Viewing the balanced scorecard in a practical light

Citation

Kium Teoh, W. (2006), "Viewing the balanced scorecard in a practical light", Measuring Business Excellence, Vol. 10 No. 2. https://doi.org/10.1108/mbe.2006.26710baf.001

Viewing the balanced scorecard in a practical light

Viewing the balanced scorecard in a practical light

Introduction

As far back as the early 1950s, progressive companies, such as General Electric, Dupont and General Motors, have observed the need to substantiate financial measures with non-financial measures in evaluating business performance. The quality movement during the 1980s brought about refreshed enthusiasm and ideas on viewing quality measures in substantiating the use of traditional financial measures in order to better monitor performance in the increasingly competitive and global environment. As the corporate world moved into the information age, executives in the 1990s became increasingly concerned that traditional performance measurement systems simply failed to track performance in a timely, complete and effective manner. This, in turn, led to the conceptualization of various new management techniques, including the balanced scorecard (hereafter abbreviated as BSC).

The short historical review above shows that executives have been tracking multiple financial and non-financial measures prior to the conception of the BSC framework. Indeed, the fundamental ideas behind the BSC are not new. The packaging and labelling of such ideas, however, are innovative and have captured the attention of executives and researchers.

A main distinguishing feature of the BSC from other existing performance measurement tools is the presentation of multiple measures grouped or chunked into different perspectives. Advocates of the BSC believe that such presentation is effective in guarding against the sub-optimization that occurs in traditional systems where a single financial perspective is considered. They also believe that the chunking of measures into perspectives actually reduces or eliminates the cognitive demands that managers face when using multi-measure performance measurement systems.

In contrast, existing empirical evidence provides limited support for the BSC’s acclaimed benefits (Ittner and Larcker, 2001). In fact, recent behavioural experiments (e.g. Lipe and Salterio, 1998, 2000, 2002; Libby et al., 2002; Banker et al., 2002; Dilla and Steinbart, 2002; Krumwiede et al., 2002; Ittner et al., 2003) report that managers, owing to their cognitive limitations, focus on common and financial measures, and undermine unique and non-financial measures of performance. The findings of such studies imply that the BSC’s aim of directing managerial attention to the drivers of performance (i.e. unique and non-financial measures) may not be achievable because of cognitive limitations inherent in humans.

Another criticism of the BSC that has surfaced in recent years is the lack of practicality of the BSC’s concurrent maximization of diverse performance measures. In contrast to Kaplan and Norton (1992, 1996), many researchers (e.g. Norreklit, 2000; Jensen, 2001) suggest that concurrent maximization of multiple and diverse measures is an impossible mission. Business is about prioritizing, and managers need to know the relative importance of the different measures in order to make purposeful decisions. Researchers even predict that the lack of information on the prioritization of the different measures within the BSC system may lead to confusion and disillusion, and eventual abandonment of the system (Jensen, 2001). In a recent case study, Ittner et al. (2003) report that the high level of subjectivity in the BSC plan led many branch managers to complain about favouritism in bonus awards and uncertainty in the criteria being used to determine rewards. Such dissatisfaction, in turn, led to the abandonment of the BSC system in favour of a formulaic plan based solely on revenues.

The main objectives of this paper, hence, are to examine whether the existing BSC presentation is effective in facilitating judgment in performance measurement based on the analysis of existing research in the business and psychology fields, and to provide some preliminary suggestions on how to improve the usability of the BSC in practice. The primary contribution of this paper rests on the suggestions on how to reduce or eliminate the cognitive difficulties that executives face when using the BSC. Recommendations made in this paper are based on an extensive study of the BSC over the past three years, and interviews with corporate executives and BSC consultants in Singapore over a period of three months (from August to October 2003). It is believed that the paper, which integrates academic research with practical lessons on maximizing the BSC system, will be most useful for practitioner-managers who are planning to implement the BSC, and for those who are looking for ways and means to improve their existing BSC model. The paper also suggests avenues for future research which are critical in the progression of the BSC theory.

