Managers and business management researchers around the globe are increasingly interested in understanding the secrets of high performing organizations. The search for the keywords “high performance organizations” delivers a list of over 2700 books at Amazon.com. Organizations such as the Performance Management Association (PMA) report a rapidly growing number of members. The attendance to the conferences and seminars around the topics of high performing organizations shows constant growth in Europe and in US. Finally, almost all leading consulting companies established teams that provide professional advisory services to private and public organizations, which by now have become a multimillion dollar business (e.g. Tollman et al. 2009).

Since the 1980s, advances in business management research led to the development of various theoretical frameworks describing the characteristics of high performing organizations. Top selling books by Tom Peters and Bob Waterman “In Search of Excellence” and “Built to Last” by Jim Collins are just two of the most prominent examples. While in depth overview of these framework has been intensively described elsewhere (e.g. Bourne et al. 2009; de Waal 2010), the essence of these books can be summarized as follows: few success factors such as “strategy alignment”, “customer orientation” and “personnel excellence” are often shared by high performing organizations.

Such statements may be familiar to you and they may provide you with rhetorical ammunition for the next top executive meeting. But does it really help to manage the business? Despite the great success of the books like “In Search of Excellence” and “Built to Last”, this work has been criticized for being far too general and imprecise for companies to be able to work with. In fact, these success factors are very abstract and are applicable to almost all existing organizations. With other words, this general knowledge is of little value for the practice (Duncan and Harrop 2006).

In 2010s managers want to know exactly which characteristics make their specific organization successful. They want to understand them, to set up projects and to deliver tangible results. The question for managers today remains – which high performance characteristics does my company have and how can these characteristics be managed?

Fortunately, universities and professional consultants developed sophisticated procedures how these characteristics can be identified and described quantitatively (e.g. Pavlov and Bourne 2011). One of the best practice examples for this work is the methodological approach developed by Andy Neely and the Performance Management Association (link to book). This approach is based on a four steps model. These steps are:

1. Causal performance modeling: define your performance criteria, identify your specific success factors, measure the relationships between the factors and performance
2. Set up projects: based on insights from step 1, setup projects that impact your success factors
3. Measure progress: measure your performance with key performance indicators
4. Make decisions: do your decisions have an impact on the success factors and consequently on the performance?

Klick on the chart below to see the framework.

In the following blogs, I will report on each of the four steps presented above starting with the first step. You will find out how powerful statistical methods enable managers to better understand the performance driving characteristics of their organizations and which are worth being actively managed.

References:

• Bourne, Mike; Mura, Matteo; Franco-Santos, Monica; Pavlov, Andrey; Martinez, Veronica; Lucianetti, Lorenzo (2009): Performance management practices and the drivers of business performance. Performance Measurement Association Conference Paper. Centre for Business Performance. Bedfordshire.
• Duncan, Sue; Harrop, Anne (2006): A user perspective on research quality. In International Journal of Social Research Methodology 9 (2), pp. 159–174. Available online at 10.1080/13645570600595462.
• Ed Barrows and Andy Neely (2011): Managing Performance in Turbulent Times: Analytics and Insight ; John Wiley & Sons; Cambridge.
• Pavlov, Andrey; Bourne, Mike (2011): Explaining the effects of performance measurement on performance. An organizational routines perspective. In International Journal of Operations & Production Management 31 (1), pp. 101–122.
• Tollman, Peter; Bixner, Ralf; Keenan, Perry; Powell, Kimberly (2009): Cascading change. Edited by Boston Consulting Group. Boston.
• Waal, André de (2010): Performance-driven behavior as the key to improved organizational performance. In Measuring Business Excellence 14 (1), pp. 79–95. Available online at http://www.emeraldinsight.com/journals.htm?issn=1368-3047&volume=14&issue=1.

Read also:

• Huelsbeck, David P.; Merchant, Kenneth A.; Sandino, Tatiana (2011): On testing business models. In Accounting Review 86 (5), pp. 1631–1654.
• Hung-Yi, Wu (in press) Constructing a strategy map for banking institutions with key performance indicators of the balanced scorecard Evaluation and Program Planning, Available online 8 December 2011
• Original Research Article 
  ► It demonstrates a clear roadmap to help management prioritize performance indicators based on influential directions and strengths of causal relationships. ► Three most essential evaluation indicators for banking performance are customer satisfaction, sales performance, and customer retention rate. ► Through the strategy map, management could better invest limited resources in the areas that need improvement most. ► Nonfinancial measures, particularly, in the customer perspective, may be more emphasized by the service sector as the foremost outcome measures. ► The proposed framework can be applicable to institutions in other industries.

