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PERFORMANCE
MEASUREMENTS—DESIGNING THE GUIDANCE SYSTEM FOR YOUR ORGANIZATION INTRODUCTION Your business is changing. JIT, TQM, Reengineering, Information Technology, Teams, Time Based Competition, the supply chain and the decline of the Command/Control organization structure are just some of the changes taking place. The critical success factor is knowledge, not physical work. Competitive advantage can no longer be perpetually and automatically maintained. In many industries continuous change and improvement is no longer an option, it is a way of life. But what are we measuring? Often organizations are measuring the same things they were 10, 20 and even 50 years ago. Most organizations are still using a cost accounting structure developed in the 1920’s. Many are still focusing their measurement efforts on direct labor, even though it is typically less than 10% of product cost and the key to business success is no longer "make and move", but knowledge work. Many businesses still measure function (e.g. purchasing department) when the focus of the business is cross functional process (e.g. material acquisition process). Steps have been taken to address these shortcomings—quality measures, cycle time measures and cross functional process performance measures. Activity Based Costing models that mirror the business value chain have been developed and used. But many of these are merely measures added to existing measures without a consideration of the effect on the organization. A few companies on the "cutting edge" have developed Balanced Scorecard systems whose design is driven by business strategy and implementation is performed in parallel with other systems initiatives. This presentation will discuss the multiple roles a performance measurement system plays in today’s organization—control, information and motivation. It will also discuss the various dimensions in which a performance measurement system must work effectively and their interrelationship. The presentation will then describe some of the pitfalls of a poorly designed measurement system and how to avoid them. Finally, it will present a generic framework for a performance measurement system that can help the attendee evaluate and validate the organization’s present measurement system and assist in designing a more effective one. Examples and graphical representations of multidimensional performance measurement will be shown. PROBLEMS WITH TRADITIONAL PERFORMANCE MEASUREMENT Why has performance measurement system development lagged behind business process system development? Why did it not parallel the changes in the business organization it intended to measure? There are many reasons, some or all of which apply to organizations whose measurement system has not kept up. Among them are:
To affect organizational behavior, the factors in the organization that create and encourage that behavior must be changed. As Shoshana Zuboff (1988) states "...if managers are to alter their behavior, then methods of evaluation and reward that encourage them to do so must be in place." PERFORMANCE MEASUREMENT AS A SYSTEM To improve the effectiveness of performance measurement, it must be defined and developed as a system, not just a collection of measures the organization has historically used to control individual behavior. The characteristics of a performance measurement system are that it must be:
PURPOSE OF PERFORMANCE MEASUREMENT Performance measurement has several purposes in the business organization, both internal and external. Performance measurement for external purposes is an extensive topic in itself and outside the scope of this paper. In a supply chain, internal performance measures may extend beyond the traditional boundaries of the organization. Internal purposes can be further broken into three general categories with some overlap, as shown below:
CHARACTERISTICS OF MEASUREMENT All effective measurement systems have a multitude of characteristics. These characteristics apply in varying degree to each measurement, but must be taken into account if a measurement system is to have maximum value. The characteristics are:
In a continuous change environment, vector measures take on increasing importance since the focus is no longer on where the organization is (static), but the direction in which organizational performance is heading (vector).
Statistical measures and hypothesis testing can determine whether or not a particular value or set of sample values of a variable are within the same probability distribution as an expected value. Relative and statistical measures can be combined in powerful ways. For example, a series of inventory cycle counts can be taken and compared to a similar series from the previous year. If it can be shown that these two samples came from different probability distributions, it can be inferred that inventory accuracy is improving (or deteriorating) relative to a previously measured baseline and a pre-established goal.
Examples of unintended consequences include: 1) end of the month push to meet sales goals, 2) cutting activities vital in the long term to make short term profit goals or meet budgets, 3) setting goals that are easily achievable (…and maximize the bonus) and 4) focusing on hard number cost goals while neglecting the softer measures of quality and service goals. Unintended consequences are more likely to occur when measures are: 1) less direct, 2) static, rather than vector, 3) singular rather than combinations of measures, 4) statistical expected values treated as hard number measures and 5) used for command/control of individuals or groups rather than information which can be used to adjust the process. Performance measurement systems that have certain characteristics run the risk of not measuring anything meaningful and leading to unintended consequences that can interfere with good performance. Most at risk are those performance measurement systems that focus on: 1) precise, hard numbers that are used to measure specific performance to specific indirect parameters, rather than: 2) using vector, relative and statistical measurements combined with management judgment. In short, type 1) above is the very performance measurement system many companies have carried over from their hierarchical command/control days and are now trying to use to coax quality, participative, continuous improvement from their organization. It is not hard to understand why many organizations meet what seems like intentional resistance to organizational change and continuous improvement initiatives, both internally and within the supply chain. PERFORMANCE MEASUREMENT AND THE BUSINESS PROCESS As mentioned above, performance measurement is still a stepchild of financial measurement in many organizations. Metrics are added haphazardly as needed to clarify or control without regard for integration with organization goals and objectives. Many organizations still believe that if each individual and function is measured to some quantifiable standard, the sum of the results will be organizational effectiveness. Performance measurement system characteristics were discussed above. Here are some points of integration:
