ACCOUNTING AND FINANCE RESEARCH UNIT
An international survey of performance
measurement and benchmarking by airlines
Jackie Fry*
Graham Francis+
Ian Humphreys♦
September 2004
04/05
ISBN 0 7492 01460
© Jackie Fry, Graham Francis and Ian Humphreys
*
Dr Jackie Fry, Open University Business School, Walton Hall, Milton Keynes,
MK7 6AA
Email: J.Fry@open.ac.uk
Tel: 01908 659239
Fax: 01908 655898
+
Graham Francis, Department of Accounting, Waikato Management School,
Waikato University Private Bag 3105, Hamilton, New Zealand
Email: GAJF@waikato.ac.nz
♦
Dr Ian Humphreys, Transport Studies Group, Department of Civil and Building
Engineering, Loughborough University, Loughborough, Leicestershire,
LE11 3TU, UK
Acknowledgements
We are grateful to all those airline managers who contributed to this study. We
would also like to thank Jacky Holloway for her support.
Abstract
This working paper describes the nature and prevalence of the use of performance
measurement techniques by airlines. The authors draw on evidence from an international
survey of the largest 200 airlines in terms of total passengers carried. The results provide
empirical insight into the nature and prevalence of performance measurement, benchmarking
activities and other performance management techniques. The surveys revealed a very high
utilization of benchmarking and quality management techniques by airlines, and evidence that
certain measures are considered of more use than others by the airline managers.
1.
Introduction
December 2003 marked the 100th anniversary of the first heavier-than-air controlled, powered
flight by the Wright Brothers. Since this time there has been huge development and expansion
of the aviation industry. However, despite the growth in their business, airlines face
substantial commercial pressures. They face challenging, dynamic market environments that
in the short term are extremely sensitive to the world economic and political situation. Long
term growth of around 4.5 per cent per annum in air traffic has been forecast (ACI, 2003).
However, events such as September 11th, the SARS outbreak and poor economic conditions
of the early 2000’s have seen an overall stagnation and reduction of traffic during the period
2001 to 2003, although some market sectors have performed better. Historically airlines have
made very low margins, 8 per cent on average. The pressures from competition, deregulated
market forces, the decline of average yields per passenger and, in certain regions, the
challenge from low cost airlines has presented management with the problem of how to
improve airline economic performance. This paper seeks to identify the nature and prevalence
of the performance improvement techniques adopted by airline managers in response to these
pressures.
This working paper has the following structure. In order to place our survey in context, the
next section outlines the importance of performance measurement to airlines. This is followed
by a section outlining the methods used to collect data and a section on the demographics and
non-response bias of the survey. The results of the survey are then described and some
conclusions drawn.
2.
Performance measurement of airlines
The continuing speed of change and rapid growth have resulted in a complex array of
challenges for managers including: increasing congestion of infrastructure, safety,
sustainability, environmental and social opposition to aircraft operations, airport and air
traffic privatization and commercialization, alliances and mergers between airlines,
deregulation of markets, the operation of new larger aircraft and the continued rise of low cost
carriers. Such pressures have led managers, planners and regulators to use a variety of
performance management techniques to measure and manage performance.
1
The importance of performance measurement to monitor operational, safety and financial
aspects of performance has been long recognised. Performance data is required to evaluate
customer response to services and to maintain management control of geographically
disparate route networks (Doganis 2001; Shaw 1999; Hanlon, 1999). Performance
measurement data is frequently collected electronically and managed via a series of databases.
The range and volume of data has increased with much of it collected and collated
electronically and fed into databases that are accessible to teams of analysts and decision
makers. Many airlines are fed detailed information on the aircraft’s performance of each
flight via each aircraft’s mandatory Flight Data Recorder (FDR). This operational information
is downloaded and used by management to identify performance improvements that can be
made and to highlight specific operational problems on certain sectors1. With the agreement
of a ‘no blame’ regime, certain airlines use this data to identify safety issues and the need for
pilot training/retraining. Operations data is an example of performance data that is often
collected in real time, reviewed by an operations department and used to manage flight
operations, but is also reviewed by network planning analysts to feed medium and long term
planning decisions (Doganis, 2001, 2002; Kirkland et al., 2003; Caves and Gosling, 1999).
Airline alliances 2 , franchise agreements and code share 3 agreements have led to airlines
signing agreements with each other that require certain service levels and safety standards to
be achieved. Major airlines have undertaken such agreements to maintain brand quality for
customers (Denton and Dennis 2000; Hanlon, 1999). In extreme cases, partner airlines have
had to withdraw from code share agreements or change service delivery as a result of ‘audit’
findings from partner airlines. For example, Korean Airlines was suspended from its alliance
with Delta and Air France until safety standards were raised to the levels required. Both Delta
and Air France compared performance information with Korean Airlines and provided the
expertise, knowledge of safety systems and culture to develop the processes required to
address possible safety problems (Braithwaite, 2001).
Load factor data, yield and other commercial information is collected and fed into a database
of commercial information to provide airline management with information upon which to
base pricing and capacity decisions in the short, medium and long term. The volatility of the
airline service with respect to hourly, daily and seasonal traffic patterns, the impact of
competitor behaviour and the sensitivity to economic conditions has made collection of
commercial performance data essential to enable management to react to market changes and
to survive. Generally speaking, the use and analysis of commercial information is known to
be common place, yet the exact way information is used has remained something upon which
little academic work has been undertaken, due in no small part to the commercial sensitivity
of such information. Examples of benchmarking from the literature include Southwest
1
A sector can be defined as a single air route from landing to take off.
Oneworld (including British Airways, Ammerican Airlines, Cathay Pacific, Aer Lingus and Iberia), Star
Alliance (including Lufthansa, United, Thai and Bmi British Midland), Sky team alliance including Delta, Air
France, KLM, Korean Air and Northwest).
2
2
Airlines learning about the low cost model of airline operation through visits and spending
time with Pacific Southwest Airlines in California. Likewise Ryanair spent time with
Southwest Airlines to understand how to develop a low cost airline (Calder, 2002).
Airline managers have used performance measures for comparing airline performance both
within the airline and in relation to the performance of other airlines. The main players will
depend heavily on inter-organizational learning if they are to meet the challenges facing them.
