Achieving contextual ambidexterity in R&D organizations: a management control system approach

Achieving contextualambidexterity in R&Dorganizations: a managementcontrol system approach

Ian P. McCarthy and Brian R. Gordon

Beedie School of Business, Simon Fraser University, 500 Granville Street, Vancouver, BC, CanadaV6C 1W6. [email protected]; [email protected]

Research on how managers control R&D activities has tended to focus on the performance

measurement systems used to exploit existing knowledge and capabilities. This focus has been

at the expense of how broader forms of management control could be used to enable R&D

contextual ambidexterity, the capacity to attain appropriate levels of exploitation and

exploration behaviors in the same R&D organizational unit. In this paper, we develop a

conceptual framework for understanding how different types of control system, guided by

different R&D strategic goals, can be used to induce and balance both exploitation and

exploration. We illustrate the elements of this framework and their relations using data from

biotechnology firms, and then discuss how the framework provides a basis to empirically

examine a number of important control relationships and phenomena.

1. Introduction

Controlling R&D is a challenge. Managershave long struggled to develop effective

control systems for directing and adjustingR&D behaviors and outcomes. Consequently,researchers have been motivated to examineR&D control from three complementary levelsof analysis: the firm, the market and the inno-vation system (Chiesa and Frattini, 2009). Thishas resulted in studies that explore how R&Dactivities and outputs should be measured (e.g.,Souder, 1972; Schumann et al., 1995; Wernerand Souder, 1997; Kerssens-van Drongelen andBilderbeek, 1999; Chiesa and Frattini, 2007); howR&D organizations should be designed and man-aged (e.g., Tymon and Lovelace, 1986; Whitting-ton, 1991); and how markets and governmentscan support R&D (e.g., Moravesik, 1973; Martinand Irvine, 1983).

A feature of research on R&D control is thatit has largely focused on the design and impactof performance measurement systems, which areonly one type of control system – the diagnosticcontrol system (Otley, 1980; Simons, 1994). Asdiagnostic systems are used to evaluate and rewardorganizational activities, they tend to inducerelatively measurable exploitation behaviors thatensure current viability, at the expense of the moreintangible exploration behaviors needed for ensur-ing future survival. This bias is counter to thenotion that sustained organizational performancerequires an organization to effectively balanceexploitation with exploration (March, 1991), acapability known as ‘organizational ambidexterity’(Duncan, 1976; Tushman and O’Reilly, 1996).

Although sustained organizational performanceis associated with a firm’s ability to be ambidex-trous, it is a capability that is conceptually ambig-uous and difficult to achieve. On the one hand,

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ambidexterity is viewed as the attainment of abalance between exploitation and exploration,whereby ‘organizations make explicit and implicitchoices between the two’ (March, 1991, p. 71) toattain an ‘optimal mix’ (March, 1991, p. 75). Onthe other hand, exploitation and exploration areconsidered to be mutually enhancing, so that it ispossible for firms to attain high levels of both(Gupta et al., 2006; Jansen et al., 2006). In ourpaper we follow the ‘balanced’ view of ambidexter-ity, and assume that R&D managers face decisionsabout allocating resources and attention to activ-ities that can be relatively explorative or relativelyexploitative in nature.

Although the classic definition of ambidexterityprovided by March (1991) would seem to suggestthat R&D is exploration, the dilemma of balancingexploitation and exploration clearly exists in R&Dorganizations. Ahuja and Lampert (2001), forexample, explain how R&D activities vary acrossthe exploitation-exploration continuum. They de-fine R&D exploration as activities and outputsthat focus on novel, emerging and pioneeringtechnologies; they define R&D exploitation asactivities and outputs concerned with mature,familiar and propinquituous technologies. Simi-larly, McNamara and Baden-Fuller (1999, 2007)argue that ambidexterity is fundamentally aboutdifferent forms of learning, and that R&D orga-nizations, in common with other types of organi-zation, must maintain a balance of short-termexploitation and long-term exploration to be suc-cessful over time. These characterizations of R&Dexploration and R&D exploitation follow the viewthat ambidexterity is the capability to balancedifferent types of knowledge production (Levinthaland March, 1993).

While organizational ambidexterity is a relativelystraightforward concept to understand, it is not aneasy capability to attain. Exploration and exploita-tion have fundamentally different qualities. Exploi-tation is characterized by short-term time horizons,efficiency, reliability and refinement, while explora-tion involves long-term time horizons, search, ex-perimentation, innovation and adaptability. Tosimultaneously induce and balance these differ-ences, there are two recognized approaches. Oneis ‘structural ambidexterity’ (Tushman and O’Re-illy, 1996), which involves splitting exploitation andexploration into different organizational units (i.e.,separate divisions, departments or teams). It is thenthe task of senior managers to ensure that therespective exploitation and exploration outcomesof each organizational unit are integrated to createvalue. This integration task, however, can also be

difficult to achieve because the organizational unitsare disconnected. A second complementary ap-proach is ‘contextual ambidexterity’ (Birkinshawand Gibson, 2004; Gibson and Birkinshaw, 2004;Raisch and Birkinshaw, 2008). It involves creatingan organizational context – the organizationalstimuli that inspire, guide and reward people toact in a certain way (Ghoshal and Bartlett, 1997) –that will allow exploitation and exploration beha-viors to transpire in the same organizational unit.

We argue that contextual ambidexterity is im-portant and suited to R&D organizations for atleast two major reasons. First, the problems ofattaining ambidexterity by structural separationare compounded for R&D organizations. R&Dactivities are often already structurally separatedand operationally distinct from other organiza-tional activities such as legal, manufacturing orsales. Thus, any further partitioning (i.e., separat-ing the ‘R’ from the ‘D’) increases the problem ofintegrating and utilizing R&D outputs through-out the organization. This is especially so forsmall- to medium-sized organizations, whoseR&D activities are tightly intertwined. Second,we suggest that contextual ambidexterity is suitedto the ‘clan control’ typically found in R&Dorganizations (Ouchi, 1979), as it involves using‘processes or systems that enable and encourageindividuals to make their own judgments abouthow to divide their time between conflictingdemands for alignment and adaptability’ (Gibsonand Birkinshaw, 2004, p. 211).

In this paper we focus on the problem of howto attain contextual ambidexterity in a singleR&D organizational unit. We present and illus-trate a conceptual framework that shows howbroader forms of control system, guided by R&Dgoals, could be used to encourage teams andindividuals in R&D organizations to simulta-neously pursue both exploitation and exploration.We present our arguments in four major sections.

First, we review the R&D management controlliterature, highlighting the need to move beyondexploitation and metric-focused performancemeasurement. We identify the importance oflinking the design and use of control systemsto the R&D goals of the organization. Second,we develop our conceptual framework by synthe-sizing R&D control concepts with control the-ories developed in the fields of accounting andstrategic management. Specifically, we adaptSimons’ (1994) ‘levers of control’ framework,which consists of four types of control system:beliefs systems, boundary systems, diagnosticsystems and interactive systems. We explain how

Achieving contextual ambidexterity in R&D organizations

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these four types of control system, guided byR&D strategic goals, can work together to de-velop and harness both exploitation and explora-tion in an individual R&D organization. Third,although studies have recognized that beliefs,boundary, diagnostic and interactive systemswork together to create different behaviors andoutcomes (e.g., Widener, 2007; Chiesa et al.,2009a), significant ambiguity remains in the lit-erature regarding what these systems actually are.That is, what actual rules, policies, procedures,processes, technologies and incentives mightR&D managers use to create the control asso-ciated with each type of control system? Inresponse, we presented our framework to man-agers and scientists employed by small- andmedium-sized biotechnology firms. This was notdone to inductively derive the framework, nor toprovide strong empirical support for it. Rather,we sought examples to help describe and illustratethe framework, to provide some preliminary facevalidity for our arguments, and to exemplify whatthese control systems actually are. Fourth, wediscuss some general implications of our concep-tual framework for R&D management, each ofwhich points to future areas of research. Wesuggest that our framework provides a basis forempirically studying the extent to which multipleR&D strategic goals drive the use of differenttypes of control system. We also contend that ourframework provides a starting point from whichto examine how the use and attention of differentmanagement control systems can be altered overtime so that R&D managers can ‘dynamically’manage the exploitation–exploration balance.

