The balanced scorecard, developed by Kaplan and Norton in 1992,
gained enormous popularity as a way to "translate a company's
strategy into specific measurable objectives." In practice,
however, relatively few of those adopting the BSC seemed to achieve
measurable benefits. Why the shortfall? Was an organization's
culture a deciding factor, as Kaplan and Norton posited? A literature
search turns up significant empirical research supporting this link,
which the authors further tested with a field-type study. The target
population was county government employees in one of the 10-most
populated counties in the U.S. that had implemented a BSC. The
statistical analysis of survey results confirmed the positive link
between BSC effectiveness and organizational culture, particularly four
distinct aspects: involvement, consistency, adaptability, and mission
trait.
**********
Since its development, the Balanced Scorecard (BSC) has gained
widespread popularity. The Bain & Company Management Tools and
Trends 2009 reports that 53% of the respondents were using the BSC as
part of their strategic decision-making process. Even though the tool
has been widely implemented, many, if not most of the user companies
believe that long-term results will not be realized (Niebecker, Eager,
and Kubitza, 2008). In fact, fewer than 20% of companies utilizing the
BSC have realized measurable performance improvement (Williams, 2004).
Buytendijk (2007) proposes that the perception that implementation of a
BSC, in and of itself, will lead to organizational alignment is a
"fairy tale."
Bititci, Mendibil, Nudurupati, Turner, and Garengo (2004) posit
that implementing and using such performance measurement systems is
greatly affected by organizational culture and management styles.
Indeed, Kaplan and Norton (2004) observed that companies with successful
BSC implementations "had a culture in which people were deeply
aware of and internalized the mission, vision, and core values needed to
execute the company's strategy."
In spite of the apparent relationship between organizational
culture and BSC effectiveness, there has been little research on the
subject. With the widespread use of the BSC and, at the same time, a
high level of BSC project failure, future research in this area is
warranted.
This article presents results of a study that examines the
relationship between organizational culture and Balanced Scorecard
effectiveness.
The Balanced Scorecard
Background. The BSC was developed by Robert S. Kaplan and David P.
Norton and published in 1992. It was the result of a year-long study
that arose out of a general notion that as knowledge became a basis for
competition, conventional financial measures were becoming obsolete
(Kaplan and Norton 1992).
The term balanced reflects the balanced consideration given to
long- and short-term objectives, financial and nonfinancial measures,
leading and lagging indicators, and external and internal performance
perspectives (Kaplan and Norton, 1996a). The basis for the BSC was the
causal linkage of performance measures, both financial and nonfinancial,
from four different perspectives: innovation and learning; internal
business; customer; and last, but not least, the financial (Kaplan and
Norton, 1992). The system involves four processes: 1) Clarifying and
translating the vision; 2) Communicating and linking; 3) Business
planning and setting targets; and 4) Strategic feedback and learning. As
a performance measurement system, the BSC combined a multitude of
performance measures, related to different strategic objectives, into a
single report. At the same time, the BSC helped top management avoid
"sub-optimization" (Kaplan and Norton, 1992), by creating a
picture of how changes implemented to produce improvements in one area
can adversely affect another area.
BSC Research. Most of the research to date regarding the BSC
concentrates on the relationship to firm performance. Kaplan and Norton
(1996b, 2001) discuss their research, now spanning 17 years, throughout
their publications. The research cited takes the form of case studies
and generally provides anecdotal evidence supporting the proposition
that a properly designed and implemented BSC can result in overall
performance improvement for the organization. However, they provide no
empirical data to support their hypotheses.
Empirical research regarding the relationship of the BSC to firm
performance has shown mixed results (Davis and Albright, 2004). Davis
and Albright posit two possible reasons for the lack of consistent
findings: 1) The results may indicate a lack of linkage between the BSC
measures chosen and the targeted financial objectives; and 2) The use of
cross-sectional analysis, in the studies cited previously, allow the
comparison of performance and performance measures only at one point in
time.
Kaplan and Norton (1992) recognized that the BSC would not be
effective for all organizations. They posited that "Even an
excellent set of balanced scorecard measures does not guarantee a
winning strategy. The balanced scorecard can only translate a
company's strategy into specific measurable objectives"
(Kaplan and Norton, 1992).
