order to do this, he had to make a long-distance call (paid for out of his own pocket) to his friend Pepa, who is a chemist, who told him that the density of petrol is 0.75 kg/litre. Encouraged by his progress, before sending his report back by e-mail, Pepe wants to show off his skills as an analyst by performing a simulation which uses the same regression model but where the price is not a parameter, but rather a variable with a normal probability distribution given as:
This document is one of the copies authorized for use only in GMBABL-ENG – MARCH 2013 by IE BUSINESS SCHOOL

Price probability distribution (€/litre) in the year 21: Average maximum: minimum: 70 90 50

In addition, Pepe knows that in a tourist location like Taraland much more petrol is sold in the summer than in the winter. So, he has obtained the following quarterly data in order to expand his annual estimate with a three-month estimate that takes this seasonal variation into account and allows the Logistics Department to do its job.
YEARS 1 QUARTER I II III IV 2 I II III IV 3 I II III IV 4 I II III IV CONSUMPTION thousands of tonnes 1360.7 1502.1 1619.4 1408.4 1483.7 1614.1 1761.6 1535.7 1574.6 1741.9 1891.6 1644.9 1701.4 1852.5 2039.5 1780.7

2

YEARS 5

QUARTER I II III IV

CONSUMPTION thousands of tonnes 1799.4 1993.8 2181.9 1898.0 1887.6 2057.1 2284.5 1997.7 1948.3 2162.6 2384.8 2075.1 2045.0 2231.1 2498.8 2187.7 2022.8

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