STRATEGIC FRAMEWORKS

In recent years there has been a growing interest in the relationship between management control systems (MCS) and strategy. It has been suggested that the MCS should be tailored explicitly to support the strategy of the business to lead to competitive advantage and superior performance (Dent, 1990; Samson et al., 1991; Simons, 1987a, 1990). Also, there is evidence that high organizational performance may result from a matching of an organization’s environment, strategy and internal structures and systems (Govindarajan & Gupta, 1985; Govindarajan, 1982). Strategy was not used explicitly as a variable in MCS research until the 1980s. This is surprising considering the field of business strategy or business policy has become increasingly important since it emerged in the 1950s (see Chandler, 1962). Much of the empirical research in this area follows a contingency approach and involves a search for systematic relationships between specific elements of the MCS and the particular strategy of the organization (Simons, 1987a; Merchant, 1985b; Govindarajan 81 Gupta, 1985). Case studies have also been undertaken to investigate the role of the MCS in supporting and influencing the strategic processes within organizations (Simons, 1990; Roberts, 1990; Archer & Otley, 1991). The focus has been primarily on business strategy at the senior management level of the organization. However, since the mid-198Os, in the operations management literature there has been a growing interest in researching the way that manufacturing strategies can be used to gain competitive advantage (Buffa, 1984; Schonberger, 1986; Hayes et al., 1988). Normative studies and single case studies have explored the relationship between MCS and strategy at the manufacturing level (for example, Kaplan, 1990). However, empirical research only began to emerge recently (for example, Daniel & Reitsperger, 1991). Management control was defined by Anthony (1965) as “the process by which managers ensure that resources are obtained and used effectively and efficiently in the accomplishment of the organization’s objectives.” This definition limited subsequent researchers not only to envisage MCS as encompassing the largely accounting-based controls of planning, monitoring of activities, measuring performance and integrative mechanisms, it also served to artificially separate management control from strategic control and operational control. MCS provide a means for gaining cooperation among collectives of individuals or organizational units who may share only partially congruent objectives, and channeling those efforts toward a specified set of organizational goals (Ouchi, 1979; Flamholtz, 1983).

Controls have been categorized in many ways. For example, formal and informal controls (Anthony et al., 1989) output and behavior controls (Ouchi, 1977) market, bureaucracy and clan controls (Ouchi, 1979) administrative and social controls (Hopwood, 1976) and results, action and personnel controls (Merchant, 1985a). A brief discussion of these classifications will illustrate the breadth of controls used in research. Formal controls include rules, standard operating procedures and budgeting systems. These are the more visible, objective components of the control system, and thus, the easiest to research. Empirical research that studies MCS and strategy has focused primarily on formal controls. These include output or results controls which are of a feedback nature, and often financially oriented. They include controls that aim to ensure that specific outcomes will be achieved and involve monitoring, measuring and taking corrective actions. Controls that focus on feedforward control (ex-anti controls) include administrative controls (standard operating procedures and rules), personnel controls (human resource management policies) and behavior controls (the ongoing monitoring of activities and decisions). Informal controls are not consciously designed. They include the unwritten policies of the organization and often derive from, or are an artifact of the organizational culture. Ouchi (1979) described clan controls that derive from the shared values and norms, or the culture of the organization. 1 Usually clan controls are Informal, rather than formal controls, However, some formal controls also derive from the organizational culture. For example, the formal organizational mission or objectives may reflect the values and beliefs of the dominant culture. Informal controls are important aspects of MCS and the effectiveness of formal controls may be dependent on the nature of the informal controls that are also in place (Otley, 1980; Flamholtz, 1983).

