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Using systems thinking to enhance strategy maps Martin Kunc School of Business, University of Adolfo Iban ˜ ez, Santiago, Chile Abstract Purpose – This paper aims to propose a method to assist organisations to develop their causal models, as well as to understand them, and to propose systems thinking as a method to achieve these objectives. Design/methodology/approach – The paper starts with a review of the literature related to the concerns existing with respect to strategy maps and the interrelationships between measures. Then it explains the benefits of systems thinking and causal loop diagrams. Finally, the paper presents the results obtained from a group of 32 students who took a course in strategic control systems and used systems thinking to design a performance measurement system for their businesses. Findings – The number of concepts included in students’ causal loop diagrams averages 16, which are in line with the number of measures suggested in the Balanced Scorecard literature, but only 48 per cent of concepts were related to the four perspectives suggested in the Balanced Scorecard methodology. Few students acknowledged the existence of time delays in the interrelationships. Research limitations/implications – While the sample is statistically significant, it represents the results of one course. Practical implications – The use of systems thinking and causal loops diagrams simplifies the design of a Balanced Scorecard and improves the alignment of the organisation with the performance measurement system. Originality/value – While scholars have criticised the interrelationships between measures in the Balanced Scorecard, few have suggested solutions to this issue. The paper presents the application of a well-known tool to improve the processes of designing and understanding the interrelationships between measures in the Balanced Scorecard. Keywords Balanced scorecard, Performance management, Strategic management, Cause and effect analysis, Business performance Paper type Research paper Introduction In recent years, new strategic control systems that combine a set of financial and non-financial measures have become widely available for managers (Nørreklit, 2000). The most well known strategic control system is the Balanced Scorecard (Kaplan and Norton, 1996a). The Balanced Scorecard aims to translate a business unit’s mission and strategy into tangible objectives and measures. The measures represent a balance between outcome measures – the financial performance of the organisation – and the measures that will drive future performance – such as customer satisfaction, critical business processes, innovation, learning and growth (Kaplan and Norton, 1996a). The Balanced Scorecard has followed a process of evolution from its beginnings as a performance measurement tool, which looked beyond the traditional financial measures, to a strategic management and control system (Neely et al., 2003; Marr and Schiuma, 2003; Lawrie and Cobbold, 2004; Bible et al., 2006). Early on, a navigation metaphor was used to illustrate the need for additional performance measures (Kaplan The current issue and full text archive of this journal is available at www.emeraldinsight.com/0025-1747.htm Using systems thinking 761 Received November 2007 Revised February 2008 Accepted February 2008 Management Decision Vol. 46 No. 5, 2008 pp. 761-778 q Emerald Group Publishing Limited 0025-1747 DOI 10.1108/00251740810873752

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Using systems thinking toenhance strategy maps

Martin KuncSchool of Business, University of Adolfo Ibanez, Santiago, Chile

Abstract

Purpose – This paper aims to propose a method to assist organisations to develop their causalmodels, as well as to understand them, and to propose systems thinking as a method to achieve theseobjectives.

Design/methodology/approach – The paper starts with a review of the literature related to theconcerns existing with respect to strategy maps and the interrelationships between measures. Then itexplains the benefits of systems thinking and causal loop diagrams. Finally, the paper presents theresults obtained from a group of 32 students who took a course in strategic control systems and usedsystems thinking to design a performance measurement system for their businesses.

Findings – The number of concepts included in students’ causal loop diagrams averages 16, whichare in line with the number of measures suggested in the Balanced Scorecard literature, but only 48 percent of concepts were related to the four perspectives suggested in the Balanced Scorecardmethodology. Few students acknowledged the existence of time delays in the interrelationships.

Research limitations/implications – While the sample is statistically significant, it represents theresults of one course.

Practical implications – The use of systems thinking and causal loops diagrams simplifies thedesign of a Balanced Scorecard and improves the alignment of the organisation with the performancemeasurement system.

Originality/value – While scholars have criticised the interrelationships between measures in theBalanced Scorecard, few have suggested solutions to this issue. The paper presents the application of awell-known tool to improve the processes of designing and understanding the interrelationshipsbetween measures in the Balanced Scorecard.