--When strategy or goals change. --When systems or processes change. --When a measurements becomes dysfunctional (i.e. exhibits unintended consequences). Variables measured, measurement methodology and measurement goals must all be reviewed. BEHAVIOR SPACE MEASUREMENT How does a measurement system design fulfill all these criteria? An important attempt has been made by Kaplan and Norton (1996) in the Balanced Scorecard approach. It is a comprehensive, systematic methodology that measures groups and individuals on a variety of performance metrics, usually tied to corporate goals. However, Balanced Scorecard uses a weighted average method to reduce a variety of measures to a performance index. This leads groups and employees to "perform to maximize the index", often with little regard for the desired performance. This occurs because the measurable factors that make up the index are not substitutable for one another. A more effective method is to define a "Behavior Space" bounded by several measurement dimensions that define individual, department and organizational performance. Although this is somewhat more complex than the index, it is well within the ability of most systems to collect, analyze and report the information involved. The increase in usable information, both to the individual and to the organization more than offsets any additional cost and effort required. The example shown below reflects a performance measurement framework for only two levels in the organization--the Operations Manager or facility level (see Table One) and the Supervisory or department level (see Table Two). A comprehensive system would encompass all levels of the organization, from business planning to shop floor control. The model contains six attributes to be measured:
Although other organizations might have additional significant attributes to their business processes, these are probably basic to all. Also, the critical success factors, goals and metrics selected are representational and not intended to be appropriate for all situations. Table One
Table Two
In using the framework to measure performance, both static and vector characteristics of all measurement are tracked and compared to both Short Term and Long Term goals. Use of the system is primarily informational rather than control oriented or punitive. As such it is used to identify 1) problem areas such as lack of resources and/or training and 2) process improvement opportunities for continuous improvement teams. The system must be constantly re-evaluated by management to insure that it 1) still represents and supports the strategy of the organization, 2) provides correct and adequate information to manage and improve the business and 3) is not contributing, directly or indirectly, to the creation of unintended consequences or waste. REPORTING BEHAVIOR SPACE PERFORMANCE Rather than reducing the performance report to an index which requires judgmental weighting and makes the measurement even more indirect, a graphical representation provides a more satisfying and accurate method for the following reasons:
Below, Table Three shows actual performance against the managerial measures shown in Table One followed by a set of graphical representations of the performance against goals. The percent variance is calculated by dividing the value over or under the short term goal by the range between the short term and long term goals. For example, for the Cost measure: (17% - 10%) / (30% - 10%) = +35% Variance from short term goal. TABLE THREE
Figure One shows the table in graphical form. Expected results, the Expected Behavior Space, lies between the inner short term goal boundary and the outer long term goal boundary. The black area represents measures where performance exceeded short term goals and gray areas represent measures where performance fell short. The graph clearly indicates the employee’s performance profile and shows where and how employee resources need to be redirected. FIGURE ONE
The above representation has several advantages over the weighted average index that is often used in the Balanced Scorecard approach:
Figure Two shows the vector component of the Quality metric. It indicates performance against a constantly increasing short term goal and the gap that exists between the current short term goal and the long term goal. The Figure Two graphic would exist for each of the six metrics that defines the Behavior Space. FIGURE TWO
This is only a sample of the information that can be provided using the Behavior Space Measurement model. Each individual and any team with goals can be measured. Additional formats and methodologies have been developed to incorporate indices, where appropriate, that accurately reflect actual performance results against goals. CONCLUSION Designing, developing and implementing performance measurement as a system, integrated into and changing with the business process is a critical challenge for organizations that hope to move into the next millennium successfully. Traditional measures are inadequate. While the Balanced Scorecard approach is a giant step forward, it too is flawed and must be improved. Multi dimensional Behavior Space performance measurement systems move beyond Balanced Scorecard to a more robust system tied to business strategies and critical success factors that will allow the organization to attain and maintain world class performance. SELECTED BIBLIOGRAPHY Brown, Mark Graham, (1989) Keeping Score, Quality Resources, New York. Case, John, (1995) Open Book Management--The Coming Business Revolution, Harper Business School Press, New York. Drucker, Peter F., (1973) Management Tasks, Responsibilities, Practices, Harper & Row, New York. Drucker, Peter F., (1992) Managing for the Future, Truman Talley Books/Dutton, New York. Drucker, Peter F., "The Information Executives Truly Need", Harvard Business Review, January/February 1995. Hamel, Gary and C.K. Prahalad, (1994) Competing for the Future, Harvard Business School Press, Cambridge, MA. Kaplan, Robert and David Norton, (1996) The Balanced Scorecard, Harvard Business School Press, Boston. Maskell, Brian, (1991) Performance Measurement for World Class Manufacturing, Productivity Press, Inc., Cambridge MA. Maskell, Brian, (1996) Making the Numbers Count, Productivity Press, Portland OR. Tarr, James D., "Developing Performance Measurement Systems that Support Continuous Improvement Goals", Hospital Material Management Quarterly, November, 1995. Tarr, James D., "Performance Measurement for a Continuous Improvement Strategy", Hospital Material Management Quarterly, November, 1996. Zuboff, Shoshana, (1988) In the Age of the Smart Machine, Basic Books, Inc., New York.
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[Ellen
Kane, CPIM] [James Tarr, CPIM] [Doug
Howardell, CPIM]
The ACA Group © The ACA Group 2004
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