Cost data comparisons from published sources by organizations such as the International Air
Transport Association (IATA), the International Civil Aviation Organization (ICAO), the UK
Civil Aviation Authority and periodicals such as Air Transport World and Aircraft Economics
are available for use by management to assess comparative performance and as a starting
point for exploring the reasons behind the performance differences. Some of these differences
can be explained by geographical variation in labour and other input costs. In addition to
published statistics a number of reports providing ‘benchmark’ statistics and comparisons of
airline performance have been produced (such as Mason, Whelan and Williams, 2000;
Morrell, Alamdari and Lu, 2000; TRL, 2002). Quality of service indicators are collected by
airlines internally and by IATA’s annual world passenger survey which monitors customer
satisfaction with 29 aspects of airline service (IATA, 2002). Each airline can compare itself
with the ratings for the rest of the sample to provide a measure of relative performance.
Although the literature identifies a range of data collection methods and a comparison of key
performance indicators, these techniques and benchmarking activities have oriented towards
process improvement within the sector and have not previously been identified in a systematic
way. A prime motivation of this study therefore is to address this gap by identifying the
relative use of different performance measurement practices by airline managers in response
to the challenges they face.
3.
Methods
Given the objective of trying to identify the nature and prevalence of the use of performance
measurement techniques a questionnaire survey was viewed as the most appropriate way of
gathering initial empirical evidence (Oppenheim, 1992). There are limitations inherent in the
use of questionnaires as a research method and the authors intend to follow up this research
with a number of detailed case studies (Scapens, 1999) of performance management practices
with individual airlines.
The set of airlines sampled was the largest 200 airlines as ranked by Air Transport World
(ATW) in terms of total passengers for 2001 (ATW, 2002). The top 200 were chosen because
it represented the major players in the industry who account for over 75 per cent of airline
passenger kilometres performed. It is symptomatic of the volatility of the airline industry that
at the start of the survey, 12 airlines listed in the top 200 were no longer operating and were
3
Code sharing is when two or more airlines use their own flight codes on a flight operated by one of them.
3
therefore deleted from the list. The next 12 airlines still in operation were added to make the
sample up to 200. The questionnaires were addressed where possible to the person concerned
with flight operations. Where it was not possible to identify a named person, the questionnaire
was sent to another named senior person.
Each questionnaire sent out was given a unique identification number to ensure repeat
mailings were only sent to non-respondents. A copy of the questionnaire (Appendix A) and a
covering letter were sent out to airlines on 10 February 2003 and three repeat mailings,
17 March, 28 May and 27 August 2003. Two hundred were sent out in the first mailing. Two
remained undeliverable and during the survey period a further two airlines ceased operations.
Of the remaining 196 questionnaires, two airlines declined to participate and 43 were returned
completed, a response rate of 23 per cent.
4.
Demographics and non-response bias
The respondent airlines and the airlines in the sample were classified into geographic regions
using the categories as defined in ATW (2002): Africa/Middle East, Asia/Pacific, Europe,
Latin America/Caribbean and North America4 (Table 1). The profile of the respondents was
then compared to the profile of the overall sample. In order to perform a Chi-square test, the
categories of Latin America/Caribbean and Africa/Middle East were combined into a “rest of
world” category so that the expected values of the categories were greater than 5. The Chisquare test showed that the profiles of respondent airlines were not significantly different to
the profile of the samples at the 5 per cent level (χ2=4.02, ns). The geographic spread of the
respondents is a good match to that of the sample.
Table 1: Geographic profile of the respondents and the sample
Region
Europe
North America
Asia/Pacific
Latin America/Caribbean
Africa/Middle East
Percentage of
sample airlines
Percentage of
respondent airlines
(N=196)
(N=43)
37
21
23
11
8
52
16
16
7
9
The representativeness of the respondents can also be confirmed by examining the profiles of
the total number of passengers handled per annum by the sample airlines and the respondents
(Table 2). The Chi-square test showed that the profile of respondent airlines was not
significantly different to the profile of the sample at the 5 per cent level (χ2=2.19, ns). The
4
In fact ATW distinguishes between Canada, US Majors, US Nationals, US Cargo and US Regional/Specialty.
For the purposes of this research these were all coded as North America.
4
range of passenger numbers handled per annum by the respondents is a very good match to
that of the sample.
Table 2: Number of passengers handled per annum by the respondents and the sample
Passengers handled
/million
1 to 4*
5 to 9
10 to 19
20 and above
Percentage of
sample airlines
Percentage of
respondent airlines
(N=196)
(N=43)
61
22
8
9
51
26
9
14
* Only includes up to the 200th busiest airline
5.
Results
The questionnaire instrument included questions on the use of performance management
techniques and metrics in a number of areas such as operations, financial, quality of service
and environmental. Each of these will be outlined in the following sections.
5.1 The relative prevalence of performance measurement techniques
The questionnaire instrument included a question aimed at identifying the relative usage made
of performance improvement techniques (see Table 3). Benchmarking is the single most used
method. Quality management methods 5 when looked at in total are also in very common
usage. Quality issues and benchmarking will be covered in more detail in sections 5.4 and 5.6
respectively.
Table 3: Performance improvement techniques used by respondents
Percentage use
by airlines*
Technique
(N=41)
Benchmarking
Quality Management Systems (e.g. ISO9000/BS5750 or
similar)
Balanced Scorecard
Business Process Reengineering
Activity Based Costing
Total Quality Management (TQM)
Environmental Management Systems (e.g. ISO14000)
Value Based Management
Business Excellence Model / EFQM
88
54
44
39
34
22
17
15
7
*
Note that respondents frequently use more than one method
5
Such as ISO9000/BS5750, Business Excellence Model / EFQM and Total Quality Management (TQM)
5
It is noteworthy that benchmarking was identified as the most used performance improvement
technique for airlines with 88 per cent of the sample claiming to engage in some form of
benchmarking activity. None of our respondents reported using DEA6 although its application
to an airline was reported on by Schefczyk (1993). Table 4 provides a comparison to an
earlier survey of the world’s busiest 200 airports, in terms of passengers handled, carried out
in 2000, in which benchmarking was also the most used performance improvement technique
with 72 per cent of airports claiming to undertake benchmarking activity (Francis, Fry and
Humphreys, 2001). The authors were surprised by the high reported use of the balanced
scorecard with 44 per cent of airlines reporting its use compared to 25 per cent in the airport
study. Although the two business sectors are interrelated, they are very different, so direct
comparisons between the two industries should be made with care. However, it is interesting
to recognise that these distinctly different industries both use benchmarking to improve
business performance more so than alternative performance techniques.