Keywords Balanced scorecard, Performance management, Strategic management,Cause and effect analysis, Business performance

Paper type Research paper

IntroductionIn recent years, new strategic control systems that combine a set of financial andnon-financial measures have become widely available for managers (Nørreklit, 2000).The most well known strategic control system is the Balanced Scorecard (Kaplan andNorton, 1996a). The Balanced Scorecard aims to translate a business unit’s mission andstrategy into tangible objectives and measures. The measures represent a balancebetween outcome measures – the financial performance of the organisation – and themeasures that will drive future performance – such as customer satisfaction, criticalbusiness processes, innovation, learning and growth (Kaplan and Norton, 1996a). TheBalanced Scorecard has followed a process of evolution from its beginnings as aperformance measurement tool, which looked beyond the traditional financialmeasures, to a strategic management and control system (Neely et al., 2003; Marr andSchiuma, 2003; Lawrie and Cobbold, 2004; Bible et al., 2006). Early on, a navigationmetaphor was used to illustrate the need for additional performance measures (Kaplan

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0025-1747.htm

Using systemsthinking

761

Received November 2007Revised February 2008

Accepted February 2008

Management DecisionVol. 46 No. 5, 2008

pp. 761-778q Emerald Group Publishing Limited

0025-1747DOI 10.1108/00251740810873752

and Norton, 1996a, p. 1). Over time, the navigation metaphor expanded to include theprocess of strategic mapping (Kaplan and Norton, 2004) and decisions about where tolead a firm (Kaplan and Norton, 2006). To summarise, the Balanced Scorecard intendsto be a feed-forward control system as it links outcome measures and performancedrivers in cause-and-effect relationships (Nørreklit, 2000).

However, the Balanced Scorecard has received some criticisms related to theinterrelationships between measures (Nørreklit, 2000; Marr and Schiuma, 2003; Lawrieand Cobbold, 2004). In a recent review of performance measurement systems, scholarshave recommended that greater clarity in the linkages between different dimensions ofthe organisational performance should become an important issue during the processof designing performance measurement systems (Neely et al., 2003). For example, Ittnerand Larcker (2000, p. 3) suggest the lack of an explicit casual model of the relationsbetween measures contributes to difficulties in evaluating the relative importance ofperformance measures, and they add “without knowing the size and timing ofassociations among measures, companies find it difficult to make decisions or measuresuccess based on them”. As organisations increasingly use causal models like strategicmaps for the basis of their performance measurement systems (Franco-Santos andBourne, 2005), methodologies already established to develop causal models can bemore widely employed to help in the design phase of performance measurementsystems.

This paper aims to contribute with a method to assist organisations to develop theircausal models (Othman, 2006) as well as understanding them (Franco and Bourne,2003). In this paper, systems thinking (Senge, 1999) is proposed as a method to achievethese objectives. The use of systems thinking, as a methodology to overcome some ofthe criticisms, arises from the author’s experience in teaching strategic control systemscourses in executive MBA programmes. The paper is organised as follows: first areview of the criticisms of the Balanced Scorecard is introduced and, later on, anintroduction to systems thinking and its role on improving the design andunderstanding of Balanced Scorecards. Then the results of the application of systemsthinking in class are shown before concluding with some remarks.

The role of causal models in performance measurement systemsWhen a performance outcome is wrong, managers should clearly know where theerrors are coming from so they can intervene in leveraging points that improve theperformance of the organisation at the lowest possible cost. A relevant notionemployed in the previous statement is that of interconnectedness between processes,areas and functions in the organisation: the belief that all different aspects andfunctions of the organisation are interrelated and that one cannot improve one area, orthe whole, without influencing other areas as well (Porter, 1996). In other words, theBalanced Scorecard should be robust enough to assist the implementation of strategythrough a reduction of the causal ambiguity between actions and results (Marr, 2005;Marr and Schiuma, 2003).

In order to understand how long-term, non-financial objectives of interconnectedprocesses, areas or functions in the organisation translate into value, Kaplan andNorton developed the idea of mapping causal relationships between strategicobjectives and their measures into a strategy map in chapter seven of their first book(Kaplan and Norton, 1996a). Later on Kaplan and Norton emphasised this idea in a

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later book “Strategy Maps: Converting Intangible Assets into Tangible Outcomes”(Kaplan and Norton, 2004). Recent studies have found that about half of the firmsemploying formal performance measurement systems visualised causal links betweenmeasures using cause-and-effect diagrams (Marr, 2005). Research has also shown firmsusing causal models had higher performance over time than companies than did notuse them (Marr, 2005; Othman, 2006). However, only half of the companies with formalperformance measurement systems have implemented and tested causal relationshipsbetween measures (Marr, 2005); and other firms implemented strategy maps thatsimply resembled process maps without any connection to firms’ strategy andcompetitive advantages (Wilkes, 2005).

