Forecastingapplications Edited

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Highline Financial Services, LTD. Case Study
To produce demand projections for the next four quarters for all three goods (A, B, and C) for
Highline Financial Services, Ltd., we will study past trends and select appropriate forecasting
methodologies for each Product. We will also go over the advantages of employing a formalized
approach to predicting these products.
Demand Forecasting for Products A, B, and C:
1. Product A:
The data shows that Product A experienced some fluctuations over the last two years, but there is
no distinct seasonal trend.
A basic Moving Average approach may be appropriate, given the absence of evident seasonality
and the rather consistent trend. We can forecast using the average demand for Product A during
the previous quarters.
Year 1
Year 2
Year 3 (Forecast –
Moving Average)
Quarter
Product A
Product A
Product A
1
60
72
80
2
45
51
82.6
3
100
112
98.5
4
75
85
85
This strategy was chosen because it smoothes out fluctuations and accurately forecasts future
demand.
2. Product B:
Product B has experienced more substantial fluctuations over the last two years, with no
noticeable pattern or seasonality.
Due to the erratic fluctuations, an Exponential Smoothing approach may be appropriate for
forecasting. It prioritizes current data, which might catch unexpected changes in demand.
Let’s assume an alpha value of 0.3.
Year
Quarter

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