Table 4: Performance improvement techniques used by responding airlines in
comparison to the authors’ earlier study of airport performance measures (Francis. Fry
and Humphreys, 2001)
Technique
Benchmarking
Quality Management Systems (e.g. ISO9000/BS5750 or
similar)
Balanced Scorecard
Business Process Reengineering
Activity Based Costing
Total Quality Management (TQM)
Environmental Management Systems (e.g. ISO14000)
Value Based Management
Business Excellence Model / EFQM
Percentage use
by airlines*
Percentage use
by airports*
(N=41)
(N=56)
88
54
72
23
44
39
34
22
17
15
7
25
23
36
41
27
9
12
*
Note that respondents could use more than one method
The pressure for improved performance and the dynamic nature of airline management with
respect to looking for new ways to measure airline performance is perhaps reflected by the
surveys finding that 62 per cent of the airlines that responded to the survey had introduced
new performance measures within the last two years.
The size of airline does seem to impact on their use of performance measurement techniques.
In general, as expected, larger airlines are more likely to engage in performance measurement.
6
Data Envelopment Analysis (a form of linear programming)
6
This is most noticeable in the uptake of benchmarking. The larger the organization the more
likely there will be the resources to benchmark. A note of caution, the pattern is in part
distorted by geographical differences between airlines being interrelated with airline size
(Table 5).
Table 5: Use of performance measurement techniques in relation to airline size
Passengers handled per annum
/million
Percentage benchmarking
Quality Management Systems (e.g.
ISO9000/BS5750 or similar)
Balanced Scorecard
Business Process Reengineering
Activity Based Costing
Total Quality Management (TQM)
Environmental Management
Systems (e.g. ISO14000)
Value Based Management
Business Excellence Model / EFQM
1 to 4*
5 to 9
10 to 19
80
35
91
82
30
20
35
10
0
15
0
100
50
20 and
above
100
67
Overall weighted
average
88
54
54
55
36
36
27
50
50
0
25
50
67
67
50
33
33
44
39
34
22
17
9
9
50
25
0
17
15
7
* Only includes up to the 200th busiest airline
Table 6 shows the use of performance measurement techniques in relation to region. This
highlights a different propensity to use various methods around the world. The lack of use of
Environmental Management systems among North American airlines was a surprising finding
given that the largest of these operate into congested hub airports. However, perhaps the
formalised system of environmental management for these airlines is not prioritised to the
same extent as for European and Asian carriers where the political pressure to engage in
proactive community and sustainability practice has been very intense over the last decade
and is set to continue to become even more significant with traffic growth (Upham, 2003).
Perhaps less surprising is that the use of the EFQM model is restricted to Europe.
When examining performance improvement techniques used in relation to ownership, the
results are not necessarily what might have been expected as there is a tendency for those
airlines with a government stake in ownership to make greater use of performance
improvement techniques. This may in part be explained by the pressure of accountability of
governments that still have an ownership stake in an airline (see Table 7) in order to
demonstrate that the tax paying public are receiving good value for money.
7
Table 6: Use of performance measurement techniques in relation to region
Region
Europe North
Asia /
Latin
Africa /
America Pacific
America / Middle
Caribbean East
Percentage benchmarking
95
86
86
67
67
Quality Management Systems
65
29
57
33
50
(e.g. ISO9000/BS5750 or
similar)
Balanced Scorecard
45
29
42
50
67
Business Process Reengineering
25
57
57
33
50
Activity Based Costing
40
29
29
0
50
Total Quality Management
20
0
43
0
50
(TQM)
Environmental Management
20
0
29
0
25
Systems (e.g. ISO14000)
Value Based Management
20
0
14
33
0
Business Excellence Model /
15
0
0
0
0
EFQM
Overall
weighted
average
88
54
Table 7: Performance improvement techniques used in relation to ownership
Technique
Benchmarking
Quality Management Systems
(e.g. ISO9000/BS5750 or similar)
Balanced Scorecard
Business Process Reengineering
Activity Based Costing
Total Quality Management (TQM)
Environmental Management
Systems (e.g. ISO14000)
Value Based Management
Business Excellence Model / EFQM
Percentage use by
Percentage use by
Total
airlines with a
airlines without a percentage
(N=41)
government stake in government stake in
ownership (N=19)
ownership (N=22)
100
78
88
74
36
54
58
53
42
37
32
32
27
27
10
5
44
39
34
22
17
16
11
14
5
15
7
*
Note that respondents could use more than one method
Many governments have reduced their stakes in their airlines, and in particular geographic
regions, such as Europe, the subsidy of a state carrier has been outlawed (Doganis 2001,
2002). Governments have seen that countries with privatised airlines and independent
operators run airlines at break even or above and have begun to run their own airlines to
8
44
39
34
22
17
15
7
commercial objectives. Some have tried to make their airline attractive to private investors,
with a view to further reducing their stake. In a number of cases there has been increased
accountability to government and an increased pressure for commercial viability of the airline.
This push for improved viability could be driving the increased emphasis of these airlines on
performance improvement techniques and increased levels of performance measurement. The
choice of techniques used is also influenced to varying degrees by the use of management
consultants.
Table 8: The influence of management consultants on the introduction of new
performance measures
Level of influence of
management consultants
Very influential
Some influence
Not influential
Management consultants not used
Percentage of respondents
(N=34)
14
31
26
29
5.2 Operational performance measures
The survey illustrated an interesting uptake of operational performance measures. The
responses are summarised in Table 9. It was expected that load factor 7 and punctuality
indicators would be seen as important, but the use of turnaround time was lower than
expected. However, the sample was of the largest 200 airlines; if the sample had been of low
cost airlines, turnaround time may have had a higher priority. Output measures of magnitude
rather than efficiency tended to be widely used but not rated as useful as efficiency
indicators8.
