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«Paul M. Collier Aston Business School, Aston University Accounting for Managers Accounting for Managers: Interpreting accounting information for ...»

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organizational objectives are often vague, ambiguous and change with time... measures of achievement are possible only in correspondingly vague and often subjective terms... predictive models of organizational behaviour are partial and unreliable, and... different models may be held by different participants... the ability to act is highly constrained for most groups of participants, including the so-called ‘controllers’. (p. 241) Based on work by Berry et al. (1995), Emmanuel et al. (1990) presented a simplified diagram of the control process as a regulator. This is contained in Figure 4.4.

This model differs from that by Anthony as it emphasizes the importance for control of a predictive model, which is necessary for both feedback (reactive) and feedforward (anticipatory) modes of control. The difficulty with each form of control is the reliability of the predictive model. A standard, such as a budget, requires a predictive model of the organization and how it interacts with its environment.

Otley and Berry (1980) defined four types of control:

1 First-order control adjusts system inputs and causes behaviour to alter.

2 Second-order control alters system objectives or the standards to be attained.

–  –  –

Figure 4.4 Necessary conditions for control Reprinted from Emmanuel, C.

, Otley, D. and Merchant, K. (1990). Accounting for Management Control.

(2nd edn). London: Chapman & Hall.


3 Internal learning amends the predictive model on the basis of past experience and the measurement and communication processes associated with it.

4 Systemic learning or adaptation changes the nature of the system itself – inputs, outputs and predictive models.

The problem of a predictive model is in understanding the complex and ambiguous relationship between means and ends, or inputs and outputs. Ouchi (1977) argued that there were ‘only two phenomena which can be observed, monitored, and counted: behavior and the outputs which result from behavior’ (p. 97).

To apply behaviour control, organizations need agreement or knowledge about means–ends relationships. To apply output control, a valid and reliable measure of the desired outputs must be available. Ouchi argued that as organizations grow larger and hierarchy increases, there is a shift from behaviour to output control.

Management planning and control systems and managementaccounting

Daft and Macintosh (1984) described six components of management control systems: strategic plan, long-range plan, annual operating budget, periodic statistical reports, performance appraisal, and policies and procedures. Management accounting should be understood in this broader context of management control. Emmanuel et al. (1990) believed that management accounting was important because it represents ‘one of the few integrative mechanisms capable of summarizing the effect of an organization’s actions in quantitative terms’ (p. 4). Because management information can be expressed in monetary terms, it can be aggregated across time and diverse organizational units and provides a means of integrating activities.

Otley and Berry (1994) described how in management control:

accounting information provides a window through which the real activities of the organization may be monitored, but it should be noted also that other windows are used that do not rely upon accounting information. (p. 46) Otley (1994) called for a wider view of management control, with less emphasis on accounting-based controls. Criticizing Anthony’s model of planning and control, Otley argued that ‘[t]he split between strategic planning, management control and operational control, which was always tendentious, now becomes untenable’ (p. 292).

Otley claimed that there was widespread agreement that undue emphasis was given to financial controls rather than to a more ‘balanced scorecard’ approach, hence the increasing importance given to non-financial (or multidimensional) performance management in the study of management control systems.

Otley et al. (1995) argued for expanding management control beyond accounting, distinguishing financial control from management control, the latter as:


a general management function concerned with the achievement of overall organizational aims and objectives... management control is concerned with looking after the overall business with money being used as a convenient measure of a variety of other more complex dimensions, not as an end in itself. (p. S33) Otley (1999) proposed a framework for management control systems around five central issues: objectives, strategies and plans, target-setting, incentive and reward structures, and information feedback loops. The framework was tested against three major systems of organizational control: budgeting, economic value added (EVA) and the Balanced Scorecard. Otley concluded that performance management provides an important integrating framework.

Non-financial performance measurement The limitations of financial measures were identified most clearly by Johnson and Kaplan (1987), who argued that there was an excessive focus on short-term financial performance.

They commented:

Managers discovered that profits could be ‘earned’ not just by selling more or producing for less, but also by engaging in a variety of non-productive activities: exploiting accounting conventions, engaging in financial entrepreneurship, and reducing discretionary expenditures. (p. 197)

such as:

R&D, promotion, distribution, quality improvement, applications engineering, human resources, and customer relations – all of which, of course, are vital to a company’s long-term performance. The immediate effect of such reductions is to boost reported profitability, but at the expense of sacrificing the company’s long-term competitive position. (p. 201) Johnson and Kaplan (1987) emphasized the importance of non-financial indicators,


Short-term financial measures will have to be replaced by a variety of nonnancial indicators that provide better targets and predictors for the firm’s long-term profitability goals, signifying this as a return to the operationsbased measures that were the origin of management accounting systems.

(p. 259) The development of the Balanced Scorecard (Kaplan and Norton, 1992; 1993; 1996;

2001) has received extensive coverage in the business press. It presents four different perspectives and complements traditional financial indicators with measures of performance for customers, internal processes and innovation/improvement.


–  –  –

Figure 4.5 Translating vision and strategy: four perspectives Reprinted by permission of Harvard Business Review.

From ‘Using the Balanced Scorecard as a strategic management system’ by R. S. Kaplan and D. P. Norton, Jan–Feb 1996. Copyright 1996 by the Harvard Business School Publishing Corporation; all rights reserved.

