Free online reading
The prime managerial purpose of performance measurement (PM) is to control (Behn, 2003; Bruggeman 2004). The idea is that managers control behaviors by sup- plementing manual monitoring, which is unfeasible in large organizations, with for- mal, information-based control systems (Simons, 1994; Simons 1995). Such perfor- mance measurement systems (PMS) specify required employee actions to achieve organizational goals and measure whether employees have undertaken those actions. Thereby, managers intend to get what they measure (Kaplan and Norton, 1992).
Since the early 1980s, PM has evolved from financial reporting to multidimen- sional, integrated frameworks, addressing the need of organizations to align PMS with their strategic objectives to secure long-term business success. In principal, the consistency between performance measures, strategic goals and actions promotes strategy implementation (Kennerley and Neely, 2002; Pun and White, 2005).
Although the integration of PMS is well documented in the literature and regarded as an important aspect of efficient and effective management of organizations, most companies underperform due to breakdowns between strategy and operations (Kaplan and Norton, 2008). Empirical studies show that 90 percent of managers fail to carry out their corporate strategies (Neely et al., 2002). Thus, if designed and executed poorly, PM initiatives may not yield the expected benefits or even cause organizational performance to deteriorate (Bird et al., 2005).
While there are numerous possibilities associated with PM for strategy imple- mentation, there are as many pitfalls and risks involved. Therefore, the aim of this essay is to discuss and elaborate on findings in the literature on how to leverage po- tential opportunities and avoid key risks. For the purpose of this essay, possibilities are defined as probable benefits, the realization of specified goals and sustainable performance improvement. Conversely, risks relate to potential costs, results adver- sarial to initial expectation and threats to long-term success. The essay is structured into four arguments that reflect my view on PM as a tool for strategy implementation:
(1) strategic alignment and failure, (2) strategic adaptability and rigidity, (3) inade- quate and comprehensive PM, and (4) dysfunctional and purposeful incentivation. The main points and required future research areas are summarized in the conclusion.
2 Risks and possibilities of PM for strategy implementation
In the main section, I first discuss the key benefits that arise when adopting PM throughout the organization to execute strategies, followed by common design and implementation shortcomings as well as PM inefficiency and ineffectiveness in par- ticular. I continue with stressing the importance of strategic flexibility to stay compet- itive in dynamic markets. Next follows the downsides of mono-dimensional PM and a clarification of why effective PM frameworks have to be comprehensive in nature. Finally, I close the discussion by underlining that too simplistic PMS regularly en- courage employees to behave contrary to the management’s intentions.
2.1 Strategic alignment and failure
Kaplan and Norton (2008) suggest that by integrating PM organizations foster strategic alignment, become more strategy-focused and quantify strategy execution. Through decomposing strategic objectives and identifying the critical success factors and metrics, employees receive better feedback and can focus more closely on the activities that drive performance, which increases their motivation. In that, PMS pro- vide a shared language for making better judgments about resource allocation in terms of people, time and budget (Kula, 1986). In addition, companies gain accounta- bility by assigning responsibility to performance targets (Hall, 2008). Also, strategic PM promotes organizational learning as managers monitor results, review barriers to strategy execution and propose actions to close performance gaps (Kaplan and Nor- ton, 2008). Similarly, Bititci et al. (1997) contend that the PMS is the basis for a closed-loop control system that supports decision making. Moreover, the PMS gener- ates performance data that directly benefits the strategy formulation process, which increases responsiveness (Hudson et al., 2001). Based on statistical analysis managers can cut losses more rapidly if strategic initiatives and actions do not improve perfor- mance indicators as expected (Kaplan and Norton, 2008).
In contrast, failure of PMS is often attributed to its design and implementation. Flaws in the PMS design are caused by measuring metrics that are not associated with a company’s formalized strategic objectives. As a result, employees question the va- lidity of the measures and are not able to prioritize their actions in line with the organization’s goals (Neely and Bourne, 2000). Lacking goal congruence undermines strategic control since individual employee expectations of performance are incon- sistent with those of the managers (Bruggeman, 2004). Additionally, due to political challenges, a lack of infrastructure or a loss of focus, the implementation of the PMS may fail (Neely and Bourne, 2000). However, even if a company manages to align measures and to implement the PMS successfully, integration is incomplete. To se- cure long-term success, organizations have to integrate the PMS with other important control mechanisms, such as responsibility structures, reward and recognition sys- tems or human resource trainings (Bruggeman, 2004; Micheli and Manzoni, 2010).