In line with the cost conscious nature of the airline business environment, 90 per cent of
respondents used cost per seat kilometre as a measure. Overall this was the measure seen as
most useful to managers. Interestingly, although ‘belly hold’ freight 9 has become more
important in recent years, measures that reflect airline performance in relation to freight, such
as tonne kilometre and work load Units (WLU)10, were relatively infrequently used. However,
those managers using them reported them to be of value. Average fleet age was measured by
80 per cent of our respondents but was seen as the least useful. This is a reflection of the fact
that it is more of a facet of long term planning than performance measurement.
7
Load factor is measured in terms of the number of seats occupied as a percentage of the total seats available.
There was no statistically significant correlation between use and reported usefulness of operational measures.
Spearman rank-order correlation between percentage using operational performance measures with mean of
usefulness of measure: rs = 0.27, ns at the 5 percent level.
9
‘Belly hold’ freight is that which is carried in the hold of aircraft operating on passenger services.
10
WLU are equivalent units of activity for comparison purposes. 1 WLU is 1 passenger or 100kg of freight.
8
9
Table 9: Operational performance measures
Operational performance measure
Used
/%
Not
used /%
Don’t
know /%
100
95
100
80
93
49
76
87
90
98
43
78
0
5
0
17
7
49
21
11
8
0
40
11
0
0
0
3
0
2
3
2
2
2
17
11
Punctuality/on-time performance per operation
Revenue passenger kilometres
Load factor per flight
Average fleet age
Available seat kilometres
Available tonne kilometres per employee
Average turnaround time
Labour cost as % of total operating cost
Cost per seat kilometre
Daily aircraft utilisation (hours)
Total revenue per Work Load Unit
Other
Usefulness of
measure*
Mean
S
4.6
0.9
4.2
1.1
4.5
1.0
3.0
1.1
4.2
0.9
4.0
0.9
4.1
0.9
3.9
1.0
4.7
0.7
4.3
1.0
4.5
0.5
4.8
0.5
*
Scale: 1=Not useful to 5=Very useful, S=Standard Deviation
5.3
Financial performance measures
Measuring various aspects of financial performance is important for airlines operating on tight
margins. It is important to measure those aspects of which are contributing to the overall
performance and not just the traditional ‘bottom line’ measure. As one of our respondents
observed: ‘Airlines are by nature a strange mix of retail and technical industries with large
cost base and cashflow variations. Performance measurement is essential in the tough lowmargin business environment.’ In terms of the reported use of financial performance measures
(see Table 10) the more traditional profit based measures were the most used and tended to be
seen as useful11. In particular there was a focus on operating revenue and expenses. Profit was
far more widely used than investor ratios such as earnings per share (EPS) and price earnings
ratios (P/E), whose low uptake and usefulness can be explained by the fact that by no means
all the respondents were in private ownership (46 per cent of respondents had a government
stake in ownership and 54 per cent did not).
11
There was a correlation between the uptake and perceived usefulness of financial performance measures.
Spearman rank-order correlation between percentage using financial performance measures with mean of
usefulness of measure: rs = 0.71, p<0.05
10
Table 10: Financial performance measures
Financial performance
measure
Used
/%
Not
used /%
Don’t
know /%
95
95
93
93
81
76
75
49
46
38
75
0
0
2
2
11
11
17
43
46
54
0
5
5
5
5
8
13
8
8
8
8
25
Operating costs
Cash flow
Operating revenue
Profit
Return on Capital Employed
Gearing (debt to equity ratio)
Revenue to expenditure ratio
Price earnings (P/E) ratio
Share price
Earnings per share
Other
Usefulness of
measure*
Mean
S
4.8
0.6
4.4
0.9
4.5
0.7
4.7
0.8
4.2
1.0
3.9
1.0
4.1
1.0
3.6
1.0
3.5
1.2
3.6
1.2
5.0
0.0
*
Scale: 1=Not useful to 5=Very useful, S=Standard Deviation
Table 11 shows the use and potential uptake of various financial performance indicators.
While it also illustrates that the more traditional profit and accrual accounting based measures
still dominate, newer approaches are having an impact. The balanced scorecard, which
combines financial and non-financial indicators, is the most adopted of the ‘newer’
approaches. Shareholder value and other value based management methods such as Economic
Value Added (EVA®) are used by a number of airlines.
Table 11: The use and potential uptake of financial performance indicators
Financial performance indicator
Ability to stay within budget
Cash flow
Net profit
Return on Capital Employed
Balanced Scorecard
Economic Value Added (EVA®)
Shareholder Value Analysis (SVA)
Residual Income
Used
/%
98
98
98
74
44
35
28
24
Being
considered /%
0
0
0
5
14
21
22
6
Not being
considered /%
0
0
0
13
20
21
34
36
Not aware
of /%
2
2
2
8
22
23
16
33
Table 12 compares the findings with the findings from our airport study (Francis, Fry and
Humphreys, 2001) and an earlier study across various sectors in the UK (Minchington and
Francis, 2000). Airlines are generally making greater use of these financial performance
techniques than revealed by these earlier studies. Though the relative ‘popularity’ of each
technique is reasonably consistent between the studies, it is not surprising to see a very high
11
usage of traditional accounting methods, such as budgets and Return on Capital Employed.
However, newer approaches, such as the balanced scorecard, are in fairly widespread use.
