QUESTION $1$

CASE STUDY: THE NORTH$-$SOUTH AIRLINE

In $2010,$ Northern Airlines$*$ merged with Southeast Airlines to create the fourth largest

U$.$S$.$ carrier. The new North$-$South Airline inherited both an aging fleet of Boeing $737200$

aircraft and Stephen Ruth. Ruth was a tough former secretary of the navy who stepped in as

new president and chairman of the board.

Ruth$$s first concern in creating a financially solid company was maintenance costs. It

was commonly believed in the airline industry that maintenance costs rose with the age of the

aircraft. Ruth quickly noticed that, historically, there has been a significant difference in reported

B$737200$ maintenance costs $($from ATA Form $41$s$)$ both in the airframe and engine areas

between Northern Airlines and Southeast Airlines, with Southeast having the newer fleet.

On November $12,2010,$ Ruth assigned Peg Young, vice president for operations and

maintenance, to study the issue. Specifically, Ruth wanted to know $(1)$ whether the average

fleet age was correlated to direct airframe maintenance costs and $(2)$ whether there was a

relationship between average fleet age and direct engine maintenance costs. Young was to

report back with the answer, along with quantitative and graphical descriptions of the

relationship, by November $26.$

First, Young had her staff construct the average age of Northern and Southeast B$737-$

$200$ fleets, by quarter, since the introduction of the aircraft to service by each airline in late $2001$

and early $2002.$ The average age of each fleet was calculated by first multiplying the total

number of calendar days that each aircraft had been in service at the pertinent point in time by

the average daily utilization of the respective fleet to total fleet$-$hours flown. The total fleet$-$hours

flown was then divided by the number of aircraft in service at that time, giving the age of the

"average" aircraft in the fleet.

The average utilization was found by taking the actual total fleet$-$hours flown at

September $30,2010,$ from Northern and Southeast data, and dividing by total days in service for

all aircraft at that time. The average utilization for Southeast was $8\mathrm{.}3$ hours per day, and the

average utilization for Northern was $8\mathrm{.}7$ hours per day. Because the available cost data were

calculated for each yearly period ending at the end of the first quarter, average fleet age was

calculated at the same points in time.

The fleet data are shown in the following table. Airframe cost data and engine cost data are

both shown paired with fleet average age.

Northern Airline Data

Airframe Cost Engine Cost Average

Year per Aircraft per Aircraft Age $($hrs$)$

$200351\mathrm{.}8043\mathrm{.}496,512$

$200454\mathrm{.}9238\mathrm{.}588,404$

$200569\mathrm{.}7051\mathrm{.}4811,077$

$200668\mathrm{.}9058\mathrm{.}7211,717$

$200763\mathrm{.}7245\mathrm{.}4713,275$

$200884\mathrm{.}7350\mathrm{.}2615,215$

$200978\mathrm{.}7479\mathrm{.}6018,390$

$*$Dates and names of airlines and individuals have been changed in this case to maintain confidentiality.

The data and issues described here are actual.

Deliverable

Prepare Peg Young$$s response to Stephen Ruth. This should be in the form of a report to include

the following:

$1.$ Summary of issue $(2$ marks$)$

$2.$ Analysis $(22$ marks$)$

Hint: Do not combine the data sets $($Northern and Southern$).$ Consider all possible

regressions. Be sure to include all relevant graphs based on analyses.

$3.$ Recommendation$/$Conclusion $(3$ marks$)$

QUESTION $2($INDEPENDENT OF THE ABOVE CASE$)$

A cheque$-$processing centre uses exponential smoothing to forecast the number of incoming cheques

each month. The number of cheques received in June was $40$ million, while the forecast was $42$ million.

Smoothing constant of $0\mathrm{.}2$ is used. $(5$ marks$)$

a$)$ What is the forecast for July? $(2$ marks$)$

b$)$ If the centre received $45$ million cheques in July, what would be the forecast for August? $(2$

marks$)$

c$)$ Why might this be an inappropriate forecasting method for this situation? $(1$ mark$)$

PS: Show all working for parts a$)$ and b$).$

Southeast Airline Data

Airframe Cost Engine Cost Average

Year per Aircraft per Aircraft Age $($hrs$)$

$200313\mathrm{.}2918\mathrm{.}865,107$

$200425\mathrm{.}1531\mathrm{.}558,145$

$200532\mathrm{.}1840\mathrm{.}437,360$

$200631\mathrm{.}7822\mathrm{.}105,773$

$200725\mathrm{.}3419\mathrm{.}697,150$

$200832\mathrm{.}7832\mathrm{.}589,364$

$200935\mathrm{.}5638\mathrm{.}078,259$