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Organizational Linkages: Understanding the Productivity Paradox (1994)

Chapter: 7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX

« Previous: 6 THE INFLUENCE OF ORGANIZATIONAL LINKAGES AND MEASUREMENT PRACTICES ON PRODUCTIVITY AND MANAGEMENT
Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
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7
Decomposing the Productivity Linkages Paradox

Robert D. Pritchard

The productivity paradox can be stated as follows: How can improvements in performance that occur at one level of analysis seem to disappear when performance is measured at broader levels of analysis?

Many interventions developed by behavioral science and the more technological disciplines are geared to improving the performance of individuals and groups. Those disciplines have frequently been satisfied with claiming success for an intervention when it can be shown that measures of the performance of the users have improved. Thus, if a group-based intervention shows that group output has improved, the claim is made that the intervention will help organizations function better. The assumption is that if the group performs better, the organization will function better.

The productivity paradox calls this assumption into question. Indeed, it calls into question the very foundation of much of the work done to improve organizational functioning. Typically, the ultimate justification for work in such areas as personnel selection, training, equipment design, motivation, task design, group structure, and feedback systems is that it will help the organization function better. The paradox suggests the possibility that "successful" interventions can actually have no effect on organizational functioning in that the positive effects of the intervention are somehow being absorbed or negated somewhere in the organization.

The panel's focus on organizational linkages is based on the premise

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

that to understand why the paradox occurs, one must look to the linkages between the levels of analysis. If performance improves at one level but does not show up in the next, there is something about the linkage between the levels that is causing the disappearance of the affect. Understanding the linkages between levels of analysis can lead to a much better translation of improvements at lower levels in the organization into improvements at higher levels in the organization. In other words, if the design and evaluation of improvement interventions are grounded in an understanding of the linkages and their effects, they will have a more positive impact on overall organizational performance.

LINKAGES DEFINED

An organizational linkage occurs when the outputs from one organizational subsystem are combined with the outputs of another subsystem into broader outputs. Consider the example of a small manufacturing firm of the type exemplified in Figure 7-1. The firm has three levels of analysis above the individual: the unit, the division, and the total organization. The firm comprises a production division, a marketing division, and such other divisions as personnel, maintenance, purchasing, and accounting. The production division includes a design unit and a manufacturing unit. All units and divisions are managed by a top management group. If a new product is being considered, top management makes the decision to allocate resources to develop the new product. The design unit develops the design for the product, the manufacturing unit makes it, and the marketing division sells it.

This organization can be thought of as a set of linked subsystems. There are several levels of subsystems in this organization. According to Katz and Kahn (1978) and Naylor et al. (1980), as well as Chapters

FIGURE 7-1 Example of an organizational structure.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
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FIGURE 7-2 Organizational subsystem structure. NOTE: I = inputs; P = processing of inputs; O = outputs.

4-6, a subsystem has inputs, it does processing of some sort with those inputs, and it generates outputs. The individuals in each unit are themselves systems that become subsystems for the broader organization. This is depicted graphically in Figure 7-2, which shows the production division from the example above. At the bottom of the figure are the individuals. These individuals have inputs (I) in the form of materials, equipment, training, information, and so on. The individuals process (P) the inputs to produce outputs (O). An individual in the design unit might produce the output of an idea for one aspect of the new product's design.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

The design unit is also a system in itself. An important part of its inputs is the outputs produced by the individual. This is shown in the figure by the line going from the outputs of the individuals to the inputs of the design unit. These and other inputs are processed by the design unit, which produces outputs in the form of designs for the product.

The design unit is also a subsystem in the production division. The outputs of the design unit are combined with the outputs of the manufacturing unit to be inputs to the production division. Finally, there is the entire organization as a system. One major source of its inputs is the outputs of the production division. Thus, the organization can be considered as a series of related systems from the individual to the entire organization. The outputs of the more molecular subsystems become inputs for the next-level system.

To return to the definition, a linkage occurs when the outputs of one subsystem are combined with the outputs of another subsystem into the outputs of broader organizational units. In the example, a linkage occurs when the outputs of the individuals must be combined to produce the inputs the design unit uses to produce a new product design. Another linkage occurs when the outputs of the design unit must be combined with those of the manufacturing unit to produce a product of sufficient quality to meet customer needs. Finally, a linkage occurs when the outputs of the production division must be combined with outputs of other parts of the organization to form the outputs of the total organizational system.