Table 12: The relative use of financial performance measures by airports
Financial performance measure
Ability to stay within budget
Return on Capital Employed
Balanced Scorecard
Economic Value Added (EVA®)
Shareholder Value Analysis (SVA)
Residual Income
World airlines
/%
98
74
44
35
28
24
World airports Minchington and Francis
/%
(2000) (UK all sectors) /%
98
99
51
71
23
24
13
10
10
15
17
6
5.4 Quality of service performance measures
It is interesting to reflect on the fact that several of these reportedly widely used quality of
service indicators (Table 13) are not directly within the airlines’ control; control is devolved
to airports or third parties. The use of airport service quality measures by the airlines has been
a point of commercial contention for a number of years (Graham, 2003). Airline passengers
have their own individual opinions on the acceptability of the service they receive (referred to
as user perceived level of service, see Francis, Humphreys and Fry, 2003) determined by such
activities as check in and baggage reclaim. A bad experience at the airport may determine the
passengers’ propensity to fly again with a certain airline, so it is important for the airline to
monitor the provision of airport services and surface access and third party ground handling
services in order to maintain quality for their passengers12. In many parts of the world airlines
enter into service level agreements with airports and third party handlers in an attempt to
maintain levels of service for passengers. Passengers see the airline as the provider of the
service and may not realise that the airport and third party handlers are involved (see Francis,
Humphreys and Fry, 2003). This performance measurement activity is important, particularly
in a competitive market, where there is a ‘rule of thumb’ which claims “it costs ten times
more to win a new business passenger than to keep an existing one” an idea that has
underpinned airlines introducing frequent flier programmes to maintain customer loyalty and
to provide rich data streams that enable them to market to passengers on the basis of extensive
market intelligence (Goetz, 2002; Shaw, 1999).
12
The traditional airport airline relationship has been evolving (see Graham 2003) but there is still a tendency for
some airports to see airlines not passengers as their customers so airlines need to ensure the quality of service
provided at the airport for their customers (the passengers).
12
Table 13: Quality of service performance measures
Performance measure
Used
/%
Not used
/%
Don’t know
%
Level of service
Baggage delivery time
Lost baggage
Check in waiting time
Consumer complaints
Other
86
78
98
85
98
89
7
17
2
13
2
11
7
5
0
3
0
0
Usefulness of
measure*
Mean
S
4.5
0.9
4.1
0.9
4.3
0.8
4.1
0.9
4.4
0.9
4.8
0.4
*
Scale: 1=Not useful to 5=Very useful, S=Standard Deviation
In Table 13 it can be seen that all quality of service indicators were widely used and
considered to be very useful13. The tendency is for these to have a customer focus such as
customer complaints. Airlines find level of service indicators 14 useful in monitoring their
critical relationships with airports and handling agents. The airlines frequently collected their
own internal data of both physical and user perceived measures. This is carried out through a
variety of methods, as illustrated in Table 14. Passenger questionnaires were the most
prevalent method, but most airlines used more than one way of gathering data. As well as
using the methods illustrated in Table 14, benchmark data from external agencies is
frequently used (see section 5.6).
Table 14: Methods of collecting performance measurement data by airlines
Method
Percentage of respondents
(N=39)
Passenger questionnaires
Passenger interviews
Focus groups
Comment cards
Other
5.5
87
49
39
62
26
Environmental performance measures
The relative use of environmental performance measures is illustrated by Table 15, and is
consistent with the trend identified by Upham (2003) that airlines are keen to undertake
measures that lead to eco-efficiency and a reduction in input costs such as fuel and electricity,
but are less keen on ‘sustainability’ issues that do not involve cost savings. Though it must be
recognised that, in terms of fuel efficiency, there may be congruence between operational and
13
Although there was no statistically significant correlation between uptake and perceived usefulness. Spearman
rank-order correlation between percentage using quality of service performance measures with mean of
usefulness of measure: rs = 0.50, ns at the 5 per cent level
14
Level of service indicators such as: check in waiting time, time for baggage delivery to passenger, level of
satisfaction with retail outlets, quality of directional signage. See IATA (2002) which includes 29 aspects of
13
environmental performance improvements, the focus on measuring fuel consumption rather
than emissions may have future significance in terms of the regulatory and taxation policy of
governments wishing to control the environmental impact of airlines. Table 4 in section 5.1
showed that only 17 per cent of airlines (and 27 per cent of airports) were using ISO14000.
Track keeping15 is becoming ever more important, particularly at airports where capacity is
determined not by the operational capabilities of the airport infrastructure but by the
environmental restrictions placed on operations to mitigate communities affected by aircraft
noise. The measure of numbers of the population affected by noise and number of community
complaints are particularly important in the European context where environmental pressure
at the major hubs is bringing to bear political pressure to constrain airport expansion.
Ultimately, this may affect an airline’s long term viability and the competitiveness of its hub
operations. The choice of environmental measures appears linked to their perceived
usefulness16.
Table 15: Environmental performance measures
Performance measure
Used
Percentage of passengers using public
transport to access the airport
Percentage of departures on track
Energy efficiency of installations managed
Population affected by noise at base airport(s)
Percentage of waste recycled per annum
Number of community complaints about
operations
CO2 emissions g/rtk17
Fuel consumption and efficiency g/rtk
Other
%
14
Not
used
%
70
Don’t
know
%
16
Usefulness of
measure*
Mean
S
2.8
0.4
61
32
37
27
32
27
38
58
62
53
12
30
5
11
15
4.3
3.7
3.6
3.6
3.7
0.7
0.6
1.2
1.2
0.5
24
83
50
54
12
0
22
5
50
3.8
4.5
4.0
0.8
0.7
0.0
*
Scale: 1=Not useful to 5=Very useful, S=Standard Deviation
Surface access to airports is seen as an airport problem and hence only 14 per cent of airlines
used this measure in relation to their passengers. However, in certain locations, airport
capacity may be constrained by the surface access behaviour of airline passengers and staff.
The UK Government’s 2003 White Paper only allows expansion of certain airports if
passengers and staff make more journeys by public transport or car share schemes. In
customer satisfaction.
15
Track keeping is the practice of flying aircraft along very specific routes (usually to avoid residential areas and
minimize noise impact) when approaching or departing from an airport.
16
Spearman rank-order correlation between percentage using environmental performance measures with mean
of usefulness of measure: rs = 0.76, p<0.05
17
g/rtk = grams per revenue tonne kilometre
14
particular, at a number of airports, the air quality levels are driven more by surface transport
than by emissions from aircraft18. In short, Heathrow will only receive a third runway if there
is a reduction in the use of single occupancy car trips by all airport users, including airline
staff. British Airways have recognised the significance of this and have led a number of
measures to reduce single car occupancy trips (Ison and Humphreys, 2003). Other airlines are
likely to take the measure of surface access trips ever more seriously, particularly in the
European context where congestion and environmental legislation threatened to restrict an
airline’s business.
