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Journal ofPerformanceManagement
The Financial Crisis: Was It Just About Credit Or Was There Another Underlying Issue That We Could Have Seen Coming?
- RICH WEISSMAN -
Organizational Specificities That Affect The Use Of CorporatePerformance Measurements Process In The Banking Sector.
- GUMMA FAKHRI / KARIM MENACERE / ROGER PEGUM -
Strategic Positioning And Capacity Utilization:Factors In Planning For Profitable Growth In Banking
- ANJAN ROY -
Volume 23, Number 3
The Journal of Performance Management seeks articles from management informationprofessionals on subjects related to management information in the financial servides industry.
Manuscripts should be typed with double spacing and generous margins. Please contact AMIfs for complete Manuscript Guidelines prior to submitting your article.
Submit manuscripts to:AMIfs14247 Saffron CircleCarmel, IN 46032
(317) 815-5857 FAX: (317) 815-5877Email: [email protected]: www.amifs.org
All articles in the Journal reflect the views of the authors and should not be construedas the opinions of the Association for Management Information in Financial Services.Contributing authors are required to sign a copyright agreement.
AMIfs Research CommitteeJeff Nathasingh, BBVA Compass, ChairGreg Fitzgerald, AmTrustWilliam Di Filippo, Frost BankChris Rebant, Huntington
The Research Committee can be contacted by email at [email protected]
Copyright ©2011 by the Association for Management Information in Financial Services. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher.
For a complete list of previous Journal issues, refer to theAMIfs web site at www.amifs.org. Orders for previous issues
may be placed directly on the website under the Education page.
TABLE OF CONTENTS 1
Table of Contents
Prologue ......................................................................................................... 2
The Financial Crisis: Was It Just About Credit Or Was There AnotherUnderlying Issue That We Could Have Seen Coming? ............................. 3- RICH WEISSMAN -
Organizational Specificities That Affect The Use Of CorporatePerformance Measurements Process In The Banking Sector. ................... 5- GUMMA FAKHRI / KARIM MENACERE / ROGER PEGUM -
Strategic Positioning And Capacity Utilization:Factors In Planning For Profitable Growth In Banking ................................ 23- ANJAN ROY -
ASSOCIATION FORMANAGEMENT INFORMATION
IN FINANCIAL SERVICES
THE ORGANIZATION
The Association for Management Information in Financial Services (AMIfs) is the preeminent organi-zation for management information professionals in the financial services industry. Founded in 1980 (known then as NABCA), AMIfs has become the premier organization of its type, and counts among its members individuals who set the policies and advance the concepts of management information at major financial institutions worldwide.
ASSOCIATION MISSION
AMIfs is a not-for-profit professional association dedicated to developing and advancing the profession of management information for the financial services industry. Its goals are:
n Leadership: Develop opportunities for members to advance the profession by participating in the Association.
n Research: Identify and coordinate research activities that support the goals of the organization and advance the profession.
n Education & Training: Provide professional development opportunities for industry practitioners.
n Networking: Provide opportunities for members to interact and share experience, knowledge, and insights.
n Other Member Services: Provide related services that add value to membership.
n Infrastructure: Establish and maintain an organizational structure designed to accomplish the Association’s mission through ongoing involvement of industry professionals.
JOURNAL OF PERFORMANCE MANAGEMENT 2
Prologue
The Financial Crisis: Was It Just About Credit Or Was There AnotherUnderlying Issue That We Could Have Seen Coming?
The Financial Crisis: Was It Just About Credit Or Was There Another Underlying Issue That We Could Have Seen Coming?
Rich Weissman, DMAwww.DMAcorporation.com
3
1
How did the meltdown happen? Was it simply poor credit risk management, or was there another fundamental bubble waiting to burst? At DMA, we’ve conducted lot of research to understand meltdowns. For many years, we’ve looked at historical data, and conducted modeling and analysis. We’ve found that the banking and credit union industry had created an unsustainable bubble independent of the credit crisis, and the meltdown could have been predicted. And, this understanding has been translated in measurement systems that can help banks and credit unions develop new risk strategies to stay clear of future meltdowns. The objective is to learn from the past, and focus on those activities that can minimize a repeat. Let’s share our insights. We divide the last 80 years into three distinct cultural phases. Phase 1 began after the Great Depression (“Pre-Deregulation Phase”), where the industry operated under strict regulations. Institutions didn’t compete with each other on products, price, or the ability to sell more. The government determined what could be offered, and institutions differentiated themselves through branch networks and providing quality service to customers/members. This phase ended with an act of Congress in the 1980’s, and the industry quickly adopted the concept of marketing/selling as fundamental (“Sales Culture Phase” – Phase 2). Everyone got on the bandwagon to aggressively market/sell products, compete on price, and focus on three key measures for assessing success: balance sheet growth, sales volumes, cross-sell ratio. Unknowingly, banks and credit unions were creating a bubble in their income statements. Volume-driven cultures create environments in which most products sold, most customers/members served, and most marketing/sales activities are unprofitable. Each year, as banks and credit unions sold more, they created a dependency on a smaller group of products and customers/members for positive earnings. This group got smaller and smaller each year as the banks and credit unions sold more unprofitable products to unprofitable customers/members, creating a bubble waiting to burst. Why? Because it wasn’t a sustainable way of earning profitability. And it burst with the credit crisis. Could this have been seen? Sure! We call it “Profit Risk”, a term we developed and coined some time ago that did indeed predict the meltdowns. How? It’s all in understanding the increasing concentration of the income statement in fewer and fewer products and customers/members as sales volumes increase over time, ultimately leading to unhealthy concentration levels that can act as predictors of meltdowns.
JOURNAL OF PERFORMANCE MANAGEMENT 4
2
The problem is that although institutions track the bottom line, very few know how they got there, and most do not understand how to manage the income statement from a “Profit Risk” perspective. Sure they manage credit risk and asset-liability risk, but they are not managing the income statement for its concentrations in its product lines, customers/members, markets, branches, or sales officers. This lack of “Profit Risk” management forms the foundation for the meltdown of the income statement. What should banks and credit unions do? First, they need to understand that just selling more only creates greater concentrations, which lead to meltdowns. Second, they need to enter the next phase (“Profitability Phase”). Phase 3 is about understanding the income statement in the most micro analytic way, and correlating its components with future earnings growth/loss, and then managing to maximize future income growth and minimize future income losses. An institution can watch its earnings grow, but if those earnings are heavily concentrated, then earnings can quickly head south before the institution sees it coming. A “Profit Risk” system and analytics show that there are tipping points at which earnings will become volatile and decline over time as concentrations increase, even in a rising earnings environment. Quantifying and measuring these points, and developing specific strategies and tactics to minimize “Profit Risk” and ensure long-term sustainability of the income statement, is what banks and credit unions need to do. What should you do differently? Get started and learn about “Profit Risk” and how to measure and manage it, and have a new crystal ball. Phase 2 thinking has to go. You need to understand your income statement in altogether new ways, and you need to adopt a Phase 3 culture as a fundamental culture, based on assessing concentrations and developing strategies to minimize the concentrations so that the income statement is sustainable. That’s a good starting point.
1
How did the meltdown happen? Was it simply poor credit risk management, or was there another fundamental bubble waiting to burst? At DMA, we’ve conducted lot of research to understand meltdowns. For many years, we’ve looked at historical data, and conducted modeling and analysis. We’ve found that the banking and credit union industry had created an unsustainable bubble independent of the credit crisis, and the meltdown could have been predicted. And, this understanding has been translated in measurement systems that can help banks and credit unions develop new risk strategies to stay clear of future meltdowns. The objective is to learn from the past, and focus on those activities that can minimize a repeat. Let’s share our insights. We divide the last 80 years into three distinct cultural phases. Phase 1 began after the Great Depression (“Pre-Deregulation Phase”), where the industry operated under strict regulations. Institutions didn’t compete with each other on products, price, or the ability to sell more. The government determined what could be offered, and institutions differentiated themselves through branch networks and providing quality service to customers/members. This phase ended with an act of Congress in the 1980’s, and the industry quickly adopted the concept of marketing/selling as fundamental (“Sales Culture Phase” – Phase 2). Everyone got on the bandwagon to aggressively market/sell products, compete on price, and focus on three key measures for assessing success: balance sheet growth, sales volumes, cross-sell ratio. Unknowingly, banks and credit unions were creating a bubble in their income statements. Volume-driven cultures create environments in which most products sold, most customers/members served, and most marketing/sales activities are unprofitable. Each year, as banks and credit unions sold more, they created a dependency on a smaller group of products and customers/members for positive earnings. This group got smaller and smaller each year as the banks and credit unions sold more unprofitable products to unprofitable customers/members, creating a bubble waiting to burst. Why? Because it wasn’t a sustainable way of earning profitability. And it burst with the credit crisis. Could this have been seen? Sure! We call it “Profit Risk”, a term we developed and coined some time ago that did indeed predict the meltdowns. How? It’s all in understanding the increasing concentration of the income statement in fewer and fewer products and customers/members as sales volumes increase over time, ultimately leading to unhealthy concentration levels that can act as predictors of meltdowns.