In fact, Williams (2004) reports that fewer than 20% of the
companies with BSC projects have realized overall performance
improvement. She suggests that this is primarily because companies
choose too many performance measurement indices or continue to rely on
historical financial data. Other factors affecting the success of
performance measurement systems, such as the BSC, include organizational
culture and management styles (Bititci, et al., 2004).
Organizational Culture
Background. As many as 164 definitions of organizational culture
have been proposed in the literature (Detert, Schroeder, and Mauriel,
2000), but Schein's definition (1990) is frequently quoted:
(a) A pattern of basic assumptions, (b) invented, discovered, or
developed by a given group, (c) as it learns to cope with its problems
of external adaptation and internal integration, (d) that has worked
well enough to be considered valid and, therefore (e) is to be taught to
new members as the (f) correct way to perceive, think, and feel in
relation to those problems.
The study of organizational culture as a concept is fairly recent.
Most of the literature points to the late 1970s and the work of
Pettigrew as the origin of such research (Detert, et al., 2000).
In the early 1980s, the popular business press began to reflect an
awareness that something out there, beyond a set of behaviors, would, if
repeated, would lead to business success. Ouchi's (1981) Theory Z
addressed the issue comparing Japanese companies to American companies.
A company's culture reflects its values, according to Ouchi. He
asserted that culture and not technology was the primary difference
between Japanese and American companies.
Peters and Waterman's In Search of Excellence, published in
1982, accelerated research in the area of organizational culture,
perhaps because it linked an organization's performance with its
culture (Lewis, 1998). While praised by business practitioners, the
research presented was criticized by academic scholars as little more
than anecdotal evidence (Janz, 1987), lacking sufficient rigor to be
generalizable. Tom Peters (2001) ultimately confessed that much of the
supporting data had been fabricated, but contended that the conclusions
were correct.
Denison (1984) was one of the first to propose measuring corporate
culture based on survey data. Up to that point, most of the research
used qualitative, longitudinal, ethnographic studies (Cooke and
Rousseau, 1988). These methodologies required a considerable investment
in time, and generalizability could not be verified statistically.
According to Denison, survey research allowed the same methodology to be
applied to a large number of organizations in the identical manner. This
facilitates generalization, but, on the downside, could lead to false
conclusions. Since the acceptance of survey research as a viable
methodology by the academic community, a robust stream of research has
ensued.
Much of the empirical research in the area has addressed how to
measure culture (Marcoulides and Heck, 1993), what culture types are
most effective (Bhaskaran and Sukumaran, 2007; Cameron and Quinn, 1999;
Denison, 1997; Denison and Mishra, 1995; Kotter and Heskett, 1992;
Mavondo and Farrell, 2003), and how to change organizational culture to
more effective types (Cooke and Rousseau, 1988; Korte and Chermack,
2007; Rashid, Sambasivan, and Rahman, 2004; Schwartz and Davis, 1981).
Denison's (1997) culture and effectiveness model is most
relevant to this survey. The model is based on four hypotheses related
to the dimensions or traits of organizational culture, which Denison
synthesizes into a framework. The first hypothesis, involvement,
suggests that when members are encouraged to participate, a sense of
ownership and responsibility develops, leading to commitment to the
organization. Consistency, the second hypothesis, posits that when the
organization's culture, comprised of shared beliefs, values, and
symbols, becomes internalized, consensus and coordination are more
effectively achieved. The third hypothesis, adaptability is based on the
need for the organization to recognize changes in the external and
internal environment and then make the appropriate responses to
accommodate those changes. Finally, the mission hypothesis states that
in the presence of a clearly communicated, broadly shared mission, the
organization finds purpose and meaning as well as direction. These, in
turn, help to define the appropriate course of action for the
organization and its members. According to Denison's (1997)
hypotheses, all of the cultural traits are positively related to
effectiveness.
As noted, Denison (1997) integrates these hypotheses into a
framework comparing two continuums: one contrasting change and
flexibility with stability and direction on one axis and the other
contrasting external orientation with internal integration. Denison has
since developed an organizational culture survey instrument (OCSI) to
measure the four culture traits within an organization.
Each trait is further broken down into three indices as shown in
Figure 1 (Fey and Denison, 2003).
Since the original publication of this research, Denison and his
associates have collected over 35,000 individual survey responses from
over 160 organizations. The results of this research continue to support
his hypotheses.
