Five Seasons Case

Five Seasons is a manufacturer of all weather shoes. The company is particularly interested in monitoring the sales profile of one of its best-selling product families, the waterproof boots. In Table 1.1 the profile of the bimonthly sales registered for this item in the last three years is reported. Please note that, given the extremely special features of the concerned product, no sales are recorded in July and August hence data are grouped in five bimonthly periods every year.

Table 1.1 the bimonthly demand of waterproof boots (pair of boots/two months)

2013_01	2013_02	2013_03	2013_04	2013_05
1,230	2,140	3,210	1,300	1,080
2014_01	2014_02	2014_03	2014_04	2014_05
1,220	2,140	3,290	1,400	1,350
2015_01	2015_02	2015_03	2015_04	2015_05
1,250	2,800	3,560	1,450	1,120

Applying the time-series forecasting static method, please identify:

• The time-series systematic components affecting data
• The average seasonal factors for each period
• The forecasts for the first three periods of 2016

Notwithstanding the demand profile recorded in the last three years, the company is not 100% confident in the reliability of the sales history for the future potential demand of 2016. What tools and techniques could the company employ for supporting the generation of reliable forecasts for the next year in conditions of growing uncertainty?

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