yemenia focus 4 - breaking the rules

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Yemenia Focus (Issue No. 4) BREAKING THE RULES RIYADH OR KUWAIT OPERATION! By : Mohammed Salem Awad Aden Regional Director - Yemenia When I was student, there was a saying i.e "To Fit a Data is an Art" I think it is a fair statement if we refer to Ryanair forecasting graph at appendix no. 2. The constrains are fairly defined in the boundaries levels. While in practice the story is different, especially in the crises, the data cannot reflect the right pattern of model in peacetime. However, no doubts about the forecasting rules and its impacts in practice, usually airlines works on the typical patterned for the forecasting. Today the rules are changed, it is not a question of best fit of curve, and get higher score in a class, NO , really we are looking for some characteristics of the forecasting model, as base trend line and its variation in good time – seasonality index that develop some tangible and reasonable figure may work on it. Therefore, airlines operate to any destination based on the sound of the market, which will add revenue/profit to the network of the airline. However, it is a question of GO or NO GO first on papers before we invest for nothing or poor decision. We have two scenarios in such cases based on the request situation, 1- First, if the destination is a new one for the network, for the airline, we have to use Gravity Model. To evaluate the demand. 2- Second, while if this destination is existing one but we want to evaluate and compare it with another one due to our limited resources, then we have to study the historical data to predicate the right demand. (Our case study) The Problem: Due to Yemen crises, the operation from Aden is the economic one as Aden airport at a Sea Level. Therefore, a primary network is setup that includes Doha (DOH) and Kuwait (KWI) by top management of Yemenia in Cairo, the proposed table is shown

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Yemenia Focus (Issue No. 4) BREAKING THE RULES

RIYADH OR KUWAIT OPERATION!

By : Mohammed Salem Awad

Aden Regional Director - Yemenia

When I was student, there was a

saying i.e "To Fit a Data is an Art"

I think it is a fair statement if we refer

to Ryanair forecasting graph at

appendix no. 2. The constrains are

fairly defined in the boundaries levels.

While in practice the story is different,

especially in the crises, the data cannot

reflect the right pattern of model in

peacetime. However, no doubts about

the forecasting rules and its impacts in

practice, usually airlines works on the

typical patterned for the forecasting.

Today the rules are changed, it is not a

question of best fit of curve, and get

higher score in a class, NO , really we

are looking for some characteristics of

the forecasting model, as base trend

line and its variation in good time –

seasonality index that develop some

tangible and reasonable figure may

work on it.

Therefore, airlines operate to any

destination based on the sound of the

market, which will add revenue/profit

to the network of the airline. However,

it is a question of GO or NO GO first

on papers before we invest for nothing or poor decision.

We have two scenarios in such cases based on the request situation,

1- First, if the destination is a new one for the network, for the airline, we have to

use Gravity Model. To evaluate the demand.

2- Second, while if this destination is existing one but we want to evaluate and

compare it with another one due to our limited resources, then we have to

study the historical data to predicate the right demand. (Our case study)

The Problem:

Due to Yemen crises, the operation from Aden is the economic one as Aden airport at

a Sea Level. Therefore, a primary network is setup that includes Doha (DOH) and

Kuwait (KWI) by top management of Yemenia in Cairo, the proposed table is shown

2 2

in appendix no.1 . The past tell us the most successful destinations from Aden are

Jeddah (JED) and Riyadh (RUH) but unfortunately, they are not addressed in the

table. So how to come with right decisions to compare these destinations in numbers,

what are the basic rules to solve this problem, what is the right seasonality pattern of

these sectors, how many flight per month, and how many passengers per flight to be.

Basic Concept of Forecasting Model:

Forecasting is a unique science, very useful in practice, and use widely in many fields,

especially Aviation. Here we are concerning on

the application of Forecasting for Airlines, and

Airports. Airlines can define their seasonality,

and its impacts on operations and maintenance

programs, we have to define the right demand for

the right sector in the right segment. While most

of Investors in Airline Industry are concerned for

the performance factors that’s Traffic and

Capacity, RPM ,ASM , and Load Factor. They

are evaluated them by comparing their values in

past according to month-by-month approached.