Strategy maps formalise managers’ business models as a step for creating a testablestrategy (Franco-Santos and Bourne, 2005; Merchant, 2007). Therefore, these type ofcontrol systems can be used not only to cascade down performance metrics toimplement the strategy but also to provide with the necessary information to verify thecontent and validity of the actual strategy (Franco-Santos et al., 2007). The implicitbelief with the development of causal models for performance measurement is that,from the thousands of observable variables and their interrelationships, only somecausal linkages will be dominant in determining overall performance of the firm. In anycircumstance, performance measures should reflect business’ reality, adequacy andpracticality (Neely et al., 2003).

Banker et al. (2004) suggest that when managers understand the linkages betweenperformance measures and strategic objectives, they tend to use more strategicallylinked performance measures for evaluating the performance of employees thancommon financial measures. Moreover, employees tend to use more strategicallylinked performance measures to guide their decisions and actions (Banker et al., 2004).The use of performance measurement system becomes more interactive inhigh-performing businesses as managers communicate and discuss performanceboth at formal meetings and “at every opportunity” (Bourne et al., 2005). Bothmanagers and employees will benefit from the adoption of well developed causal mapssupporting the Balanced Scorecard (Banker et al., 2004), and the performance of thefirm will improve through the development of appropriate behaviours in theorganisation (Franco-Santos and Bourne, 2005).

Causal models and organisational learningAn adequate causal model helps members of organisations to understand howobjectives can be achieved (Kaplan and Norton, 1996a) as well as to evaluateindividual’s performance based on strategically linked measures rather than commonfinancial measures (Banker et al., 2004). In other words, strategic control systemsespoused with causal maps can enhance learning processes in the organisation.

After implementing a Balanced Scorecard, managers can develop a strategicfeedback system to test, validate, and modify the hypotheses embedded in a strategy(Kaplan and Norton, 1996b). These hypotheses are related to magnitude and speed ofresponse between changes in performance drivers and the associated outcomemeasures. Initially these impacts must be done subjectively and qualitatively but it is astart until the organisation gets enough data to conduct periodic strategic reviews(Kaplan and Norton, 1996a). These reviews should seek to understand the past in orderto learn about possible futures. In that sense, Kaplan and Norton (1996a) said:

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Whether managers reaffirm the existing strategy but adjust their judgments about the speedand magnitude of the cause-and-effect relationships, or the managers adopt a modified orentirely new strategy, the scorecard will have successfully stimulated a strategic(double-loop) learning process among key executives about the viability and validity oftheir strategy (p. 269).

This aspect is important since Rich (2007) found that managers did not rate theimportance of individual performance measures equally and the decision outcomeswere not always related to the factors which managers thought were important at thebeginning of the process of designing a Balanced Scorecard. This aspect is alsosignificant when different managers do not weight similarly the information employedin strategic decisions even though they face similar problems and have access tosimilar information (Kunc and Morecroft, 2007).

The time dimension in the Balanced ScorecardThe development of the scorecard should also describe the temporal relationship of thestrategy in order to assist organisations in understanding how decisions made todaywill affect future outcomes (Kaplan and Norton, 1996a, p. 160). Without knowing thesize and timing of associations among measures, companies find it difficult to makedecisions or measure success based on them (Ittner and Larcker, 2000). However, it hasreceived criticism because the temporal link between the variables is not clear(Nørreklit, 2000). For example, the learning and growth perspective suggest trainingand other activities to improve the performance of business processes and, later on, thevalue added to customers, but it does not explicitly portrays the temporal horizonbefore results can be seen.

A cognitive view of performance measurement systems and systemsthinkingNørreklit (2000) suggests that relationships between the indicators of the BalancedScorecard seem to be of finality rather than causality and this situation invalidates theconcept of Balanced Scorecard. A finality relationship occurs when human actions andviews are related to each other or, in other words, the actions are performed becausethey are adapted to views of a person and consequently are result of managers’cognition (Nørreklit, 2000). However, the author disagrees with Nørreklit (2000) that theBalanced Scorecard may not be valid if finality relationships tie the performancemeasures in the balanced scorecard.