The remainder of this paper is organized into five sections as follows. The first section discusses existing psychological findings on information overload and chunking, setting the theoretical grounding for investigating whether the BSC’s chunking presentation actually reduces or eliminates the information overload problem typically observed in multi-measure systems. The second section reports the conflicting views between the advocates and critics of the BSC on whether the BSC performance measures can be maximized concurrently or should be prioritized. In the third section, descriptive results of the interviews with corporate executives and BSC consultants are presented. The fourth section presents various suggestions for increasing the practicality or usability of the existing BSC model to organizations based on academic analysis and interview findings in the earlier sections of this paper. Finally, the concluding section discusses the implications of such suggestions, and provides concluding remarks to the paper.

Information overload and the chunking theory

Back in 1975, Mintzberg raised concerns that measurement systems of that time suffered from the following deficiencies: information was too limited in scope, late, unreliable, too aggregated and general to be of much use for effective decision making and control. The situation today, however, is very different. Companies today rarely suffer from having too few performance measures (Eccles, 1991; Kaplan and Norton, 1992; Meyer, 1994; Simons and Davila, 1998; Ittner and Larcker, 1998; Simons, 2000). In fact, one of the problems executives face today is the confusion and lack of focus in their increasingly complex measurement system and the long list of performance measures. The advent of information technology has reduced the cost of collecting, analyzing and reporting performance data significantly. As companies compete in an increasingly competitive and fast-moving environment, executives become more and more aware of the need to consider different aspects of the business in order to excel in the present and future. It is therefore not surprising that their list of performance measures is becoming longer and more complex.

However, when the number of performance measures increases, focus becomes an issue. A complex set of measures may result in confusion and lack of focus as to which measures require the most managerial attention (Eccles, 1991). Some true drivers of performance may receive too little attention while measures that are interesting but not crucial may be overemphasized (Jensen, 2001).

Further, psychological findings reveal that the human mind has limited processing and storing capacity, and human performance is impaired when information overloads (Miller, 1956). When an individual faces an increasing number of variables for judgment and decision making, even though the individual’s total information capacity increases, his/her accuracy for any particular variable is inevitably sacrificed. That is, when several dimensions are considered simultaneously, human beings can at best make relatively crude judgments because of their limited cognitive ability in processing information. Although scientists have yet to recommend the precise measures of information processing capacity, psychologists frequently quote and recommend the classic rule of thumb by Miller (1956) that the span of perceptual dimensionality is somewhere in the neighbourhood seven, plus or minus two (or the “Magical Number Seven” theory). Seven seems to contain just about the right amount of information for people to remember conveniently and process effectively.

In view of Miller’s theory, it appears likely that managers using a multi-measure performance measurement system such as the BSC may suffer from information overload. For instance, Kaplan and Norton (1996) recommend to BSC users that 20 to 25 measures across four perspectives are optimal to start with (and can be increased as and when the need arises). Such a number, however, clearly exceeds the general rule of thumb recommended by psychologists. A diverse set of performance measures may actually reduce performance by exceeding executives’ processing capabilities when making judgments. It may also cause executives to spread their efforts over too many objectives, reducing the effectiveness of the performance measurement system.

However, a striking characteristic of the BSC is its presentation format. The BSC chunks the multiple measures into perspective groups. By chunking the 20 to 25 measures into four perspectives, the information processing required may be significantly reduced because the number of information bits now is only four (instead of 20 to 25).

As observed in organizational psychology, schematically organized information is more easily coded, stored and subsequently decoded than information without such organization. Chunking theory provides that as individual elements are categorized, attributes become associated with the categories or chunks as opposed to the individual elements of the chunk, and an individual element is interpreted based in part on its membership within the chunk (Chase and Simon, 1973). In view of chunking theory, the BSC presentation of multiple measures grouped into perspectives or chunks may well reduce the cognitive effort required in processing such information, facilitating judgment and decision making. It should also be noted that consistent with chunking theory in psychology, various accounting studies (e.g. Casey, 1980; Blocher et al., 1986; Blocher and Davis, 1990; Hopkins, 1996; Hirst and Hopkins, 1998; Chen and Shoderbeck, 2000) find that the presentation format of financial information can affect the use and processing of such information, and the grouping of information bits can result in improved judgment in comparison to a situation where information is not grouped (Libby et al., 2000).