Furthermore, PMS are often neither efficient nor effective. Neely and Bourne (2000) recognized that managers take the availability of PM frameworks and tools as an invitation to measure as much as possible. Unfortunately, this measurement frenzy is very time-consuming and constrains efficiency, which requires to measure as little as possible and only the things that matter for business success. However, based on consistent evidence Ittner et al. (2003) conclude that measuring more metrics than required by a company’s strategy does not adversely affect firm performance. Neely and Bourne (2000) continue that companies are often incapable of using PM data effectively and thus take the right actions. The inability to extract value from PM data stems from the missing link between the actions derived from performance indica- tions and the operational improvement processes that are connected to the strategic objectives. Thus, the PMS may not has beneficial impact on decision-making, render- ing the whole endeavors fruitless (Kaplan and Norton, 2008; Neely and Bourne, 2000). In that regard, Neely et al. (2002) take one step back and argue that an organi- zation’s capabilities and processes may not be aligned with its overall strategy in the first place. Even more severe, initial assumptions about the underlying drivers of business success and the developed strategy may be incorrect (Neely et al., 2002). In addition, for small and medium-sized enterprises strategy is mainly emerging and therefore strategy formalization does not receive much consideration (Garengo and Biazzo, 2012). Thus, based on these critical aspects that have been identified in the literature I conclude that effectively designing and integrating the PMS for strategy implementation primarily rests on three prerequisites: (1) the strategy is formulated and (2) based on correct assumptions and (3) the processes and capabilities of an organization are aligned with its strategic objectives.
2.2 Strategic adaptability and rigidity
Many company examples I encountered in the literature and in real life demon- strate that failures in management control can be fatal and expose businesses to high risks and endanger its operations. In this regard, Simons (1995) elicited four levers of control that a company needs to manage and balance in order to effectively secure long-term business success. As one of the four levers, diagnostic control systems (DCS) specifically control for strategy implementation by measuring progress to- wards targets of critical performance variables. Periodical feedback is then used to improve processes to eventually realize strategic objectives. Furthermore, DCS dra- matically free up management resources that were formerly employed in workforce monitoring. However, strategic control additionally requires boundaries for conduct, core values and frequent interactions (Simons, 1995). More specifically, PMS have to be dynamic in nature since most organizations operate in highly competitive indus- tries, which may render strategies during their execution obsolete (Lynch and Cross, 1991; Simons, 1995). PMS have to be evaluated and modified regularly to reflect the rapidly changing competitive situations and to maintain the strategic relevance of PM (Eccles, 1991; Hudson et al., 2001). As a result, measures that are most relevant to business success change over time (Neely, 1999). Thus, implementing strategies and facilitating strategic renewal requires a balance between alignment and empower- ment, between diagnostic and interactive control systems respectively (Henri, 2006; Kolehmainen, 2010; Micheli and Manzoni, 2010; Simons, 1995).
In my opinion, the risk that organizations implement overly rigid PMS, which cause organizational inertia to change, cannot be overstated. Ossification, one of the main unintended consequences of PM, characterizes bureaucratic PMS that inhibit innovation (Smith, 1995). Similarly, Likierman (2009) constitutes that PMS rarely evolve at the same pace as the business and therefore companies stick too long to their measures. From a strategic perspective, Mintzberg et al. (1998) argue that the most innovative strategies emerge from within the organization through learning and exploring new opportunities. In contrast, deliberate top-down strategy implementa- tion exploits strengths and opportunities by directing and exercising control, which stifles innovation and organizational learning (Mintzberg et al., 1998; Pun and White, 2005). However, not all emerging strategies are promising and executives still need to plan ahead and roll out their strategies (Kaplan and Norton, 2008). In sum, I empha- size that an effective PMS has to resolve the tension between strategic alignment that is necessary to increase organizational performance and strategic autonomy to con- tinuously adapt and promote innovation.
2.3 Inadequate and comprehensive PM
Kaplan and Norton (2008) suggest that if progress toward an objective is not measured, then a company cannot manage to improve it. In other words, PM provides clear visibility to progress (Veth, 2006). However, I believe that organizations regu- larly take a too simplistic approach to PM, which does not meet the requirements to implement their strategy. Power (2004) argues that companies value the reduction of complexity for its own sake to simplify decision making and accommodate a distinc- tive management style. For instance, traditional financial metrics lack important fea- tures of strategic PM since they primarily measure past performance, which is not useful to evaluate the impact of today’s decisions on future performance (Bruns, 1998; Dixon et al., 1990; Likierman, 2009; Verweire et al., 2004). Similarly, measur- ing absolute performance by comparing current results with a plan or budget does not support the definition of competitive strategies and actions (Kaplan and Norton, 1992; Likierman, 2009). Although generating profits to create shareholder value re- mains the primary goal of every market-oriented company, an organization cannot be managed based on a single-bottom line (Bruns, 1998). Failure to incorporate stake- holder preferences in the PMS, which may be important for business success, can undermine long-term performance (Verweire et al., 2004; Springer, 2008).