These measures are grounded in an organization’s strategic objectives and competitive demands. The Balanced Scorecard is shown in Figure 4.5.

Kaplan and Norton (1996) argued that the Scorecard provided the ability to link

a company’s long-term strategy with its short-term actions, emphasizing that:

meeting short-term financial targets should not constitute satisfactory performance when other measures indicate that the long-term strategy is either not working or not being implemented well. (p. 80) The Balanced Scorecard took as a starting point the goal to generate long-term economic value, which required other than financial measures as drivers of

long-term performance and growth. Kaplan (1994) described how:

the new concepts and theories emerged from attempting to document, understand and subsequently influence the management accounting practices at innovating organizations. (p. 247) There had been earlier attempts at non-financial performance measurement.

Eccles (1991) argued that ‘income-based financial figures are better at measuring the consequences of yesterday’s decisions than they are at indicating tomorrow’s performance’. Meyer (1994) proposed a ‘dashboard’ in contrast to Kaplan and


Norton’s Balanced Scorecard. He argued that traditional performance measurement systems don’t work as they track what happens within not across functions.

The few cross-functional ‘results measures’ are financial. In contrast, ‘process measures’ monitor the activities that produce given results.

Innes (1996) described the tableaux de bord that had been developed by ‘subdepartments’ in French factories. These comprise non-financial measures that managers identify as critical to success and that are developed and monitored locally, rather than being part of the formal reporting process.

There have been other efforts at Balanced Scorecard-type models, such as the Performance Pyramid of Lynch and Cross (1991). Although the initial concern of most Balanced Scorecard-type systems was with manufacturing businesses, Fitzgerald et al. (1991) emphasized the needs of service businesses and developed a Results and Determinants Framework containing six performance dimensions divided into two different categories. Competitiveness and financial performance as ‘ends’ reflected the success of the chosen strategy, while the others, the ‘means’, determined competitive success. They applied this model to three ‘service archetypes’ – professional services, service shops and mass services – using the number of customers handled as the differentiating factor. Figure 4.6 shows the Results and Determinants Framework.

A further model, reflected in the practitioner rather than the academic literature, is the ‘Business Excellence’ model developed by the European Foundation [Image not available in this electronic edtion.] Figure 4.6 Results and Determinants Framework Reprinted from Fitzgerald, L., Johnston, R., Brignall, S., Silvestro, R. and Voss, C. (1991). Performance Measurement in Service Businesses. London: Chartered Institute of Management Accountants.


for Quality Management (EFQM). This is an integrated self-assessment tool comprising nine elements that are weighted and divided into two groups: results and enabling criteria. The results criteria are business results, people satisfaction, customer satisfaction and impact on society. The enablers are processes, people management, policy and strategy, resources and leadership.

Another model used in industry is the ISO 9000 quality model, while in the UK Chartermark is used in the public sector and Investors in People is used for human resource and training and development strategies. All require external assessment.

The difficulty with performance measurement systems is that multiple measures are a result of multiple stakeholders inside and outside the organization. There are inherent difficulties in the predictive model that a business explicitly or implicitly uses to obtain resources and implement processes in order to deliver product/services to customers.

The Performance Prism was developed at Cranfield University by Neely et al.

(2002). It differs from other non-financial performance measurement systems in that it considers all stakeholders in the business, such as regulatory agencies, pressure groups and suppliers. This ensures that the performance measurement system used presents a balanced picture of business performance. It also differs from Balanced Scorecard-type systems in that the performance measures are not developed from strategy, as Kaplan and Norton (2001) suggest, but informs management whether the business is going in the strategic direction that is intended.

A research study by the Chartered Institute of Management Accountants (1993) found that most companies tend to make decisions primarily on financial monitors of performance. Boards, financiers and investors place overwhelming reliance – often exclusively – on financial indicators such as profit, turnover, cash flow and return on capital. Managers mostly support the view that non-financial performance information should only be used internally. There is no optimal mix of financial and non-financial performance measures and the non-financial indicators used are not fixed. The report argued that performance measures need to mirror operational complexity, but must be kept simple to be understood.

In order to compete in a global economy, manufacturers have had to move towards higher quality, shorter cycle times, smaller batch sizes, greater variety in product mix and cost reduction. The development of new manufacturing philosophies such as computer integrated manufacturing (CIM), flexible manufacturing systems (FMS), just-in-time (JIT), optimized production technology (OPT) and total quality management (TQM) has shifted the balance from financial to non-financial performance measurement.

However, Sinclair and Zairi (1995b) argued that performance measurement has been dominated by management control systems that are focused on ‘control’ rather than ‘improvement’. They saw management accounting and financial performance as a limiting constraint rather than a tool for managing continuous improvement. Sinclair and Zairi (1995a) undertook a survey of performance measurement in companies implementing TQM and found that despite the aims of TQM being communicated to managers, performance measurement systems were inappropriate.


Research suggests that the management control paradigm may still be dominated by management accounting and that non-financial performance measurement is isolated from, rather than integrated with, management accounting.

Despite the proliferation of non-financial measures, many remain rooted in shortterm financial quantification.

Brignall and Ballantine (1996) described the concept and history of multidimensional performance measurement (PM):

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