Question: Month Passengers Jan - 2 0 1 3 4 4 1 7 1 8 Feb - 2 0 1 1 9 4 2 2 2

Month Passengers
Jan-2013441718
Feb-2011942221
Mar-2014670996
Apr-2014286844
May-2014537314
Jun-2015906101
Jul-2017362586
Aug-2016969528
Sep-2014010920
Oct-2013599030
Nov-2012919746
Dec-2014289105
Jan-2113970077
Feb-2112230963
Mar-2115447435
Apr-2114507038
May-2115516063
Jun-2116487702
Jul-2117954910
Aug-2117786357
Sep-2114408817
Oct-2114374254
Nov-2113258104
Dec-2115182616
Jan-2214470077
Feb-2212730963
Mar-2215947435
Apr-2215007038
May-2216016063
Jun-2216987702
Jul-2218454910
Aug-2218286357
Sep-2214908817
Oct-2214874254
Nov-2213758104
Dec-2215682616Case Study: North London Airport Hub
Your line manager has presented you the passenger data from 202022 shown in Table 1.
Currently the airport is forecasting the passenger numbers using 2Month Moving Average
method. Your line manager is concerned that this may not be the most appropriate and accurate
method of forecasting for the company. She is proposing that the airport moves to 2Month
Weighted Moving Average method of forecasting with the weight of 0.7 for the most recent
period and 0.3 for the older period. She is also interested in finding out which method of
forecasting you would select for the company [N.B. You must select one of the forecasting
methods covered in the module].
She wants you to analyse the available data (shown in Table 1) and produce a short report (2,000
words \pm 10% excluding figures, tables and references) that include relevant tables and figures to
fully address the issues listed below. Your report needs to consider three different methods of
forecasting; current model, model proposed by your line manager and a model you have selected.
Your aim is to identify a forecasting method that is most appropriate for the North London Airport
Hub.
Include the following in your report:
1. Analyse the data given to you. How does the data behave? What patterns are present in
the demand? How do you know? How is this relevant to selecting a forecasting model?
Support your analysis with appropriate tables and figures.
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MGT2221 & MGT2222 Operations Management; 202324
2. Generate the forecast for 202022 using the current model. Analyse the results. Is
appropriate forecasting model being applied? Why/why not? Discuss. Support your
analysis with appropriate formulas, tables and figures.
3. Generate the forecast for 202022 using the model propose by your line manager. Analyse
the results. Is this appropriate forecasting model for the company? Why/why not? Discuss.
Support your analysis with appropriate formulas, tables and figures.
4. What forecasting model would you use? Justify the model you have selected. Why do you
think this is the best forecasting method for the company to use? Generate the forecast for
202022 using the model you have proposed. Analyse the results. Support your analysis
with appropriate formulas, tables and figures. [N.B. You must select one of the forecasting
methods covered in the module]
5. Determine the forecast error for the current model, the model proposed by your line
manager and the model you selected. Explain and justify the method you have used to
calculate the forecast error. Analyse the results and compare the three forecasting
methods. What are your key observations? How could you use this information when
selecting the method of forecasting? Support your analysis with appropriate formulas and
tables/figures.
6. Provide two key recommendations for the company, i.e. what action should they take and
why. You must deliver your recommendations from the analysis you have conducted in this
report. Justify your recommendations.
7. Discuss the role of forecasting and the implications of forecasting accuracy to operations of
the airport. Why is forecasting important and how might passenger forecast be used by the
airport? Consider some of the operational issues covered in this module.
8. Cover page, table of content, introduction, conclusions and list of references.

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