Forecasting, Supply Chain, and Planning in the Airline Industry

Forecasting Techniques in Airline Industry

1.Air passenger numbers are affected by school holidays, major sporting events, advertising campaigns, competition behavior, etc. Holidays often do not coincide in different countries, and sporting events sometimes move from one city to another.
Which forecasting techniques do you think should be used in calculating Air Passenger Forecast? Time series models? Causal models? Qualitative models? In causal modeling, what types of independent variables might be used? Justify your answer in detail.

2.Describe three qualitative forecasting techniques and compare their strengths and weaknesses.
2.1.Explain how the Airline business could benefit from using qualitative forecasting techniques. Provide examples to illustrate your explanation.

3.The Supply Chain of an Arline Company has to ensure that the goods are available not just at the airline’s own hub, but at every place that scheduled flights depart from, all over the world. In the right quantity, at the right time, every time, with minimum cost to the company.  Supplies may include Blankets, Headphones, Paper napkins, Cutlery, Wine, Pre-packaged dinners, and Water, all with the goal of affecting a passenger’s perception of the airline.
Explain, what is a collaborative planning, forecasting, and replenishment (CPFR) system and how might it benefit those who choose to use it?

4.What is the purpose of S&OP and what takes place at the strategic, tactical, and detailed planning and control levels?

5. Describe the differences between level, chase, and mixed production plans

6.Describe how both top-down and bottom-up planning work, and the situations where one approach is superior to the other. Provide an example of each approach (when they can be used) in relation to the topic described in the case study.

7.Problem – Forecast:
Using the from the table below, Develop 3 different forecast models for Periods 19 through 24
a.Forecast # 1: Use 2 period moving average model forecast
b.Forecast # 2: Use 3 period moving average model forecast
c.Forecast # 3: Use Exponential Smoothing Forecasting model

Calculate the MFE & MAD and APE for Periods 19 through 24  (n = 6) for all 3 Forecast.
Show all your manual calculations and formulas on the last page.