In order to successfully implement strategies, I endorse the position of Neely (1999) that organizations need to assess performance from a wider perspective than traditional financial measures. Based on a comprehensive literature review, Hudson et al. (2001) clustered critical dimensions of performance into six groups: time, quality, flexibility, finance, customer satisfaction, and human resources. These dimensions are assumed to cover all aspects relevant to operating performance and thus encourage a holistic alignment with strategic success factors. However, unless non-financial measures are elicited through sophisticated analysis rather than managerial guess- work, they do not contribute more value to PM than traditional financial metrics (Itt- ner and Larcker, 2003). Since the early 1990s, several frameworks have been devel- oped and refined to emphasize a comprehensive view and balance the tension be- tween financial and non-financial, backward and forward looking, action-oriented and monitoring measures. Prominent examples are the SMART system (Lynch and Cross, 1991), the balanced scorecard (BSC) (Kaplan and Norton, 1992) or the performance prism (Neely et al., 2002). These models have been classified as ‘strategic PMS’ since they specifically aim to integrate long-term strategy and operations (Gimbert et al., 2010). In general, these frameworks translate strategy into operations more effec- tively, make strategizing an ongoing process and align organizational processes and competencies (De Geuser et al., 2009; Pun and White, 2005).
Empirical evidence largely confirms these notions. Ittner et al. (2003) find that firms which incorporate a more comprehensive mixture of financial and non-financial metrics than companies with similar objectives and success drivers have better share price performance. Regarding the BSC, findings by Malina and Selto (2001) indicate that the BSC is an effective scheme for strategic control. Moreover, empirical results by De Geuser et al. (2009) conclude that the BSC improves organizational perfor- mance. Nevertheless, organizations have to be clear about what they want to achieve before implementing a BSC, otherwise employees may be afraid of organizational change or even hinder the transformation (McCunn, 1998). Furthermore, adopting frameworks like the BSC will not supplement the task of identifying which individual performance drivers determine organizational success (Ittner and Larcker, 2003).
2.4 Dysfunctional and purposeful incentivation
To my mind the saying “You get what you measure” contains an important message: Employees respond to measures and reflect them in their work prioritiza- tion. Many examples demonstrate how employees and teams achieve their perfor- mance targets, yet their actions are actually detrimental to the firm (Neely et al., 2002). Smith (1995) documented major unintended behaviors as a consequence of the publication of performance data especially in the public sector. According to the au- thor, dysfunctional behavior is a result of PM that fails to reflect the complexity, dy- namism and required control discretion of an organization (Smith, 1995). Specifical- ly, Likierman (2009) argues that as soon as an organization decides to manage by metrics, managers manipulate the PMS no matter how good the organization is gov- erned. The manipulation of actual behavior, known as gaming, has been extensively discussed in the literature and accepted as an inherent problem of PM (Likierman 2009; Neely et al., 2002; Smith, 1995). Often, this detrimental behavior is a desperate reaction by employees and managers under pressure to enhance their reported per- formance in order to meet ambitious targets (Simons, 1995). In response, counter- measures such as diversified PM schemes have been proposed, which confirm the relevance of comprehensive PMS as outlined above (Smith, 1995).
Therefore, I find that the opportunity of PM for strategy execution can only be realized by promoting intended behaviors and attitudes. Returning to Simons’ (1995) levers of control, organizations have to integrate the different roles of strategic PM. Beside strategy implementation (‘diagnostic system’) and reformulation (‘interactive system’), PMS inherently communicate the core values (‘belief system’) of a compa- ny, such as its mission and vision, that stimulate desired behaviors. Furthermore, PM schemes set common rules and limits to actions (‘boundary system’) that purposeful- ly restrain employee conduct (Micheli and Manzoni, 2010; Simons, 1995). Thereby, an organization’s culture can be further aligned with its strategy, which characterizes a ‘high-performance culture’. However, if a strategy-culture misfit exists a priori, the PMS encourages a ‘low-performance culture’ and dysfunctional behaviors such as gaming (Bruggeman, 2004). Table 1 summarizes my discussion and view on the four main risk and possibility areas of PM as a mechanism for strategy implementation.