2. R&D management control: movingbeyond performance measurement

When Freeman (1969, p. 11) argued ‘if we cannotmeasure all of the information generated by R&Dactivities because of a variety of practical diffi-culties, this does not mean that it may not beuseful to measure part of it,’ he spurred a genera-tion of scholars to understand what constituteseffective R&D management control, in both in-dustrial and government settings. Table 1 presentsa selection of control system studies published inleading R&D management and innovation jour-nals. For each study, the table lists the type ofcontrol system examined, according to the controlsystems in Simons’ (1994, 1995a) framework.These are (i) beliefs systems that are used toinspire employees to engage in activities central

to the values, purpose and direction of the organi-zation; (ii) boundary systems that limit strategicallyundesirable activities and outcomes; (iii) diagnosticsystems that measure activities to ensure they are inaccordance with organizational objectives; and (iv)interactive systems that scan for and communicatestrategic information to employees so as to adjustthe direction of the organization. For each studywe also list the type of analysis undertaken, and thecontribution made.

Looking across these studies, we identify fourthemes that characterize much of the existingresearch in the area, and provide the motivationfor the conceptual framework that we develop.First, existing studies have predominantly focusedon how performance measurement systems (i.e.,diagnostic control systems) promote the efficiencyof behaviors central to R&D exploitation.Although there are some studies that examinebroader forms of control, including the effects ofprocess formality (Bart, 1993), project structure(Cooper and Kleinschmidt, 1986), professionalrituals (Whittington, 1991) and goal setting activ-ities (Kerssens-van Drongelen and Bilderbeek,1999; Yawson et al., 2006), there is only one studywe know of that has used Simons’ (1994) controlframework in an R&D context (see: Chiesa et al.,2009a). Furthermore, although Table 1 only listsempirical studies (so as to focus and limit ourreview to established R&D control concepts), awider reading of the R&D management controlliterature reveals that diagnostic control has so fardominated prior work on R&D control frame-works (e.g., Chiesa and Masella, 1996; Bremserand Barsky, 2004), taxonomies (e.g., Tymon andLovelace, 1986) and reviews of R&D measures(e.g., Werner and Souder, 1997; Geisler, 2002;Garcıa-Valderrama and Mulero-Mendigorri, 2005).Consequently, the motivation for our paper followsthe view that although ‘measuring performance ishelpful, it is only part of the story’ (Chiesa et al.,1996, p. 105). In particular, we argue that differenttypes of control system, guided by R&D strategicgoals, can work together to balance different levelsof exploitation and exploration in individual R&Dorganizations.

Second, research on the diagnostic control ofR&D has traditionally focused on the perfor-mance measures as opposed to the systems (i.e.,the rules, procedures and technologies) thatmanagers might use to direct and adjust R&Dbehaviors. This measure-based approach treatsR&D organizations as ‘black boxes,’ ignoringtheir inner workings and the relationships be-tween goals, controls, behaviors and outcomes.


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By focusing on the different types of controlsystem used, and collecting data from managersand scientists in biotechnology firms, we aim to

provide examples of these systems. This followsother studies of R&D control that focused on theactual systems used (e.g., Szakonyi, 1995; Chiesa

Table 1. Review of empirical studies within the R&D management control literature

Article Controlsystemsexamined

Empirical analysis Findings

Schainblatt(1982)

Diagnostic Literature and company survey thatcompared the use of R&Dproductivity measurement systems

Systems should differ according toresearch activities and developmentactivities, and overall R&D goals

Martin andIrvine (1983)

Diagnostic Measures for allocating funds toscientific research institutes

A system of indicators for assessingscientific research progress

Cooper andKleinschmidt(1986)

Diagnostic;boundary

How variations in the structure andstages of the new productdevelopment process influenceinnovation outcomes

A model that explains how controlefficiency and control reliabilityinfluence project outcomes

Cordero(1990)

Diagnostic A study the links between firm levelR&D investments, productivity andreward allocation

A model that combines technical andcommercial performance andspecifies how measures varyaccording to organizational levelsand process stages

Whittington(1991)

Boundary A study of in-house and independentR&D organizations and three typesof structural control: market,hierarchical and professional

R&D organizations with marketcontrol are more productive thanthose with hierarchical andprofessional control

Bart (1993) Diagnostic;boundary;interactive

Interviews with R&D managers inlarge companies on the tightness orformality of their control systems

The importance of balancing formaland informal controls, in line withR&D goals

Hauser andZettelmeyer(1997)

Diagnostic Interviews with CEOs, CTOs andresearchers at ten research-intensiveorganizations on the use ofperformance measures

Effective measures depend upon thegoals and research intensity of theR&D and engineering activity

McGrath andRomeri (1994)

Diagnostic Determining R&D effectiveness inelectronics companies by assessinginvestment versus new productperformance

Firms with a high R&D effectivenessindex are more productive, reliableand innovative

Kerssens-vanDrongelen andCook (1997)

Diagnostic Literature review, company surveyand in-depth interviews to assess useof R&D measures and system designprinciples

Outlines the importance ofcontingency factors and specifiescontrol system requirements anddesign parameters

Werner andSouder (1997)

Diagnostic Survey to understand measurementphilosophy and perceived usefulnessof measurement

Control system design is dependenton control aims, type of R&Dactivity, data availability and cost

Kerssens-vanDrongelen andBilderbeek(1999)

Diagnostic;beliefs

Survey of performance measurementpractices and effectiveness

Explores the importance ofcontingency factors and highlightsthe importance of feedback and feed-forward control

Godener andSoderquist(2004)

Diagnostic Use and impact of performancemeasurement on decision-makingand operations

Using performance results willimprove R&D relevance andcoherence, decision-making andemployee motivation

Karlsson et al.(2004)

Diagnostic Case study that examines productand process development

Systems should be designed to suittype of R&D activity, control needsand strategic goals

Yawson et al.(2006)

Diagnostic;beliefs

Case study that examines balanced-score card use in a research institute

Systems can align measurement withstrategic objectives and addresscapability and utilization issues

Chiesa et al.(2009a)

Diagnostic;beliefs;interactive;boundary

Case studies that examine how thesesystems are employed in differentphases of the radical innovationprocess

Beliefs and interactive systems aremore prominent in the early stages ofthe process, while diagnostic systemsare more prominent in the later stagesof the process


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et al., 1996) and emphasized that control is aboutmore than choosing a set of metrics (Kerssens-vanDrongelen and Cook, 1997; Kerssens-van Dron-gelen and Bilderbeek, 1999).