The organisational outcomes in terms of firm performance and competitiveadvantage are, in a philosophical yet practical sense, reflections of managers’ valuesand cognitive biases. In other words, firms can be viewed as top management mentalmodels (an interpretist view of business) transformed into real organisations(a functional view of business) (Kunc and Morecroft, 2008). Kaplan and Norton (1996b,p. 17) affirm that a properly constructed Balanced Scorecard should articulate thetheory of the business. In other words, the Balanced Scorecard should reflect thedominant logic (Prahalad and Bettis, 1986) of the top management team since itrepresents the top management team’s conceptualisation of the business and it is usedas an administrative tool to accomplish managers’ goals and make decisions to achievethis conceptualisation. However, managerial cognition has to be tied up to the reality ofcompanies, and reality is determined by accounting data and financial calculus

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(Nørreklit, 2000) as well as resources (Warren, 2002). Thus, even performance measuresthat reflect managerial cognition should have a connection to financial information andreflect business’ reality (Neely et al., 2003).

The Balanced Scorecard can be an important representation of the dominant logicexisting in the organisation, and, as such, it can be considered as a key tool for strategiccontrol and learning (Kaplan and Norton, 1996b) but it needs different assumptionsand tools to construct it. These tools should consider performance indicators(especially leading indicators) and their relationships as simply representations of topmanagement team dominant logic, or theories in use about the business, and theyshould not impose frameworks that restrict or encapsulate managers’ presentation oftheir strategy, such as the four perspectives suggested in the Balanced Scorecard. Inother words, the development of performance measurement systems should start fromwhat is important to measure for the managers, and what is important to measure isdetermined by their dominant logic rather than non-familiar templates.

A wealth of methods for mapping out managerial cognition has been developed bymany scholars, from causal mapping to mind mapping. For a review of methods formapping out managerial cognition see Ackerman and Eden (2004). Each of these toolsaims to capture not only the concepts (or indicators) but also ways in which they areconnected together (interrelationships). In performance measurement systems, thesetools enable people in the organisation to understand how they contribute to the overalldirection giving them a sense of purpose of their actions and how differentperformance measures impact on one another (Ackerman and Eden, 2004). Finally,cognitive maps with associated performance measurement indicators can be testedusing simulation models so managers can be alerted to the path that the organisationwill follow and prevent them from falling into the trap of implementing actions whichcan make things worse (Ackerman and Eden, 2004; Akkermans and van Oorschot,2005). In this paper, it is proposed to use systems thinking and causal loop diagrams astools for mapping out managerial cognition.

Systems thinkingSystems thinking is a conceptual framework to make the full patterns of the systembehaviour clearer by seeing the structures that underlie complex situations (Senge,1999). While Kaplan and Norton (1996a, p. 270) recommended systems thinking in theirfirst book, there have not been attempts in the performance measurement literature totest and explain its use. Thus, why can systems thinking be relevant to the design ofthe Balanced Scorecard or any performance measurement system?

(1) While the Balanced Scorecard is designed to handle the complexity of thestrategy through many variables, which generates detail complexity,organisations abound in dynamic complexity because cause and effectrelationships of managerial interventions are not easily identified immediatelybut they appear over time. Dynamic complexity makes difficult to assert thecausality between performance indicators making invalid the assumptionsabout cause-and-effect relationships used in the Balanced Scorecard. Systemsthinking aims to identify the dynamic complexity existing in organisations bylooking at multiple cause-and-effect relationships over time (Senge, 1999).

(2) Measurement and assessment of organisational performance influence both thedecision-making process and the people involved in strategic decision making

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and strategy implementation (Tapinos and Dyson, 2007; Franco-Santos andBourne, 2005). Causal relationships described in the Balanced Scorecardliterature between performance measures follow a linear logic: cause ! effect,and do not consider the information feedback processes where the outcomeperformance measures (effects) are used to change processes captured in theleading performance indicators (causes). Thus, the information in the BalancedScorecard is not neutral to the process of decision-making and can affect thefuture value of the performance indicators leading to a circular process:causes ! effects ! causes. The design of the causal relationships shouldconsider the feedback processes existing between the information given by theperformance indicators and the likely intervention in the organisation to correctdeviations. Causal loop diagrams can illustrate the feedback processes existingbetween performance indicators and related organisational processes.