STRATEGIC FRAMEWORKS

Strategy has been operationalized in many different ways in MCS research. Interestingly, he basic concepts and frameworks developed in the strategy literature during the past two decades have not always been widely adopted in these studies and the multidimensional nature of strategy is seldom recognized (Govindarajan & Gupta, 1985, is an exception). These problems can lead to under-specification, or a misspecification of the research design and may affect the integrity of research findings. In this section, some strategic concepts and frameworks will be outlined to position MCS research within a more general strategic context. Also, the strategic typologies and variables that have heen used in empirical research on MCS and strategy will be described and compared. Defining strategy Strategy has been defined in many ways. For example, strategy has been described as a pattern of decisions about the organization’s future (Mintzberg, 1978) which take on meaning when it is implemented through the organization’s structure and processes (Miles & Snow, 1978). Johnson (1987, pp. 4-5) stated that strategic decisions occur at many levels of managerial activity. They are concerned with the long-term direction of the organization, the scope of an organization’s activities, the matching of organizational activities to its environment and resource capabilities, the allocation of major resources within the organization, and consideration of the expectations and values of the organization’s stakeholders. Corporate strategy is concerned with decisions about the types of businesses to operate in, including what businesses to acquire or divest, and how best to structure and finance the company (Johnson & Scholes, 1889, p. 9). It is concerned with the way resources are focused to convert distinct competences into competitive advantage (Andrews, 1980, pp. 18-19). Business (or competitive) strategies relate to each business unit of the organization and focus on how individual SBUs (strategic business units) compete within their particular industries, and the way that each SBU positions itself in relation to competitors. Operational strategies address how the various unctions of the organization contribute to the particular business strategy and competitiveness of the organization. Much of the research that studies the relationship between MCS and strategy focuses on business strategy. However, there is an increasing interest in considering the nature of MCS and operational strategies (particularly manufacturing strategies). Strategy formulation and implementation Strategic management is often conceptualized as the rational progression from strategy formulation to strategy implementation (Snow & Hambrick, 1980). Strategy formulation is the managerial activity (often of a cognitive nature) Involved in forming strategies while strategy implementation is concerned with translating the chosen strategy into actions (Johnson & Scholes, 1989, . 15). These actions encompass allocating resources and designing suitable administrative systems, including MCS (Preble, 1992). Contingency approaches to research on MCS and strategy often (implicitly) address strategy implementation (see, for example, Govindarajan, 1988), while case study applications often emphasize the processes of strategy formulation and change (see, for example, Simons, 1990). Descriptions of strategy formulation and implementation often imply that strategy is an outcome of a deliberate stream of decisions. However, not all implemented strategies arise in the same way (Mintzberg, 1978, 1988). Intended strategies are those that are formally planned, but may not always be realized due to unrealistic expectations, misjudgments of the environment, or changes in plans during implementation. Realized strategies may develop from those intended strategies, or may emerge incrementally. A MCS that is designed to support a certain intended strategy may not contribute to effectiveness if that strategy is never realized, and a different strategy emerges. However, in empirical research the importance of the distinction between Intended and realized strategy is rarely acknowledged, and only in case studies are the processes of strategy development and change considered. Alternative research paradigms Like many areas of research, different discipline bases and paradigms have been used to study strategy. Some research follows a positivist approach, assuming that strategy is an outcome of rational choice. Alternatively, strategy may be considered a craft. Mintzberg (1987) and Quinn (1980) stress the ambiguous and messy nature of strategic decisions, and the need to design systems that allow for flexibility and encourage creativity in strategic planners. In such situations, formal control systems may be counter-productive as they impose constraints and discipline (Gooid & Quinn, 1990). A more extreme view is that rational normative models of strategy exist in organizations only as ritual, and that the “true” strategy of an organization is not the one formally espoused in mission statements and company documents; strategy develops and resides in the minds of key managers. Using a normative model of strategic decision making, Schwenck (1984) illustrated how cognitive simplification pro cesses may limit the rational procedures within each stage of the model. Porac Thomas and Emme (1987) explained how cognitive constructions of managers consist of beliefs about the actions of competitors, suppliers and

customers, and the causes of success and failure. A manager may choose to engage in certain strategic activities based on those beliefs. This cognitive view of the strategy process is difficult to adopt in research which embraces a positivist stance when objective measures of strategy are sought, but may be used in case study approaches where subjective perceptions of strategy can be recognized. Operationalizing strategy Hambrick (1980) proposed four different approaches to operationalizing strategy: textual description, partial measurement, multivariate measurement and typologies. Textual description was seen as appropriate for case study research and theory building, but too weak for theory testing as descriptions cannot be generated in large enough numbers to produce generalizable results.