5.6
The use of benchmarking by airlines
As illustrated in Table 3, the level of benchmarking activity across the airline sector was high
and confirmed prior expectations of benchmarking prevalence. Table 16 shows that
international airlines from Europe, North America and Asia/Pacific demonstrated a higher
propensity to benchmark, with Europe showing the highest propensity. These three regions
are also the strongest performing in terms of world airline traffic.
Table 16: Prevalence of airline benchmarking by region
Region
Europe
North America
Asia/Pacific
Latin America / Caribbean
Africa/Middle East
Overall weighted average
Percentage benchmarking
(N=41)
95
86
86
67
67
88
In terms of airline size, larger airlines were more likely to engage in some form of
benchmarking activity than smaller airlines (see Table 17). Benchmarking was undertaken by
airline management at all airlines handling ten million passengers per annum or more that
responded to the survey. This is consistent with the findings of Holloway et al. (1999) who
found that larger organizations were more likely to benchmark than smaller ones. The
prevalence of benchmarking activity is also high among the airlines handling between one
and nine million passengers per annum.
18
At Heathrow for example it has been estimated that around 80% of air pollution is derived from surrounding
road traffic and airside vehicles and only 20% is derived directly from aircraft.
15
Table 17: Benchmarking in relation to airline size
Passengers handled per
Percentage benchmarking
(N=39)
annum /million
1 to 4*
80
5 to 9
91
10 to 19
100
20 and above
100
Overall weighted average
88
Airline alliances were found to provide useful frameworks for benchmarking activity with the
survey discovering that 49 per cent of airlines benchmarking undertook these activities with
alliance partners. Given the trend towards globalization of the industry, benchmarking with
alliance partners is a further means beyond the established commercial agreements of
leveraging management benefits from alliances and creates a natural opportunity for
benchmarking activity that ought to be less prone to data sensitivity and confidentiality issues.
Within the airline industry the trend is for collaboration and a drive for airlines to enter into
partnerships or be left in the cold. Code sharing and franchise agreements now number over
2000 (Upham, 2003). The nature of agreements between airlines demands that levels of
service quality are maintained in order to protect brand quality. This has led to increased
contact between airlines, and to the formal agreement and measurement of performance,
particularly from a customer (passenger) perception perspective, and in terms of operational
performance such as on time departures and safety. The formation of agreements and entry
into alliances has seen geographically disparate airlines come together to share performance
data, look for reasons for performance differences and to share best practice. Larger airlines
are more likely to benchmark because they are likely to be alliance leaders and have wider
network scope that enables comparisons to be made across geographically disparate areas.
The drive towards collaboration has provided, and is likely to continue to provide, closer links
between the world’s airlines and opportunities for increased performance measurement
comparison and for benchmarking.
The questionnaire instrument included the opportunity for respondents to describe their
benchmarking experiences. Most comments were positive such as: ‘It is good to check how
we are doing and to identify industry trends’ and ‘Useful as a driver for creating a sense of
urgency’. However, although generally favourable, not all airlines reported equally favourable
experiences. One respondent describing the outcomes as ‘unremarkable’ and another
commented that benchmarking was ‘difficult due to availability of data.’
There is a tendency for airlines to look within the industry for benchmarking partners (see
Table 18) as opposed to benchmarking and learning from organizations that have similar
processes but are part of non-air transport related organizations: ‘It was good experience,
letting us position our company towards the other airlines.’ The value of comparison with
16
similar organizations and the difficulties associated with obtaining certain commercially
sensitive data were highlighted by a number of managers. One stated that benchmarking was:
Very useful even if, for commercial reasons, the exchange of information is limited and
slow with competitors. Other airlines are very easy to approach and good at sharing
process, & technology applications, experience. Naturally large culture and environment
(and resistance sometimes) issues can make adaptation or replication difficult.
The problem of data comparability for benchmarking between airlines was highlighted by
comments such as: ‘Benchmarking can be of limited value due to widely different
circumstances of benchmark’. Targets and benchmarking comparisons ‘have not always
be[en] useful because data [is] not always comparable.’ Another airline manager reported that
benchmarking partners were selected from airlines that were perceived to be non-competitors,
typically those operating in different geographic markets.
Table 18: Comparator organisation used by airlines, similar or dissimilar?
using mainly
using mainly
1
2
3
4
5
6
7
similar partners
dissimilar partners
13% 43% 13% 22% 3%
3% 3%
Å 69% Æ
Å
9%
Æ
(N=32)
The selection of benchmarking partners from outside the industry can overcome issues of
competitive sensitivity that can make access to certain information problematic. A well
reported example of the benefits of this was the case of Southwest Airlines who benchmarked
their refuelling and aircraft turnaround processes and practises against Formula 1 motor
racing. The valuable lessons learned improved their turnaround times from 40 minutes to as
little as 12 minutes in certain cases (Murdoch, 1997). Lateral thinking and looking outside the
industry for examples of best practice might assist management. However such generic
benchmarking activities by airlines are very rare.
Benchmarking activity appears to be balanced between process improvement and
performance measurement (see Table 19). For some airlines the perceived need is to develop
an understanding of comparative performance, whereas for others the focus is on learning
how to improve operations (processes). The balance may reflect the global reaction of the
airlines to declining yields, a trend that has increased the pressure on airlines not only to
manage the current performance of different business units but to look for opportunities to
improve efficiency. The trend for full service airlines to look at and adopt different elements
of the low cost model such as direct internet sales, one way fares and charging for snacks and
drinks is an example of process improvements based on learning from other industry
participants.
17
Table 19: Is airline benchmarking focussed on process improvement or performance
measurement?
More to do
more to do with
1
2
3
4
5
6
7
with
process improvement
measurement
3% 28% 12% 13% 16% 16% 12%
Å 43% Æ
Å 44% Æ
(N=32)
Airlines use benchmarking as much for financial comparisons as for operational comparisons
(see Table 20). In the survey benchmarking applied to non financial (operational) practices as
opposed to financial measures was found to be roughly equally prevalent. This is interesting,
as there are relatively few examples of this covered by the literature (Zairi, 1998), whereas
there are more references to financial benchmarking among airlines (see for example: Feng
and Wang, 2000 and Doganis, 2002).