(3) The complex nature of organisations makes the design of a set of performancemeasures very complicated. Nørreklit (2000) suggests it may be more useful toestablish coherence between performance measurements, given the aim ofobtaining certain results from organisational activities, than trying to establishcausal relationships in a Balanced Scorecard. However, the ability to judgecoherence and predict results depends on knowledge of both means and endsover time (Nørreklit, 2000) but it is difficult to judge coherence in managers’actions since organisations are complex systems where cause and effect areoften separated both in time and space (Sterman, 2000). Systems thinking is amethodology designed, in most of the cases in conjunction with simulation, toaddress all the issues related to judging coherence in strategic decision makingand performance measurement systems (Akkermans and van Oorschot, 2005;Morecroft, 1985).

In the next section, the application of systems thinking with a group of students ispresented during the process of identifying their theories-in-use for the design of aperformance measurement system.

Applying systems thinking to design a performance measurement system:some resultsThis section illustrates the expected outcomes that may be observed when systemsthinking is employed to design a performance measurement system.

The application of systems thinking in classSystems thinking has been utilised in classroom for many years. For example,Attwater and Pittman (2006) suggested that causal loops diagrams[1] are the naturalstarting point for teaching the basic aspects of systemic thinking for two reasons. First,learning the mechanics of drawing these diagrams is fairly simple and typically can behandled in less than one class period. Second, experience with a vast number ofstudents has shown that they enjoy using them to describe their mental models aboutthe business where they worked or owned. Booth Sweeney and Sterman (2000)proposed that teaching specific systems thinking skills should include the ability tounderstand how the behaviour of a system arises from the interaction of its agents overtime (i.e. dynamic complexity); discover and represent feedback processes; recognise

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delays and understand their impact; identify nonlinearities; and identify and challengethe boundaries of mental (and formal) models. Maani and Maharaj (2004) found thatindividuals, who display the characteristics of systems thinkers, even if they areunaware to the fact, perform better on complex decision-making tasks. Moreover, thesubject’s approach to the problem also appeared to be highly pertinent to taskperformance, as better performing subjects attempted first to gain understanding ofthe system structure, then developed and implemented strategies, and carefullyassessed the outcomes of their decisions, in order to determine the validity of theirunderstanding of system structure.

The Balanced Scorecard in classDifferent scholars have recently shared their experience in introducing the BalancedScorecard in class using different methods, e.g. Gumbus (2005), Rachman-Moore andKenett (2006) and Kallas and Sauaia (2004). Both Rachman-Moore and Kenett (2006)and Kallas and Sauaia (2004) presented results from their experience in introducing theBalanced Scorecard using simulation games where students could practice the processof performance management. On the other hand, Gumbus (2005) used a race car driveras an analogy to understand and rely on multidimensional performance measurementsystems.

The process followed in classThe task for the students was to develop a theory of their businesses before designingtheir performance measurement system. Before this task, students went through a casestudy: “McDonald’s: Super-Sized Troubles (A)” (Roberto, 2003). The task during thiscase study was to discuss the strategic issue facing McDonald’s CEO initially usingbrainstorming, but later on, with the help of the professor, they explained a theory ofthe issues facing McDonald’s business using causal loop diagrams. After reviewing thecase study using causal loop diagrams, they discussed the performance measures thatthey would need to control McDonald’s business. The case study was an example toshow them how to elicit theories of a business using causal loop diagrams beforedesigning performance measures to track the performance of the business over time.After the case study, students were requested to develop a causal loop diagramexplaining the theories, as a set of causal links, employed to manage their areas ofresponsibility as a first step to develop a performance measurement system for theirareas. The students have on average 12 years of work experience and 78 per cent havemanagerial or higher responsibilities in their organisations. A total of 32 studentsreturned their task. A summary of the results of the activity is presented in Table I.The Appendix shows few causal loops diagrams from different students to illustratethe type of results observed.