Table 1: Overview of risks and possibilities associated with PM as a tool for strategy implementation
illustration not visible in this excerpt
Source: Author’s own analysis
In aspiration to carry out strategies successfully, academics and practitioners alike have recognized the power of integrating PMS for organizations. As I pointed out, by aligning strategy and operations through PM managers benefit from strategic control, better decision making and organizational performance. Furthermore, com- panies have to integrate the levers of control to stay competitive in dynamic markets. In addition, I endorse measuring the critical success factors through a comprehensive PMS that provides a holistic approach towards strategy implementation. Lastly, only by promoting desired behaviors companies execute their strategies as intended.
In contrast, I conjecture that executives frequently design and implement ineffi- cient and ineffective PMS due to a priori breakdowns between organizational pro- cesses and their strategic objectives and assumptions. If PM schemes are not adjusted to changes in the competitive landscape, organizations furthermore risk to ossify and measure obsolete performance metrics. Likewise, measuring past financial perfor- mance while neglecting important stakeholder preferences fails to execute strategies altogether. Ultimately, I find that too simplistic PMS are pervasive and incentivize unintended employee behavior detrimental to long-term performance.
Although strategic PM has benefited from substantial research in the last dec- ades, I conclude that consensus over its benefits and restrictions has not been reached. Research in this field has been undertaken by academics from various disciplines, such as accounting, management and operations. As a result, until today the body of knowledge in PM lacks cohesiveness. Thus, scholars need to overcome their discipli- nary boundaries and combine research findings to achieve new breakthroughs (Marr, 2003; Neely, 1999). In addition, to increase the generalizability of the discussed theo- ries and findings for practice researches have to be more specific about the PMS they investigate for the purpose of strategy implementation (Franco-Santos et al., 2007). Recently, much attention in the academic literature has been dedicated to the concept of dynamic strategic PMS since sustainable competitive advantage rests on continu- ous organizational transformation over time. However, theories to build dynamism into PMS also require further examination in the future (Gimbert, 2010; Kennerley and Neely, 2002; Kolehmainen, 2010).
Behn, R. D. 2003. Why measure performance? Different purposes require different measures. Public administration review, 63 (5): 586-606.
Bird, S. M., David, C., Farewell, V. T., Harvey, G., Tim, H., & Peter, C. 2005. Per- formance indicators: good, bad, and ugly. Journal of the Royal Statistical So- ciety: Series A (Statistics in Society), 168 (1): 1-27.
Bititci, U. S., Carrie, A. S., & McDevitt, L. 1997. Integrated performance measure- ment systems: a development guide. International Journal of Operations & Production Management, 17 (5): 522-534.
Bruggeman, W. 2004. Integrated Performance Management through Effective Man- agement Control. Verweire, K., & Berghe, L. (Eds.). Integrated performance management: a guide to strategy implementation. London: SAGE Publica- tions, 152-173.
Bruns, W. 1998. Profit as a performance measure: powerful concept, insufficient measure. In Performance Measurement-Theory and Practice: The First In- ternational Conference on Performance Measurement, 14-17.
De Geuser, F., Mooraj, S., & Oyon, D. 2009. Does the balanced scorecard add value? Empirical evidence on its effect on performance. European Accounting Re- view, 18 (1): 93-122.
Dixon, J. R., A. J. Nanni, and T. E. Vollman. 1990. The New Performance Chal- lenge: Measuring Operations for World-Class Competition. Homewood, IL: Business One Irwin.
Eccles, R. G. 1990. The performance measurement manifesto. Harvard business re- view, 69 (1): 131-137.
Franco-Santos, M., Kennerley, M., Micheli, P., Martinez, V., Mason, S., Marr, B., & Neely, A. 2007. Towards a definition of a business performance measurement system. International Journal of Operations & Production Management, 27 (8): 784-801.
Garengo, P., & Biazzo, S. 2012. Unveiling strategy in SMEs through balanced score- card implementation: A circular methodology. Total Quality Management & Business Excellence, 23 (1): 79-102.
Gimbert, X., Bisbe, J., & Mendoza, X. 2010. The role of performance measurement systems in strategy formulation processes. Long Range Planning, 43 (4): 477- 497.