Organizational Specificities That Affect The Use Of Corporate Performance Measurements Process In The Banking Sector. 5
Organizational Specificities That Affect The Use Of CorporatePerformance Measurements Process In The Banking Sector.
Gumma Fakhri1
Karim Menacere2
Roger Pegum3
1
Organizational Specificities that affect the Use of Corporate Performance Measurements Process in the Banking Sector.
Gumma Fakhri1
Karim Menacere 2 Roger Pegum3
Abstract
The paper tries to explore the use of multiple-perspectives of performance measures in the context of performance evaluation within the banking sector. It will also examine the impact of some organizational specificity of the use performance measures. Hence, this paper identifies the reality of measures perspective taken from the performance measurement literature, and investigates the impact of five chosen organizational individuality (e.g. the nature of bank services, the customers’ demands, size of bank, and the listing on stock market) on the use of performance measures. Based on a scale survey in a sample of 55 respondents from sampled banks, the study develops hypotheses concerning the paper objectives, and uses descriptive and inferential statistical analysis in order to determine and assess the underlying impact of using multiple performance measures. The findings of this study have revealed that most of the respondents sample put their emphasis greatly on financial measures as a primary approach to evaluate performance, although several banks are adopting the non financial measures, and they tend to implement customer related measures and learning and employee growth measures more frequently. The study has also discovered that there are significant differences in the use of financial and non financial measures according to banks' characteristics (nature and particularities) of banks, which lead to have varied perspectives in the use of performance measures in the banking sector. Keywords: Performance Measurements, Banking sector, Management Accounting.
1.1 Introduction
Drury, (2004) suggests that the management accounting literature underlines the
importance of performance measurement process and how performance measurement
systems play an important role in the financial success of the organisation, and as a source
which provides appropriate information about internal activities. Therefore, firms focus on
the use of performance measures to allow managers to make basic decisions in order to
achieve organisational objectives. In this regard, Anthony and Govindarajan (2001) 1 Faculty of Business and Law at Liverpool John Moores University +44(0)151 231 3858 E: [email protected] 2 Faculty of Business and Law at Liverpool John Moores University +44 (0) 151 231 3593 E: [email protected] 3 Faculty of Business and Law at Liverpool John Moores University +44 (0) 151 231 3849 E: [email protected]
JOURNAL OF PERFORMANCE MANAGEMENT 6
2
stresses that performance measures are important for managers to track and to measure
performance for their subunits, as well as for employees at lower levels to understand the
financial impact of their operating decisions. In addition, the importance of use
contemporary performance measures like quality service, customer satisfaction, comes
from the highly competitive financial industry, particularly the banking sector, as well as
in other services and even in manufacturing organisations (Hussain, 2002). Consequently,
measuring the performance of financial and non-financial require special consideration in
this particular kind of service organisation. Although a lot has been written about the need
for accurate measurement of multi-dimensional performance measures, and there is plenty
of research concerning performance measurement, however comparatively very little is
known about performance measurement systems in services and the banking sector
especially in developing countries. Therefore, the main purpose of this paper is to examine
the impact of the characteristics of banks on the use of financial and non-financial with
particular reference to developing countries’ Banks.
1.2 A Brief Literature Review and Development of Hypothesis
1.2.1 Financial Measures:
Financial performance measures are used to provide financial information to the managers
and other users, also to evaluate efficiency and effectiveness. The more popular financial
measures used for example are: return on investment; return on assets; return on capital
employed; and earnings per share (Ittner and Larcker, 2003). Although the use of financial
performance measures is important in performance measurement, researchers seem to
suggest that there are limited in scope. For example, Ittner and Larcker, (1998); Neely,
(1999); Kaplan and Norton, (1996): (2001); and Banker et al, (2000) conclude that there is
agreement about the limitations of financial measures such as, they are too financially
oriented, internal looking, historical and focusing on inputs not outputs, and are short term
oriented. These limitations indicate that financial measures should be expanded to
incorporate the valuation of the company's intangible and intellectual assets such as; high
quality products, motivated and skilled employees, responsive and predictable processes,
and satisfied and loyal customers in order to reflect the assets and capabilities that are
critical for success in today's competitive environment (Kaplan and Atkinson, 1998).
These types of measures can be categorized as non-financial performance measures.
Organizational Specificities That Affect The Use Of Corporate Performance Measurements Process In The Banking Sector. 7
3
Furthermore, Kaplan and Norton (1996) argue that measurement using only financial
measures can damage an organisation’s capacities and they recommend that a combination
of financial and non-financial measures are better suited for evaluating performance.
1.2.2 Non -Financial Measures:
Several recent studies have provided empirical evidence on the positive impact of non-
financial performance measures on the organisations’ financial performance in the long-
term (Anderson and Lanen, 1999; and Banker et al, 2000). Non-financial performance
measures provide managers with timely information concentrated on the causes and
drivers of success and can be used to design integrated evaluation systems (Fitzgerald et
al, 1991; Kaplan and Norton, 1996; Banker et al, 2000). Fisher (1995) states that there are
three main reasons for the emergence of non-financial performance measures: the
limitations of traditional financial performance measures, competitive pressures, and the
growth of other initiatives. In addition, Neely (1999) points out several reasons for this
performance measures revolution such as increasing competition, changing organisational
roles, changing external demands and the power of information technology. This in turn
has led to the recognition that financial performance measures do not present a clear
picture of organisational performance (Bourne and Neely, 2002). Most studies of non-
financial performance measures are related to manufacturing with very few studies
including services firms (Kald and Nilsson, 2000). Several studies (Fitzgerald et al, 1991;
Kaplan and Norton, 2001; Hussain, et al 2002; Lorenzo, 2008) have emphasised the need
to use multidimensional performance measures in the service sector such as the banking
sector. Berry et al (1993) studied performance evaluation in UK bank lending decisions,
they argue that although manufacturing companies tend to emphasise the importance of
non-financial performance measures, bankers are concerned with more financial
performance measures. Ostinelli and Toscano (1994) have assessed the use of non
financial measures namely customer satisfaction and improvement in quality management
as an operational tool of control in three Italian banks. They found that the management
control system was able to integrate both financial and non-financial measures to evaluate
performance. Hussain et al (2002) carried out research on the role of management
accounting practices in non-financial performance measures in financial institutions
(including banks) in three countries Finland, Sweden and Japan. Their study found that
JOURNAL OF PERFORMANCE MANAGEMENT 8
4
contextual factors such as economic, normative, coercive factors have affected the role
and the use of non-financial performance measures in the financial sector in three different
countries. Al-Enizi et al (2006) examined the use of non-financial performance measures
in the Gulf Cooperation Council Countries in four service companies (one of them was a
bank). They suggested that non-financial performance measures have a positive impact on
long-term profitability. Hussain and Hoque (2002) assessed the role of management
accounting in non-financial performance among Japanese financial institutions-banks.
They reported that management accounting has played a key role in measuring
performance in different banks in Japan, but its role in non-financial performance
measures has been less significant than its role in financial performance measures. The
findings concluded that non financial performance measures are needed and the contextual
factors affected the use of non-financial performance measurement in the sample studied.
The above discussion suggests that there are relatively few empirical studies which
directly examine the use of financial and non financial measures for performance
measurement purposes in the banking industry in developing countries. In addition, the
conclusions from related previous studies provide two main arguments regarding the use
of financial and non financial measures. The first argument points out that the use of
financial measures is more common and standardized than non financial measures across
the organization's sub-units as financial outcomes are the primary performance objectives.
The second argument concludes that non financial measures have greater use beside
financial measures in performance measurement systems, because non financial measures
are better measures to driving future financial performance, and they reflect the value of
long term aspects. Over the last decade, the balanced use of financial and non financial
measures for performance measurement have been strongly recommended by scholars and
professionals (e.g. Kaplan and Norton 1996). It could therefore be argued that if financial
measures are still fundamental for performance measurement in the banking sector
context, this paper sets the following hypothesis:
H.1 The banking sector tends to use financial measures rather than nonfinancial
measures more frequently.