DiscussionCausal loops diagram and its relationship with the Balanced Scorecard contentStudents identified on average 15.5 concepts in their maps with a standard deviation of4.8 concepts. The number of concepts can be considered in line with good practice indesigning a Balanced Scorecard according to Kaplan and Norton (1996, pp. 162-163).This result generates an interesting question about the number of variables thatexperienced managers can handle and how effective can performance measurement

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Table I.Results obtained fromcausal loops diagramsdeveloped by students

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systems be with more than 20 measures. Sometimes detailed complexity (too manymeasures) hinders the process of decision making, especially when individuals weightdifferently the information (Rich, 2007; Kunc and Morecroft, 2007). The qualitativeaspects of the concepts found in the causal loop diagrams, a mix between common andunique measures, are also in line with Gagne et al. (2006) who found that both commonand unique measures were informative for managers. The usage of recognised andspecific language in performance measurement systems is important to develop a set ofperformance measures that can be accepted in the organisation. In other words, theresults confirm that performance measures should reflect business’ reality, adequacyand practicality (Neely et al., 2003).

However, only 48 per cent of the concepts existing in the causal loop diagrams canbe related to Balanced Scorecard metrics associated with any of the four perspectives.This result is very interesting because it supports the concerns raised by scholarsabout the usability of the Balanced Scorecard (Marr and Schiuma, 2003; Lawrie andCobbold, 2004). There are also differences in the emphasis given to each of the fourperspectives. Almost 50 per cent of the concepts are related to the internal processperspective instead of a balance between the four perspectives. This result can berelated to student’s actual or recent job because students working in operations areasdeveloped their maps containing a high number of concepts related to the internalprocesses perspective. The results confirm Franco and Bourne (2003) findings thatmanagers want their performance measurement systems to be specific to their taskenvironments.

One criticism of the Balanced Scorecard is the lack of identification of time delaysbetween cause and effect. The results show that only 38 per cent of the studentsexplicitly identified time delays in the interrelationships existing between measures –or that two out of three students believed that the relation between cause and effectwas instantaneous. The lack of knowledge about timing between concepts makesdifficult to measure the success of a decision (Ittner and Larcker, 2000), or, even worse,decision-making processes can overreact to a perceived lack of effect wastingresources. A basic measure of a time delay can be to measure “all time” taken by aprocess to be completed. For example, the success of training – a cause – in increasingproductivity – an effect – should be measured considering not only training time butalso some adaptation time to the new rules before seeing any result. Another way ofmeasuring delays is analysing time series of related measures to detect lags and itssize. These results support research in behavioural decision making that found peoplemisperceive delays existing in feedback processes (Sterman, 1987, 1989a,b, 2000).

Extensions to the Balanced Scorecard found in the causal loops diagramsAnother interesting observation is the number of feedback loops identified by thestudents in their maps. The concept of feedback loops helps managers to realise theinterconnectedness between different performance measures and how changes in onearea lead to changes in other areas. The interconnectedness shown in the causal loopdiagram also facilitates managers to comprehend how their decision-making processesmay affect the leading indicators. Feedback loops aid managers to move fromunidirectional causal relationships to bi-directional relationships, and what is moreimportant help them to visualise the dynamic complexity of their business. Figure 1provides a small example.

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Figure 1(a) shows that at least we need two concepts to have a feedback loop, Aaffects positively B and B affects positively A, for example marketing expenditureincreases the number of clients and more clients increase sales which augmentsmarketing budget even more. However, if there is more than one feedback loop like inFigure 1(b), analysing interrelationships between concepts will be more complex.Figure 1(b) also has two concepts per feedback loop but the variable B is affected by Aand C, A is affecting indirectly C through B and C is affecting A through B. Thecoupling effects, and with different directions, of A and C on B make difficult for anymanager to realise what is going on in B. For example, marketing expenditureincreases clients, more clients means more saturation in customer services but asaturated customer service reduces the number of clients because of lack of attention.In this example, should managers reduce marketing expenditure? Or should managersincrease expenditures in customer services? And when should managers implementthese changes? Causal loop diagrams can uncover multiples effects over oneperformance measure, which contribute to managers’ perceived lack ofinterrelationship between different measures if a linear and unidirectional logic isapplied.

In their causal loop diagrams, students have identified on average 5.5 feedbackloops. Considering there are on average 15.5 concepts in each map, the average numberof variables per feedback loop is 2.70. Therefore, there is at least one intermediaryconcept between two concepts in a feedback loop. Given the increasing complexity ofthe maps even with 15 concepts, it is hard to believe that linear cause-effectrelationships can be a good way to represent strategies in strategy maps.