It is important to recognize that this definition indicates that what is combined in a linkage is the outputs of a subsystem. It is the outputs that are combined with other subsystems' outputs to generate broader organizational outputs. The refrigerator is made by combining compressors with electric motors and painted panels. It is not outputs relative to inputs (efficiency) or outputs related to expectations (effectiveness) that are being combined in the linkage. While one might measure efficiency, effectiveness, or one of the other aspects of performance discussed in Chapter 6 and aggregate it across organizational levels, that is a measure of organizational functioning, not what is being combined across a linkage.

In order to understand why the productivity paradox occurs, the paradox must be decomposed. In order to decompose it, the factors that could produce it must be examined. Many of the factors that could produce it have been discussed in earlier chapters. In Chapter 3, for example, Goodman and his colleagues identified a series of intra-and intertask factors that could produce the paradox.

My approach in this chapter is to break down the possible factors

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

into three groups. The first group contains structural characteristics. These factors are fairly permanent organizational characteristics that by their very nature would produce the paradox. The second group involves side effects from organizational interventions that could reduce or eliminate the positive effects of an intervention. The third group comprises measurement issues. The first two groups of factors have been discussed in earlier chapters and thus are only touched on briefly here for the sake of completeness.

Structural Factors

Structural factors are characteristics of the organization itself that could produce the paradox. Time lag is one such factor. Because of the structure of tasks in an organization, improvements in one subsystem sometimes take considerable time to show up in the combined outputs of the broader system. Other structural factors are slack, bottlenecks in the availability of needed inputs, the centrality of the task to the overall functioning of the organization, and the degree of interdependence of people and subsystems in producing the output. (See Chapters 24 for discussions of structural factors.)

Structural factors have two important things in common. First, they are natural and unavoidable aspects of organizational functioning. Second, they all reduce the one-to-one correspondence between the outputs of one subsystem and the outputs of a broader subsystem. That is, they will in and of themselves produce data that look like the productivity paradox. Thus, to the extent that the paradox is caused by structural factors, there is no real paradox. This leads to the following hypothesis:

  • The greater the presence of structural factors that naturally reduce the one-to-one correspondence between the outputs of subsystems that combine their outputs, the greater the likelihood of the appearance of a productivity paradox.

Intervention Side Effects

The second group of effects that could produce the paradox consists of unintended consequences of the intervention. It could be that direct measures of the effects of an intervention indicate improvement, but other effects of the intervention have a negative consequence at a broader level of analysis.

There are several types of such side effects. One type occurs when the intervention changes the focus of the effort from one unit of analy

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

sis to another. For example, giving each person is a unit a personal computer could result in people working individually rather than in groups. If the task for the unit requires high interdependence if it is to be done effectively, the shift from group to individual activity could decrease the combined, integrated output of the group while increasing the output of each individual. Another type of side effect is that the intervention could lead to changes in communication patterns. The new technology or work process could result in changes in the work structure that would disrupt a well-established informal communication pattern. It might take considerable time to reestablish a new pattern that is as efficient as the old one. Thus, although some output measures increase due to the changed technology, the decrease in communication effectiveness could decrease the unit's overall output.

These and other unintended side effects were discussed in Chapters 24. The important thing to note for the purposes of this chapter is that this class of factors exists and can be part of the paradox. Unintended side effects can produce the paradox in that performance can improve in one aspect of the work, but decreases that occur in other aspects of the work can eliminate the positive effects when the aggregation to a higher level of analysis occurs.

This leads to the following hypothesis:

  • To the extent that unintended negative side effects of a successful intervention occur, they will reduce the overall output of the subsystem and thereby produce the appearance of a productivity paradox.