Organizational Specificities That Affect The Use Of Corporate Performance Measurements Process In The Banking Sector. 9
5
1.3 Banking Characteristics Influencing Performance Measures
Since the 1980, there have been many studies that focus on different aspects of
management accounting practices especially in performance measurement such as the
relationship with contextual factors (e.g. organistaional size, customers’ demand, nature of
organization, and the joining to stock market) (see for instance Hussain and Hoque, 2002).
The different aspects of the literature will now be investagiated in more detail.
1.3.1 The Impact of Size of Organisation
In response to such economic pressures, management accounting practices become
adaptive to their environment with various degrees of responsiveness, but the
characteristics of the company (e.g. size and type) are a key determinant to the degree of
possible change and adaptation to the economic pressures (Granlund and Lukka, 1998;
and Hussain and Gunasekaran, 2002). As far as the impact of size of organisation of
performance measurement systems, several previous studies (Chenhall, 2003; Ezzamel,
1990) suggest that top management in large firms will implement a multiplicity of
performance measures relative to small firms to motivate managers of different
responsibility centers .For example, Chenhall (2003) indicates that size indeed affects the
design of performance measurement systems: larger organizations use more sophisticated
performance evaluation systems and tend to introduce non-financial measures. In
addition, organisational size might influence the shape of control systems used which
tends to be more sophisticated within bigger firms than smaller ones (Libby and
Waterhouse, 1996; and Speckbacher et al, 2003). In considering the impact of size of bank
on the use of financial and non financial in the banking sector, this study argues that the
size of service of a bank might impact accordingly on the use of financial and non
financial measures in the banking sector. Previous research has indicated that size indeed
affects the design of performance measurement systems: larger organizations use more
sophisticated performance evaluation systems (Chenhall 2003) and tend to introduce non-
financial measures (Hoque and James 2000). This leads to the following hypothesis:
H.2 Size of bank is positively associated with the use of financial and non financial
performance measures.
JOURNAL OF PERFORMANCE MANAGEMENT 10
6
1.3.2 The Impact of Customers’ Demands
The change in customers’ attitudes and behaviour is one of the most important issues
mentioned by the literature as a motive for using non financial measures, for example,
Vaivio, (1999) indicates that customers’ demands could be a basic theme to any
organisation particularly in the service industries, devoting attention to customers leads to
the introduction of some non-financial measures (customer satisfaction measures) which
reflects the customer-organisation relationship. Moreover, there is an increase in the
number of organisations using customer satisfaction measures, due to managers’ belief
that these measurements affect financial performance outcome (Ittner and Larcker, 2003).
However, Anderson and Lanen, (1999) found positive associations between customer
satisfaction and return on investment in Swedish manufacturing organisations, but weaker
or negative connections in service organisations. Given the importance of customer needs,
performance measurement systems should track the change of customer performance
regularly.
H.3 Customers’ demands tend to affect the use of financial/non financial measures
more frequently.
1.3.3 Nature of Banking Industry
It could be argued that the nature of the banking industry is service oriented and depends
on human resources and this nature forced banks management to be very aware about
achieving a high level of quality, on-time delivery, customer satisfaction and loyalty and
employee satisfaction and loyalty in change of business environment. Hussain and
Gunasekaran, (2002) stress that the nature of the banking industry is considered to be one
of the motives for using range of performance measures as mentioned by their study’s
conclusion.
Cobb et al (1995) conclude that banking the activities, like bad loans in multinational
banks, has an impact on practice of non financial performance measures. In addition, Mills
and Morris (1986) argue that customers of services organizations is essential to the
production activities, so, some non financial measures (like quality) could be determined
simply in manufacturing organisations, however in service organizations (like a bank), it
is difficult to assess the quality of its services because of their intangibility and transitory
nature. In this case Smith’s (1998) points out that measurement of the quality of service
Organizational Specificities That Affect The Use Of Corporate Performance Measurements Process In The Banking Sector. 11
7
organisations is notoriously difficult. Seemingly the nature of services affects
performance measurement systems. In considering the impact of the nature of financial
industry impact on non financial performance measures is investigated. This substantive
hypothesis arose from the above discussion and there was no contradictory evidence.
Therefore, the fifth formal hypothesis is:
H.4 “The nature of the banking sector as a service oriented industry is one of
the major motives that affect the use of financial/non financial measures more
frequently.
1.3.4 The Impact of the Stock Market.
Larson and Kenny, (1995) argue that the development of accounting information systems
are fundamental for the improvement of the stock market, because users of accounting
information (e.g. investors) require reliable and fitting information. In addition, Adhikari
and Tondkar, (1992) indicates that there is a significant relationship between the
development of the stock market and accounting information systems particularly in
developing countries. The growing number of listed companies on the stock market
creates a need for new information and services such as specific information such these
about performance information. Furthermore, Doupnik and Salter (1995) suggest that, as
the level of activities increase in the stock market, users of information (i.e. investors and
managers) want more financial and non-financial information about the companies’
activities to assist in making decisions. Relating to the above, this study expects that the
development or establishment of stock market may increase the need for using financial
and non financial measures for performance measurement purposes. Therefore, the
rationale for joining the stock market is that banks aim to improve the adoption and the
uses of non financial performance measures more than non other banks that have not
jointed yet. A null hypothesis statement is used as the basis for this rationale:
H.5 There is no difference between Listed and Unlisted banks in stock market
regarding the use of financial and non financial measures more frequently.
1.4 Research method and survey instrument
The research has been conducted through a questionnaire preceded by an introductory
letter clarifying the purposes and objectives of the entire project. The sample consists of
JOURNAL OF PERFORMANCE MANAGEMENT 12
8
ninety five managers from different types in the banking sector. Among this group of
banks, the researcher contacted managers (include chief executive officer, senior and
branch manager) directly in order to select a list of banks prepared to cooperate with the
research. The survey was carried out by sending a questionnaire during the second half of
2009. After three follow ups by phone calls made to non-respondents to increase survey
response rate, 83 questionnaires (55 usable) were sent back. The final response rate is
about 57% represents an acceptable target when the questionnaire involves top and middle
management levels. The questionnaire was developed and refined as follows: nearly all
items in the performance measures and characteristics factors were adapted from
previously published works. A preliminary draft of the questionnaire was discussed with
my supervision team and some research students at LJMU to assess the content validity
prior to pilot testing; and a pilot test was conducted with a group of five branches, whose
inputs were used to improve the clarity, comprehensiveness and relevance of the survey
instrument.
The questionnaire was structured in two parts. In the first part banks were asked to
indicate on a five point Likert scale – from 1 (not at all important/used), through 3
(moderately), up to5 (extensively) – the extent to which they used a set of performance
measures coming from academic/practitioner management accounting literature (Kaplan
and Norton 1996, 2000; Gosselin 2005). The second part listed some characteristics
related to banks such as the nature of banking services, and size of banks.
o Sample Features
Data was analysed using the SPSS package v15.0. The reliability of the questionnaire was
also verified. Internal consistency was established using Cronbach’s Alpha it was equal
(.815). The first empirical evidence of the survey is shown displayed through the use of
descriptive statistics. Table (1) gives an account about some general information date of
establishing, type of business, ownership, the total of assets, and the state of banks in the
stock market. Table (2) describes the distribution of respondents by the evaluation of the
importance to success of banks and the extent of current used of performance measures. In
addition, adjusting these measures as the size of bank and listing on stock market.
Organizational Specificities That Affect The Use Of Corporate Performance Measurements Process In The Banking Sector. 13
9
1.5 Findings of hypotheses testing
1.5.1 The use of financial and non financial measures
To test H1, the financial and non financial performance measures are ranked according to
the mean of the extent to which respondents from sampled banks are ranking them as
important to success of long term and are using them in aforementioned practices. Table
(1) accounts for the overall diverse measurements, the columns highlight this indicator
which calculates by average standardised rating of importance and using for each category
(financial and non financial measures). This indicator shows that if the level of overall
diverse measurements is up to 3 that means banks use diverse sets of performance
measures at a high level, however if the rate is less than that it means it is not a high level
of use for diverse sets of performance measures. From the table, it could be noted clearly
that the sampled banks are still relying on financial performance measures.
The highest rate of overall diverse measurement colum relate to financial measures which
ranked by mean (3.530) and other the non financial measures are ranked less than the level
of absenteeism (ranked +3). Therefore H1 is confirmed.