Third, by definition, research on the diagnosticcontrol of R&D tends to highlight what we call aspecific ‘control orientation.’ This is the extent towhich individuals and teams conceive and under-take control in an ex post (after-the-event) or exante (before-the-event) manner. Prior research onR&D control has tended to focus on the ‘feed-back control orientation,’ which is when after-the-event information (e.g., errors, failures andother unsatisfactory organizational outcomes) isused to direct and adjust organizational beha-viors. This feedback control orientation is centralto exploitation as it promotes single-loop learningand the continuous refinement of organizationalpractices and capabilities (Argyris and Schon,1978; Kerssens-van Drongelen and Bilderbeek,1999). In contrast, a ‘feed-forward control orien-tation’ involves seeking and receiving before-the-event information about future trends, events andtheir effects (e.g., changes in regulations, compe-tition and demand). This information is used toadjust organizational behaviors so as to preventunacceptable outcomes from occurring. It is acontrol orientation that energizes the explorationand double-loop learning needed for individualsand organizations to radically rethink and altertheir existing capabilities (Argyris and Schon,1978; Kerssens-van Drongelen and Bilderbeek,1999). Using our conceptual framework, we ex-plain how different types of control system worktogether to generate both feedback and feed-forward control orientations, which together pro-vide informational stimuli to induce the behaviorsnecessary for contextual ambidexterity.

Fourth, it is clear from the studies listed inTable 1 that the effectiveness of R&D control iscontingent on a number factors, one of the mostprominent of which is the R&D goals of theorganization (see: Schainblatt, 1982; Bart, 1993;Chiesa et al., 2009b). Thus, in the next section ofour paper we describe how four R&D goals –growth, innovation, reliability and efficiency –relate to and drive the use of control systemsand the attainment of R&D ambidexterity.

3. A management control framework forR&D contextual ambidexterity

In this section of our paper we develop ourconceptual framework. We synthesize manage-

ment control ideas and advances from the fieldsof accounting and strategic management, andapply these to the domain of R&D control. Inparticular, we explain how the use of the fourtypes of control system proposed by Simons(1994), guided by different R&D strategic goals,can be used to induce and balance the exploita-tion and exploration behaviors, and the feedbackand feed-forward control orientations necessaryfor attaining contextual ambidexterity.

3.1. Simons’ levers of control

In the fields of accounting and strategic manage-ment, researchers have argued that managementcontrol involves using a number of different, butinter-related types of system (Ouchi, 1979; Otley,1980; Eisenhardt, 1985; Marginson, 2002; Turnerand Makhija, 2006). To explain how controlsystems can vary and function, Simons (1994)proposed an influential framework of manage-ment control built around what he termed the‘four levers of control’ – beliefs systems, bound-ary systems, diagnostic systems and interactivesystems. Collectively these four types of controlsystem represent the policies, procedures andtechnologies that influence the cultural norms,behaviors and outcomes of individuals andgroups. Each type of control system has uniqueeffects but, importantly, they also work in con-junction with one another to manage ‘the inherenttensions between (1) unlimited opportunity andlimited attention, (2) intended and emergentstrategy and (3) self-interest and the desire tocontribute’ (Simons, 1995a, p. 28). We placeSimons’ (1994) four types of control system asthe central element in our conceptual framework(see Figure 1), and argue that R&D managers,guided by R&D strategic objectives, can useSimons’ control systems to shape the organiza-tional conditions necessary for contextual ambi-dexterity. We now discuss each type of controlsystem in more detail.

Beliefs systems are ‘the explicit set of organiza-tional definitions that senior managers commu-nicate formally and reinforce systematically toprovide basic values, purpose and direction forthe organization’ (Simons, 1995a, p. 34). Theyhelp ensure that the attitudes and behaviors ofindividuals are aligned with the R&D strategicgoals and the scientific principles that underpinthe R&D organization. They provide the ‘positiveenergy’ necessary for exploration (Simons,1995a), and the strategic coherence necessary for




R&D employees to search for new knowledge andopportunities in an autonomous, but focusedmanner.

Interactive systems enable ‘top-level managersto focus on strategic uncertainties, to learn aboutthreats and opportunities as competitive condi-tions change, and to respond proactively’ (Si-mons, 1995b, p. 81). These systems are used byR&D managers to scan, ‘explore’ and acquireinformation about events and trends in theirorganization’s external environment (Daft andWeick, 1984). They also include the communica-tion processes that R&D managers use for insti-gating debate with colleagues about the future ofthe organization. Intra-organizational networks(Swan et al., 1999), information technology(Alavi and Leidner, 2001) and group based pro-cesses such as brainstorming and sand-pit events(Cummings, 2004), are all example of interactivesystems that managers can use to engage inexploration and knowledge sharing.

Boundary systems delineate ‘the acceptabledomain of strategic activity for organizationalparticipants’ (Simons, 1995a, p. 39). These are

the systems that define and enforce the limitsbeyond which employees must not stray. Thisdemarcation role of boundary systems helps pre-vent R&D organizations from over-exploring andbecoming too stretched. Thus, boundary systemsare central to reliability-based exploitation beha-viors, in that they ‘transform unbounded oppor-tunity space into a focused domain thatorganizational participants can be encouragedto exploit’ (Simons, 1995a, p. 41).

Diagnostic systems are the ‘feedback systemsused to monitor organizational outcomes andcorrect deviations from preset standards of per-formance’ (Simons, 1994, p. 170). If non-confor-mance is identified this can prompt changes inorganizational activities and in the other types ofcontrol system, to adjust what is done and how itis done. As highlighted by our review of the R&Dcontrol literature, diagnostic systems tend tofocus on measuring tangible and exploitationactivities, which in turn motivate R&D employeesto be productive and efficient. Consequently,strong diagnostic systems, if used in conjunctionwith weak or inappropriate boundary and beliefs

Figure 1. Relationships between R&D strategic goals, control system type and R&D contextual ambidexterity.


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systems, can promote the ‘what you measure, iswhat you get’ phenomenon, which can sometimeslead to unintended and undesirable consequences.

3.2. R&D strategic goals

One of the earliest definitions of a managementcontrol system describes it as a collection ofsystems that managers use to ‘ensure that re-sources are obtained and used effectively andefficiently in the accomplishment of the organisa-tion’s objectives’ (Anthony, 1965, p. 17). Simi-larly, R&D management scholars have arguedthat for an R&D management control system tobe effective it should be aligned with the R&Dstrategic goals of the organization (Schainblatt,1982; Bart, 1993; Chiesa et al., 2009b).

We define R&D strategic goals as statementsthat motivate R&D organizations to attain a levelof proficiency in a specific R&D capability. Interms of what these goals might be, we followstudies that emphasize the importance of R&Dgoals to control system design and use (Schain-blatt, 1982; Bart, 1993; Karlsson et al., 2004;Chiesa et al., 2008). Together these studies sug-gest that R&D goals can vary in terms of howthey specify different types of research activity(i.e., basic research, applied research, and devel-opment), innovation activity and outputs (i.e.,incremental and radical), so as to support theoverriding business strategy and rules of competi-tion governing the R&D organization. The fourR&D strategic goals we use – growth, innovation,reliability and efficiency – are distilled from theseprinciples, and from the notion that each of thecontrol systems proposed by Simons (1994,1995a) is individually oriented toward one ofthese strategic goals. This is indicated by thegoal-control linkages in Figure 1: growth-beliefs,innovation-interactive, reliability-boundary andefficiency-diagnostic. These relationships are notexclusive, however, and this is indicated by thesingle arrowed line that broadly connects all ofthe R&D strategic goals with all of the controlsystem types.

We define R&D growth goals as the extent towhich an R&D organization seeks to increase ormaintain its organizational size (e.g., number ofemployees, R&D capacity and R&D outputs).They indicate the degree to which an R&Dorganization is concerned with developing itsinnovative capacity by increasing its project port-folios, the number of R&D employees and otherrelated resources (Addison et al., 1976). This is

consistent with Simons’ (1995a) claim that man-agers will use beliefs systems to inspire employeesto overcome organizational inertia and grow (i.e.,build), or alternatively to focus, be persistent andcomplete existing projects (i.e., harvest). Conse-quently, we suggest that the nature and use ofbeliefs system in an R&D organization will belinked to its growth goal.