However, the BSC chunking effect cannot be simply assumed because it is further complicated by two elements. First, while presentation format studies in accounting are typically focused on the presentation format of financial information, three out of the four BSC perspectives are non-financial. An interesting question is whether the chunks can be easily aggregated and directly compared as in the case of financial information. Second, in contrast to existing chunking experiments in psychology that typically involve elements with similar denominations (e.g. chess playing or mental multiplication), the non-financial measures of the BSC are not commonly denominated. The different denominations range from monetary terms, percentages, and head counts to survey scores.

Although it appears plausible that the BSC chunking effect may facilitate judgment and decision making, direct empirical findings on the positive impact of such chunking are limited. A recent study by Lipe and Salterio (2002) attempted to examine the chunking effect of the BSC. The study reports that the BSC chunking format in some ways changes the processing of the multitude of measures included by integrating them into four chunks. The MBA student subjects recognized the potential relations of measures within a category, and considered the performance of the category as opposed to individual measures. However, it is interesting to note that while the chunking appears to have an effect on the experimental subjects’ processing strategy, Lipe and Salterio (2002) report that their subjects continue to show bias in their judgment, over-weighting common measures and under-weighting unique measures of performance. Considering the findings as a whole, while the BSC chunking presentation may somewhat simplify the information processing, it does not actually change the common measure bias inherent in people. This, in turn, implies that while the unique BSC presentation may facilitate judgment to a certain extent, it does not actually improve decision making.

It should be stressed that the above analysis is based on very limited empirical evidence. Further research is needed to resolve the issue. For example, future research may directly examine whether the BSC chunking presentation actually leads to an improvement in decisions, and whether managerial experience may actually reduce or eliminate the bias observed in MBA student subjects.

Concurrent maximization versus prioritization

Kaplan and Norton (1992) believe that the BSC brings together many seemingly disparate elements of a company’s competitive agenda: becoming customer oriented, shortening response time, improving quality, emphasizing teamwork, reducing new product launch times, and managing for the long term. Rather than viewing such elements or performance measures as requiring complex trade-offs, the measures are assumed to be intimately-related and tied together in a series of unidirectional cause-and-effect relationships. The unidirectional causal assumption suggests that learning and growth are the drivers of internal business processes, which are the drivers of customer satisfaction, which in turn, is the driver of financial results. As every BSC measure is linked to the other in a unidirectional causal relation, there does not arise a need for making trade-offs or setting of priorities among the measures. The causal assumption, in other words, allows advocates to deem trade-offs and prioritization as unnecessary and to recommend the concurrent maximization of the BSC measures.

However, a few scholars (e.g. Ittner and Larcker, 1998; Norreklit, 2000, 2003; Jensen, 2001) have recently questioned the BSC cause-and-effect assumption. Norreklit (2000) finds the BSC causal assumption simplistic and unrealistic, and may lead to the anticipation of performance indicators which are faulty, resulting in dysfunctional organizational behaviour and sub-optimized performance. Instead of a causal relationship, Norreklit suggests that the relationship between the BSC measures is that of interdependence. The influence between measures is not unidirectional. For instance, while Kaplan and Norton (1996) provide that increased customer satisfaction and loyalty causes a better company image, Norreklit (2000) argues a good image may equivalently be the reason for greater customer satisfaction and loyalty. Hence, the reasoning is not unidirectional, but circular; and the relationship between customer satisfaction and loyalty and company image is not causal, but that of interdependence.

Similarly from an economic perspective, while increased customer satisfaction may lead to greater sales and profitability, efforts on improving customer satisfaction may lead to increased expense, which in turn, may reduce profitability. Such an example shows that while the causal effect between measures can be predicted, it cannot be assumed. Indeed, it is only in rare circumstances that all the performance measures are moving in the same direction. In reality, performance measures may show conflicting performance, particularly within the single period whereby performance is typically measured and evaluated.