Another criticism to the Balanced Scorecard is its lack of identification of exogenouseffects. The results show that 70 per cent of the students have included other conceptsrepresenting exogenous factors affecting the firm. The concepts vary from limits tofirm expansion to stakeholders’ and competitors’ reactions. This result verifies Francoand Bourne (2003) findings related to the need of having business and industryinformation in the measures selected. The causal loop diagrams that did not haveexogenous factors were related to maps describing internal operation areas.

Thus, managerial background and actual task environment may be an importanteffect on managers’ attention leading to differences in the design and use ofperformance measurement systems.

ConclusionsGraphical representation of the links between measures and objectives can make iteasier for individuals to identify relations among data (Franco-Santos and Bourne,2005; Banker et al., 2004). Moreover, when managers understand the linkage between

Figure 1.Simple causal loops

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performance measures and strategic objectives, strategically linked measures will havegreater impact than common financial measures on performance evaluations (Bankeret al., 2004). Therefore, tools that help managers to understand the linkages betweenperformance measures and strategic objectives will facilitate the adoption of theBalanced Scorecard and better organisational performance[2].

Strategic linkage models with only activity and outcome perspectives can representa simplification of the Balanced Scorecard strategic linkage model (Lawrie and Cobbot,2004; Neely et al., 2003). A single outcome perspective replaces financial and customerperspectives, and a single activity perspective substitutes learning and growth andinternal business process perspective. Causal loops diagrams share a similarsimplification in the relationships between activities and outcomes.

A good Balanced Scorecard tells everyone in your organisation the story of yourentire strategy in a single page (Kaplan and Norton, 1996a). A good designed causalloops diagram also offers in a single page the story of your strategy but in an evenbroader context because it is not constrained to four perspectives.

Strategic feedback systems should be designed to test, validate, and modify thehypotheses embedded in the strategy (Kaplan and Norton, 1996b). However, to test thecause-and-effect relationships based on correlations is rather simplistic and evendangerous considering the complexity existing in any organisation (Sterman, 2000).Kaplan and Norton (1996a, p. 270) even argue for the need of introducing dynamicsystem thinking to develop the Balanced Scorecard and for testing the theory of thebusiness on which the strategy is based using double-loop learning processes.

Limitations of the studyThe problem of relevance of experimental studies can surface in many different formsas Plott (1982) suggests:

. “real” businessmen do not behave as do the subjects in experiments (the subjectsof these experiments were real managers with more than 12 years of experience);

. the laboratory environment is artificial (subjects were asked to describe theirown business rather than exposed them to an unknown firm and industry like inBanker et al. (2004)); and

. processes do not occur in isolation because they are embedded in larger socialcontexts (since students in the experiment developed their theories-in-useisolated from their working environment, they were not subject to peer pressuresor political games that might have affected their perceptions of what set of casuallinks were relevant in determining the performance of their businesses).

Before suggesting ideas to overcome the limitations of the actual study, it is importantto highlight that the experiment only provided an arena within which the relativeaccuracy of certain literature was evaluated (Plott, 1982). Other researchers, e.g. Ittnerand Larcker (2000), proposed using statistical analysis of leading and laggingindicators to test the causal links between performance indicators rather than askingmanagers their perceptions of causality.

One way to overcome the limitations of the actual study can be observed inAkkermans and van Oorschot (2005). They developed a causal map of a managementteam, and not only one subjects’ map, so they captured issues of peer pressures andorganisational decision-making processes. Additionally to the causal map, they

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developed a simulation model using the performance indicators agreed during thedevelopment of the causal map. A simulation model implies a detailed analysis ofcausal links between indicators using statistical analysis, performing measurements ofactual processes or using algebraic formulae. Thus, a simulation model is a goodreality check for a set of indicators developed through a causal map.

Implications for practice and researchGiven the stronger relevance of causal models in performance measurement systems, itmay be important that performance measurement scholars develop a research agendawith managerial cognition literature. Managerial cognition literature presenteddifferent tools for mapping out causal models (Jenkins and Huff, 2002) which can beused to evaluate the relevance of existing performance indicators for actual users assuggested by Franco and Bourne (2003) or Ittner et al. (2000). This task can beperformed not only at managerial level but also at lower levels in the organisation toidentify the gap existing in the alignment of the organisation to the strategy and themeasures implemented to control the implementation of the strategy (Ittner andLarcker, 2000).

