In the case of the Hamilton hotel, Snow needs to make a decision as to if 60 additional rooms reservations should be accepted which could lead to overbooking (Weatherford & Bodily,1990). It is a problem of capacity utilization that is being faced in this particular case where revenue maximization is aimed while minimizing customer dissatisfaction.
In this report the case is put forward and various methods have been chosen to come to a sensible conclusion. Firstly the raw data provided is used and the exponential smoothing model (ESM) is used to predict the outcome of guests on Saturday the 22nd of August. Next basic statistics are used and standard deviation is calculated with which the …show more content…
Data Analysis and Forecasting: Choice 1
By combining the raw data given as per figure 1 one can deduce three groups by utilizing the most recent data for model validation, middle for fitting, and oldest for starting values. One can see irregular and indeterminable data patterns if the raw data is viewed graphically (Weatherford & Bodily,1990). Once the base, index, and trend starting values are examined through multiple ESM methods, the basic ESM forecasting method is used to make Tuesday afternoons forecast for the next weeks demand starting Saturday through Friday.
As seen in figure 2 of the four options, Basic, Trend, Seasonal, Winter’s forecasting model (Weatherford & Bodily,1990), the Basic model gives the lowest mean absolute percentage error on placing the adjusted pickup ratio data. The difference between demand and forecast is shown in Figure 3. Next a model validation is done to forecast Saturdays adjusted pickup ratio.
The adjusted Pickup Ratio