1.5.2 The impact of banking Individualities on performance measures
A factor analysis is undertaken in order to classify the measures into categories and to find
out the underlying themes among the 8 items. Principal Component Analysis (table 5)
reveals two interpretable factors with Eigen values greater than 1 that account for 64% of
the variance. The two factors are labelled as follow: customers’ demand (4 items); nature
of banking services (4 items);
To test the remaining four hypotheses a bivariate correlation is undertaken between the
four factors, two of them coming from the Principal Component Analysis (PCA)
(customers’ demand, and the nature of banking services), while the other two factors the
joining of stock market and size of organisation come from general information that
categorize the respondents to listed and unlisted banks and small and large banks
according to the total of assets.
Table (6) shows all the results of this analysis. Kendall’s tau (t) association coefficients
help to determine whether there are some associations among the four factors. These
estimates are accompanied by p-values from statistical significance tests. The size of bank
JOURNAL OF PERFORMANCE MANAGEMENT 14
10
is positively correlated with non financial performance measures while it is so with
financial performance measures but it is not significant. Thus, H.2 (Size is positively
associated with the use of financial and non financial performance measures) is accepted.
With regard to the nature of banking services, it is positively correlated with quality,
financial, employee, and customer measures respectively, but less correlated with
community measures. These results sustain the idea that the nature of banking services
tend to use more non financial measures. Hence H.3 is confirmed.
The customers’ demands are positively correlated with financial and non financial
performance measures (even if these values are not statistically significant). So H.4 (The
customers’ demands are tend to use financial and non financial measures for performance
measurement) is not confirmed.
Banks that are listed in stock market are positively correlated with all performance
measures while unlisted banks are negatively correlated with non financial performance
measures (even if this value is statistically significant). Overall these results appear
coherent with the notion given that listed banks are positively correlated with the use of
non financial performance measures while, at the opposite end, unlisted banks are
negatively correlated. Therefore, H5 (The joining of stock market tends to affect the use of
financial/non financial measures more frequently) is confirmed.
1.6 The Findings and the Literature
1.6.1 The use of financial and non financial measure
In terms of the use of financial and non financial measures this paper provides evidence
that the banking sector is still reliant on financial measures with more attention for some
non financial measures. These results are consistent with findings for number of previous
studies (i.e. Mohamed and Hussain 2005; Ong and Teh 2009; Ismail 2007; Banker et al,
2004; Chen et al, 2006; Frigo and Krumwiede, 2000).
The possible reasons for above result are that many sampled banks still adopt conventional
accounting practices in addition to insufficiency of qualified accountants and dominance
of Central Bank as monitor. Regulations exclude sampled banks from requiring
permission to create new internal change.
Organizational Specificities That Affect The Use Of Corporate Performance Measurements Process In The Banking Sector. 15
11
1.6.2 The impact of bank size on the use of financial and non financial
measure
The size of bank as measured by total of assets has emerged as one of the motives
encouraging the use of financial and non financial measures. The results indicate that there
is a significant relationship between size of bank (total of assets) with the extent of using
financial and non financial performance measures. as this result has already been achieved
by some of previous study such as Verbeeten, 2004.
1.6.3 The impact of customers’ demands on the use of financial and
non financial measure
The results indicate that there i a weak relationship between customer’s demand and the
extent of using financial and non financial performance measures. This result is nearly
similar for Al-Enizi et al’s study in 2006.
1.6.4 The impact of nature of banking services on the use of financial
and non financial measure
The nature of the banking sector emerged as a purpose leading to the use of financial and
non financial measures. This finding is in agreement with previous findings or statements
in the literature (see, for example, Cobb et al, 1995 and Hussain and Gunasekaran, 2002).
1.6.5 The impact of joining the stock market on the use of financial
and non financial measure
The results confirm that there is relationship but not significant between joining the stock
market and the extent of using financial and non financial performance measures. The
study did not find support for this finding in the literature.
1.7 Limitations of the study
The aim of this paper is to contribute to a better understanding of what performance
measures are used by managers in the sampled banks. Specifically this paper upgrades the
existing theory, establishes relationships between contingencies factors and performance
measures with contingency theory and shows some results that it would be interesting to
JOURNAL OF PERFORMANCE MANAGEMENT 16
12
develop further. However, this paper has some limitations. Finally, the sample comes from
the banking sector without considering other perspectives (e.g., manufacturing, another
services). In addition the sample was chosen from the banking sector in developing
country which is not be able to generalize the findings to other banking sector within
developed countries like the UK. Furthermore the paper does not consider how these
contingency relationships may impact on the organisational performance and what
combinations of performance measures can lead to improve financial results and
organizational behaviour with more regular use.
o Acknowledgement
Special thanks are owed to my two supervisors who assisted in this paper, Dr. Karim
Menacere and Dr Roger Pegum for their guidance, helpful and insightful comments. In
addition, I am also grateful for the financial support provided by Libyan Bureau Cultural
affair in London.
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16
Appendices:
Table (1) Description of banks covered by the classification of survey Classification Of banks by year of establishing business typology:
Number (%) Before 1980
42 (76.5) Between 1991-2006
8 (23.5)
Classification of banks by ownership typology :
Number (%) State-owned (public bank)***
28 (51.5) Private
PAPP* 14 (25.0)
PSE** 12 (23.5)
Classification of banks by total of assets typology: Number (%) Less than 100
9 (16.5) Above 100 46 (83.5)
Classification of banks by Listing on Libyan Stock Market: Number (%) Listed Unlisted
23(41.2) 18(39.8) State-owned public bank*** = (the state owns more than 50% of their shares), PAPP*= private after process of privatisation (before that they were public), PSE**= private since establishing
Table (2) extent of use of performance measurements
Table (3) The customers’ demands
Mean Std. D
Comparisons of survey results by Typologies:
Listing on SM Size Ls Unls S L
Financial 3.706 0.774 3.600 3.814 3.686 3.765
Customer 2.985 0.837 2.857 3.116 3.020 2.882
Employee 2.324 0.742 2.257 2.388 2.412 2.059
Quality 3.206 0.907 3.171 3.234 3.196 3.235
Community 2.250 0.655 2.286 2.217 2.255 2.235 UNL un listed banks, L Listed banks, S small banks, L large banks, SM stock market
The level of importance Mean
Std. D
Comparisons of survey results by Typologies:
Listing on SM
Size
1/ 2 3 4/5 Ls Unls S L Customer demands in banking industry is a critical factor that affects the use of performance measures in different banks
70.6 26.5 2.9 2.118 0.763 1.657 2.608 2.314 1.529
The bank checks its customer satisfaction regularly, although it requests high cost to obtain.
76.4 23.5 0 1.897 0.756 1.371 2.454 2.098 1.294
Organizational Specificities That Affect The Use Of Corporate Performance Measurements Process In The Banking Sector. 2117
Table (4) The nature of banking services
Table (5) Factor analysis Rotated Factor Matrix for 8 items
Components The nature of
banking services Customers’ demands
The banking industry is influenced by the changes in the level of progress in IT services. 0.5778 It is extremely difficult to predict another bank competitive move. 0,6464 It is intricate to predict and keep up with changes in the governmental (The Central Bank of Libya) regulations. 0,8329
Banking attributes and methods of service are constantly adapting to change and therefore unpredictable. 0,8651 Customer demands in banking industry is a critical factor that affects the use of performance measures in different banks 0,6326
The bank checks its customer satisfaction regularly, although it requests high cost to obtain. 0,7431
Bank’s management believe that customer attained is key factor that affects the use of performance measures. 0,5878
There is an increasing change in the customers’ demands and attitude regarding banking service. 0,5491
Eigenvalues 4.231 4.148 % of variance 10.07 9.875 Cumulative % 10.07 19.95
Table (6) Correlation Matrix (Tau (t) Kendall association measure
Size of bank
The nature of services
Customers’ demand
Listing on SM
Bank’s management believe that customer attained is key factor that affects the use of performance measures.
47.1 35.3 17.6 2.588 1.011 2.000 3.221 2.824 1.882
There is an increasing change in the customers’ demands and attitude regarding banking service.
1.5 51.5 47.1 3.603 0.756 3.657 3.550 3.706 3.294
Level of importance of
nature of banking services
Mean Std. D
Comparisons of survey results by Typologies:
Listing on SM
Size
1 2/3 4/5 Ls Unls S L The banking industry is influenced by the changes in the level of progress in IT services.
17.6 78 4.4 2.236 0.794 2.200 2.272 2.353 1.882
It is extremely difficult to predict another bank competitive move. 29.4 69.1 1.5 1.985 0.782 1.943 2.033 1.980 2.000
It is intricate to predict and keep up with changes in the governmental (The Central Bank of Libya) regulations.
47.1 53 0.0 1.588 0.604 1.457 1.721 1.667 1.353
Banking attributes and methods of service are constantly adapting to change and therefore unpredictable.