Here we look forward, to the future to set targets. So forecasting is tilling us the future patterns for these factors, which

consequently, we can develop and forecast the expected Load Factor, which

means also define the future performance for airlines. There are many

methods of forecasting, but the approach of Max/Min Signal Tracking,

deliver the best scenario for the data that can be analyzed. No grey region,

just in a black and white / Good or Bad based on the constrains that we are

applied.

Objective:

The main objective of the study is to developed a solid base of data that may reflect

the future, yes the country in total mess, so we will not address the goodness of fit as a

main factor to accept the study, but we will work on

1- Averages Trend Line That Have A Zero Growth, and

2- Defining the Seasonality Index of Stable Period.

If these two steps are evaluated, then we can explore and extend the model to the

target period safely.

Basic Data:

The data are the number of passengers and cycles that reported by Aden airport.

Three basic periods are addressed:

1- 2008-2010 (Stable Period – Basically use for analysis)

2- 2011-2015 (Yemen Crises Period)

3- 2015-2016 (Target Period - Forecast)

Unstable Period Forecast Stable Period

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Analysis:

1- Riyadh Sector. (RUH)

Riyadh is the capital of Saudia Arabian Kingdom, it consider as the political and

commercial center in kingdom, it is located in middle of the kingdom closer to east

part. The sector can be represents by a normal pattern of airline seasonality model.

One operator dominate the operation the sector ADE-RUH i.e Yemenia (IY) and

operate a direct flights. The period of the analysis is 2008-2010. While the target

period is 2015-2016.

The analysis address the passengers and the cycles, so we can evaluate passengers per

flight.

- Passengers

- Cycles

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2- Kuwait Sector. (KWI)

Kuwait is gulf competitive hub for Asia continent, more closely to the northern for

Arabian peninsula, it consider an excellent gate that may serve European cities with

Fareast cities. but the operation to other side i.e to Africa needs a lot of investments,

yes Yemenia can operate on the bases of 3th

and 4th

traffic freedom but that operation

is not enough to run a feasible operation, based on the data base of 2008-2010 period,

which shows a poor traffic movements ended by stopping the operation to Aden

airport at half period, except those indirect flights, represents by 1 flights in the graph

for the purpose of the analysis. The analysis address the passengers and the cycles, so

we can evaluate passengers per flight.

- Passengers

- Cycles

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Results:

Riyadh Operation

Kuwait Operation

Conclusions:

The propose of study is to find a solid base that we can move forward, the concept is

to evaluate Flight/week, based on stable historical data (2008-2010), overriding the

crises period with a zero growth and reflecting the same seasonality index for the

target period (2015-2016). Using a typical forecasting model.

The results are fair; we use the same assumption on both cases for Riyadh and Kuwait

operation. Based on the result tables Riyadh destination is in a better position to serve

Aden, where there is a poor traffic flow for Kuwait.

Final word, to those who are seeking for a high forecasting accuracy please get my

presentation as shown in appendix No. 2.

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Appendix No. 1.

Operation flights to/from ADE:

SUN 13 SEP 15

IY649 A320 AMM 0800 ADE 1130 LT

IY852 A320 ADE 1230 DXB 1620 LT

MON 14 SEP 15

IY853 A320 DXB 1000 ADE 1200 LT

IY854 A320 ADE 1300 BOM 1930 LT

TUE 15 SEP 15

IY855 A320 BOM 1000 ADE 1130 LT

IY648 A320 ADE 1300 AMM 1630 LT

WED 16 SEP 15

IY649 A320 AMM 0800 ADE 1130 LT

IY826 A320 ADE 1230 KWI 1600 LT

THU 17 SEP 15

IY827 A320 KWI 0800 ADE 1130 LT IY824 A320 ADE 1230 DOH 1530 LT

FRI 18 SEP 15

IY825 A320 DOH 1000 ADE 1215 LT

IY822 A320 ADE 1330 DXB 1720 LT

SAT 19 SEP 15

IY823 A320 DXB 1000 ADE 1200 LT

IY648 A320 ADE 1300 AMM 1630 LT

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Appendix No. 2

http://www.slideshare.net/wings_of_wisdom/ryanair-presentation-42268156