As a guest-speaker, Professor Andy Neely will deliver the key note and participate at the podium discussion structured around the following topics:

• Performance Measurement: Challenges and concepts that work
• Controlling systems: Opportunities and solutions in practice
• Implementation: Hurdles and results
• Business Performance Management: Planning, Budgeting and Performance Reviews
• Individual Performance Management: Myth MbO and alternatives
• Infrastructure: How to integrate the individual and the institutional performance management

You can download the presentation by Andy Neely here:  http://www.sphereadvisors.com/media/archive1/Events/ManagingPerformanceInTurbulentAge.pdf

Six workshops in the areas of control, performance management, finance, human resources, strategy, risk, governance and compliance will be held on one day. The detailed description and the agenda can be found here:

https://www.xing.com/cgi-bin/groups-stream.pl?name=controlling&id=83027

You will meet me there.

Follow the link for more information:

http://www.performanceportal.org/controllersxchange-2011-l-6-october-d%C3%BCsseldorf-l-performance-management

Peer reviewed articles also identify PMS integration as one of the critical success factors of business management. In fact, claims that the degree of PMS integration, both vertical and horizontal, may have a positive impact on performance are not new (Bititci, 1994). For example in her literature review Langfield-Smith (1997) argues that theoretical and normative research in that area began to appear in the mid-1980s, but still lacked empirical evidence in the mid-1990s. More than a decade later, empirical studies that explicitly model PMS integration as the independent variable and performance as the dependent variabel are still rare.

Since the publications by Kaplan and Norton (1996a, b) integration of PMS has been frequently refered to in academic literature. However, the review by Franco-Santos and Bourne (2005) showed that this concept is not uniformally understood. According to them, two perspectives on integration can be identified (see figure below). The first perspective refers to the integration as the vertical allignment along the reporting chain. This understanding includes the interaction of performance measurement with the organizational strategy, cascading the strategic goals down to operational divisions and the linkage to individual incentives (Bititci, 1994; Chenhall, 2005). The second perspective refers to the horizontal integration, which is the cross functional connection of the performance measurement system along divisions. Horizontal integration includes the interconnection of PMS with other management control systems, such as planning and budgeting (Henri, 2008), strategic accounting systems (Cadez & Guilding, 2008), costing (Anderson, 2006), ERP (Kallunki, Laitinen, & Silvola, forthcoming) and benchmarking (Herzog, Tonchia, & Polajnar, 2009). Both perspectives have been reserached by scholars – with limited results.

For example, the impact of integration (vertical and/or horizontal) on performance is not clearly researched. While some authors state that integration is one of the critical success factors of performance measurement initiatives (Chenhall, 2005; Chenhall & Langfield-Smith, 2007; Franco-Santos & Bourne, 2005), others doubt that integration is important per se (Rom & Rohde, 2007). In fact, it has been argued that companies may need a certain level of PMS integration (Chapman & Kihn, 2009), but may be better off with specialized stand alone solutions instead of creating fully integrated systems (Pike, Tayles, & Abu Mansor, forthcoming). An interesting research question would be therefor, if there is an impact of integrated performance measurement systems on performance. And if there is an effect, through which mechanisms does it take place.

References

[PDF] Accenture (2010). Swedish match: Enterprise performance management framework. Retrieved from http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture_FPM_Helped_Swedish_Match_Implement_an_EPM_Framework.pdf

Anderson, S. W. (2006). Managing costs and cost structure throughout the value chain: Research on strategic cost management. In C. S. Chapman (Ed.), Handbooks of Management Accounting Research (pp. 481–506). Elsevier.

[PDF] Bititci, U. S. (1994). Measuring your way to profit. Management Decision, 32(4), 16–24.

Cadez, S., & Guilding, C. (2008). An exploratory investigation of an integrated contingency model of strategic management accounting. Accounting, Organizations and Society, 33(7/8), 836–863.

Chapman, C. S., & Kihn, L.-A. (2009). Information system integration, enabling control and performance. Accounting, Organizations and Society, 34(2), 151–169.