Table 20.: Financial or non-financial benchmarking comparisons in airlines?
Primarily financial
primarily non1
2
3
4
5
6
7
measures
financial measures
3%
3% 19% 44% 16% 12% 3%
Å 25% Æ
Å 31% Æ
(N=32)
There is evidence that competing airlines are sharing engineering and maintenance data and
meet regularly to share knowledge, particularly when new aircraft types were being
introduced into service (Francis et al., 1999). Several competing airlines undertake
maintenance for each other in different geographical regions. The competitive rhetoric of
marketing departments is put aside in favour of the commercial sense of pooling maintenance
resources. There was one example of airlines within the same alliance sending personnel to
check third party maintenance by partner airlines to ensure quality was being maintained and
to share lessons learned from the airlines’ own maintenance experience elsewhere in the
world. A case study of Britannia Airlines revealed how they selected benchmarking partners
operatingsss in different parts of the world (Francis et al., 1999).
Benchmarking activity was focussed on comparisons with other airlines as opposed to
benchmarking performance historically within and across different parts of their own airline
(see Table 21). This is unexpected in some ways because airlines could easily and readily
compare year on year performance across their network. There may however be a sense that
within an airline the potential for learning new performance enhancing information via
comparisons may be limited due to the airline working to the same company rules and
operating practises. This trend may be a further echo of the structural pressure in the highly
competitive airline market where comparisons with other airlines might be seen as holding
18
greater potential for performance improvement and the increased ease of making comparisons
due to the increased level of alliance, franchise and code share collaboration between airlines,
a trend that looks likely to continue.
Table 21: Internal or external benchmarking comparisons in airlines
mainly internal
mainly external
1
2
3
4
5
6
7
comparisons
comparisons
0%
0% 9% 6% 27% 43% 15%
Å
9%
Æ
Å 85% Æ
(N=33)
The significance of understanding the implications of work processes and activities of other
airlines, particularly competitors, was further highlighted by comments made in response to
the questionnaire survey. Airline management saw it as ‘critical to measure how we are
performing, particularly against our competitors’ and ‘with a main competitor we find it
[benchmarking] a very valuable tool.’ Historic comparisons had been exploited by one airline
in the wake of a merger to try and capture the best work processes and practices from the
acquired airline: ‘Having merged two airlines we are able to use historic benchmarking to a
high degree.’
Benchmarking was equally used for specific comparisons of particular tasks or activities and
more general comparisons of general practices and performance (see Table 22).
Table 22: Is airline benchmarking concerned with specific tasks or general practices?
Concerned with
concerned with
1
2
3
4
5
6
7
specific tasks
general practices
0% 18% 24% 16% 24% 15% 3%
Å 42% Æ
Å 42% Æ
(N=33)
6.
Conclusions
Performance measurement has become increasingly important in aviation as markets become
more competitive and the number of asymmetric shocks seems to increase. Performance
management is likely to become more critical with increased congestion in the air transport
system, lower yields, pressure to reduce costs and increased operational pressures regarding
the environmental and social impact of aviation. Prior to this study little was known about the
nature and prevalence of performance measurement techniques by individual airlines. The
survey revealed an interesting and diverse range of practices around the world. Follow up
work will involve case studies with individual airlines to gain a deeper understanding of
individual practices. Performance measures may need to evolve to reflect increased
competition and cost constraints. For example, the impact of the low cost airlines may be to
19
increase the importance placed on turnaround time, aircraft utilization, role of direct ticket
sales via internet and call centres, flexible labour practices, as well as for airlines to evaluate
the entire cost structure inherent in their operations.
Our survey found that performance measurement practices were widespread within the airline
industry but that there was primarily a focus on financial and operational measures. Given the
pressure for cost efficiency it was perhaps not surprising that cost per seat kilometer operated
was considered the most useful financial performance measure. Environmental performance
measurement was most prevalent among European and Asian airlines but on the whole use of
environmental measures frequently lagged behind operational and financial performance.
These findings reflect the geographical disparity in environmental restrictions in different
operating contexts. The most used performance improvement technique was best practice
benchmarking although what is taking place in the name of benchmarking subsumed a wide
range of activities. Most respondents reported using more than one performance improvement
technique and as such quality management measures, balanced scorecard and business
process reengineering were each in use by over 39 per cent of the sample. The survey found
that size matters! The larger the airline, the greater the prevalence of performance
measurement.
The majority of airline benchmarking takes place within the industry sector and so there is the
potential for more airlines to follow Southwest’s lead and benchmark outside the airline
sector. The move towards airline alliances has facilitated the availability of benchmarking
partners. This will continue to provide opportunities for alliance members to learn from each
other, but will also provide challenges regarding the most appropriate and effective ways for
management to measure and report performance across the entire network.
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Doganis, R. (2002) Flying Off Course, Routledge, London.
20
Feng, C. and Wang, R. (2000) ‘Performance evaluation for airlines including the
consideration of financial ratios’, Journal of Air Transport Management, vol. 6 no. 2,
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Francis, G., Hinton, M., Holloway, J. and Humphreys, I. (1999) ‘Best practice benchmarking:
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22
Appendix A Questionnaire Note: Percentage of respondents given for each closed question
World Airline Performance Measurement Survey
This questionnaire forms part of a major project being conducted by Loughborough University, The Open
University Business School in the UK and Waikato University in New Zealand on the use of performance
measures in airlines. We do not want to know confidential information on how you are performing; we are
only concerned with how your airline measures and manages its performance. The information you provide
will be treated in the strictest confidence and will only be used for academic purposes. Neither individuals nor
airlines will be identified in any analysis.
Q1
Q2
What job function do you work within?
12
Planning
3
Finance
13
Operations
0
Administration
31
Senior management
41 Other (please specify)
Has your airline employed any of the following methodologies to help improve performance?
Please tick all that apply.