As evidenced in cross-sectional studies, financial performance need not necessarily improve following an increased effort in promoting specific non-financial perspectives (e.g., Andersen, Fornell and Lehman, 1994; Hemmer, 1996; Bickley et al., 1997; Foster and Gupta, 1997; Behn and Riley, 1999; Banker et al., 2000; Thevaranjan et al., 2001). The impact on the financial measures depends on the design of the non-financial measures (e.g. Hemmer, 1996; Thevaranjan et al., 2001), and the industry grouping of the business (e.g. Andersen et al., 1994; Foster and Gupta, 1997).

Hence, while the causal assumption is accepted as central to the BSC theory, empirical evidence suggests that the causal relationship between financial and non-financial measures need not necessarily hold true in reality. At best, existing empirical evidence shows that in some (not all) cases, financial and non-financial measures display some form of association. Association, however, does not indicate a cause-and-effect relation.

As discussed, the general acceptance of the causal assumption leads BSC proponents to the recommendation that the different BSC measures can and should be maximized concurrently. However, in reality, executives need to know which variables matter most to the company to be able to set realistic goals and take congruent actions in achieving such goals. Making trade-offs between different objectives and prioritizing them is inherent in business. Without any sense of priority on the multiple BSC performance measures, executives may face difficulties in both setting realistic goals and taking congruent actions. Jensen (2001) argues that human beings cannot make rational and purposeful decisions in face of multiple measures and no sense of trade-offs among the measures. If the trade-offs among the measures are not known, executives cannot know whether they are becoming better off by making specific decisions, except in very rare cases when all measures are increasing or moving in the same direction. Hence, Jensen suggests that a single objective function (as opposed to concurrent maximization of multiple objectives) that is consistent with the organization’s strategy is needed to motivate congruent behaviours and actions. A single objective function consists of multiple objectives that are defined in an overall function (V) such as V=f(a, b, c, …), where a, b, c, … etc. are the various objectives. The function f is monotone, providing clear instructions to managers on the prioritization of the objectives. It should be noted that a single objective function is different fundamentally from a single perspective of performance. Traditional measurement system that is based entirely on financial measures reflects the latter.

Undoubtedly, effective communication of corporate priority is important to all businesses. Corporate priority may be communicated via a clear set of strategic priorities, informing everyone the organizational focus. As observed in goal-setting research in organizational psychology, people tend to perform better when goals are specific as opposed to when goals are diffused (e.g. Locke and Latham, 1990). Focus explicates the goals that managers should set in order to be congruent with the overall corporate goals. Conscious goals regulate human behaviour. Increased specificity of such goals has frequently been observed to improve judgment outcome (Locke and Latham, 1990). In a multi-dimensional system such as the BSC, executives have a repertoire of different strategies for solving decision problems. When faced with a choice among several objectives but indeterminate options, people experience uncertainty and inconsistency (Tversky, 1972).

Additionally, choice behaviour studies also show that there exists a tendency for people to select the strategy that best meets his/her goals in a particular situation (Vermeir et al., 2002). Given the array of possible dimensions without any direction on priority, individuals may make deliberate choice among goals in the BSC system that may not necessarily be in the company’s interest.

Interviews with practitioners

A series of one-to-one interviews with five top executives and eight BSC consultants in Singapore was performed over a period of three months (from August to October 2003) as an exploratory study. The top executives were two CEOs and three CFOs from five Singapore companies that have implemented and used the BSC as a performance measurement system in the past three years. The BSC consultants, on the other hand, provide advisory services to companies in the BSC domain. All the consultants have more than five years of consultancy experience. The BSC is a relatively new concept in the Singapore business environment, and not many companies have actually implemented the BSC system. The interview sample, hence, is most significant and captures a significant portion of Singapore practitioners who are involved in BSC projects.

The interviewees were asked a series of questions that led to the revelation of many important lessons learnt from their experience in using the BSC. The interviewees were invited to discuss their personal and firm experience, particularly on the issues faced (for the five executives, the issues that their respective company faced in the implementation and maintenance of the system; and for the eight consultants, the typical barriers to implementing and maintaining the BSC system that their clients faced), the lessons learnt, and the pros and cons of their respective BSC system. In the final part of the interview, the interviewees were also invited to provide practical advice to executives who may be thinking of implementing the BSC system in their own company or improving their existing BSC system.