22.1 69.1 8.8 2.206 0.890 1.771 2.662 2.392 1.647
JOURNAL OF PERFORMANCE MANAGEMENT 2218
Financial 0.079 0.065 .334(**) 0.138 Customer .192(*) 0.122 .282(**) .358(**) Employee .432(**) 0.001 .330(**) .454(**)
Quality .578(**) 0.032 .370(**) .498(**) Community .407(**) 0.133 .210(*) .403(**)
** Correlation is significant at the 0, 01 level (two - tailed). * Correlation is significant at the 0, 05 level (two - tailed).
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 23
Strategic Positioning And Capacity Utilization:Factors In Planning For Profitable Growth In Banking
Anjan RoyAssistant Professor
National Institute of Bank ManagementMaharashtra, India
1
Strategic positioning and capacity utilization:
Factors in planning for profitable growth in banking
Anjan Roy Assistant Professor
National Institute of Bank Management Maharashtra, India
1.0 Introduction
Banks are motivated to grow and acquire large size and market share, often with the
expectation of gaining “too big to fail” advantage as well as higher profitability.
Higher profitability is expected to accrue from market power (Rhoades, 1982;
Gilbert, 1984) and/ or superior efficiency (Demsetz, 1973; Peltzman, 1977). While,
the market power hypothesis has been supported in studies of U.S. (Berger and
Hannan, 1989; Jeon and Miller, 2005; Tregenna, 2009) and European banking
(Molyneux and Thornton, 1992), the efficiency hypothesis has also been supported in
studies of US (Smirlock, 1985) and Portuguese banking (Mendes and Rebelo, 2003).
Maudos (1998) has reported both sources of profitability from their study of data in
Spanish and German banking.
Some other set of studies, interestingly, suggest that larger size may have
inverse impact upon profitability. Berger, Hanweck and Humphrey (1987) found that
bank costs reduce only slightly with size and very large banks often even face scale
inefficiencies. Schwartz (2007) reported that large banks do not have sustained
advantages in funding costs over small banks. Rapoport (2007) found smaller
community banks as having higher net interest margin than regional and large
diversified banks. Kosmidou, Tanna and Pasiouras (2005) found that size has
JOURNAL OF PERFORMANCE MANAGEMENT 24 2
negative impact over bank profits. Few others such as Goddard, Molyneux and
Wilson (2004) and Micco, Panizza and Yanez (2007) report only a weak relationship
between bank size and profitability. Some studies (Gallick, 1976; Hughes and Mester,
1993) have reported that the positive relationship between size and profitability exists
only over small to medium size groups.
While the size-profitability relationship remains inconclusive, the evidence of
negative impact of size on profitability arouses concern. Why must banks lose
profitability as they grow bigger? This study points towards certain factors behind the
size-profitability paradox in banking that have been left largely unaddressed. In
particular, it looks at the shortcomings in the planning practices that might prevent a
bank from achieving growth with profit. Planning function in banks may lack
strategic perspective of managing a multi-unit organization. In consequence,
therefore, they may fail to reap the benefits and efficiencies from diversification. By
making use of a well known growth-share matrix and an industrial cost-capacity
framework, the lack of planning view on strategic positioning and capacity
constraints is illustrated.
In section 2.0, studies discussing issues of planning in banks are reviewed to
construct the background to the problem of lack of profitable growth. In section 3.0
and 4.0, the frameworks for strategic positioning and capacity constraints
respectively, are discussed. In section 5.0, the industry and organizational context of
the bank is reported along with the findings from applying the frameworks to the
business and performance data of the bank. In section 6.0, the findings are put
together to reveal gaps in the planning process and the need for revised allocation of
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 25 3
growth target and/or resource budget. In concluding, it is suggested that banks
attending to both market positioning and capacity constraints during planning are
likely to be better at delivering profitable growth performance.
2.0 Planning for growth and profit in banking
Profitable growth of a bank can be constrained by external factors such as economic
environment, target market, industry structure, etc. as well as internal factors such as
branch network, technology and managerial capability for innovation and
differentiation, marketing, customer relationships, etc. While the external factors can
be beyond control of individual banks, bank management is responsible for astutely
positioning its business to achieve the right “fit” and foundation for performance.
Haslem (1968) has long back identified differences in management as one of
the key factor contributing to the difference of profitability between banks.
Subsequent studies such as by DeYoung (1994), Punt and Rooij (2001) have pointed
out to “X-efficiency” and management quality as a crucial factor explaining
profitability and financial performance of banks. Sarkis (1999) noticed that output
prices of banks tend to fall as they grow in size because their product mix evolves
from high margin geographically focused retail products towards diversified products
including those with marginally profitable activities. Pilloff and Rhoades (2002)
further reported that while bank concentration in local markets is significantly related
to profitability, though there is not enough evidence to support such relationship at
the bank level (Larreche, 1980 in Wind and Mahajan, 1891; Goddard et al., 2004).
These observations suggest that as banks expand into different markets and lines of
JOURNAL OF PERFORMANCE MANAGEMENT 26 4
businesses to grow in size and complexity, planning issues on both cost as well as
revenue side become imminent. Banks need to cultivate their planning expertise
commensurate with the pace of growth (Hopkins and Hopkins, 1997). An important
aspect of planning in a multi-unit enterprise such as a bank is about allocative
efficiency. Allocative efficiency refers to achieving the right combination of inputs to
produce outputs, leading to the best possible utilization of market potential as well as
resource capacity. Several studies have reported the impact of allocative efficiency on
performance in banks to be non-trivial (DeYoung, 1994; Brissimis et al., 2010). Al
Shamsi et al. (2009) have pointed out that allocative inefficiency rather than technical
inefficiency has been the dominant source of inefficiency in UAE banking.
Literature on planning process inform that planning in banking has evolved
over time from performance budgeting to long range planning and strategic planning
(Wood, 1980; Austin, 1990; Bird, 1991) and impacted bank performance (Wood and
Laforge, 1979; Newkirk-Moore, 1995). However, the link between planning and
performance has been questioned (Gup and Whitehead, 1989; Whitehead and Gup,
1985). Prasad (1984) has pointed out that planning in banks is primarily based on
price information (i.e. cost of money) which is not enough to make decisions for
competitive operational advantage. Austin (1990) has suggested that bank planning
must enable market share penetration and, therefore, involve evaluation of market
potential through analysis of underlying financial and economic strengths. Planning
and target setting in banks have, however, been found to involve as many as twenty
indicators including several superfluous ones (Lovell and Pastor, 1997) and,
therefore, Rogers et al. (1999) have suggested that planning system design in banks
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 27 5
must address the required type and amount of information relevant to its strategy.
More recent literature on financial crisis and bank behavior, however, indicate that
banks are often prone to “herding” (Rotheli, 2001; Acharya and Yorulmazer, 2008),
such as in respect of credit (Uchida and Nakagawa, 2007), branching (Chang et at.,
1997) and pricing (Alhadeff, 1980) decisions, which may potentially undermine the
planning function.
Literature on strategic management of the firm has the positioning school and
the resource-based view as the two most acknowledged and practiced approaches to
achieve sustainable competitive advantage. While the former stresses the selection of
strategic positioning amidst competitive forces in the market (Porter, 1980), the latter
posits the role of the firm‟s resource capacity, in particular its managerial
competencies (Penrose, 1959; Barney, 1991), as the foundation for profitable growth.
Planning processes in banks may not address the strategic factors - market positioning
and capacity constraints - adequately thereby leading to growth at the expense of
profitability. The necessary requirements for growing profitably is that, the bank must
be positioned in markets where (a) growth potential exists, (b) it is competitively
positioned with respect to the peer banks and (c) it has the internal capacity to grow.
Strategic planning of growth with profitability involves assessment of these three
aspects, and appropriate allocation of targets and resources, for the business units of a
bank.
3.0 Strategic positioning
JOURNAL OF PERFORMANCE MANAGEMENT 28 6
Banks operate in multiple markets that are usually defined in terms of product
categories (loans, deposits, payment, fund transfer, custody, etc), customer segments
(business, professionals, pensioners, salaried, etc), etc. Usually, however, banks are
organizationally structured into geographical units (country, region, district, city,
etc.), signifying the key markets where they are present. In order to have greater
stability and profit efficiency, banks must have competitive power in the markets they
operate (Ariss, 2010). Market power is indicated by the share of market, which has
been extensively studied for its effect upon profit performance. Market share stems
from the attractiveness of a bank in terms of the spread of branch network, match
between its product offerings and customer needs and distinctiveness of its service
differentiation. It is important for a bank to select and position itself in certain target
markets in order to define the space and potential for profitable growth. Positioning,
in strategy parlance, means making the choice of niche, or locating in the product
market domain (Mintzberg, 1987). The positioning school of strategy has typically
used analytical frameworks and matrices, such as Ansoff‟s matrix, Boston Consulting
Group‟s (BCG) matrix, etc. to create certain positions and performance categories.