Porter (1980, 1985) described three generic strategies - cost leadership, differentiation and focus. Each of these intended strategies provides a basis for a sustainable competitive advantage within an industry and potentially defines the context for actions in each functional area of the organization. The successful implementation of each strategy involves different resources and skills, supportive organizational arrangements and control systems. Cost leadership implies that the organization aims to become the lowest-cost producer in its industry. The source of this competitive advantage may arise from factors such as economies of scale, access to favorable raw material prices, and superior technology. An organization with a differentiation strategy focuses on providing products with attributes that are highly valued its customers. These include quality or dependability of the product, after-sales service, the wide availability of the product and product flexibility. In a focus strategy a company dedicates itself to a segment of the market that has special needs that are poorly served by the other competitors in the industry. Competitive advantage is based on either cost leadership or differentiation.

Miller and Friesen (1982) categorized firms as conservative or entrepreneurial, using the extent of product innovation. The two types differed in their degree of environmental hostility, organizational differentiation, environmental heterogeneity and technocratization. Conservative firms engage in innovation with reluctance, usually as a response to serious challenge. Entrepreneurs aggressively pursue innovation, and control systems were used to warn against excessive innovation.

The classification of build, hold, harvest and divest focuses on variations in strategic missions (Gupta and Govindarajan, 1984). The choice of strategic mission signifies the organization’s intended trade-off between market share growth and the maximizing short-term earnings. A business that follows a build strategy aims to improve market share and competitive position, even though this may decrease short- term earnings or cash flow. This can only be achieved if the firm has some competitive superiority within the industry. Under a harvest strategy a firm strives to maximize short-term profit and cash flow rather than increase market share. A hold mission is often used by businesses to protect market share and competitive position, aiming to maintain market share while obtaining a reasonable return on investment. These firms often operate with a high market share in high growth industries. A divest strategy occurs when a business plans to cease operations. Integrating the strategy variables The range of strategic variables that have been used in research that studies the relationship between MCS and strategy can create confusion and may hamper the integration of research findings. To assist in integrating this research, the differences and similarities between the various strategy classifications can be considered. These differences can be viewed as related to scope and focus. For example, the typology of prospector vs defender has a broad scope, while the competitive positioning of cost leadership vs differentiation is much narrower. The entrepreneur vs conservative classification is focused on the extent of product innovation, while build vs harvest is based on the market share vs short-term profit trade-off. As illustrated in Figure 1, the strategies followed by particular business units can be described along three dimensions: typology, strategic mission and competitive position. When the detailed descriptions of these typologies and variables are reviewed common characteristics, particularly in relation to the degree of environmental uncertainty, are revealed, which leads to the configurations proposed in Figure 2.3 For example, a viable combination may be for prospectors to compete via differentiation and to pursue a build mission. However, it would seem inconsistent for a prospector to pursue differentiation and a harvest strategy. While further empirical research needs to be undertaken to validate the combinations proposed in this diagram, the classifications will be used in the following section to compare the findings of various empirical research studies.

Miles and Snow described prospectors as having difficulty implementing comprehensive planning systems due to the changing demands of their environment. Control systems may focus more on problem finding than problem solving, and flexible structures and processes may assist the organization to respond rapidly to environmental change and to create such change. However, coordination may be expensive and difficult due to overlapping project teams and shared information and resources. The use of broadly defined jobs and the lack of standard operating procedures may encourage innovation. Control may be decentralized and results oriented. Porter (1980) saw a differentiation strategy as also relying on control through coordination, rather than on formal controls, to encourage creativity and innovation. It has also been argued that firms that follow an entrepreneurial strategy (similar to prospectors) require a control system that signals when productivity and efficiency have fallen, to signal when innovation needs to be curbed (Miller & Freisen, 1982). These studies clearly suggest there is a level of consistency between the organizational and control characteristics of a defender and cost leader, and a prospector and differentiator, which further supports the proposed fit between these two dimensions of strategy.