Measurement Issues

The third group of factors that can explain the paradox involves measurement issues. A major point in this chapter is that measurement issues are a critical key to decomposing the productivity paradox. There are two classes of measurement issues. The first comprises issues that are natural phenomena in organizations, and although they should be recognized and understood, they are not a cause for particular concern. The second class of measurement issues comes to the fore when there are actual errors or conflicts in the measurement of organizational performance. This class of measurement issues is much more critical to organizational functioning than the first class and much more problematic for decomposing the productivity paradox. In the next two sections, I examine each class of measurement issues in detail.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

MEASUREMENT ISSUES: NATURAL PHENOMENA

Different Measurement Purposes

Organizational performance is measured in different ways for different purposes. This is true whether what is being measured is productivity, effectiveness, efficiency, or any other aspect of performance. There are five major purposes in measuring organizational performance, each of which has very different implications for what is measured (Pritchard, 1992).

The first purpose of measuring is to compare large aggregations of organizations to each other. Examples would be comparing the national economies of the United States and Japan and comparing the health care and computer industries. This type of performance measurement may be used by government agencies in determining how to control monetary policy, by government officials who are negotiating trade agreements with other countries, or by researchers studying broad organizational trends. A typical measure used for this purpose is price-deflated gross national product divided by the number of worker hours used (e.g., Kendrick, 1984; Mahoney, 1988).

The second purpose of measuring is to evaluate the overall performance of individual organizations for comparison with other organizations or with some standard. In this type of measurement, yearly sales figures, profit and loss margins, price/earnings ratios, and percentages of market share would typically be used. Performance measurement of this type might be used by individual investors to determine where to place their investment dollars.

The third purpose of measuring is for use as a management information system. Here, the focus is on a single organization, and the measurement deals with the functioning of the human-technological system. The question to be answered is how the entire organization or major parts of it are functioning, and whether that functioning is improving or declining. This type of measurement is used by upper management to determine major resource allocations, long-range goals, strategic plans, and the like.

The fourth purpose of measuring is to control parts of the organization. Although this type of measurement is often overlooked (Weiss, 1989), the control of the movement and timing of material resources and products is quite important to the efficiency of an organization. Under this heading are included such activities as production engineering and scheduling, quality control, materials distribution and management, and inventory control. The goals of this type of measurement include

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

identifying whether problems are developing and assessing the effect of changes made in operations.

The fifth purpose of measuring is for use as a motivational tool (e.g., Algera, 1989). The objective is to improve performance by encouraging behavioral changes in individuals. The assumption underlying this type of measurement is that the human resources of an organization can have a significant impact on the organization's performance. In other words, personnel can exert more effort, be more persistent in their efforts, and spend their efforts in more optimal ways, thereby working more efficiently and effectively.

Although the last three purposes appear to be somewhat similar, there are important differences. Each measures performance in a single organization, but they focus on different things and at different levels of the organization. The management information system is concerned with the overall functioning of the organization or its major subsystems and deals with macro measures, such as the profitability of the total organization or the contribution of different units to some type of overall effectiveness. The measurement information is rarely given to lower-level personnel in the form of feedback. Data gathering for the control purpose is typically done on smaller-sized organizational units than for the management information system, and it uses less macro measures, such as the flow of resources to various units and how well work is being scheduled. In addition, it does not attempt to separate the effects due to personnel from the effects due to technology. Measurement for motivation is concerned with the performance of individuals or work groups and gathers data on the accomplishment of specific work objectives. It is done, ideally, so that the effects due to personnel can be separated from the effects due to the technology, and the results are typically given to unit personnel in the form of feedback.

Different Measurement Purposes Require Different Measures

What is most critical for the discussion here is that measuring for different purposes involves measuring different things. As one moves from measuring for motivational purposes to measuring the total organization, new causal factors come into play that will affect the values produced by the resulting measurement. This is illustrated in Figure 7-3. The middle section of the figure represents the transformation of outputs that is made from individual to unit, to division, to total organization. As noted above, the outputs of the more molecular levels become the inputs of the more molar levels. However, other inputs are added at each level in addition to the outputs of the more molecular level. The upper section of the figure shows some of the many factors

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

FIGURE 7-3 Measurement levels and sources.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

that are added at each level of analysis in the form of inputs or constraints. In Figure 7-3, the behavior of the individual, the most molecular level, is combined with the existing technology to produce unit-level outputs. The supervision of the individual also influences the transformation of individual outputs to unit outputs. As an example, design engineer using a computer-assisted design (CAD) system produces specific designs for parts of a new product. Individual or submit outputs are combined through an integration and coordination function that is overseen by the supervisor. The combined effects of individuals, the technology, and the supervision function produce the unit's outputs. Thus, the designs of individuals or small groups are combined into an integrated, final design for the new product, which is the output of the design unit.

