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Measuring Corporate Effectiveness

management, business, effectiveness, corporate effectiveness, planning, directing, controlling, staffing, managing

To assess organizational effectiveness, one must find outcome measures that truly reflect what an organization is doing and are as objective as possible. Although this may be self evident it is surprising how frequently organizations take stock of themselves by saying something like ‘well it fells like we’re doing okay’.

The organization then must develop some model of what constitutes effectiveness for it. From that model, it needs an explicit list of the actual decisions for which effectiveness data will be used. Campbell indicates six kinds of decisions for which organizational outcome data could be used. All expect the last address practical problems that organizations face, yet, only the first and last have received any research attention:
1.Determination of whether some part of the organization is in a ‘good’ or ‘bad’ state. Among the possible outcome measures are profitability turnover and frequency of complaints.
2.Determination of why the system is in that particular state. In other words what causes profitability turnover or complaints?
3.Decisions about plans that will change the system. What can be done to improve profitability, turnover rates or the level of complaints?
4.Evaluation of an organizational change. Did the change provide the expected results?
5.Comparison of organizations for lawmaking or public policy purposes. For example, the Bureau of Labor Statistics collects labor force data to help determine affirmative action and other laws.
6.Identification of the antecedents of effectiveness. This is the typical reason that scientists want effective data; they wish to determine what factors can predict effectiveness.

Bear in mind that effectiveness data are often used to serve different and conflicting purposes, as when personal performance data are collected to inform the organization about training needs and performance appraisal. A single set of data cannot serve these two masters. Data used to determine training needs should point out deficiencies in performance on the other hand it is certainly in the performer’s best interest to provide data supporting the view of superior performance when it comes to performance appraisal. The kinds of outcomes or criteria data collected then should be determined by the kinds of decisions that data will be used to help make and how they will be used. Data used to find out what went or may have gone wrong procedurally or operationally should be independent of data used to identify how well things are done.

A number of investigations have used single measures of organizational outcomes such as overall effectiveness, readiness, productivity, stability, absenteeism, and so on. Three problems are inherent in this approach. First it is virtually impossible to capture the essence of an organization’s performance in a single measure. Second, these outcome measures may reflect researchers’ bias. If an organization sets high productivity as a goal it is worth measuring. But for a researcher to state that high productivity is a goal and then measure it is to mislead. Third, though many measures are thought to contribute to effectiveness, no one knows exactly how. Single measure studies are less complete in assessing this relatively amorphous construct than are ‘multimeasure’ studies.

One might suspect that a number of variables are interrelated and have a complementary relationship to effectiveness. If so one design effectiveness studies that simultaneously assess these many variables. The specific variables chosen would depend on the specific goals of the organization under scrutiny and the researcher’s hypotheses about the connections among the variables.

Although we know that there appears to be no link between effectiveness and corporate social responsibility, various ways to measure the latter can be found elsewhere. Managers might select from any arbitrary list of factors and add to it criteria that seem important in their organizations, or use it as a springboard for generating a completely different list. A manager with a systems orientation will emphasize different factors than one with a goal perspective. The astute manager combines the two approaches in constructing an assessment program.

In using the final list, one should be careful not to assume that criteria, like turnover, have only one meaning. In one setting turnover may reflect poor organizational performance, whereas in another it may be functional to the organization. A second caution is to fight the tendency search for ‘objective’ measures of things. Economists engage in this search every day. Generally, this task is probably doomed to failure. Although conventional wisdom says that objectivity is good, what we think are objective criteria are simply subjective criteria once removed.
Published: 2007-04-14
Author: Martin Hahn

About the author or the publisher
Martin Hahn PhD has received his education and degrees in Europe in organizational/industrial sociology. He grew up in South-East Asia and moved to Europe to get his tertiary education and gain experience in the fields of scientific research, radio journalism, and management consulting.

After living in Europe for 12 years, he moved to South-East again and has worked for the last 12 years as a management consultant, university lecturer, corporate trainer, and international school administrator

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