Innovation goals define the kinds of outcomesthat R&D organizations seek to produce. At themost general level, this involves specifying thevelocity, magnitude and application range oftechnological change (McCarthy et al., 2010). Inan effort to be parsimonious, we focus only on themagnitude of change in a technology’s capability,and the degree of benefit it brings to the market(Wheelwright and Clark, 1992; Maine and Garn-sey, 2006). As recently argued by Chiesa et al.(2009a, p. 419), such innovation differences sig-nificantly influence ‘the adoption of specific man-agerial approaches, organizational solutions andoperative instruments,’ i.e., the design and use ofappropriate control systems. Furthermore, it isargued, as interactive control systems promoteexploration and learning they are more prominentin the early stages of the radical innovationprocess (Chiesa et al., 2009a). On this basis, wesuggest that R&D organizations in pursuit ofradical innovation goals would benefit fromgreater use of interactive control systems; con-versely, R&D organizations in pursuit of moreincremental innovation goals would require lessuse of interactive control systems.

Reliability goals indicate the extent to whichthe activities of R&D organizations should betrustworthy and dependable (Kiella and Golhar,1997). This type of goal has become important,with R&D organizations increasingly undertak-ing quality improvement programs. Reliabilitygoals determine the extent to which an R&Dorganization should be proficient at reachingproject milestones on time (Cooke-Davies andArzymanow, 2003), and the propensity of theorganization to engage in post-project assess-ments that promote organizational learning (vonZedtwitz, 2002). As these activities involve adher-ing to acceptable R&D domains and practices, wesuggest that the degree to which the R&D orga-nization desires high levels of reliability, willdetermine the extent to which boundary systemsare used to ‘establish explicit limits and ruleswhich must be respected’ (Simons, 1994, p. 170).

Efficiency goals define the extent to which anR&D organization focuses on using its resourcesto maximize the production of innovations. As




discussed in our review of the R&D controlliterature, this particular goal has captured theattention of managers and scholars who havefocused on performance measurement systemsand exploitation-related criteria such as R&Dproductivity. Consequently, the attainment of thisgoal is closely linked to diagnostic control systemsthat establish targets, and measure activities andoutcomes to help ensure that the other R&Dstrategic goals are being achieved efficiently.

3.3. R&D contextual ambidexterity

We define R&D contextual ambidexterity as theability to attain appropriate levels of exploitationand exploration behaviors in the same R&Dorganizational unit. The right-hand element ofour framework indicates how the four controlsystems combine to produce the behaviors andcontrol orientations necessary for this ability. Wesuggest that beliefs systems and interactive sys-tems jointly produce exploration and a feed-for-ward control orientation. Beliefs systems provide‘momentum and guidance for opportunity-seek-ing behaviors,’ and interactive systems ‘focusorganizational attention on strategic uncertaintiesand thereby provoke the emergence of initiativesand strategies’ (Simons, 1994, p. 172). Togetherthese two types of control system promote pro-specting, experimentation and sense-making; allof these are not only central to exploration, butalso promote a feed-forward control orientationfor anticipating future events and their effects.Thus, beliefs systems and interactive systemsunderlie the proactive scanning and planningbehaviors essential for determining when andhow R&D activities should be modified.

Our framework also suggests that the exploitationaspect of R&D contextual ambidexterity is linked tothe joint use and effects of diagnostic and boundarysystems. Boundary systems permit discovery andlearning, but within clearly defined limits of free-dom. Diagnostic systems monitor R&D activitiesand outputs, and use this after-the-event informa-tion to reward conformance, or to modify processesand systems to correct non-conformance. Diagnosticsystems measure activities and outputs so that R&Dmanagers know when things are going well, or aregoing wrong. This creates a context for makinginformed decisions about resource allocation andprocess redesign. Thus, together diagnostic andboundary systems induce exploitation as employeesare directed and rewarded to refine and applyexisting knowledge and competences.

4. Framework illustration: the case ofbiotechnology firms

In this section, we present data to exemplify theelements of our framework in terms of what theyare (i.e., the actual goals, systems and behaviors),and what they do (i.e., their effect on otherelements of the framework and on an R&Dorganization). These data are used to illustratethe framework, and make it more connected toR&D reality. Similar approaches have been usedto illustrate conceptual frameworks dealing withR&D performance measurement systems (Chiesaet al., 2008), user innovation (Berthon et al., 2007)and external technology commercialization (Bian-chi et al., 2009).

4.1. Setting and methodology

We focused on biotechnology firms, definedbroadly as those firms that undertake life-scienceresearch to develop therapeutic products, medicaldevices or biotechnology related services. Bio-technology firms are particularly appropriate forillustrating our framework, for several reasons.First, they are often considered to be a proto-typical example of an R&D organization. Second,even though researchers have argued that thelong-term success of these firms depends oncontinued exploration (e.g., discovery, productformulation and preclinical trials), and effectiveexploitation (e.g., clinical trials and the new drugapplication stage) (McNamara and Baden-Fuller,1999, 2007), we know relatively little about howthis R&D ambidexterity can be attained. Third,the exploitation and exploration activities of thesefirms are significantly intertwined with each other.This means that biotechnology firms are suited tocontextual ambidexterity, because it is proble-matic to structurally separate these intertwinedactivities. This is especially the case for small- andmedium-sized biotechnology firms as their orga-nizational size limits any major and viable separa-tion of resources. Lastly, by focusing only onbiotechnology firms, our data are bounded, help-ing to provide a focused illustration of the ele-ments of our framework.

To collect the data, we took advantage of abiotechnology management education program,led by one of the authors of this paper. Thelearning nature of this university-industry pro-gram was useful for our research, as it providedrespondents with the opportunity and environ-ment to reflect, analyze and discuss the control


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systems within their firms. From 2006 to 2008 wecollected data from over 40 senior managers andscientists, from 15 different biotechnology firmswhose organizational size ranged from 35 to 284employees (see Table 2). With this number offirms, we did not seek to develop rich case studiesfor inductive theory building, or to provide strongempirical support for our framework. Instead, wesought multiple sources of data to help describeand tentatively validate the elements and logic ofour framework.

All of the firms were located in Western Canada,and undertook biotechnology related R&D. Ap-proximately half of the sample, Firms A–H, wereresearch service organizations that undertook R&Dactivities to develop their portfolio of testing andmodeling services for drug development and health-care organizations. The other half of our sample,Firms I–O, were involved primarily in the discoveryand development of drugs or medical devices. All 15firms were at least three years old and employedmore than 10 people, ensuring that they were likelyto employ some form of formal management con-trol system (Davila and Foster, 2007).

Given our illustrative aims, the data collectionbegan by presenting our conceptual framework(Figure 1) to groups of between five and 10respondents. During these presentations, each ele-

ment of the framework was defined and explained.This was followed by a discussion to further clarifythe function and scope of each element of theframework. Next, we collected data from indivi-dual respondents using a semi-structured inter-view. Respondents were first asked to confirmthat their firms had an active R&D capability,and to provide the following background informa-tion about their firms: age, size in terms ofemployee numbers and the area of biotechnologythe firm focused on. The respondents were thenasked to comment on the validity of the logic ofthe framework in general terms, and to considerthe extent to which their firms focus on and use thedifferent types of control system. This latter pointrequired the respondents to reflect on the numberof people, rules and processes associated witheach type of system. Next, the respondents wereasked to give examples of how each element ofthe framework exists, and to exemplify links be-tween the different elements of the framework(see Table 3).1 The aim was to elicit actual exam-ples of the goals, the control systems and theassociated behaviors and control orientations.The final stage of data collection involved anumber of follow-up interviews, where respon-dents were contacted to either seek further infor-mation or to clarify aspects of their answers.