Hall, M., 2008. The effect of comprehensive performance measurement systems on role clarity, psychological empowerment and managerial performance. Ac- counting, Organizations and Society, 33 (3): 141-163.
Henri, J. F. 2006. Management control systems and strategy: a resource-based per- spective. Accounting, organizations and society, 31 (6): 529-558.
Hudson, M., Smart, A., & Bourne, M. 2001. Theory and practice in SME perfor- mance measurement systems. International Journal of Operations & Produc- tion Management, 21 (8): 1096-1115.
Ittner, C. D., & Larcker, D. F. 2003. Coming up short on nonfinancial performance measurement. Harvard business review, 81 (11): 88-95.
Ittner, C. D., Larcker, D. F., & Randall, T. 2003. Performance implications of strate- gic performance measurement in financial services firms. Accounting, Organi- zations and Society, 28 (7): 715-741.
Kaplan, R.S., & Norton, D.P. 1992, The balanced scorecard - measures that drive performance, Harvard Business Review, 70 (1): 71-91.
Kaplan, R. S., & Norton, D. P. 2008. Mastering the management system. Harvard business review, 86 (1): 62-77.
Kennerley, M., & Neely, A. 2002. A framework of the factors affecting the evolution of performance measurement systems. International journal of operations & production management, 22 (11): 1222-1245.
Kolehmainen, K. 2010. Dynamic strategic performance measurement systems: bal- ancing empowerment and alignment. Long Range Planning, 43 (4): 527-554.
Kula, W. 1986. Measures and men. Princeton, NJ: Princeton University Press.
Likierman, A. 2009. The five traps of performance measurement. Harvard business review, 87 (10): 96-101.
Cross, K. F., & Lynch, R. L. 1991. Measure up - The essential guide to measuring business performance, Mandarin: London.
Malina, M. A., & Selto, F. H. 2001. Communicating and controlling strategy: an em- pirical study of the effectiveness of the balanced scorecard. Journal of Man- agement Accounting Research, 13 (1): 47-90.
Marr, B., & Schiuma, G. 2003. Business performance measurement - past, present and future. Management Decision, 41 (8): 680-687.
McCunn, P. 1998. The balanced scorecard... the eleventh commandment.
Management Accounting, 76: 34-37.
Micheli, P., & Manzoni, J. F. 2010. Strategic performance measurement: Benefits, limitations and paradoxes. Long Range Planning, 43 (4): 465-476.
Mintzberg, H., Ahlstrand, B., & Lampel, J. 1998. Strategy safari: A guided tour through the wilds of strategic management, Prentice-Hall: New York.
Neely, A. 1999. The performance measurement revolution: why now and what next?. International Journal of Operations & Production Management, 19 (2): 205- 228.
Neely, A., & Bourne, M. 2000. Why measurement initiatives fail. Measuring busi- ness excellence, 4 (4): 3-7.
Neely, A., Kennerley, M., & Adams, C. 2002. Performance measurement frame- works: a review. Neely, A. (Eds.). Business Performance Measurement: Uni- fying theories and integrating practice. New York: Cambridge University Press, 143-162.
Power, M. 2004. Counting, control and calculation: Reflections on measuring and management. Human relations, 57 (6): 765-783.
Pun, K. F., & White, A. S. 2005. A performance measurement paradigm for integrat- ing strategy formulation: A review of systems and frameworks . International Journal of Management Reviews, 7 (1): 49-71.
Simons, R. 1994. How new top managers use control systems as levers of strategic renewal. Strategic Management Journal, 15 (3): 169-189.
Simons, R. 1995. Control in an age of empowerment: how can managers promote innovation while avoiding unwelcome surprises? Harvard Business Review, 73 (2): 80-88.
Smith, P. 1995. On the unintended consequences of publishing performance data in the public sector. International journal of public administration, 18 (2-3): 277- 310.
Springer, C. B. 2008. Moving From Performance Measurement to Strategic Man- agement. American Society for Public Administration, 31 (11): 9.
Veth, G. 2006. Translating Strategy into Action: The Missing Link. DM Review, 16 (7): 6.
Verweire, K., Baeten, X., Somers, L., & Van den Berghe, L. 2004. Performance from a Finance Perspective: Shareholder Value and Beyond. Verweire, K., & Berghe, L. (Eds.). Integrated performance management: a guide to strategy implementation. London: SAGE Publications, 19-36.
- Quote paper
- Konstantin Kugler (Author), 2014, Performance Measurement as a Tool for Strategy Implementation, Munich, GRIN Verlag, https://www.grin.com/document/300066