The outputs of the manufacturing unit would be finished products. The outputs of the design and manufacturing units are then combined into outputs for the production division. To accomplish this, a coordination function is required so that the outputs of the units can be integrated effectively. The plans developed by the design unit, for example, must be manufacturable at a reasonable cost. In addition, a major resource acquisition process occurs when the person in charge of the division must acquire resources from top management. The more effectively this is done, the greater the outputs of the division tend to be.

The entire division has its own outputs that relate to the finished product. To measure the performance of the division, measures might be taken of how long it took to develop a manufacturable product, how economically the product can be made in the future, and how well the product meets customer needs. What is critical here is that the measures of the division's performance include not only the outputs of the two units forming it, but additional causal factors as well. Specifically, the effectiveness of division management in getting resources, how well those resources are divided between the two units, and how well the coordination is done between the two units will all influence how well the division performs on its measures.

The same process occurs for higher levels in the organization. One division's outputs are combined with those of other divisions to be inputs for the total organization. In this example, the outputs of the production division are combined with those of the marketing division to produce sales and revenues for the total organization. These are combined with the costs and revenues of other divisions to produce the organizational-level outputs. If the total organization is measured on such factors as return on investment, total revenues, net profits, and so on, new causal factors are again added to the performance measure. In Figure 7-3, the factors shown are the strength of the economy, govern

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

ment regulations, and actions of competitors. These are factors that will influence the overall performance of the organization on its measures, but they are not a function of the actions of the organization's divisions.

At the bottom of the figure, some of the different measurement purposes are listed. They indicate graphically that different factors are included when measurement is done for different purposes. Measurement for motivational purposes should measure only what the individual or the unit has control over. It will frequently measure up to the level of unit output, but it should try to remove the effects of the technology. The management information purpose encompasses individual behavior, the performance of the technology, how well supervision is done, the effectiveness of coordination of the individual units, and the effects of resource acquisition. Measuring total organizational performance typically includes all the factors shown in Figure 7-3, including those outside the organization.

One should expect the productivity paradox to occur when measures collected for different purposes are compared. For example, suppose an organization introduces CAD technology and finds that its design engineers are able to create better designs and in less time. It then measures overall organizational outcomes, such as return on investment and gross profit and finds no change. This is an example of the paradox, but it really makes no sense that the two measures should be related. As Figure 7-3 illustrates, measures at the organizational level of analysis will be influenced in a very minor way by the design unit's producing the better designs. This leads to the following hypotheses:

  • The more factors that are added to a measure of organizational functioning when it is aggregated from lower to higher levels of the organization, the weaker the relationship between the original measure and the composite measure will be.

  • The more factors that are added to measures of organizational functioning when they are aggregated to higher levels of the organization, the greater is the likelihood of finding evidence of a productivity paradox.

Different Aggregation Strategies

The problem being discussed here can be seen as an issue of aggregation. The concept of linkages is by definition a cross-level issue—measures are aggregated across levels of analysis. In order to deal with cross-level questions, measures must be developed that go across levels

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

(Hulin et al., 1978; Rousseau, 1985). If one wants to know the effects of, for example, computer technology on organizational functioning, one is raising a cross-level question. Computers are typically used at the level of individuals or small groups. Measuring overall organizational functioning requires a much broader unit of analysis. A key problem is how to go about this aggregation process so that the question can be answered.

In dealing with the productivity paradox, it is important not to confuse two very different aggregation strategies. The first strategy is to construct measures that add many sources of influence into the final, more global measure. That is the typical strategy, and the one described in this section. It amounts to adding error (uncontrolled variance) to the more molar measure. It will by definition reduce the relationship between the more molecular and the more molar measures and yield the productivity paradox.