All the interviewees agreed that the BSC was a long-term project, and the average time of setting up the system took between one-and-a-half to two years. The BSC project was usually initiated either by a top executive from the Finance or Strategic Planning Department with the approval of the Board of Directors or by the mandate of an overseas head office. All the five executives interviewed revealed that BSC consultants were appointed for the project, and unanimously agreed that such appointment was necessary to ensure that the project was handled professionally.

At the initial stage of BSC implementation, the consultants typically help companies to define and clarify their vision and strategy. Two of the BSC consultants interviewed revealed that some of their clients were so anxious in developing their scorecard that they set up a long list of performance measures without considering their corporate vision and strategy. All the BSC consultants interviewed stressed the importance of the vision and strategy in driving the BSC development, and emphasized the importance of drafting a Strategy Map that shows how the stated strategy can be achieved. To quote one of the consultants, “once the vision and strategy are well defined, understood and actionable, half the battle is already won.” Six out of the eight BSC consultants interviewed stated that unclear vision and strategy represents the most important reason for failure of BSC projects in companies.

Another challenge that BSC implementers face is the engagement of everyone in the BSC project. Both of the CEOs interviewed in this study admitted that they had not even heard of the BSC system prior to the mandate of their head office to implement such a system, and were unsure whether such a system was simply a “Western management fad” that would prove difficult in the Singapore corporate environment. However, they quickly embarked on the learning process, and appointed BSC consultants to present the concept to their senior managers. The BSC consultants interviewed also shared similar experiences that many senior managers were initially sceptical about the benefits that the BSC would bring. However, they observed that the senior managers’ acceptance is critical in communicating down the BSC idea to the entire organization, and in convincing all employees that they should understand strategy and conduct their daily business in a way that contributes to the success of the overall corporate strategy. All the 13 interviewees unanimously agreed that the main benefit of the BSC to their organization came from the increased communication and appreciation of each team’s and individual’s contribution via the increased top-down direction and bottom-up feedback.

The interviewees also consistently found that the linkage of the BSC to incentive compensation was the most powerful device in motivating people to contribute to the project. All the five CEOs and CFOs interviewed used different methods in linking BSC measures to compensation. Four out of the five companies selected a set of three to five Key Performance Indicators (KPIs) from their list of BSC measures, and specified how such KPIs should be linked (three companies ranked the measures while one company set weights to each measure). However, the performance evaluation of the KPIs contributes only to part of the entire employees’ bonus package. Other considerations (e.g. superior, peer and/or subordinate evaluations) are made in calculating the final bonus. The eight BSC consultants also did not have a universal proposal regarding the linkage of the BSC to incentive compensation but advised that the compensation design should be tailored to the specific needs, circumstances and culture of the organization.

As discussed, the interviewees did not only share their experiences but were also invited to give practical advice on how to improve the BSC model. In the next section, the interviewees’ experiences and advice are integrated with existing academic research and knowledge in developing a list of useful guidelines on increasing the practicality of the existing BSC model.

Towards a more practical BSC model

While some scholars have dismissed the BSC as flawed (e.g. Jensen, 2001), or overly simplistic and unrealistic (e.g. Norreklit, 2000), it is submitted that present empirical research has not provided conclusive evidence that it does not actually work in practice. The very fact that many organizations are using the BSC model and reporting success from their implementation shows that there are benefits to be gained from the BSC. Perhaps an interesting question is why some companies are claiming success while others have abandoned the BSC model. Clearly, there are practical lessons to be learnt from such companies.

From the interviews with practitioners in Singapore, it is observed that some companies have developed variations of the original BSC model as proposed by Kaplan and Norton (1992, 1996, 2001). For instance, some companies select only a handful of BSC measures and denote the selected measures as Key Performance Indicators (KPIs), instead of considering all the multiple measures of the BSC concurrently and without differentiation. Such KPIs are denoted as the most critical indicators of performance that executives should focus their efforts on. The remaining BSC measures are considered “good to track or monitor but not critical” for success. Some companies even link the KPIs directly to executive incentive and compensation package. Other companies assign individual weights to all the BSC measures in order to inform executives about the priority of the company. During the process of developing the BSC, executives become increasingly aware of the growing list of measures that they have in their portfolio, and that some measures are more important than others with respect to the prevailing corporate strategy. Executives also recognize the need for trade-off among some measures. The weights, which are reviewed on a periodic basis, reinforce the strategic priority of the company. Such weights also serve as an objective approach to periodic performance measurement.