For a multi-market business such as a bank, positioning is closely related to strategic
planning, which involves setting priority rules for allocating targets and resources to a
mix or portfolio of markets such that the potential and capacity is optimally utilized to
ensure net positive earnings along with growth.
Henderson (1968) formulated the BCG matrix relating profitability and
growth rate to provide a framework for evaluating decisions regarding investment and
growth for a portfolio of product businesses or market segments (Figure 1). This
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 29 7
planning matrix is based upon the principle of balancing cash flow requirements
amongst businesses keeping in view the life cycle stages of the business.
Accordingly, product sales growth rate of business units are plotted on the vertical
axis of the matrix with a horizontal line (usually representing 10% growth rate)
demarcating between high and low growth rates. The relative market share of product
business as against the nearest rival has been used as a proxy for profitability (Buzzel,
Gale and Sultan, 1975) and is plotted on the horizontal axis on a log scale where a
value of 1.0 indicates the demarcation between low or high market shares. In this way
the portfolio of growth markets has been classified into categories such as wildcat
(also called as problem child), star, cash cow and dog.
Gro
wth
rate
20%
15%
10%
5%
2%
1%
Star
Wildcat
Cash Cows
Dogs
10x 5.0x 3.0x 2.0x 1.0x 0.5x 0.3x 0.2x 0.1x
Relative Market Share
Figure 1: BCG market share – growth rate matrix
The wildcat is a market segment that is at the growth stage of development
whose ultimate business potential is unknown but expected to be good. This segment
demands heavy investments and cash inflows without any immediate generation of
profits or earnings. Investment in this segment is, therefore, to lay the foundation for
future business earnings and cash inflows. The growth decision strategy for such
JOURNAL OF PERFORMANCE MANAGEMENT 30 8
market is to continue investments towards obtaining a dominant market share. In the
absence of significant market share gains, this segment may require to be redefined or
withdrawn from. The star is the developed product market generating positive
earnings but still requiring continuous investment for increasing their market share.
The near term earning potential for such markets is proven and, therefore, is a strong
contender for growth and management attention. The key strategy for star markets is
to maintain the growth spree despite of low (or even negative) cash inflows. Cows are
the most mature product market segment where growth in market share is low but still
high yielding. This market does not call for growth strategies but need investments to
maintain the market share and positive cash inflows. Such segments are usually
milked for their cash inflows which are diverted to other growth markets demanding
cash outflows. Dogs represent the declining market segments whose attractiveness to
the firm has become diminished owing to their low earning potential. They tend to
have negative cash flows when turned on growth but are positive cash flow
generators when the capacities are deliberately shrunk. The key strategy
recommended for such a market is withdrawal and unlocking of resources or
repositioning of the offerings appropriately to counter competition. In this way, the
BCG matrix provides a system of priorities for investment and allocation of funds
between businesses with the highest priority accorded to the star followed by wild cat
and cash cow.
The BCG matrix has been a widely used technique for planning of business
portfolio (Morrison and Wensley, 1991; Olsen and Ellram, 1997) although its effect
on corporate performance is yet to be conclusively agreed upon. Earlier studies such
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 31 9
as Hambrick, MacMillan and Day (1982) have found that businesses actually differed
in their strategic attributes and performance according to the two dimensions of the
BCG matrix, studies such as by Armstrong and Brodie (1994) have pointed out that
the use of BCG technique could also lead to selection of projects and businesses that
were less profitable. Also, the two dimensions of the matrix are insufficient to define
market exhaustively and many real life observations do not seem to fit well into the
matrix‟s descriptions (Thompson and Strickland, 1983). Subsequently, therefore,
frameworks such as General Electric‟s Attractiveness-Strength Matrix and Shell‟s
Directional Policy matrix (Robinson et al., 1978) have used several factors to
characterize industry attractiveness and business strength thereby enabling
identification of different market positions. These frameworks, however, have been
found to be more complex (Hax and Majluf, 1983) and have found much lesser
application in practice (McDonald, 1990). The strength of the BCG matrix has been
its simplicity, though its application has been prone to oversimplification (Seegar,
1984).
The BCG matrix may not be readily applied to planning process in the
service industry (Carman and Langeard, 1980) and particularly in banking owing to
the intangible nature of input and output markets, which are also often overlapping.
Banks primarily operate in deposit and advance markets that may be related and
accordingly the service output in banking can be viewed differently as intermediation
(where deposit forms the input resource along with establishment and human resource
costs and advances the output) or as financial service (where both deposit and
advance are the service outputs with establishment and human resources as input).
JOURNAL OF PERFORMANCE MANAGEMENT 32 10
Banks have often contradicted the positive relationship between market share and
profitability (Wind and Mahajan, 1981) and are unlike other businesses where dogs
can be divested easily. Analogous to the BCG matrix, Boussofiane et al. (1991) and
later Camanho and Dyson (1999) have suggested the efficiency-profitability matrix,
for the banking industry. In this matrix, bank branches have been classified into four
quadrants as stars, sleepers, question marks and dogs. Units that are in the star
quadrant are benchmarks for good operating practice. The sleepers are profitable but
inefficient. These units face a favorable business environment but are the prime
candidates for efficiency improvement. Question marks have potential for both
greater efficiency and profitability. Branches in the dog quadrant are operating
efficiently but are relatively low on profitability owing to unfavorable business
environment. Calandro and Lane (2007) and Alexakis and Tsolas (2009) have also
applied the matrix to banking, though not as a portfolio organizing tool, but to study
the competitiveness of banks in the Greek banking industry.
The BCG Matrix, however, can be applied in banking for determining the
relative growth and profit potential for the various markets in which a bank operates.
The strength behind this assertion is drawn from the fact that banks operate through
similar business units in various geographical locations, which operate as
independently but together constitute its market portfolio. Financial need of
households and, therefore, markets for deposit and loans demonstrate life cycle
behavior (Roy, 2003) following changes in demography, income and competition
from initial expansion to maturity and saturation. Old branches often face stagnation
while new branches that address new generation customers with technology based
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 33 11
services may grow rapidly. Planning function in banks comprises mainly the
allocation of growth targets and resource budget to the various deposit and advance
markets depending upon the life cycle stage. Matching fund flows between markets is
a key result area of planning function that might be helped from the use of the matrix.
Besides, regulation does provide for rationalizing and repositioning of loss making or
under-performing branches.
While market growth data can be obtained from external market research
sources, market share data may not be readily available to reveal the business unit‟s
relative share in its service area. For this, the cost of deposit or yield on advances can
be used as a proxy of market share in the deposit and advance markets respectively.
This argument flows from the fact that banks having large market shares in local
markets can exercise power over competitors through their pricing of loans and
deposits. Rhoades (1992) and Edelstein and Morgan (2006) have used loan and
deposit rates as indicators of market sizes of banks. Vajanne (2010) has also inferred
market power from retail deposit interest rates in the Euro market. Average growth
rate and cost (yield) of the bank can be used as heuristic criteria to cut off between the
different performance groups. Combining the deposit and advance market categories
into a strategic planning matrix (Table 1) leads to the relative allocation of operating
budgets to different business units. The allocation is based on the simple logic of
providing the highest incremental budget (indexed as 1.0), from the total cost budget
for the bank, the region having the highest growth potential. The star category of
business areas receive the highest incremental budget of 1.0 compared to the wildcat,
cash cow and dog categories who receive 0.8, 0.5 and 0.3 respectively. Businesses
34JOURNAL OF PERFORMANCE MANAGEMENT 12
have budget allocations based upon both deposit and advance potential (each being
given equal weights) and are normatively expected to have allocations between a
maximum and minimum relative to the next higher and lower category respectively.