Linking the Balance Scorecard and Organizational Culture
Background. A considerable body of literature links performance
management systems to organizational culture. This is especially true
for the Balanced Scorecard. Further, the body of literature regarding
the relationship of organizational culture to the BSC is growing as the
BSC matures.
Rigby and Bilodeau (2007) acknowledge that corporate culture
directly affects the success of management tools used to aide companies
in process improvement and decision making. Kaplan and Norton (2004)
report that companies that successfully implemented the BSC had a
culture in which "people were deeply aware of and internalized the
mission, vision, and core values needed to execute the company's
strategy." Research by Bititci, et al. (2004, 2006) and Assiri and
Eid (2006) support the direct relationship of organizational culture to
successful implementation of the BSC.
Methodology
Introduction. Based on the literature just presented, it is
apparent that the BSC has become a widely-used management tool. Kaplan
and Norton (2001) list some 37 examples of anecdotal evidence to support
the idea that the BSC can be useful in communicating corporate strategy
throughout the organization and facilitating the implementation of that
strategy. Empirical evidence further supports the position. However,
there is evidence that many, if not most, BSC implementation projects
are not successful.
The literature further points to organizational culture as being a
key mediating factor in BSC effectiveness as measured by performance
improvement (Kaplan and Norton, 2004; Rigby and Bilodeau, 2007).
Behaviors alone cannot account for BSC success or failure. If merely
measuring performance resulted in performance improvement, would not all
companies be successful?
The literature suggests that the BSC leads to performance
improvement in the presence of the appropriate organizational culture
(Assiri and Eid, 2006; Bititci, et al., 2004). In BSC terminology,
organizational learning and growth leads to internal process
improvement, customer satisfaction, and, ultimately, performance
improvement. This is illustrated in Figure 2.
[FIGURE 2 OMITTED]
Accordingly, the research question that guided this study is: What
is the relationship, if any, between organizational culture and BSC
effectiveness?
Population. For the purpose of this study, the target population
was county and municipal government organizations. In particular, this
investigation studied county and municipal government employees working
in departments in one of the 10 most populated counties in the U.S. that
have implemented a BSC. This was a field type study.
This population was chosen for two primary reasons. First, the
county government has a well publicized, ongoing BSC program. The
program is broken down by departments, with over 60 different
departments and agencies at different stages of implementation. The
organization has about 30,000 employees. Second, while new research is
being performed in the public arena, this area still has not been
studied regarding the subject at hand.
Sample. Respondents were administrative, professional, supervisory,
and management personnel in the various departments of the county
government under study. The list of e-mail addresses for the 1,815 staff
members with access to the county's BSC administration software was
provided by the county and used for the study.
The staff members were notified via an internal e-mail from the
county representative that the study was taking place and requesting
their participation. Notice of the survey was then distributed via
e-mail to the participants. Participants were asked to respond via an
online form hosted by Zoomerang.com. A second e-mail was sent by the
county representative one week later, followed by a reminder from
Zoomerang.com. A final Zoomerang.com reminder was sent one week after
that, with the survey closed out the following week.
Dependent variable. The dependent variable in this study was BSC
effectiveness, which was measured by self-assessment. It is appropriate
to use such a measure for this variable since it has been found that
subjective measures of performance correlate with objective measures
(Fey and Denison, 2003; Lopez, Peon, and Ordas, 2004).
Independent variable. Organizational culture as measured by the
Denison and Neale (2000) organizational culture survey instrument (OCSI)
was the independent variable for this study. The OCSI breaks down
organizational culture into four traits, as noted in Figure 1:
involvement, consistency, adaptability and mission. This permits further
analysis of the relationship of each of the four traits to BSC
effectiveness.
Survey instrument. The survey instrument was a 70-question, online
form developed for this study. It used a 5 point Likert scale. Questions
1-8 collected demographic data; questions 9 and 10 measured BSC
effectiveness based on a self-assessment; and questions 11-70 measured
organizational culture vis-a-vis the Denison and Neale (2000) OCSI.
Hypotheses. Based on the research question previously stated, the
hypotheses tested in this study are as follows:
H11: There is a positive relationship between organizational
culture and BSC effectiveness.
H12: BSC effectiveness is positively related to involvement.