Control systems and the level of competition. Before the 1980s there were no published research studies that examined explicitly the relationship between strategy and control systems. However, Khandwalla (1972) studied the relationship between control systems and competition, an aspect of the environment that may determine the nature of an organization’s strategy. He distinguished between three forms of competition - product, process and marketing - and found the more intense the level of competition, the greater was the reliance on formal control systems. In particular, he argued that intense product competition may require complex organizational forms, with departments for research and development, new product testing, and scanning for new markets; sophisticated control systems may play an integrative role. While the nature of strategy was not explicitly considered, organizations that face intense product competition are likely to be those that follow the strategies of a prospector or differentiator (Miles & Snow, 1978; Porter, 1980). However, the specific controls measured by Khandwalla - formal accounting controls such as standard costing, flexible budgeting, internal auditing, use of ROI and inventory control - are not those that might be expected to act as an integrative device in an innovative, product-focused organization, with an emphasis on flexibility and quick responses, and after-the- event control (Miles & Snow, 1978; Porter, 1980). Burns and Stalker (1961) suggested that innovation was more suited to unstructured and organic organizations, where there was less reliance on formal controls. Similarly, Thompson (1967) argued that innovation and administrative controls were not compatible. Khandwalla (1972) is notable in providing the first empirical evidence of the relationship between MCS and the level of competition. However, it contributes little to our knowledge of the relationships between MCS and strategy, and the fidings of this study are ambivalent, particularly when compared with subsequent research studies. A further limitation is the study’s focus on the use of controls, without considering controls were effective in supporting a particular strategy or level of competitiveness. 

Controls and diswetionaly decision making. 

Merchant (1985b) studied control systems, strategy and discretionary decision making in the divisions of a single company. Strategy was defined by managers within the company as rapid growth, selective growth, maintain or generate cash flow, and harvest. The controls studied extended beyond financial controls, to Include procedural and personnel controls. Merchant found that the controls used in businesses that followed a growth strategy were not noticeably different from the controls used under a maintain or selective growth strategy. When a rapid growth strategy was followed discretionary decisions were more highly affected by controls such as net income targets, head-count controls (especially hiring freezes) and the use of meetings where senior management gave directives. The findings of the study, in terms of relating MCS and business strategy are limited and Merchant acknowledges that his research was exploratory. No arguments were presented to support a conceptual relationship between growth strategies, control systems and discretionary decision making. While the link to other research on strategy and control systems is not strong, it should be recognized that at the time this study was written there was limited prior empirical research.

Strategy and cost control. 

There is some agreement among researchers that cost control is more important in firms following a defender- type strategy compared with the “opposite” prospector-type strategy. Porter (1980) suggested that tight cost controls were appropriate when following a cost leadership positioning. Miles and Snow (1978) argued that in defenders, control systems focus on cost objectives that are translated into specific operating goals and budgets. Efficiency and ongoing cost monitoring were more important to defenders, while prospectors were more results oriented. The findings of Miller and Friesen (1982) are more difficult to integrate with prior research as strategy was defined in terms of product innovation. However, their argument for the lack of sophisticated cost controls in entrepreneurs is consistent with Miles and Snow’s view of prospectors (and inconsistent with Khandwalla, 1972). Simons (1987a) is an empirical investigation of the relationship between MCS and strategy. However, many of the findings conflict with other research. First, Simons (1987a) found high performing prospectors placed importance on controls, such as forecasting data, tight budget goals and the careful monitoring of outputs, but gave little attention to cost control. Also, large high performing prospectors emphasized frequent reporting and the use of uniform control systems, which are modified when necessary. Simons (1987a) also found that control systems were used less intensively by defenders, particularly large defenders, compared with prospectors. In large defenders, high financial performance was negatively correlated with tight budget goals and the use of output monitoring. It was only in small defenders that tight budget goals were positively correlated with high performance. These findings are not consistent with those of Miles and Snow (1978) and Porter (1980). While Simons expressed “surprize” at his findings, particularly regarding defenders, he offered little explanation or speculation about the possible reasons. There are two aspects about Simons’ results that are puzzling. First, why were certain aspects of formal control systems considered important to prospectors, but used less intensively by defenders, particularly large defenders? Second, why should organizational size make a difference to the importance of controls? Small defenders found tight budget goals important, but large defenders did not. While we can cite the usual reasons for conflicting findings - different samples, different industries, empirical versus normative studies, national cultural differences - other interpretations are possible. Dent (1990) proposed several explanations for Simons’ findings. First, in prospectors control systems may restrict risk taking, particularly where authority for product development and market innovation is delegated.