A list of suggestions on increasing the practicality of the BSC model is discussed below. It is envisaged that such recommendations will not only provide useful and practical guidance for practitioners but also present researchers with new and interesting avenues of research.

Keep the number of BSC measures manageable

Spurred by the view that “what gets measured gets done”, executives tend to pile more and more measures into their performance measurement system. However, this is neither optimal nor advisable as executives may suffer from information overload, lose focus, employ simplified processing strategy and become biased in their judgment and decision making. A long list of measures also means that more time, effort and money are needed in collecting data, monitoring performance and reporting feedback. Some executives that were interviewed complained that they were spending more time attending performance measurement meetings instead of managing the business.

Kaplan and Norton (1996) suggest that while the number of BSC measures typically range from 20 to 25, the list can be increased when the need arises. However, it is recommended that companies should limit the number of performance measures in order to facilitate focus and motivate people. Although this paper abstains from giving any specific and optimal number of measures, it is proposed that as a general rule of thumb, companies that have more than 25 BSC measures should take a fresh look at the importance of each measure. Focus is important to motivate congruent behaviours and actions, and should not be sacrificed for the sake of maintaining a comprehensive list of performance measures. Executives, no matter how experienced or efficient they are, are still human beings subject to cognitive limitations. When information overloads, people give up and/or become biased and their performance actually drops. Therefore, as important as it is to consider a balanced view of the different perspectives of the business, it is vital to balance the increase in the number of performance measures with the need for executives to focus.

Effective communication of strategic priorities

The causal linkages among measures represent executives’ views and predictions of the relations. In other words, the predicted linkages need not necessarily materialize in reality. Hence, there arises a need for executives to understand the possible trade-offs among measures, not only to hypothesize the relations. This in turn indicates the need for communicating corporate priorities in accordance to the strategic emphasis of the company (which may be reviewed periodically as the emphasis changes).

In terms of communicating strategic priorities, there are two possible ways of doing so: assigning weights to BSC measures, and selecting KPIs from the list of BSC measures. One advantage of the weight assignment approach is objectivity. The weights clearly show executives the relative importance of each BSC measure. There is no ambiguity about what results are desired or how they will be measured. Such an approach facilitates a high return on management because once goals and weights are set, executives can focus their effort on their daily responsibilities. However, such weight assignment may pose unnecessary constraints on executives as it is less flexible to change since it is usually set for use for at least a year and hence fails to capture the ever-changing environment. The use of pre-set goals and milestones also may prevent adaptability and flexibility that is the essence of good strategy (Mintzberg, 1987).

Developing a list of KPIs is another way of communicating strategic priority. This is the recommended approach. Critics argue that executives lack focus in a BSC system that requires concurrent maximization of multiple dimensions without any sense of priority. The KPIs effectively create focus and priority over the other BSC measures. A set of three to five BSC measures may be selected as the KPIs. These KPIs are critical for the achievement of the prescribed strategy, while the remaining BSC measures contribute to overall performance. The relevance of each KPI may be reviewed periodically, and changed as the strategic priorities change. The KPIs also refine responsibilities and clarify accountability of each team and individual. Each team or staff may be assigned a different set of KPIs in accordance to their range of responsibilities, and in a manner that ensures that each BSC measures is accounted for appropriately. The definition of the KPIs may also lead to increased appreciation of the relationships among diverse performance measures. As executives understand the contribution of each BSC measure and their own actions to the overall success of the company, they become more motivated to bestow their energies.