H13: BSC effectiveness is positively related to consistency.
H14: BSC effectiveness is positively related to adaptability.
H15: BSC effectiveness is positively related to mission.
Data analysis and strategy. The primary data analysis techniques
employed by this study were descriptive statistics, analysis of variance
(ANOVA), and correlation analysis. Descriptive statistics were used to
analyze demographic information collected and to gauge the consistency
of the self-assessment and culture measures within the departments.
These statistics include means and standard deviation. It was not
possible to test the sample data with population data since such
population demographic data was not made available by the organization.
However, a comparison of the distribution of responses by department
utilizing a Kruskal-Wallis analysis of variance test of the population
and sample was performed.
Normality was tested using Kolmogorov-Smirnov (K-S) single sample
tests and Shapiro-Wilk (S-W) tests of normality. Cronbach's Alpha
coefficients were computed for all of the scale data and compared with
those reported by Denison, et al. (2007) to test the reliability of the
data. Factor analysis utilizing data reduction techniques including both
Varimax and Oblique rotations were used to verify that the data
supported the relationships proposed by the Denison culture and
effectiveness model. Finally, the data was subjected to a one-way
analysis of variance test to determine if there were significant
relationships between the demographics and the survey responses.
The five hypotheses were tested using Pearson's correlation to
evaluate the relationships between the effectiveness measures and the
various cultural trait scores. The hypotheses were tested at an [alpha]
level of .05.
These data analysis techniques are consistent with other studies
regarding culture and performance, in particular Ewell (2004).
Results
Of the original 1,815 invitations to participate, 46 were
undeliverable, leaving 1,769 valid invitations. A total of 537 surveys
were completed for a response rate of 30.4%. Based on prior research,
the response rate of 30.45% for this survey was excellent (Porter and
Whitcomb, 2003; Deutskens, de Ruyter, Wetzels, and Oosterveld, 2004). In
the end, 150 responses were eliminated due to missing data, conflicts
between the self-assessment questions, or minimum responses per
department requirements. This resulted in a final sample of 387
responses from 33 departments, for a usable response rate of
21.9%--still within the acceptable ranges.
Comparison with population. Comparable demographic information for
the population was not made available by the organization. However, a
Kruskal-Wallis analysis of variance test of the population and sample,
mentioned previously, concluded that the sample was representative of
the population.
Data transformations. The responses to questions 11-70 were
averaged to produce the respective indexes. The traits were developed
averaging the corresponding indexes. Finally, the overall score was
calculated based on an average of the traits. The data were further
summarized by department.
Questions 25, 34, 39, 44, 49, 53, 60, and 68 are negative
questions. For study purposes, the scores must be reversed (Denison, et
al., 2007). Accordingly, for those questions all responses of 1 were
re-coded to 5, responses of 2 were recoded to 4, responses of 4 were
re-coded to 2, and responses of 5 were re-coded to 1.
Normality. Kolmogorov-Smirnov (K-S) single sample tests and
Shapiro-Wilk (S-W) tests of normality were conducted on the responses to
questions 9 and 11-70, as well as the data developed for the indexes,
traits, and overall scores. These tests were conducted on the individual
responses as well as the by-department, aggregate scores.
In general, the ungrouped data was not normally distributed. When
grouped by department, however, the data was found to be normally
distributed, except for the data for questions 12 and 50. Question 12
produced conflicting results, with the S-W not supporting normality.
Both tests suggest rejecting normality for the question 50 data.
Only the responses for question 9 and the calculated data for the
traits and overall measurements were used for this study. Additionally,
the data were analyzed by department. Therefore, the data used to test
the hypotheses of this study were considered normally distributed.
Reliability. Cronbach's alpha coefficients were computed for
all of the scale data. This was compared with the findings reported by
Denison, et al. (2007). The coefficients for this study ranged from .665
to .940, compared with the Denison, et al. (2007) range of .70-.92.
Nunnally (1978) suggests that alpha coefficients of .7 or higher are
acceptable for research purposes. However, alphas below .70 can be found
in the literature (Harber, Ashkanasy, and Callan, 1997; Mallak, Lyth,
Olson, Ulshafer, and Sardone, 2003). Based on the literature, the alpha
coefficients from this study are acceptable.