Table 1: Relative plan allocation of budget for different business markets
Market Advance
Category Star Wildcat Cash Cow Dog
Dep
osit
Star 1.00 0.80 0.50 0.30
Wildcat 0.80 0.60 0.40 0.20
Cash Cow 0.50 0.40 0.30 0.10
Dog 0.30 0.20 0.10 0.05
4.0 Capacity utilization
The business model of a bank or the design of production and delivery operations also
imposes certain constraints to its growth. Banking is a labor-intensive multi-product
service wherein increased specialization can generate more economic methods of
production. Operating above certain measures of size and scale, therefore, leads to
proficiency of function and technical efficiency (Sarkis, 1999) and provide increased
possibilities of risk diversification. Banks also use other resource inputs such as
branch and technology whose establishment is often determined by competitive
considerations. For example, extent of branching and provision for access to the bank
constitutes the major strategy for differentiation and non-price competition. Banks set
up excess capacity for such reasons and usually face rigidities in adjusting the same
partly because these capacities are sunk or other restrictions such as labor market
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 35 13
rigidities prevail. Consequently, a significant portion of bank inputs are quasi-fixed in
the short run. Depending on level of technology there exist certain minimum efficient
scale of operations above which banks enjoy production economies of scale and
scope to achieve cost reduction from growth in output (Gramley, 1962; Tadesse,
2006). However, increasing returns to scale are experienced only until a certain size
of output (Clark, 1988; Wheelock and Wilson, 1997) above which constraints in one
or more resources may lead to diseconomies of scale. Banks, therefore, have a U
shaped cost capacity curve based on their balance sheet assets.
Capacity based metrics have not been widely applied in planning of banks and
financial service firms (Spaller and McDonald, 2003). Studies to determine scale and
capacity utilization have mainly used econometric methods often with restrictive
assumptions regarding input and output, for example assuming all inputs into the
production function are variable (Hunter and Timme, 1995) or neglecting the
financial service, or off balance sheet output, of the bank (Clark, 1996). It has also
been found that scale economies exist at business unit level, but the same may be
limited at the bank level (Durkin and Elliehausen, 1998). Such dynamics have not
been explained as much in the literature on scale and capacity in banking, whereas it
is important for bank managers to recognize when such limits are reached to prevent
the ensuing diseconomies and increase in cost.
In this regard, the model for estimation of capacity in manufacturing
industries has been found to be useful. The industrial model assumes firms to be
operating with certain fixed inputs in the short run that constrain the growth of output
beyond a certain best operating level. Firms‟ first attempt to increase production
JOURNAL OF PERFORMANCE MANAGEMENT 36 14
beyond a breakeven point, defined by the level of fixed cost and contribution from
sale, and then attempt to manage their operations within the range of scale economies.
Accordingly, a cost capacity curve can be drawn for the firm‟s operations to indicate
the capacity position at which it is operating. The formulation in Table 2 is derived
from the industrial model to construct the cost-capacity curve for banks using loss in
profits (or increase in costs) along with capacity utilization with reference to a
calculated breakeven level of intermediation volume. Inputs to the model (II, IE, FC,
AV, NII, AOP) can be obtained from annual report of performance of a bank or its
business unit.
Table 2: Formulation for constructing the cost-capacity curve
Interest earning rate (interest earned / total earning assets) ii
Interest expense rate (interest paid / total earning assets) ic
Interest spread ii-ic
Breakeven asset size bevsz cstfx / (ii – ic)
Where Fixed cost cstfx
Current capacity level (as percent of breakeven asset size) (actsz – bevsz) / bevbv
Where Actual asset size actsz
Expected operating profit expop actsz * (ii – ic) + incoth
Where Other income incoth
Profit efficiency (as percent of expected operating profit) (expop – actop) / expop
Where Actual operating profit actop
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 37 15
In the model, bank capacity has been defined in terms of its earning assets, or
the sum of advances and investments, reflecting its key function as financial
intermediary. However, the capacity of a bank in a given economic condition depends
upon its ability to provide a required threshold of access to their services, which is
determined by its fixed operating cost on branch, human resource and other channel
infrastructure. Accordingly, the level of fixed cost can be linked to the intermediation
capacity of the bank. Table 2 presents a model for the breakeven asset size a bank
needs as a financial intermediary, given its in vestment in service facilities. Interest
spread is the contribution from the intermediation function, which is largely
dependent upon external factors. Banks often find it difficult to adjust service
capacity (because of their quasi-fixed nature) with change in demand and hence
attempt to de-link the spread by engaging in off balance sheet activities beyond
financial intermediation. Banks, therefore, have income other fee based and non
interest income that reduces their fixed cost “burden” and enables them to improve
their cost efficiency. This stretch in use of capacity might lead to increase or decrease
of total costs for the bank depending upon the current utilization of capacity. The
cost-capacity curve can be determined by plotting the trend of loss in profit against its
level of capacity use (as percent additional business over breakeven volume).
The above formulation can also be applied to determine the relative cost
capacity plotting of business regions of a bank for any given period (Table 3). On the
Y axis the anticipated loss in profit (or higher incidence of cost) is plotted while the
level of capacity use (over the theoretical breakeven point) is shown in the X axis.
Using the bank average of capacity use level and loss in profit to segregate between
JOURNAL OF PERFORMANCE MANAGEMENT 38 16
the low and high performance levels, four quadrants can be carved out. The lower left
quadrant indicates to the regions facing stagnation. In the upper left quadrant are the
regions that are resource wasting. These regions are grossly underutilizing their
capacity leading to higher cost burden. The lower right quadrant has regions having
well utilized capacities that are also able to manage with lower cost. The upper right
quadrant has the regions that are clearly stretched at their current use of capacity
leading to high operating costs.
Table 3: Classification of regions based on cost-capacity position
Capacity level
Low High
Loss
in
prof
it
High Under Utilized Stretched
Low
Stagnant Well Utilized
5.0 Industry and organizational context of the study
The study has been situated in the context of banking industry in India where, since
liberalization, although banks have improved their cost efficiency, their profit
efficiency has declined (Sensharma, 2005; Das and Ghosh, 2009). Cost efficiency has
improved as banks expanded their scale of operations (Rezvanian et al., 2008),), but
inefficiencies have been discerned on the revenue side of the banking activity in
particular from losses due to allocative inefficiency (Das and Ghosh, 2009). Kumar
and Gulati (2010) have found out that improvement in cost efficiency has been driven
mostly by technical efficiency rather than allocative efficiency. Das and Kumbhakar
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 39 17
(2010) have even pointed out that many state owned banks are operating far above
their efficient scale and cost savings can be obtained by reducing their size of
operations.
Bank organizations in India are structured into geographically based regions
and branches. Historically, planning in banking has been equated with target setting
and budgeting for the various regions and branches (Mote and Shah, 1972). Mote and
Shah (1972) have criticized planning processes to be mechanistic and lacking formal
use of business environment data. Kaura (1983) found that branch performance
budgets are influenced mainly by (a) past performance of the branch, (b) policy
guidelines of the head office and (c) policy guidelines of regional office.
Environmental data of the branch usually came last in determining the performance
budget. Relying on historical data for past performance, banks have pursued growth
through their already large business units. However, correlation between data of
regional business sizes and net interest spreads (the difference between yield on
advances and cost of deposits) of banks (in 2005-06) indicate to an inverse
relationship implying that the larger regions may have lower spreads (Table 4).
Table 4: Correlation between business size with spread of regions
No
Bank Type
No of
Branches
No of
Regions
Correlation of Size and Spread
Correlation Significance
1 Public 1130 18 -0.644 0.005
2 Public 950 17 -0.475 0.041
3 Public 800 19 -0.860 0.000
3 Cooperative 105 6 -0.767 0.044
4 Private 395 8 -0.214 0.610
JOURNAL OF PERFORMANCE MANAGEMENT 40 18
The dependence on larger units to spearhead growth and consequent higher
allocation of resources to these units may well be the reason behind the decline of
efficiencies in revenue side. Even as banks adopted long range planning
(Bandopadhyay, 1982; Goyal, 1982), the planning process became even top driven
and removed from the business environment realities of the branch market (Seshadri,
1982; Kamalnayan, 1983). Banks have, therefore, always struggled to ensure that the
budgeting goals of branch offices are compatible with the strategic goals of the bank
as a whole.
ABC Bank, a public sector bank had, in 2005-06, a total business of Rs
350000 million generated from around 1100 branches distributed across 18
geographical regions (denoted later by alphabets from A to R). Geographic regions
being more homogenous aggregations of bank business, has been taken as unit of
analysis. Also, local business planning and resource allocation functions being
located at the regional offices of banks, this level of analysis is meaningful for
practical purpose. ABC Bank has been plagued with problems of stagnating income
growth and declining profitability since the year 2000 and the management has been
seriously considering ways of repositioning the Bank to affect performance
turnaround. Annual planning and performance data for the regions including growth
(planned and actual), cost of deposit, yield on advances and operating costs were
provided by the bank for the years 2005-06. Regional deposit and advance market
growth data have been obtained from publicly available sources (Reserve Bank of
India, 2006).