Link the BSC measures explicitly to compensation

Incentive theories suggest that the explicit linkage of the performance measures to executive compensation is by far the most effective approach in motivating congruent behaviour that promotes corporate performance. Interestingly, Kaplan and Norton (1996) submit that employee effort will be promoted implicitly simply through the use of the BSC, but independent of performance evaluation and compensation. The researchers even suggest that explicit rewards associated with the achievement of goals may actually crowd out intrinsic motivation that develops as individuals internalize the organizational goals. Critics, however, are doubtful that such submissions can be reconciled with incentive and motivation theories, and Kaplan and Norton’s (1992) own proposal that “what gets measured gets done”. Such submissions do not seem consistent with the organization’s effort in making executives appreciate the importance of the BSC to its success. Since executives are not evaluated based on the BSC measures, they may not be motivated sufficiently to exert effort in improving those measures. Furthermore, while the crowding effects of explicit reward on intrinsic motivation present interesting theoretical contention, there is no conclusive empirical evidence, particularly in workplace settings, of these influences (Prendergast, 1999).

It is submitted that while theorists may hope that participation in the BSC project alone may motivate people to give their best, companies should not make such simplistic assumption in practice. Although executives may derive personal satisfaction and hence be intrinsically motivated through participation in the BSC project, it is inconceivable that everyone in the organization will be homogenously enthusiastic about the prospect of additional work (in the implementation of the BSC system) and increased accountability (as the list of performance measures increases), particularly with the lack of link to reward and compensation. Hence, explicit linkage of the BSC to incentive compensation is necessary in order to move executives in a powerful way. A portion of staff compensation package should to be tied directly to BSC measures. Companies may tie the bonus package according to the pre-specified strategic priorities via a list of weighted BSC measures or a selected set of BSC measures such as the KPIs.

Implications and conclusion

In this paper, the practicality of the BSC in light of existing empirical findings in the performance measurement, strategic management, organizational behaviour and psychology studies is reviewed. Also, scholarly thoughts from both the proponents and critics of the BSC are discussed. Based on a study of the BSC and interviews with practitioners, three general recommendations on increasing the practicality of the BSC model are presented, namely: to keep the number of performance measures manageable; to communicate strategic priorities effectively; and to link the BSC explicitly to incentive compensation. The recommendations – the product of extensive academic research and learning of practical lessons – present useful alternative thinking to the BSC idea as originally proposed by its pioneers, Kaplan and Norton (1992, 1996, 2001).

After more than a decade of its conception back in 1992, the BSC model continues to be well-received by practitioners, proving to sceptics that the BSC is not a management fad, but a most important chapter in contemporary managerial accounting literature. Despite its popularity with practitioners, it is only in recent times that the BSC has caught the attention of researchers. Critics have only started to challenge current practices and thoughts in the BSC area. Criticisms, challenges and debates, however, are essential in progressing knowledge and refining understanding of the BSC model, as in the case of any theoretical development.

The paper also highlights important issues warranting further research. Future research may verify the validity of each of the three recommendations. For instance, future researchers may examine whether executives should continue to expand their list of performance measures as their business becomes more and more complex, or limit the number of measures to a manageable level. Researchers may also attempt to propose an optimal number of measures, contributing not only to the BSC literature, but also to cognitive psychology. The manner in which strategic priorities may be communicated also poses interesting avenues of research, e.g. is the present format effective or should BSC measures be assigned individual weights? What are the implications of selecting a set of key performance indicators (KPIs) from the list of BSC measures? Will such an approach lead to the over-salience of certain measures at the expense of other measures? What are the relative values of implicit versus explicit linkage of the BSC to performance evaluation and compensation?

Finally, it is submitted that the BSC represents an exciting area of research that is yet to be fully exploited. The real benefit of research in this area is to examine deficiencies and shortcomings, verify theoretical expectations, and then to provide useful recommendations in advancing the BSC model.

About the authors

Wei Kium Teoh is a currently working as a consultant in China. Prior to this, she has taught in the Nanyang Business School, Nanyang Technological University (Singapore). She specializes in management accounting and her doctoral thesis focuses on the balanced scorecard.

Hian Chye Koh is an Associate Professor and Dean at the School of Business, SIM University (Singapore). He received his doctoral degree in accounting from Virginia Tech and is a CPA. He has published widely in areas of accounting, business, statistical modelling and data mining. Hian Chye Koh is the corresponding author and can be contacted at: www.hckoh@unisim.edu.sg

Wei Kium Teoh, Hian Chye KohWei Kium Teoh, is Consultant in China and Hian Chye Koh is Associate Professor and Dean, School of Business, SIM University, Singapore.