Hypothesis testing. Five hypotheses were presented regarding the
relationship between organizational culture and BSC effectiveness. The
data were first subjected to ANOVA testing to identify any significant
relationships between the demographic data and the survey responses. It
was determined that such relationships existed based on department, job
title, and years in the department. Accordingly, the five hypotheses
were tested based on composite department scores, utilizing the Pearson
correlation method with an [alpha] level of .05.
As previously noted, department average responses to question 9,
the self-assessment of BSC effectiveness, were used as the dependent
variable in all tests, and the appropriate index or trait factors were
used as the independent variables. The complete correlation matrix
follows.
Accordingly, the following describes the results of those tests:
Regarding Hypothesis HI, Table 1 indicates a correlation of .657
with [+ or -] < .01. Given that the sig. (.000) is less than the
alpha (.05), there is support for the hypothesis that a relationship
exists between organizational culture and BSC effectiveness.
Regarding Hypothesis H2, the test results produced a correlation
coefficient of .602 with [+ or -] < .01. Given that the sig. (.000)
is less than the alpha (.05), there is support for the hypothesis that
BSC effectiveness is positively related to involvement.
Regarding Hypothesis H3, there was a correlation coefficient of
.561 and, again, [+ or -] < .01. Given that the sig. (.000) is less
than the alpha (.05), there is support for H3 that BSC effectiveness is
positively related to consistency.
Regarding Hypothesis H4, the analysis produced a correlation
coefficient of .615 with [+ or -] < .01. Given that the sig. (.000)
is less than the alpha (.05), there is support for H4 that BSC
effectiveness is positively related to adaptability.
Finally, Hypothesis H5 suggests that BSC effectiveness is
positively related to the mission trait. This is based on a correlation
coefficient of .648 with [+ or -] < .01. Given that the sig. (.000)
is less than the alpha (.05), there is support for H5.
Discussion
Based on the results of this study, a positive relationship exists
between the effectiveness of BSC projects and organizational culture.
Additionally, the study results support the hypotheses regarding the
positive relationship between the four dimensions of organizational
culture as posited by Denison (1997), and BSC effectiveness.
Implications for management. This study has advanced the literature
by identifying the link between organizational culture and BSC
effectiveness. These findings provide valuable information to managers
regarding the potential for successful implementation of the BSC in
their organizations. The authors have posed the question: If merely
measuring performance resulted in performance improvement, would not all
companies be successful? Indeed, there has to be more to it. This study
suggests that organizational culture is a key mediator in the process
and further supports the position that organizational culture plays a
significant role in determining the success or failure of BSC
implementations.
It follows, then, that organizations fostering involvement,
consistency, adaptability, and mission, as measured by the OCSI, will be
more likely to achieve measurable results vis-a-vis BSC implementation.
Organizations with less than favorable scores may choose to affect
organizational change prior to the BSC implementation. At the very
least, the organization must adjust its expectations regarding the
results to be attained and the speed at which they are realized. In the
end, the organization may decide to forgo BSC implementation all
together. In so doing, valuable resources may be redirected at efforts
that produce greater benefit to the organization.
Limitations and Recommendations for Future Research
Several limiting factors in this study might be mitigated in future
studies, thereby increasing the generalizability of the findings.
First, the study was conducted in a single, municipal county
government organization. The study methodology should be extended to
different organizations, in both public and private sectors, to evaluate
if there is a significant difference in the results.
A self-assessment for BSC effectiveness was used as the dependent
variable in the study. Future research should include objective measures
based on BSC results as the basis for establishing BSC effectiveness.
This is complicated by the paucity of literature addressing the issue of
what constitutes a successful BSC implementation. Indexes could be
developed based on the percentage of objectives achieved as well as the
degree to which they were achieved (that is, met the objective, slightly
surpassed the objective, or greatly surpassed the objective). By
developing such indexes and constructing objective measures, concerns
for unbiased assessment on the part of survey respondents would be
eliminated.
As a final thought, it may be possible that an organization's
culture can change as a direct result of the BSC process, without any
specific intervention aimed at such changes. Future research should
include longitudinal studies to track organizational culture and BSC
effectiveness over the life of the BSC project to assess if such changes
occur.