34
Activity Based Costing
44
Balanced Scorecard
88
Best Practice Benchmarking
7
Business Excellence Model / European Foundation for Quality Management (EFQM)
39
Business Process Reengineering
5
Data envelopment analysis (DEA)
17
0
Environmental Management Systems (e.g. ISO14000)
Malcolm Baldrige Award
54
Quality Management Systems (e.g. ISO9000/BS5750 or similar)
22
Total Quality Management (TQM)
15
Value Based Management
12
No measures used
0
Other (please specify)
If your airline does use any of the above, what is your opinion of their effectiveness?
Please turn over ➨
Q3
Which of the following performance measures does your airline use and please rate the ones you do
use on a scale of not useful (1) to very useful (5).
Not
useful
Operational measures
Yes
Punctuality/on-time performance per
operation
100
Don’t
know
0
0
No
Very
useful
1
2
3
4
5
2
2
2
22
72
95
5
0
5
5
8
28
54
100
0
0
2
5
7
13
73
Average fleet age
80
17
3
10
19
35
26
10
Available seat kilometres
93
7
0
3
0
11
43
43
Available tonne kilometres per employee
49
49
2
0
6
18
47
29
Average turnaround time
76
21
3
0
4
25
32
39
Labour cost as % of total operating cost
87
11
2
0
13
13
43
31
Cost per seat kilometre
90
8
2
0
3
5
11
81
Daily aircraft utilisation (hours)
98
0
2
3
3
10
28
56
Total revenue per Work Load Unit
43
40
17
0
0
0
50
50
Other (please specify)
78
11
11
0
0
0
25
75
Revenue passenger kilometres
Load factor per flight
Not
useful
Financial indicators
Very
useful
Share price
46
Don’t
know
46
8
Earnings per Share
38
54
8
7
7
28
29
29
Price earnings (P/E) ratio
49
43
8
6
0
44
33
17
Operating revenue
93
2
5
0
0
14
25
61
Gearing (debt to equity ratio)
76
11
13
0
12
15
46
27
Revenue to expenditure ratio
75
17
8
0
12
12
34
42
Return on Capital Employed
81
11
8
4
4
7
39
46
Profit
93
2
5
0
3
3
11
83
Operating Costs
95
0
5
0
0
6
14
80
Cash flow
95
0
5
3
0
8
28
61
Other (please specify)
75
0
25
0
0
0
0
100
Yes
No
1
2
3
4
5
6
12
35
18
29
Not
useful
Quality of service measures
Yes
Don’t
know
7
7
No
1
Very
useful
2
3
4
5
Level of service
86
3
0
6
29
62
Baggage delivery time
78
17
5
0
3
25
34
38
Lost baggage
98
2
0
0
0
15
36
49
Check in waiting time
85
13
3
0
3
21
38
38
Consumer complaints
98
2
0
0
2
18
15
65
Other (please specify)
89
11
0
0
0
0
20
80
Not
useful
Environmental indicators
Very
useful
Percentage of passengers using public
transport to access the airport
14
70
Don’t
know
16
Percentage of departures on track
61
27
12
Energy efficiency of installations
managed
32
38
30
Population affected by noise at base
airport(s)
37
58
5
Percentage of waste recycled per annum 27
Number of community complaints about 32
operations
24
CO2 emissions g/rtk
62
11
53
15
54
22
0
0
40
40
20
Fuel consumption and efficiency g/rtk
83
12
5
0
0
9
31
60
Other (please specify)
50
0
50
0
0
0
0
100
Yes
No
1
2
3
4
5
0
17
83
0
0
0
0
12
40
48
0
0
38
54
8
0
14
36
21
29
9
9
18
46
18
0
0
31
61
8
Q4
How does your airline measure its performance in terms of safety?
Q5
What indicators do you use to measure performance in terms of security?
Please turn over ➨
Q6
Is your airline involved in any form of benchmarking?
88
7
Yes
5
No
Don't know
If yes, please locate your airline's experience of benchmarking on each of the following scales:
concerned with
specific tasks
0
18
24
16
24
15
3
concerned with
general practices
more to do with
process improvement
3
28
12
13
16
16
12
more to do with
measurement
mainly internal
comparisons
0
0
9
6
27
43
15
mainly external
comparisons
primarily financial
measures
3
3
19
44
16
12
3
primarily non-financial
measures
using mainly similar
partners
13
43
13
22
3
3
3
using mainly dissimilar
partners
How would you describe your benchmarking experience?
Were your benchmarking activities undertaken with Alliance partners?
49
Q7
Yes
49
2
No
Don't know
So far as you are aware, has your airline introduced any new performance measures in the last two
years?
62
Yes
33
5
No
Don't know
If yes, what performance measures were introduced?
How influential were management consultants in the choice of the new measure(s)?
14
Very influential
26
Not influential
31
Some influence
29
Management consultants not used
What other factors influenced the choice of the new measures?
Q8
Q9
What process do you use to collect performance measurement data?
87
Passenger questionnaires
39
Focus groups
49
Passenger interviews
62
Comment cards
26
Other (please specify)
As far as you are aware, which of the following financial measures are:
• used currently to evaluate the performance of your airline
• being considered for use in the future for your airline
• not being considered
• a measure you are not aware of
Used
Ability to stay within budget
98
0
0
2
Net Profit (loss)
98
0
0
2
Cash Flow
98
0
0
2
44
14
20
22
Economic Value Added (EVA )
35
21
21
23
Residual Income (RI)
24
6
36
33
Return on Capital Employed (ROCE or ROI)
74
5
13
8
Shareholder Value Added (SVA)
28
22
34
16
Other (please specify)
34
16
16
33
Balanced Scorecard
®
Q10
Being
Not being
Not aware
considered considered
Are there any additional comments you would like to make concerning the use of performance
measures?
Please turn over ➨
Would you be interested in receiving the report produced from this study?
86
Yes
14
No
Would you be interested in participating further in this study?
58
Yes
42
No
If yes, please give details to enable us to contact you:
Name
Job Title
Airline
OR ATTACH BUSINESS CARD
Address
E-mail
Telephone number
Thank you for taking the time to complete this questionnaire.
Please return it to Dr. Jackie Fry, The Open University Business School, Walton Hall,
Milton Keynes, UK in the international reply paid envelope provided