Chenhall, R. H. (2005). Integrative strategic performance measurement systems, strategic alignment of manufacturing, learning and strategic outcomes: An exploratory study. Accounting, Organizations and Society, 30(5), 395–422.

[PDF] Chenhall, R. H., & Langfield-Smith, K. (2007). Multiple perspectives of performance measures. European Management Journal, 25(4), 266–282.

[PDF] Franco-Santos, M., & Bourne, M. (2005). An examination of the literature relating to issues affecting how companies manage through measures. Production Planning & Control, 16(2), 114–124.

Henri, J.-F. (2008). Taxonomy of performance measurement systems. Advances in Management Accounting, 17, 247–288.

Herzog, N. V., Tonchia, S., & Polajnar, A. (2009). Linkages between manufacturing strategy, benchmarking, performance measurement and business process reengineering. Computers & Industrial Engineering, 57(3), 963–975.

IBM (2010). Analytics: The new path to value: How the smartest organizations are embedding analytics to transform insights into action: IBM Institute for Business Value. Retrieved from http://public.dhe.ibm.com/common/ssi/ecm/en/gbe03371usen/GBE03371USEN.PDF.

Kallunki, J.-P., Laitinen, E. K., & Silvola, H. (forthcoming). Impact of enterprise resource planning systems on management control systems and firm performance. International Journal of Accounting Information Systems,

Kaplan, R. S., & Norton, D. P. (1996a). The balanced scorecard: Translating strategy into action. Boston: Harvard Business School Press.

Kaplan, R. S., & Norton, D. P. (1996b). Using the balanced scorecard as a strategic management system. Harvard Business Review, 74(1), 75–85.

Langfield-Smith, K. (1997). Management control systems and strategy: A critical review. Accounting, Organizations and Society, 22(2), 207–232.

Pike, R. H., Tayles, M. E., & Abu Mansor, N. N. (forthcoming). Activity-based costing user satisfaction and type of system: A research note. The British Accounting Review,

[PDF PhD] Rom, A., & Rohde, C. (2007). Management accounting and integrated information systems: A literature review. International Journal of Accounting Information Systems, 8(1), 40–68.

Townsend, P., Smith, S., Richards, G., & Wennekes, K. (2009). Performance management matters: Sustaining superior results in a global economy: PricewaterhouseCoopers.

Several ways to categorize performance have been presented in the literature (see literature review by Kihn, 2010). One way is to distinguish the outcomes of organizational activities and the means by which these outcomes are reached (Govindarajan & Fisher, 1990). The former is often called “performance” while the latter is commonly referred to as “effectiveness” (Ukko, 2009). Interestingly enough, this distinction appeared only after 1978 (Henri, 2004). Before that time both definitions were used interchangeably.

Another way to characterize performance is to distinguish between financial and non-financial performance (Ittner, 2008). The financial performance is often measured using traditional accounting KPIs such as ROA, ROS, EBIT, EVA® or Sales growth (Ittner & Larcker, 1997; Fraquelli & Vannoni, 2000; Crabtree & DeBusk, 2008). The advantage of these measurements is their general availability, since every profit oriented organization produces these figures for the yearly financial reporting (Chenhall & Langfield-Smith, 2007). However, balance sheet manipulations and choices of accounting methods may also lead to values that allow only limited comparability of the financial strength of companies.

The non-financial performance can be measured using operational KPIs. Market share, innovation rate or customer satisfaction are prominent examples (Hyvönen, 2007). Tangen, (2003) provides an overview of frequently used performance measures. Many researchers also use self reported measures to operationalize performance (Evans, 2004; Chenhall & Morris, 1995; Henri, 2006; Ittner, Lanen, & Larcker, 2002). Others combine both, the accounted financial KPIs and self reported measures in their reports (Cadez & Guilding, 2008). Langfield-Smith, (1997) writes that there are various ways non-financial performance can be measured, however the performance can be hardly assessed without the link to corporate strategy. The consequence for the researcher is simple: it is first to decide what the research question should be, then a performance definition can be created.

Table 1: Elements of performance definition (Timur Pasch, 2010)

References

Cadez, S., & Guilding, C. (2008). An exploratory investigation of an integrated contingency model of strategic management accounting. Accounting, Organizations and Society, 33(7/8), 836–863.