Thus, control systems may balance the innovative excess encouraged by prospectors’ organizational arrangements (Miller & Freisen, 1982). Second, prospectors may rely on performance monitoring to encourage organizational learning in the face of high task or environmental uncertainty. Finally, financial controls may be the only way that the wide scope of a prospector’s activities can be captured. Also, defenders, being more stable organizations, may not require intense cost control, but may more effectively achieve efficiency using non-financial measures (Dent, 1990). A major limitation of Simons’ study (which may reflect the era in which it was undertaken) was the focus on financial controls. However, as non-financial controls were not considered by Simons (1987a) the above explanations remain speculative. In a later section of this paper, we will consider more contemporary ideas about strategy and control systems that may cast a different light on these issues. Performance evaluation and reward systems. Several contingency studies have focused on the relationship between strategy and performance evaluation and reward systems. In particular, the choice of subjective or objective approaches to rewarding performance has been researched. We will first consider the findings for companies following defender, cost leadership and harvest strategies. Simons (1987a) found that high performing defenders awarded bonuses for the achievement of budget targets (an objective measure). Govindarajan (1988) found similar results for high performing firms following a low cost strategy, as did Gupta (1987) for harvest and low cost strategies and Porter (1980) for cost leaders. Further, the reliance on long-run criteria and subjective bonuses hampered effectiveness in firms following a harvest mission (Govindarajan & Gupta, 1985). Thus, the research findings are consistent: objective performance evaluation and reward systems have been found to support defender-like strategies. In firms that follow prospector, differentiator and build strategies the evidence is also fairly consistent. Porter (1980) argued that subjective performance evaluation was appropriate for differentiators. This was supported by Govindarajan and Gupta (1985) for organizations following a build mission, and by Gupta (1987) for firms following a build and differentiation strategy. Govindarajan and Gupta (1985) also argued that as build strategies demand a long-term orientation, incentive bonuses should also be based on long-run criteria. (Interestingly, they did not find a strong relationship between the use of short-run criteria for bonuses and effectiveness for build or harvest firms.) The reliance on behavior controls by differentiators in the Govindarajan and Fisher (1990) study may imply that subjective bases are used for performance evaluation, as may the low emphasis on meeting budget targets in Govindarajan (1988). In contrast, Gupta and Govindarajan (1986) found that while subjective, rather than objective approaches to determining bonuses were more beneficial when there is a high degree of resource sharing between business units, resource sharing itself makes a greater contribution to effectiveness in cost leaders than in differentiators. Simons (1987a) and Miles and Snow (1978) did not specify the subjective or objective nature of performance evaluation systems for particular strategies. The apparent consistent findings regarding performance evaluation and reward systems for prospector-like strategies is not surprising, especially as high environmental uncertainty is usually associated with these strategies. In these situations it may be difficult to develop performance measures that accurately reflect managers’ performance. Also, the critical success factors associated with these strategies, such as new product development, innovation and research and development, are of a long-run nature and difficult to quantify objectively. Similarly, defender-like strategies usually operate within a low level of environmental uncertainty. Their limited and stable product range, and their focus on internal efficiency may allow performance levels and rewards to be specified with greater precision. The relationship between environmental uncertainty and performance evaluation is well researched (see Briers & Hirst (1990) for a review). For example, Gupta and Govindarajan (1984) confirmed that high performing firms facing high environmental uncertainty place greater reliance on subjective performance evaluation. While environmental uncertainty may partially explain the choice of a subjective or objective performance evaluation system, it should not be assumed that strategy is a surrogate for the environment (although it is probably highly correlated). Also, to date we have only imited knowledge of the nature of performance evaluation systems under different strategies. There is a range of questions that remain unanswered, which may be contingent on the strategic orientation of the firm. These include the appropriate mix of salary and non-salary components within rewards, the potential for linking rewards to both business unit performance and corporate performance, and the frequency of performance measurement and bonus payments. While the research reviewed in this paper only considered performance evaluation and rewards of senior managers, future research may