Another avenue that can be explored through causal maps is the complexity ofdecision-making processes employed at different levels of the organisation and adaptthe set of performance indicators to the diverse levels of complexity rather thanemploying one-size-fits-all approach to performance measurement systems.

The findings imply that practitioners must start the set of performance measuresunderstanding their own, as well as others in the organisation, theories-in-use ratherthan starting from pre-defined schemes. The development of causal maps, firstindividually, and then collectively, will help to the alignment of the organisation toonly one set of performance measures rather than multiple sets of local measures.Checking-up the indicators against real data will help the organisation to realise if theyhave erroneous beliefs and learn as well as improve the validity of the measuresselected.

Notes

1. Conventions for drawing causal loop diagrams are very simple. For an in depth review seeSterman (2000) but for a brief explanation I present Atwater and Pittman’s explanation(Attwater and Pittman, 2006, p. 280). “In each two-variable link, the variable at the back ofthe arrow is said to cause a change in the behaviour of the variable the arrow points to. Thetype of change is depicted using either ‘ þ ’ or ‘ 2 ’ signs. A ‘ þ ’ means the twointerconnected variables change in the same direction, and a ‘ 2 ’ means the two variableschange in opposite directions. For example, if two variables are linked by an arrow with a‘ þ ‘sign, it means that an increase in the cause variable results in an increase in the effectvariable. Similarly, two variables linked by an arrow with a ‘ 2 ’ sign is read as an increasein the cause variable, resulting in a corresponding decrease in the effect variable. Basic loopsare created when two or more variables are linked together using arrows, which result in aclosed loop. A closed loop is the basic piece for describing dynamic behaviour in a system.”

2. There is a wealth of sources to tap in for developing systems thinking tools; for example,MIT’s System Dynamics Group, London Business School’s System Dynamics Group or PeterSenge’s Fifth Discipline book.

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Further reading

Kennerley, M. and Neely, A. (2002), “A framework of the factors affecting the evolution ofperformance measurement systems”, International Journal of Operations & ProductionManagement, Vol. 22 No. 11, pp. 1222-45.

AppendixFigure A1 shows the diagram of student number nine. This student works for a fishing companyas a finance manager. The causal loop diagram does not depict any concept related to customersbut, as a commodity producer, customers are replaced by the components of a global market forthis product: fish price, global demand and global production of fish. His theory-in-use is relatedto the interactions between supply and demand in a global market, an external resource: fishbanks, global competitors: fishing fleets as drivers of his firm profitability.

Figure A2 shows the causal loops diagram of student 25. This student is employed in thesame company as student nine but his area of responsibility is human resources. While his mapalso includes the external resource: fish population, his attention is focused on achievingefficiency and improvements in the internal operations of the firm so his theory-in-use depictsmore cause-and-effect relationships between internal factors such as technology, productionefficiency and ships. Figures A1 and A2 are interesting examples of different theories-in-useabout what is important in the firm for members of the same management team, which can affectthe performance measures that each of the managers will pay attention as well as the internalcoordination in the firm. Mapping out different managers’ mental models can assist practitioners

Figure A1.Causal loops diagram of afinance manager in afishing company

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in designing better performance measurement systems because differences about measures areelicited in order to understand them and achieve alignment.

Figure A3 shows the causal loops diagram of student 20. This student is employed in apension fund administrator and considers two key concepts as central to her theory-in-use:clients and financial advisors (sales people). The pension fund industry is highly competitive andfirms have been engaged in promotion wars for many years. The diagram captures not onlyinternal but also external forces affecting these two concepts. On the one hand, competitors andtheir actions can affect the expected number of clients – a clear example of an external factor notconsidered in a balanced scorecard. On the other hand, the productivity and capabilities offinancial advisors, which are improved through training and investment in market research, canalso affect the expected number of clients – a clear example of an internal factor usuallyconsidered in a balanced scorecard.

Figure A4 shows the causal loops diagram of student 11. This student is a manager of aservice area – credit ratings – in a commercial bank. This map is simpler than previous causalloops diagrams because his business is also simpler and oriented towards service performance.

Figure A2.Causal loops diagram of ahuman resources manager

in a fishing company

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Corresponding authorMartin Kunc can be contacted at: [email protected]

Figure A3.Causal loops diagram of asenior analyst in astrategic planningdepartment in a pensionfund administrator

Figure A4.Causal loops diagram of amanager of a service areain a commercial bank

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