Chenhall, R. H., & Morris, D. (1995). Organic decision and communication processes and management accounting systems in entrepreneurial and conservative business organizations. Omega, 23(5), 485–497.

Chenhall, R. H., & Langfield-Smith, K. (2007). Multiple perspectives of performance measures. European Management Journal, 25(4), 266–282.

Crabtree, A. D., & DeBusk, G. K. (2008). The effects of adopting the balanced scorecard on shareholder returns.Advances in Accounting, 24(1), 8–15.

Evans, J. R. (2004). An exploratory study of performance measurement systems and relationships with performance results. Journal of Operations Management, 22(3), 219–232.

Fraquelli, G., & Vannoni, D. (2000). Multidimensional performance in telecommunications, regulation and competition: Analysing the European major players. Information Economics and Policy, 12(1), 27–46.

[PDF] Govindarajan, V., & Fisher, J. (1990). Strategy, control systems and ressource sharing: Effects on business-unit performance. Academy of Management Journal, 33(2), 259–285.

[PDF] Henri, J.-F. (2004). Performance measurement and organizational effectiveness: Bridging the gap. Managerial Finance, 30(6), 93–123.

Henri, J.-F. (2006). Management control systems and strategy: A resource-based perspective. Accounting, Organizations and Society, 31(6), 529–558.

[PDF] Hyvönen, J. (2007). Strategy, performance measurement techniques and information technology of the firm and their links to organizational performance. Management Accounting Research, 18(3), 343–366.

Ittner, C. D. (2008). Does measuring intangibles for management purposes improve performance?: A review of the evidence. Accounting & Business Research, 38(3), 261–272.

Ittner, C. D., Lanen, W., & Larcker, D. (2002). The association between activity-based costing and manufacturing performance. Journal of Accounting Research, 40(3), 711–726.

Ittner, C. D., & Larcker, D. F. (1997). Quality strategy, strategic control systems, and organizational performance.Accounting, Organizations and Society, 22(3-4), 293–314.

Kihn, Lili-Anne (2010): Performance outcomes in empirical management accounting research. Recent developments and implications for future research. In International Journal of Productivity and Performance Management 59 (5), pp. 468–492.

Langfield-Smith, K. (1997). Management control systems and strategy: A critical review. Accounting, Organizations and Society, 22(2), 207–232.

Tangen, S. (2003). An overview of frequently used performance measures. Work Study, 52(7), 347–354.

[PDF] Ukko, J. (2009). Managing through measurement: A framework for successful operative level performance measurement. PhD thesis at the Lappeenranta University of Technology.

These factors include following capabilities (follow the links provided to each marked key word to discover current management thinking):

Organizational design characteristics

• D1. Stimulate cross-functional and cross-organizational collaboration.
• D2. Simplify and flatten the organization by reducing boundaries and barriers between and around units.
• D3. Foster organization-wide sharing of information, knowledge and best practices.
• D4. Constantly realign the business with changing internal and external circumstances.

Strategy characteristics

• S1. Define a strong vision that excites and challenges.
• S2. Balance long-term focus and short-term focus.
• S3. Set clear, ambitious, measurable and achievable goals.
• S4. Create clarity and a common understanding of the organization’s direction and strategy.
• S5. Adopt the strategy that will set the company apart.
• S6. Align strategy, goals, and objectives with the demands of the external environment and build robust, resilient and adaptive plans to achieve these.

Process characteristics

• P1. Design a good and fair reward and incentive structure.
• P2. Continuously innovate products, processes and services.
• P3. Continuously simplify and improve all the organization’s processes.
• P4. Create highly interactive internal communication.
• P5. Measure what matters.
• P6. Report to everyone financial and non-financial information needed to drive improvement.
• P9. Strive for continuous process optimalization.
• P8. Strive to be a best practice organization.
• P9. Deploy resources effectively.

Technology characteristics

• T1. Implement flexible ICT-systems throughout the organization.
• T2. Apply user-friendly ICT-tools to increase usage.

