The restaurant “Au Canard Truffé” opened over seven years ago in Sarlat, a town in the Périgord
region in the South West of France. The restaurant has become one of the best in the area.
Management has concluded that in order to plan better the growth of the restaurant in the future, it
is necessary to develop a system that will enable them to forecast food and beverages sales by month
for up to 6 months in advance. They have available data on the total food and beverage sales that
have been realised since they opened on 1 February 2010. These data (sales in thousand pounds) are
provided on Blackboard (Excel File CW_2019-20_Part2_Q2). Assume we are now in November 2019.
a) Plot the data as a time series
b) Analyse the data for seasonality. Include the seasonal indices for each month, and comment on
the high seasonal and low seasonal sales months. Do the seasonal indices make intuitive sense?
Discuss.
c) Forecast sales for November 2019 to April 2020 using decomposition method with trend
projection. In order to compare the results obtained with those of other methods, compute the
mean error (bias), the mean absolute deviation (MAD), the mean square error (MSE), and the
mean absolute percentage error (MAPE) of the forecasts.
d) Forecast sales for November 2019 to April 2020 using the decomposition method combined with
Holt’s method [you should attempt to determine the smoothing constants and that minimise
the MAD].
e) Plot the errors for each method as time series. Comment on these graphs and compute
autocorrelations if necessary.
f) Make recommendations as to which forecasting system/method should be used. Justify your
answer.