Table 2. Companies and Respondents

Firm* Area of biotechnology Age offirm (years)

No. ofemployees

Role of respondents

Firm A Research testing services 15 35 Chief Executive Officer,Project Manager

Firm B Research testing services 29 175 Analytical ChemistFirm C Research testing services 40 51 Chief Executive OfficerFirm D Research modeling services 10 38 Senior TechnologistFirm E Research modeling services 5 48 Research Scientist –

microbiologyFirm F Research modeling and testing services 18 62 Account ManagerFirm G Research modeling and testing services 7 32 Project ManagerFirm H Research modeling and testing services 23 134 Account ManagerFirm I Discovery and development of medical

devices17 284 Business Development

ManagerFirm J Discovery and development of therapeutic

drugs28 120 Research Scientist –

toxicologyFirm K Discovery and development of therapeutic

drugs6 50 Quality Assurance Manager,

Senior ChemistFirm L Discovery and development of therapeutic

drugs8 70 Senior Research Associate

Firm M Discovery and development of therapeuticdrugs

17 201 R&D Technologist, ProjectManager

Firm N Discovery and development of therapeuticdrugs

14 59 Senior Research Associate

Firm O Discovery and development of therapeuticdrugs

14 67 Research Scientist – oncology

*Pseudonyms and basic descriptions of the area of biotechnology areas are used to protect the anonymity of firms and respondents.




Table 3. Illustration of Model Elements

Model elements Representative and abbreviated answers*

R&D strategic goalsDefine what the goalsmean to your firm?

Growth: We are trying to survive and grow; and so we are totally focused on securingthe next round of investment. We need the money to keep existing people, to recruit newpeople and buy more equipment (Firm K). When we started out we hoped to build acompany big enough to develop multiple drugs on its own, instead, we exploredalliances and are finalizing a deal to license the technology (Firm L). Unlike mostbiotech start-ups, we are a service business that must produce a return on investmentnow (Firm B)Innovation: We are in the process of getting new approvals for our products, both interms of serving new regional markets and in terms of new applications for our existingproducts. We are trying to better target the drugs we have (Firm I). We have thistechnology, which if it works out, will completely transform the value chain for thistesting service (Firm C)Reliability: In this industry we succeed and fail on the quality of our data. If we are notscientifically valid at every stage of the process; then our products will not get approved(Firm O). If we are not reliable we will soon be out of business (Firm G)Efficiency: This is a major driver for us. Our testing services are up against existing rivalservices that are continuously improving. If our R&D does not deliver desirableenhancements to the tests and models we offer, then in the long run we won’t be able tocompete (Firm D). While return on investment is important, we only worry aboutefficiency when the money starts to run out (Firm J)

Describe how each type ofgoal relates to each typeof control system?

Growth and beliefs systems: Originally we were a local company servicing local biotechfirms; now we are trying to access global markets and work with partners around theworld, and this is clearly reflected in our mission statement and core values. (Firm F).We have grown so we have different types of stakeholders whose interests arecommunicated to us (Firm H)Innovation and interactive systems: A few years back the CEO started organizingcompany retreats, where we think about how the organization is evolving – what itmight become (Firms J). From an R&D basis we deliver monthly presentations to thechief technology officer so that he knows what we are coming up with (Firm E)Reliability and boundary systems: The trustworthiness of our research is so importantthat we strongly adhere to good laboratory practice (GLP) (Firm A). Archiving andpeer review are common systems in our industry for facilitating boundary-like controlin labs (Firm M)Efficiency and diagnostic systems: Our financial officer monitors and measures our cashburn rate (Firm E). Our project managers monitor progress each week in terms of thenumber of tests, and the quantity of data produced and recorded (Firm K)

Management control systemsProvide examples of therules, processes andtechnologies that yourfirm has for each type ofcontrol system?

Beliefs: Our mission statement is everywhere – it reminds everyone that we aspire to be asustainable business and not just a collection of research projects (Firm N). On the wallsof our labs are framed posters of famous scientists along with motivational messagesthat encourage us to try and make a difference (Firm I). Like the university recruitmentprocess each member of my team gets to meet with potential new hires to suss out howwell they would fit in (Firm D)Interactive: We use crude technology road-mapping exercises to forecast andcommunicate technological developments (Firm C). This involves two types of activity.First, our senior scientists and business development managers produce reports thatdetail relevant trends for our industry. Second, we have strategic planning sessionswhere we report this information to employees and develop action plans and allocateresources (Firm M). A bit like 3M and Google we are allowed to allocate a percentageof our time to work on pet projects (Firm F)Boundary: Code of Conduct and standard operating procedures (All Firms); employeescan call an independent whistle-blowing hotline (Firm H). We adhere to a host ofregulatory constraints regarding the disposal of waste and handling of radioactivematerial (Firm M). The tests, inspections and audits conducted by our qualityassurance department, as well as adhering to industry procedures and guidelines e.g.,International Laboratory Accreditation Cooperation (Firm B). The FDA requires us todevelop and maintain risk management systems to ensure that the benefits of ourproduct outweigh the risks (Firm N). All scientific laboratories must enforce laboratorydress codes (e.g., no shorts, no skirts, no sandals and no open-toed shoes) for safety andreliability reasons (Firm A)


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4.2. Analysis and findings

We approached our analysis from a broadlydescriptive perspective, focusing on how thedata illustrate the elements and relationships inour framework. Following guidelines for present-ing qualitative case data (see Eisenhardt, 1989),and the format used by Nag, Corley and Gioia(2007) for their study of strategic change in R&Dorganizations, we present our questions and illus-trative answers in Table 3. This summary infor-mation complements our narrative in thefollowing sections, where we describe, using ex-amples, the conceptual logic and reality of ourproposed framework. It is important to note thateven though there were no major contradictorycomments or negative assessments of the frame-work, this does not constitute empirical supportfor the framework. The data are simply used toillustrate the elements of the framework.

4.2.1. R&D strategic goals in biotechnology firmsIn terms of R&D growth goals, our frameworkand data indicate that this varied largely accord-ing to the lifecycle stages of the firm, its marketsand its products. This is consistent with strategicoptions which characterize the extent to whichfirms focus on appropriating returns from stableand limited project portfolios (harvest), versusbuilding capacity to create new knowledge andtechnologies for new products and markets(build) (Gupta and Govindarajan, 1984). FirmsE, G and K, for instance, focused on securing newsources of investment funding so as to grow R&Dcapacity, and to develop their early stage technol-ogies. These firms were relatively young, small,idea-rich, but resource-poor and thus concernedwith building R&D capacity in a way that thelarger and more established firms were not. Thelarger, more mature biotechnology organizations(e.g., Firms B, H, I and M) were more concerned

Table 3. (Contd.)

Model elements Representative and abbreviated answers*

Diagnostic: Individual scientists have specific objectives, which relate to projectmilestones that keep the investors happy (Firm K). These are the systems that measurehow much work individuals do e.g., tests per day (Firm L). Employee awards wouldconstitute this form of control (Firm G). For our R&D we have budgets and budgetarycontrols; these dictate who does what and what gets done (Firm F)

R&D contextual ambidexterityDescribe how thedifferent types of controlsystem work together togenerate the exploitationand exploration behaviorsin your firm?