Leadership characteristics

• L1. Maintain and strengthen trust relationships with people on all levels.
• L2. Live with integrity and lead by example.
• L3. Apply decisive action-focused decision-making.
• L4. Coach and facilitate.
• L5. Stretch yourselves and your people.
• L6. Develop effective, focused and strong leadership.
• L7. Allow experiments and mistakes.
• L8. Inspire the people to accomplish extraordinary results.
• L9. Grow leaders from within.
• L10. Stimulate change and improvement.
• L11. Assemble a diverse and complementary management team and workforce.
• L12. Be committed to the organization for the long haul.
• L13. Be confidently humble.
• L14. Hold people responsible for results and be decisive about nonperformers.

Individuals & Roles characteristics

• I1. Create a learning organization.
• I2. Attract exceptional people with a can-do attitude who fit the culture.
• I3. Engage and involve the workforce.
• I4. Create a safe and secure workplace.
• I5. Master the core competencies and be an innovator in them.
• I6. Develop people to be resilient and flexible.
• I7. Align employee behaviour and values with company values and direction.

Culture characteristics

• C1. Empower people and give them freedom to decide and act.
• C2. Establish strong and meaningful core values.
• C3. Develop and maintain a performance-driven culture.
• C4. Create a culture of transparency, openness and trust.
• C5. Create a shared identity and a sense of community.

External orientation characteristics

• E1. Continuously strive to enhance customer value creation.
• E2. Maintain good and long-term relationships with all stakeholders.
• E3. Monitor the environment consequently and respond adequately.
• E4. Choose to compete and compare with the best in the market place .
• E5. Grow through partnerships and be part of a value creating network.
• E6. Only enter new business that complement the company‟s strengths.

A more recent work around the characteristics of high performing organizations is provided by Kiron et al. (2011). Please read the Analytics: The Widening Divide for more details.

Sources:

• de Waal, A. (2008): The role of information technology in the high performance organization. Center for Organizational Performance.
• de Waal, A. (2010a): The characteristics of a high performance organisation. Center for Organizational Performance. Hilversum.
• de Waal, A. (2010b): Performance-driven behavior as the key to improved organizational performance. In Measuring Business Excellence 14 (1), pp. 79–95. Available online at http://www.emeraldinsight.com/journals.htm?issn=1368-3047&volume=14&issue=1.
• de Waal, A.; Duong, H.; Ton, V. (2009): High performance in Vietnam. The case of the Vietnamese banking industry. Journal of Transnational Management, Vol. 14, pp. 179–201.
• de Waal, A.; Frijns, M. (2009): Working on high performance in Asia. The case of Nabil Bank. Measuring Business Excellence, Vol. 13, pp. 29–38.
• Kourtit, K.; de Waal, A. (2008): Strategic performance management in practice. Advantages, disadvantages and reasons for use. Maastricht School of Management.

Additional reading:

• Bourne, M.; Kennerley, M.; Franco-Santos, M. (2005): Managing through measures. A study of impact on performance. Journal of Manufacturing Technology Management, Vol. 16, pp. 373–395.
• Franco-Santos, M.; Bourne, M. (2005): An examination of the literature relating to issues affecting how companies manage through measures. Production Planning and Control, Vol. 16, pp. 114–124.
• Guthrie, J. (2001): High-Involvement Work Practices, Turnover, and Productivity: Evidence from New Zealand. The Academy of Management Journal, Vol. 1, pp. 180–190.
• Karhu, J.; Ukko, J.; Rantanen, H. (2006): Performance measurement and employees. Knowledge, understanding and opportunities to participate in decisionmaking. In: Neely, Andrew; Kennerley, Mike; Walters, Angela (Ed.): Performance measurement and management: public and private. Bedfordshire: Cranfield University, pp. 377–384.

Why do some companies perform better using corporate performance measurement and management systems than others?

To cope with the increasing complexity of the business environment, management teams must prioritize effectively and focus their attention on activities that lead to higher performance. For that reason many organizations have invested substantial resources in the implementation of various performance measurement and management techniques. They believe, that performance measurement and management might help them to improve the performance somehow (see illustration below).

However, the added value of that investment often remains unclear with only few organizations reporting tangible payoff on the performance measurement systems. Consequently, managers of today need a clear guidance for their efforts to manage performance and on how to get the most value out of the existing performance measurement systems.