also consider non-managerial employees. The recent literature on balanced scorecards (Kaplan 81 Norton, 1992, 1993) and performance measurement hierarchies (Lynch & Cross, 1992) may stimulate future research agendas. Resource sharing and control systems. Govindarajan & Fisher (1990) studied cost leadership and differentiation strategies, the extent of resource sharing between strategic business units (SBUs) and the use of controls. Resource sharing refers to the sharing of functional resources by two or more SBUs within a single firm, and may include using common sales forces and common R&D facilities. They argued that the potential for synergistic benefits from resource sharing varies across strategic contexts, and the realization of these potential benefits depends on how effectively the linkages between SBUs are managed. In high performing cost leaders, Govindarajan and Fisher (1990) found that output controls (and not behavior controls) were combined with high resource sharing. However, this is not consistent with Miles and Snow (1978) who described the use of standard operating procedures by defenders, and Porter (1980) who argued that cost leaders may rely on frequent cost reports. To some extent, the interaction effect of resource sharing and controls could explain this apparent conflict. Also, Govindarajan and Fisher found that differentiators with high resource sharing relied on behavior controls (the continual monitoring of decisions and actions), which seems at odds with the entrepreneurial mode of prospectors and their reliance on subjective performance assessment (discussed in the previous section). However, it was found that where there was low resource sharing, output controls were used by effective differentiatars, but that the level of effectiveness was not as great as for SBUs with high resource sharing. Control systems theorists, such as Ouchi (1977) and Eisenhardt (1985) concluded that behavior controls are more suitable where there is high task programmability and where outcomes can be readily measured. This would seem to describe the situation facing defenders and cost leaders. As task programmability decreases and outcomes can still be clearly specified, greater reliance may be placed on output controls. This is not the situation usually faced by prospectors, as the innovative and spontaneous nature of their operations could preclude high task programmability, but the situation could still apply to defenders. Thus, the findings of Govindarajan and Fisher (1990) for differentiators conflict with Ouchi (1977). However, Ouchi (1977) also described a third situation that does seem to match the environment of prospectors - where there are neither programmable tasks nor measurable outcomes. In this situation socialization or clan controls might be appropriate. While Govindarajan and Fisher did not explicitly consider social controls, curiously, they did equate behavior controls with social controls when interpreting their findings. This is despite there being sufficient discussion in the literature to support the different nature of these two forms of control (Eisenhardt, 1985; Merchant, 1985a). Govindarajan and Fisher rely on agency theory to argue that output controls are effective in SBUs following a low cost strategy, and behavior controls in differentiators. However, their arguments are not convincing, given the specific information and operational needs of prospectors and differentiators. Operational control systems and strategy. A developing area of research interest is the relationship between control systems and manufacturing strategy. This topic has been covered in the professional literature with anecdotal case studies, and in the academic literature several normative papers have been published (see, for example, Nanni, Dixon and Vollman, 1992). However, there has been little empirical research that has studied explicitly MCS and specific manufacturing strategies. Notably, Daniel and Reitsperger (1991) studied the nature of the control systems that support particular quality strategies using two different approaches to managing quality. Under the economic conformance level model a cost minimizing quality level is achieved by balancing prevention and appraisal costs against internal and external failure costs. In these situations standard costing and the detailed recording of quality costs may be important. The zero defects model recognizes that the indirect costs of poor quality cannot be measured. Control may be achieved through continuous improvement of quality goals, the reduction in defective units and frequent feedback on quality performance to employees. Cost quantification may not be considered important (and may even be misleading), as achieving high quality is assumed to lead to lower costs. These findings are supported by Banker Potter and Schroeder (1993) who, while not formally researching strategy, examined the changes in performance reporting and control systems needed at the operational level to support an emphasis on increasing productivity and quality. In a related study, Daniel and Reitsperger (1992) compared the control systems of Japanese and US electronics manufacturers. They found that Japanese businesses were more likely to have modified their control systems to better focus employees on achieving higher production, lower costs and better quality than their US counterparts. While the nature of the firms’ strategy was not investigated, the findings of the study supported the need for MCS at the operations level to specifically support manufacturing strategies, using performance targets and feed-back information. These two papers are significant for several reasons. First, they examine the nature of the control system and a specific differentiation strategy (that of quality). Second, they consider how two different approaches to viewing the nature of quality can affect the choice of control system. Finally, control systems and strategy are considered at the operational level.

Conclusion.

The above research studies give us only limited knowledge about the forms of control systems that suit particular types of strategies. A common feature of these studies is the focus on intended business strategy; MCS are viewed as playing a supportive role within the rational strategy implementation process. However, as our knowledge in this area is limited, and sometimes ambiguous, there is clearly significant scope for further research studies to clarify some of the conflicts. Some methodological limitations of these empirical research studies are described in a later section.