MARRIOT ROOM Forecasting Case Solution And Analysis, HBR Case Study Solution & Analysis of Harvard Case Studies

Marriot Room Forecasting Case Solution

Quantitative Analysis to determine whether to accept the tour company reservation of 60 or not:

The qualitative analysis is made on the basis of forecasting by using exponential smoothing, Holt winter’s method and regression.

Exponential Smoothing Method:

The graph below shows the forecasting has been made with demand of the reservation by using the exponential smoothing, which is considered as a good technique for time series data. In this method, two filters have been used as exponential window function such as alpha of 0.8 and alpha of 0.05. The alpha at 80% shows that the forecast has been made by considering the past factors, demand of historic data, and expectation to increase the reservation. On the other hand, the alpha of 0.05 shows the deferral of the demand,which can be missed due to some unconditional factors.

The alpha shows the level of series for the smoothing constant specific value.It is normally taken as one and zero, here, the alpha value is taken as 80% and 5% for fulfill and deferral of demand respectively and then used to generate the forecasts for future fluctuation of demands and to decide whether to make reservation for 60 tourists or not.

Regression Method:

It is very a beneficial method to forecast by assuming the predators or variables as in the case of demand, economic climate is used as indicator.The family of the regression analysis is widely used in order to predict the values from the given indicators. The indicator is used as the predictor from which the demand is predicted.

The results from the regression analysis show that the demand can be predicted from the indicators. Here two factors have been taken to calculate the forecast of the upcoming demand, which includes intercept taken as minimum value that is 1073.14 and slope that is taken as the coefficient obtained from the estimators.

The intercept is the value that reflects the minimum demand from the regression analysis. The intercept is the value that reflects the demand by taking all the other variables or the indicators equal to zero.

The slope is also known as the coefficient value of the variable that is derived from the indicators, the slope or coefficient value of 30.96 shows with every increase in the indicator value by one, the value of the demand will also increase by the 30.96. The graph below shows the forecasting value has been increased than demand that shows that the company’s demand would increase more than it is expected.

Accuracy Analysis

There are number of factors that were calculated in order to identify the accuracy and the reliability of the forecasted values calculated by the different models.

The unbiased is calculated in order to examine the accuracy in the forecasted demand. The unbiased stat is calculated in order to know the minimum variance from the estimated variances. The errors are calculated by the subtraction of the forecasted demand from the actual demand. The mean error is the calculated average of all the errors in the forecasted values from the actual demand. The mean error from the regression analysis is calculated as the -1110.94 and the mean error calculated from the Holt’s Winter Method is negative 19............................

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MARRIOT ROOM Forecasting Harvard Case Solution & Analysis