Since Kaplan and Norton (1992) first introduced their Balanced Scorecard, a substantial body of research around the design, implementation, and usage of performance measurement systems (PMS), has emerged (see Neely, 2005, for literature review). Despite the growing academic and professional interest, there is currently little knowledge regarding the impact of PMS on organizations (see Bourne, Kennerley, & Franco-Santos, 2005 for literature review). Furthermore, existing research provides contradictory results concerning performance effects of the PMS usage (Martinez, Kennerley, & Neely, 2004). While some authors clearly see positive effects (Davis & Albright, 2004; deWaal, Kourtit, & Nijkamp, 2009; Ukko, Tenhunen, & Rantanen, 2007; de Geuser, Mooraj, & Oyon, 2009), others found no evidence of increasing performance after the implementation of PMS (Meyer, 2007). Therefore, a consensus in the ongoing discussion regarding the effect of PMS on organizations has not yet been achieved.

Based on results from literature, this study is set to identify the success factors leading to a better use of performance management systems. The research problem is to find out how companies can be successfully managed with measures (see illustration below).

The starting point for the research is the believe, that performance management systems (PMS) can lead to a greater performance only when PMS are used by people to make better business decisions (Chenhall, 2003). If this is the case, and other variables can be controlled for, the interesting question is what makes people take better decisions with PMS. Consequently, the conceptual model includes a link between decision making based on PMS information and performance. This link has been often described qualitatively (Goold & Quinn, 1990; Gunasekaran & Kobu, 2007; Laitinen, 2009; Lipe & Salterio, 2000), but quantitative analysis is rare (e.g. Foster, Swenson, 1997). Thus, this study wants to contribute to the research and provide evidence why some companies use PMS better than others (see illustration below).

To provide a solid answer to that question the study is organized as following:

1. Identify relevant factors leading to an effective performance management from literature.
2. Define a solid conceptual model.
3. Create instrument for measuring concepts based on suggestions from literature.
4. Gather empirical data and analyse the data.
5. Arrive at conclusions.
6. Provide final report.

Key characteristics of the research:

1. Literature based.
2. Quantitative, positivistic approach.
3. Company as unit of analysis.
4. Cross sectional non probability sample of profit oriented firms.

References:

Bourne, M., Kennerley, M., & Franco-Santos, M. (2005). Managing through measures: A study of impact on performance. Journal of Manufacturing Technology Management, 16(4), 373–395.

Chenhall, R. H. (2003). Management control systems design within its organizational context: findings from contingency-based research and directions for the future. Accounting, Organizations and Society, 28(2-3), 127–168.

[PDF] Davis, S., & Albright, T. (2004). An investigation of the effect of Balanced Scorecard implementation on financial performance. Management Accounting Research, 15(2), 135–153.

de Waal, A., Kourtit, K., & Nijkamp, P. (2009). The relationship between the level of completeness of a strategic performance management system and perceived advantages and disadvantages. International Journal of Operations & Production Management, 29(12), 1242–1265.

[Summary] Foster, George; Swenson, Dan W. (1997): Measuring the success of activity-based cost management and its determinants. In Journal of Management Accounting Research 9, pp. 109–141.

Geuser, F. de, Mooraj, S., & Oyon, D. (2009). Does the balanced scorecard add value? Empirical evidence on its effect on performance. European Accounting Review, 18(1), 93–122.

Goold, M., & Quinn, J. J. (1990). The paradox of strategic controls. Strategic Management Journal, 11(1), 43–57.

Gunasekaran, A., & Kobu, B. (2007). Performance measures and metrics in logistics and supply chain management: A review of recent literature (1995-2004) for research and applications. International Journal of Production Research, 45(12), 2819–2840.

Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard: Measures that drive performance. Harvard Business Review, 71–79.

Laitinen, E. K. (2009). Importance of performance information in managerial work. Industrial Management & Data Systems, 109(4), 550–569.

Lipe, M. G., & Salterio, S. E. (2000). The balanced scorecard: Judgmental effects of common and unique performance measures. Accounting Review, 75(3), 283.

Martinez, V., Kennerley, M., & Neely, A. (2004). Impact of PMS on business performance: A methodological approach. Cranfield.

Neely, A. (2005). The evolution of performance measurement research: Developments in the last decade and a research agenda for the next. International Journal of Operations & Production Management, 25(12), 1264–1277.

Ukko, J., Tenhunen, J., & Rantanen, H. (2007). Performance measurement impacts on management and leadership: Perspectives of management and employees. International Journal of Production Economics, 110(1-2), 39–51.