Exploration (beliefs and interactive): Some of the biggest successes in our industry haveinvolved companies changing direction with only 6 months of operating cash left. To dothis required beliefs and interactive systems capable of helping management to first spotthe opportunity and then to steer the company in a new direction (Firm O). Our beliefssystems direct what we do and why we do it, while our interactive systems provide thefreedom and mechanisms to rethink what we do and what we do it (Firm B)Exploitation (diagnostic and boundary): First and foremost we are a service company,and we view innovation and learning as necessary but costly and hard to justify. As aconsequence our control systems focus on improving project efficiency and optimizingrevenues from existing assets (Firm H). Our boundary and diagnostic systems help us toreassess risk and revise the go/no go guidelines for research activities (Firm O). I feelthat the whole drug development process, with all its checks and regulations, creates ahigh level of consumer protection but also a risk averse product development culture(Firm N).

Describe how thedifferent types of controlsystem involve a feedbackand/or a feed-forwardcontrol orientations inyour firm?

Feed-forward control orientation (beliefs and interactive): I would say these systems aremuch more open and intangible in nature – they have to be – because we use them to tryto make sense of all uncertainty in our industry (Firm I). What typically happens is thatwe use the industry forecasts and scenarios to see if we should maintain our currentportfolio of projects . . . if a major change is required then that would almost certainlyrequire a change in aspects of our mission statement and project activities (Firm F). Wecould do with formalizing these systems a lot more. This would help stop all the micro-management we have, and free these guys to see problems coming in time so that we cando something about them (Firm C).Feedback control orientation (diagnostic and boundary): These systems are obviouslyfeedback in nature – they are all about doing checks and tests to see what has happenedor should have happened (Firm E). There is a view in my company that we have toomany of these systems and they provide so much feedback that we do not know what todo with it (Firm L). Reviews, audits and certifications – these are all industry-recognized ways of obtaining feedback (Firm G).

*Some of the answers have been abbreviated to protect to protect the anonymity of firms and respondents.




with developing efficient R&D processes to cap-ture returns from existing resources and projects,and thus their investment intensity in new R&Dprojects was much smaller. A respondent fromFirm M, for example, stated that ‘once ourcompany became public the whole nature of ourR&D operations dramatically shifted from creat-ing new technologies, to marketing and sellingour approved product line.’ Furthermore, respon-dents reported that this type of goal was linked tothe use of beliefs systems which help create acommon language, a shared understanding andstrategic coherence within an R&D organization.For instance, the respondent from Firm N re-ported that ‘when we were first formed we didn’thave a mission statement. We were simply agroup of researchers who did research. Sixteenyears later, however, we have had four or fivedifferent mission statements, with the current oneemphasizing our commitment to provide value toshareholders.’ Similarly, the respondent fromFirm E reported that ‘We all know that the goalis to build a company that will be big enough, interms of talent and promising intellectual prop-erty, so as to attract partners or buyers. . . . . . .and in terms of the control system that reminds usof this goal – it is communication, communica-tion and more communication.’

Innovation goals delineate the kinds of out-comes that R&D organizations seek to produce.Although these goals can vary in a number ofways, we focused solely on the magnitude ofchange in a firm’s technology, and the degree ofbenefit it brings to the market (e.g., incrementalversus radical) (Wheelwright and Clark, 1992). Interms of our data, respondents from Firms A andB reported that their R&D focused on incremen-tally enhancing their existing service offerings forexisting customers in the biotechnology and phar-maceutical industries. In contrast, Firm O fo-cused on adapting its existing technologies forhuman therapeutic disorders for animal care(farm and pet) markets. Our data also indicatedthat when an innovation goal specified radicalinnovations, then this was associated with greateruse of interactive control than if the goal stipu-lated incremental innovations. For instance, arespondent from Firm A reported that his orga-nization’s focus on refining existing technologyfor existing customers was largely driven by theoccasional project meeting with top managers,intended to ‘boost organizational dialogue’ abouthow to improve existing testing services. In thecase of Firm O, their desire to develop radicallynew platform molecular technologies, for different

end-use markets, meant that they faced manytechnological, regulatory and market uncertainties.This required their top-management team to de-velop and continuously use interactive systems:‘We set up committees to collect and report in-formation on who was doing what in our industry.This information was internally communicated tothe necessary project teams, so they could commenton and help us plan for the opportunities andthreats that we were facing.’

Reliability goals specify the extent to whichR&D will be conducted in a timely fashion, and inaccordance with expected standards and codes ofpractice. Our data indicated that this goal iscentral to biotechnology firms, with all of therespondents in our study making statements thatconcurred with the view that ‘the success of anybiotech firm is dependent on producing andreporting good data, before funding runs out’(Firm L). The importance of R&D reliability tobiotechnology firms is reflected in the demands oftheir various stakeholders (e.g., patient groups,investors, collaborators and government agen-cies), who expect biotechnology firms to closelyfollow good scientific practice and conform torecognized rules and guidelines. Consequently, interms of the link between reliability goals andcontrol system use, our illustrative data supportthe link to boundary systems. All of the respon-dents provided comments similar to those listed inTable 3, indicating that reliability requires strongand effective boundary systems to reduce the riskof improper behaviors that might cause a projector service failure.

The fourth goal in our framework, efficiency,specifies the extent to which R&D organizationsare concerned with productivity and cost effec-tiveness as ways to maximize returns on invest-ment. Our data indicate that while efficiency is onthe whole important to all the biotechnologyfirms in our study, it was less significant to thesix drug development firms (Firms J, K, L, M, Nand O), and the one medical device firm (Firm I),than it was to the nine research services firms(Firms A, B, C, D, E, F, G and H). The view ofefficiency held by the drug and medical devicefirms, is reflected in the statement that the ‘majortime lag between R&D action and R&D outcome,typically limits our ability to efficiently controlour activities, and as a consequence being efficientis not really a top priority. We just focus on doinggood science’ (Firm J). In contrast, the researchservice organizations considered efficiency goalsto be central to their R&D, which must continu-ously produce innovations that help keep their


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services cutting edge and competitive. This varia-tion in attitudes toward efficiency was also linkedto variations in the extent to which firms useddiagnostic systems. For instance, the respondentfrom Firm B stated ‘many of our R&D projectsare in collaboration with customers who havetime, quality and cost expectations, . . . . . . andto meet these we have numerous budget andproject monitoring systems.’

4.2.2. Management control systems in biotechnol-ogy firmsThe most common examples of beliefs systemsidentified by our respondents were the companyreports, mission statements and website pagesthat each firm used to articulate the researchvision and values of the organization. For drugdevelopment firms, beliefs systems typically fo-cused on installing in employees the noble visionof serving patients, saving lives and eliminatingpain and suffering, while being guided by researchvalues such as respect, ethics, and team work. Incontrast while the research service firms we sur-veyed had similar statements about research va-lues, their visions focused more on being the bestor first choice service provider in their market.Other types of beliefs systems reported by ourrespondents included the company recruitmentprocess that ‘seeks to attract and recruit talentwith attitudes and skills that are consistent withour research values’ (Firm K), and the trainingprocess, which ‘develops people in the ‘companyway’ by continually communicating our goals andachievements to all staff’ (Firm O). Respondentsalso reported the use of intra-company challengesand socialization events to promote fun andcreative thinking, and to build organizationalcoherence. Also in some cases the architectureand decor of company buildings, along with thepictures on the walls of corridors and labora-tories, were all designed to inspire employees withcreative, funky and free-thinking values. All ofthese examples of beliefs systems are intended tofocus and energize employees in a way that isnecessary for the exploration and feed-forwardcontrol aspect of R&D contextual ambidexterity.