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 41 19
In Figure 2, the relative performance in the deposit market in respect of
growth (depgrth) and cost (depcost) of deposits for the business regions of ABC Bank
are shown. The upper right box has the deposit markets that are growing at a rate
above the bank average but at higher cost of deposit. These belong to the wildcat
category that needs special attention for development of relationship with customers
and growth of business. In the upper left box are the stars that are the deposit markets
where the bank has high growth as well as the strength of customer relationship and
market power leading to low cost of deposit. They are expected to be the profit
making operations that will lead the growth phase of the bank in the current and near-
term period. The lower left branches are the cash cows that have already established
customer relationships but are unable to grow rapidly owing to market stagnation.
The lower right box contains the dogs whose deposit growth in the current period can
only be at higher cost to the bank. The bank needs to examine whether growth
potential in such markets have totally stagnated or there is a need for repositioning the
branch or bank‟s offerings to regain strength.
JOURNAL OF PERFORMANCE MANAGEMENT 42 20
4.40 4.60 4.80 5.00
depcost
20.00
30.00
40.00
50.00
60.00
depgrth
A
A
A
A
AA
A
A
A
A
A
A
AAA
A
A
A
A
B
C
DEF
G
H
I
J
K
L
M NO P
Q
R
Figure 2: Deposit Market Growth-Share Matrix for ABC Bank
Similarly, in Figure 3, the relative business unit performances for growth (advgrth)
and yield (advyield) of advances are shown. Interpretation of the matrix can also be
made similarly with the exception that the upper left box indicates to regions having
growth potential but low yield and are, therefore, the wildcat. In the upper right box
are the Stars while the lower right markets are the Cash cows that are earning good
yield but are unable to grow rapidly. The lower left box contains the dogs.
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 43 21
7.00 8.00 9.00 10.00
advyield
20.00
30.00
40.00
50.00
60.00
advgrth
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
AA
A
B
C
D
E
F
G
H
I
J
K
LM
N
O
PQ R
Figure 3: Advance Market Growth-Share Matrix for ABC Bank
The relative positioning of the various regions of the ABC Bank can be drawn
now in respect of their growth and profit potential as in Table 5. The table also
compares the actual plan budgetary allocations to the regions with the normative plan
proposed earlier. As seen from the table, the budgetary allocation does not seem to be
well balanced between the various business regions. In about 72% of the regions,
budgetary provisions seem to be unmatched (either low or high) with their market
potential.
JOURNAL OF PERFORMANCE MANAGEMENT 44 22
Table 5: Relative budget allocations to the regions of ABC Bank
Market Advance
Category Star Wildcat Cash Cow Dog
Dep
osit
Star
K – 0.70 L – 0.85
Wildcat
B – 0 H – 0.80
G -0.62 C - 0 J – 0 Q – 0.27
Cash Cow
F – 0.35 M – 0 I – 0.37 R - 0.07
O – 0.45
Dog
P – 0.19 D – 0.18 E – 0.25 N – 0.41
A – 1.00
Applying the cost-capacity formulation to annual performance data of various
regions of ABC Bank, the relative cost-capacity positions (loss in profit reported as
“prftloss” and capacity level as “addlcpty”), are obtained as in Figure 4. The Bank has
a large number of regions falling in the stagnant, under utilized or stretched category
while just a few are well utilized.
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 45 23
100.00 200.00 300.00 400.00
addlcpty
100.00
200.00
300.00
400.00
500.00
prftloss
A
A
A
A
A
A
AA
A
A
A
A
A
A
A
A
A
A
A
B
C
D
E
F
GH
I
J
K
L
M
N
O
P
Q
R
Figure 4: Relative cost-capacity positions of the regions of ABC Bank
6.0 Gaps in strategic planning
Taking cue from Boussofiance et al. (1991), the growth-share and cost-
capacity matrices can be combined as in Table 6. In Table 6, the regions of the Bank
are arranged in order of their decreasing size along with the findings from the
application of the BCG matrix informing the mismatches between the normative and
plan budgeting of resources as well as the findings from the application of the cost
capacity matrix informing the efficiency positioning of the regions in respect of their
distance from the economic scale frontier. These findings together allow us to assess
and suggest possible modifications to the target and resource allocation strategy for
the Bank.
JOURNAL OF PERFORMANCE MANAGEMENT 46 24
Firstly, a large number of regions are in dog categories either in deposit or
advance markets or both. Most of such regions are operating at low level of capacity
underutilizing their resources towards business growth. At least one region, which is
also the largest, is clearly wasting and merits rationalization of branch operations.
Many the dog regions also enjoy a high level of budgetary allocation at the expense
of other business areas having higher growth potential. A very hard view of the
management of such regions is needed to improve the operating performance and
resource utilization or else these will continue to drag down the performance of the
bank. Secondly, cash cow businesses operate at higher level of capacity utilization
without proportionate increase in their costs. Most of such regions have lower
budgetary allocations than required to maintain their position. The budgets for these
regions need to be reviewed and increased to ensure that business and market share is
sustained. Thirdly, stars regions are being overstretched at their current capacity. A
few of them are clearly starved of resources and require higher allocation to sustain
growth. Finally, there are only two wildcats in advances market although there are
few in deposit market. But most of the latter are either poorly performing or lacking
adequate supply of budget resources.
From the above observations it seems that the bank is not well positioned in
new growth markets nor does it seem to be devoting appropriate plan attention and
budgetary support to the available growth areas. Many of its business regions are
already peaked or declining in their potential to provide growth and earnings and the
bank is unable to create or find growth sectors within its definition of business
markets. There also exist significant differences in the business profiles of regions in
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 47 25
their unbalanced exposure to deposit and advance market. Clearly, the business
planning function at the regional levels are performing at less that the required vigor.
Planning in the bank exists as a top down performance budgeting exercise with little
business-led innovation for growth and profit. Consequently, local contingencies of
demand and capacity have been overlooked during planning leading to poor
performance of the bank.
Table 6: Revised budget allocation for business regions
Region
Incremental Budget
Allocation
Cost
Capacity
Position
Revised
Budget
Allocation Normative Plan Actual
A 0.00-0.05 1.00 Stagnating Lower
B 0.50-0.80 0 Stretched Increase
C 0.20-0.40 0 Well utilized Increase
D 0.10-0.20 0.18 Underutilized Retain
E 0.05-0.10 0.25 Stretched Retain
F 0.30-0.50 0.35 Stretched Increase
G 0.40-0.60 0.62 Well utilized Retain
H 0.50-0.80 0.80 Well utilized Retain
I 0.10-0.30 0.37 Underutilized Lower
J 0.10-0.20 0 Stagnating Increase
K 0.80-1.00 0.70 Stretched Increase
L 0.20-0.30 0.85 Underutilized Lower
M 0.10-0.30 0 Well utilized Increase
N 0.05-0.10 0.41 Underutilized Lower
O 0.05-0.10 0.45 Stagnating Lower
P 0.20-0.30 0.19 Underutilized Retain
Q 0.10-0.20 0.27 Stagnating Lower
JOURNAL OF PERFORMANCE MANAGEMENT 48 26
R 0.10-0.30 0.07 Well utilized Increase
7.0 Conclusion
The study diagnoses certain gaps in the planning process of a bank that
neglects the critical factors of market positioning and capacity utilization, which can
pose as constraints to its profitable growth. It illustrates the difficulties in strategic
planning of a multi-unit business organization, where as the number of units increase,
the planning process might lose the portfolio view. This impedes the synergy gains
causing loss of allocative efficiency. The BCG market share – growth rate matrix has
been applied to assess the growth and profit potential of business regions in regards of
their deposit and advance markets and the superimposition of the industrial model of
cost-capacity position to assess the existence of production economies and resource
requirements. The application of frameworks together indicates to the needed revision
in the budget allocations for the business regions. Although based on a single bank,
the case study does lend certain credibility to the call for revisiting the planning
processes and practices in Indian banks.
The study, however, requires to be taken further using data of a larger sample
of banks and business regions as well as more number of years to confirm the
findings. While a symmetric treatment has been meted out for budgetary allocation to
both deposit and advance markets, the heuristic needs to be improved by fine tuning
the weights for budget allocation. Also, the cut off points for the performance
categories need to be determined. Suggestions for revised allocation need to be finally
Strategic Positioning And Capacity Utilization: Factors In Planning For Profitable Growth In Banking 49 27
tested for their impact on performance. In concluding, the study leads us to
hypothesize that business planning in banks must address both market and capacity
factors together in order to ensure meeting of growth and profit objectives together.
Otherwise, as size becomes the preponderant corporate objective of banks, growth
will become without profit and unsustainable.
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