Summary
This paper presented conclusions derived from an empirical study to
the effect that a relationship exists between organizational culture and
BSC effectiveness. Each of the four organizational traits--involvement,
consistency, adaptability, and mission--as measured by the Denison and
Neale (2000) OCSI are significantly related to BSC effectiveness.
Accordingly, the study affirms a relationship between organizational
culture and BSC effectiveness.
It is hoped that the recommendations regarding future research into
this subject will lead to further investigations. Such investigations
should further elucidate the relationship between organizational culture
and BSC effectiveness as well as the interrelationship among
organizational culture and BSC effectiveness.
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Jackie W. Deem, Kaplan University
Barry Barnes, H. Wayne Huizenga SBE
Sabrina Segal, H. Wayne Huizenga SBE
Robert Preziosi, H. Wayne Huizenga SBE
Dr. Deem has over 30 years of management experience with companies
including Eastern Air Lines and General Motors in North America, Europe,
and Australia. He chairs the Marketing Department in Kaplan's
School of Business. Dr. Barnes teaches graduate courses in leadership,
strategic decision-making, and organizational behavior. The recipient of
teaching and research awards, his articles on the relationship between
leadership, organizational change, and strategy have appeared in a
number of journals. Dr. Segal, professor of marketing and statistics,
has traveled widely--teaching business in Brazil and training managers
in Shanghai. She has published articles on the business scene in Russia
and other topics, is editor of Marketing Scene, and describes herself as
"an entrepreneur at heart." Dr. Preziosi, chair of the
Management Department at Nova Southeastern's Huizenga School, has
designed the curriculum for graduate degrees in human resources
management and leadership. A former corporate vice president, he now
serves on the editorial boards of four journals and as management editor
of the Journal of Applied Research. His research interests and
publications focus on practical areas of leadership and adult learning.
Table 1. Correlation Matrix
Correlations
Q9 Involvement
Q9 Pearson Correlation 1.000 .602 **
Sig. (2-tailed) 0.000
N 33 33
Involvement Pearson Correlation .602 ** 1.000
Sig. (2-tailed) 0.000
N 33 33
Consistency Pearson Correlation .561 ** 0.837
Sig. (2-tailed) 0.001 0.000
N 33 33
Adaptability Pearson Correlation .615 ** .849 **
Sig. (2-tailed) 0.000 0.000
N 33 33
Mission Pearson Correlation 0.648 .809 **
Sig. (2-tailed) 0.000 0.000
N 33 33
Overall Pearson Correlation .657 ** .941 **
Sig. (2-tailed) 0.000 0.000
N 33 33
Consistency Adaptability
Q9 Pearson Correlation .561 ** .615 **
Sig. (2-tailed) 0.001 0.000
N 33 33
Involvement Pearson Correlation .837 ** .849 **
Sig. (2-tailed) 0.000 0.000
N 33 33
Consistency Pearson Correlation 1.000 .774 **
Sig. (2-tailed) 0.000
N 33 33
Adaptability Pearson Correlation .774 ** 1.000
Sig. (2-tailed) 0.000
N 33 33
Mission Pearson Correlation .837 ** .787 **
Sig. (2-tailed) 0.000 0.000
N 33 33
Overall Pearson Correlation .918 ** 0.924
Sig. (2-tailed) 0.000 0.000
N 33 33
Mission Overall
Q9 Pearson Correlation 0.648 0.657
Sig. (2-tailed) 0.000 0.000
N 33 33
Involvement Pearson Correlation .809 ** 0.941
Sig. (2-tailed) 0.000 0.000
N 33 33
Consistency Pearson Correlation .837 ** 0.918
Sig. (2-tailed) 0.000 0.000
N 33 33
Adaptability Pearson Correlation .787 ** 0.924
Sig. (2-tailed) 0.000 0.000
N 33 33
Mission Pearson Correlation 1.000 0.929
Sig. (2-tailed) 0.000
N 33 33
Overall Pearson Correlation .929 ** 1.000
Sig. (2-tailed) 0.000
N 33 33
**. Correlation is significant at the 0.01 level (2-tailed).
Figure 1. OCSI Traits and Indices
Involvement Consistency Adaptability Mission
Empowerment Coordination & Organizational Strategic
Integration Learning Direction
and Intent
Team Orientation Agreement Customer Focus Goals &
Objectives
Capability Core Values Creating Change Vision
Development