In terms of interactive systems, our frameworkand data indicate that these include R&D specificsystems such as technology road-mapping (Phaalet al., 2006) and real options methods (Barnett,2005), all of which help companies understand theeffects of emerging technologies. There are alsomore general strategic scanning and monitoringsystems (e.g., market research, competitor analy-sis and technology benchmarking) that collect

and analyze data on changes in demand, pro-ducts, technology, competition and regulation.Respondents also reported how R&D projectswere started, adjusted and stopped using infor-mation from forecasting and assessment systems.Forecasting systems provide projections aboutwhen things will happen (i.e., a drop in thedemand for existing products and services, orthe approval of a new regulation or competitiveproduct), while assessment systems provide esti-mations of the impact of these changes on theorganization and its R&D portfolio. Such inter-active systems are also ‘interactive’ in the sensethat the managers use the information they un-cover ‘to continuously and directly involve them-selves in the decisions and behavior of theirsubordinates’ (Chiesa et al., 2009a, p. 421). Forinstance, respondents reported the use of planningsessions ‘to distribute strategic information to em-ployees, and then work with them to develop actionplans and allocate resources for existing and newprojects’ (Firm I). Respondents also reported thatproject and organizational based interactive sys-tems are used by managers and their teams tospeculate on future R&D scenarios, and to ensurethat the foci and aims of the other types of controlsystem are adjusted as R&D strategic goals shift.Furthermore, all of the firms in our study hadscientific advisory committees that provided advicethat could alter the strategies for planned, pipelineand approved R&D projects. These committeesdictated the direction of exploration and the scopeof feed-forward control, necessary for R&D con-textual ambidexterity.

Boundary systems act ‘like an organization’sbrakes’ (Simons, 1995b, p. 84). They restrain andguide employees so that the firm does not experi-ence an accident, i.e., a failure and crisis. Forbiotechnology firms the systems are typically builtinto a firm’s laboratory practices, project manage-ment methods and resource allocation decisionmaking processes. For instance, many respon-dents reported that their firms had ‘a Code ofConduct that all our employees must be certifiedto’ (Firm D) and that ‘product approval is de-pendent on us producing, analyzing and archivingrisk data to ensure that the benefits of ourplanned drug outweigh the risks’ (Firm L). Thereare also non-firm specific boundary systems,which for biotechnology firms included regionaland national laws, and regulations from institu-tions such as the US Food and Drug Adminis-tration and the European Medicines Agency.Furthermore, there are certification regimes suchas Good Laboratory Practices, which are ‘pri-




marily intended to guarantee safe animal andtoxicology testing, yet also help to ensure thatlaboratory results are internally peer-reviewed.This helps to limit the risk of producing resultsthat are wrong, fabricated or massaged’ (Firm K).In summary, as R&D researchers enjoy relativelyhigh levels of job autonomy, boundary systemsare used to avoid or mitigate unsafe or unethicalbehaviors, or actions that constitute scientificmisconduct. These systems counter the effects ofdiagnostic systems, and are most likely to producethe risk averse behaviors associated with exploi-tation and the checking of conformance that goeswith feedback control.

In terms of diagnostic systems, our frame-work and data indicate that these include projectplanning systems for target drug approval dates,budget systems for project costs, laboratory man-agement information systems for recording andanalyzing sample tests, and clinical trial systemsfor measuring the performance or efficacy of adrug. Such systems are progress-focused. Man-agers, boards and regulatory agencies identifyresearch project goals, review progress and arrangepost-project reviews to identify lessons and correc-tive actions. In terms of R&D output, both thedrug development firms and the modeling andtesting service firms in our study used a numberof corporate level diagnostic systems. These mea-sured the production of scientific papers, returnsfrom R&D collaborations, the creation and ap-proval of patents and the revenue from new servicetechnologies, licensed patents and approved pro-ducts. Thus, by their very nature, diagnostic con-trol systems are central to exploitation behaviors inthat they provide feedback, or after-the-event in-formation, that is used to adjust and improve theperformance of existing processes.

4.2.3. Contextual ambidexterity in biotechnologyfirmsIn terms of exploration, our framework and dataindicate that beliefs systems and interactive sys-tems work together to generate search and dis-covery that are relevant and adaptable. Beliefssystems such as the mission statement, the recruit-ment process, employee training and the companyrhetoric and symbols, are all used to focus andguide employees to search for and create newcompetences and knowledge. In combination,interactive systems such as technology road-map-ping, market forecasting and impact assessmentsare used to maintain or adjust the specific direc-tion of this exploration activity over time. Forexample, a respondent from Firm K described a

situation in which his biotechnology firm wasunable to make sufficient progress toward devel-oping its sole technology for a specific therapeuticdisorder, and thus was struggling to attractfurther investment. With only a few months offunding remaining, the company identified acompletely different disease, with a much greatermarket value, which could be treated using theircore platform technology. The discovery of thisopportunity is credited to the Chief ScientificOfficer ‘The fact is – his job was to continuouslysearch for, evaluate and share new technologicalopportunities with the board and project teams.He was our interactive control system – chargedwith worrying about our future.’

Similarly, in terms of control orientation – theextent to which control is ex post (after the event)or ex ante (before the event) in nature – ourframework and data suggest that beliefs systemsand interactive systems work together to promotea feed-forward control orientation. This followsthe original thinking of Simons (1995a, p. 108)who argued that interactive systems promote‘reforecasting of future states based on revisedcurrent information’; however, for this to occur,the projections must be focused and appropriateto the needs of the organization. Thus, beliefssystems work with interactive systems to ensurethat information is sought and used in a way thatpromotes prediction and change that are relevantto the organization. These systems are feed-for-ward in nature because they help managers toanticipate or forecast events and trends beforethey occur, allowing them to proactively redirectorganizational values and activities. For instance,one respondent reported ‘we know that the pa-tents on our products and our competitors’ pro-ducts will expire someday, and even though wecannot be certain what the impact will be whenthese expiries occur, we still monitor, forecast anddevelop scenarios so that we are prepared forthese events’ (Firm I).

In terms of exploitation, our framework anddata suggest this is attained by boundary systemsand diagnostic systems working in tandem.Boundary systems moderate exploration beha-viors, induced by beliefs systems and interactivesystems, by defining and restricting the searchspace and activities that can be undertaken (Si-mons, 1995a; Widener, 2007). They reign inemployee freedoms to counter the autonomyand inspiration that drive the exploration fornew knowledge. Diagnostic systems also counterexploration, by using relatively short-term effi-ciency measures to refine and extend existing


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competencies. These systems typically focus onand require exploitation related outcomes that are‘positive, proximate and predictable’ in nature(March, 1991, p. 85). These combined effects ofboundary systems and diagnostic systems wereexemplified by the statement that ‘we use bound-ary control in conjunction with our project per-formance systems to examine and check thateverything is going according to plan. We don’tlike surprises and nor do our customers’ (Firm E).This type of control counters the instability,uncertainty and serendipity often associatedwith R&D exploration.

In terms of control orientation, our frameworkand data suggest that boundary and diagnosticsystems in biotechnology firms jointly promote afeedback control orientation. Diagnostic systemsare used to monitor, review and test, so as toensure things are on track in terms of ‘what’ isbeing done. If they are not, then other controlsystems and activities can be adjusted accordingly.Managers also use this after-the-event informationto motivate and reward the behaviors of indivi-duals, teams and organizations. In contrast,boundary systems specify and check ‘how’ thingsare done, in accordance with pre-defined standardsand regulations. These systems also provide error-based feedback control, i.e., any deviation fromspecified practices leads to corrective action and ifthese deviations persist, then stronger more influ-ential boundary systems are installed. For in-stance, one of the respondents from Firm Mreported that ‘if biotechnology firms experienceone major incident or repeated minor incidents ofscientific misconduct, then this typically leads to acorrective action where guidelines and checks forlaboratory practice are tightened up.’

5. Implications and future researchopportunities

The central contribution of our paper is thedevelopment and illustration of an R&D manage-ment control framework for attaining contextualambidexterity in R&D organizations. We nowdiscuss several implications of the framework, ofrelevance to both management practice and fu-ture empirical research.

First, our framework posits that there is astrong (though not exclusive) relationship be-tween individual R&D goals and the use ofdifferent types of control system. An importantimplication of this is the need to empiricallyexamine to what extent the different R&D stra-

tegic goals influence the attention placed ondifferent types of control system. As the use ofmultiple control systems can require considerablemanagerial attention, management should prior-itize where to focus their attention and resources(Marginson, 2002; Widener, 2007). Also, as dif-ferent goals can have different and sometimesconflicting implications for organizational beha-vior, the use of different control systems couldhelp to manage any potential conflicts presentedby multiple goals. This can be examined by survey-ing employees, to assess the extent to which theirR&D organization is guided by different goals, andthe number of people hours associated with eachtype of control system (Chiesa and Frattini, 2007).

Second, with our framework and illustrativedata, we claim that beliefs and interactive systemsprovide a feed-forward control orientation thatgenerates or enhances exploration, whereasboundary and diagnostic controls provide a feed-back control orientation that generates or en-hances exploitation. While we consider this tobe true, all frameworks are simplified representa-tions of reality (Box, 1979). Consequently, wesuggest that our framework provides a startingpoint for unpacking the complexities of the con-trol-behavior relationship. For example, it is notjust the combination of control systems used thatmatters, but also the substantive content of thecontrols – what is dictated, discussed, projected,measured, monitored and evaluated. Thus, know-ing that an organization is using a certain type ofcontrol system provides a first-order level insightinto the control-behavior relationship. The nextlevel is to understand the effectiveness of thedifferent rules, procedures, technologies and in-centives that R&D managers use in conjunctionwith each type of control system.

Third, researchers could explore how controlsystems could be used to attain low or high levelsof balanced ambidexterity (Cao et al., 2009). Lowbalanced ambidexterity is when a firm’s level ofexploitation is significantly lower than that ofexploration, and vice versa; while high balancedambidexterity is when a firm has similar moderatelevels of both exploration and exploitation. Byemphasizing different control system combina-tions, it could be possible for R&D managers toattain, at specific periods in time, different mixesof this exploitation-exploration balance.

A fourth implication of our framework con-cerns the influence of other contingency factorssuch as the size, age and life-cycle of the R&Dorganization, and its industry conditions, on theuse of different management control systems.




Although the focus of our paper was on under-standing how different types of control system,guided by different R&D strategic goals, can beused to induce contextual ambidexterity, theillustrative empirical evidence we present hintsat the role of these factors. For instance, someorganizations (e.g., Firms E, G and K) wererelatively young and small, and concerned withgoals and controls that sought to build R&Dcapacity in a way that the larger and moreestablished firms were not (e.g., Firms B, H, Iand M). Thus, the framework we present could bemodified by other researchers to explore how suchantecedents drive the use and outcomes of R&Dcontrol systems.

A fifth implication of our framework concernshow R&D managers might use control systems to‘dynamically’ shift, over time, the exploitation-exploration balance. The balanced viewed ofambidexterity (March, 1991; Cao et al., 2009) islargely ‘static’ in nature, in that it refers to anoptimal mix of exploitation and exploration at apoint in time. However, as discussed above, R&Dcontrol is driven and constrained by environmen-tal antecedents such as the size, age and life cycleof the R&D organization, as well as by changes inindustry conditions such as demand, competitors,technologies, products and regulation. As each ofthese conditions has a distinct velocity (a rate anddirection of change (McCarthy et al., 2010)), – anoptimum mix of exploitation-exploration at onepoint in time is likely to become unsuitable asindustry conditions change over time. This makesthe balancing of exploitation and exploration adynamic problem. This is tentatively supportedby our data where respondents explained how thebalance of exploitation and exploration alteredover time as a firm advanced through its life cycle,or changed the focus of its R&D activities (see:Table 3, the R&D contextual ambidexterity sec-tion). For instance, the respondent from Firm Oexplained how different beliefs and interactivesystems were required to shift the balance towardexploration so as to help take the company in anew direction. The importance of this implicationhas been highlighted by scholars who suggest that‘given the dynamism of markets and organiza-tions, it is important to develop theories thatcombine static elements with more dynamic per-ceptions of ambidexterity’ (Raisch et al., 2009, p.686). Thus, we suggest that our framework can beused to explore how R&D managers use differentcontrol systems to dynamically shift the balanceor mix between exploitation and exploration overtime. This follows what McCarthy et al. (2006)

call ‘capability toggling’, and Thomas et al. (2005)call ‘irregular oscillation,’ where the balancing ofexploitation-exploration tensions is much likeriding a bike – it requires a continuous andirregular shifting of control system use over time.

6. Conclusion

In this paper, we introduced a framework thatshows how four types of control system, eachguided by an R&D goal, combine to induce thebehaviors, outcomes and control orientations(feedback versus feed-forward) necessary for con-textual ambidexterity. We illustrated these frame-work elements and their linkages, using data frombiotechnology firms, so as to clarify what theseelements are and what they do. While this helps tomake the framework more useful and meaningfulto scholars and practitioners, this illustration mightalso suggest that R&D control is a straightforwardtask. However, this is not the case. An inherentchallenge to understanding and practicing effectiveR&D management control is the fact that it isconcerned with controlling the production ofknowledge, something that is inherently unobser-vable. As knowledge increasingly redefines thewealth of nations, firms and individuals, the chal-lenges and benefits of effective R&D control willcontinue to capture the attention of scholars andmanagers. Thus, we hope that our framework willmotivate researchers to further examine howbroader forms of control, guided by R&D objec-tives and other environmental factors, act as orga-nizational levers for balancing different forms ofknowledge production over time.

Acknowledgements

We are grateful to two anonymous reviewers fortheir helpful and constructive comments. Thedevelopment of this paper also benefited fromcomments from Danny Breznitz, Elicia Maine,Jane McCarthy, Karen Ruckman, Christos Tsi-nopoulos and participants at the R&D Manage-ment Conference 2008. We also acknowledgeresearch funding from Canada’s Social Scienceand Humanities Research Council.

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Notes

1. Some of the answers have been abbreviated to protect

the anonymity of firms and respondents.

Ian McCarthy is the Canada Research Chair inTechnology and Operations Management in theFaculty of Business Administration at SimonFraser University. He received his MSc andPhD degrees from the University of Sheffield,and before joining Simon Fraser University hewas a faculty member at the Universities ofWarwick and Sheffield. His research focuses onhow firms differ in their innovation processes,product and service customization approaches,R&D management control systems, outsourcingpractices and collaborative networks. His re-search has been published in engineering andbusiness journals, including The Academy ofManagement Review, International Journal ofProduction Economics, Journal of Production In-novation Management, Technovation andOMEGA.

Brian R. Gordon is a Doctoral Candidate inbusiness administration at Simon Fraser Univer-sity. His research interests include knowledge andknowledge creation processes in strategy, entre-preneurship and innovation.




Achieving contextual ambidexterity in R&D organizations: a management control system approach

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