The second strategy is to measure for one purpose and aggregate by using the same measurement purpose in going from the more molecular to the more molar level. For example, if an organization is measuring to see how well its personnel are doing the work, it wants measures that are predominantly determined by the behavior of the personnel. It does not want the measurement to be influenced by factors outside the control of the personnel. To obtain aggregate measures, it must find a way to express individuals' or groups' performance in a measure that can be combined across levels. Thus, the measure must allow the performance of individual designers to be aggregated to produce the performance of the design unit. An analogous measure must be developed to summarize the performance of individuals in the manufacturing unit. These two unit-level measures must then be combined to form a division-level measure, and division measures combined into total organization measures. If the organization achieves this, it will at least avoid the almost certainty of producing a productivity paradox. However, there is still a problem. The broader the aggregation, the less effect any one subsystem will have on the final aggregated total. If the performance of the design unit improves by 25 percent, but the design unit is only 1 percent of the total organization-level aggregation, the improvement in the design group will have a negligible effect on the total. This also will give the effect of a productivity paradox.

This leads to the following hypothesis:

  • The greater the number of separate elements that are aggregated, the greater and more pervasive must be the change in performance to avoid the appearance of a productivity paradox.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

CONFLICTS IN MEASUREMENT

The discussion of natural phenomena that could give the appearance of a productivity paradox was not meant to suggest a complete explanation for the paradox. The second class of measurement issues is also most likely involved, that is some type of measurement conflict.

One type of measurement conflict occurs when there are differences in the objectives of units that must cooperate with each other to produce the output. Another type occurs when there is conflict in objectives across different levels of the organization. These conflicts come about when the performance of different units is formally or informally measured in a way that produces a problem, and as discussed below, correcting what is measured is ultimately the key to correcting the problem.

Conflict between Local Objectives

Different subsystems at the same level in the organization may have objectives that are not congruent. For example, the design unit in an organization may have as its objective producing an elegant design for a new product that uses the most cutting-edge technology. If this is done, the designers believe they have met their objective and done a good job. In contrast, the manufacturing unit has the objective of developing a manufacturing methodology that will produce the product as inexpensively as possible, and with the highest possible quality. The problem is that the objectives of the two units are not completely compatible. Elegant and cutting-edge designs are frequently difficult to produce. To add more complexity, the sales unit wants a product that meets customer needs. A finished product that is a compromise between design's desires for elegance and manufacturing's ideas of an easy product to make may not meet customer needs at all.

The above situation can produce the paradox. If the objectives of units that must work together are inconsistent, improving one or all units' ability to meet their own objectives does not improve the broader subsystem's performance. For example, suppose the design unit receives new, more advanced CAD equipment and it indeed helps designers to do their work better. If their improved performance is directed at making designs that are even more elegant and cutting edge, that could make it even more difficult for manufacturing to make them. Thus, the outputs of the design group go up, the outputs of the manufacturing unit go down, and there is no net change at the level of the production division. This is an example of the productivity paradox.

The example leads to the following hypotheses:

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×
  • Improving the ability of one subsystem (e.g., an individual, group, unit, division) to achieve its objectives will result in improvement in measures of broader organizational functioning only if that subsystem's objectives are consistent with the objectives of units with which it must coordinate to produce the broader subsystem's outputs.

  • The greater the inconsistency in the objectives of units whose outputs must be coordinated to produce the outputs of the broader subsystem, the greater the possibility of a productivity paradox.

Inconsistency Across Organizational Levels

A second type of measurement conflict is related to the first, but it occurs when measures and objectives are not consistent with each other across organizational levels (e.g., Tuttle, 1981). That is, what are seen as the objectives for one subsystem are inconsistent with those at a higher level. For example, suppose a sales unit is trying to develop a strong and permanent customer base. Key objectives of the unit are to satisfy the customer no matter how small the order and never to sell the customer something not needed just to make a sale. The unit believes that this approach is an appropriate strategy and in the long run will produce a strong and permanent customer base. Top management, however, is evaluated on short-term measures, such as return on investment and profits. In this situation, the objectives of the different levels are inconsistent. Greater immediate revenues and profits would be generated by the sales unit if it would focus on the larger customers and sell whatever it could, regardless of customer needs.

The paradox can occur here as well. If the objectives are inconsistent, making a change that helps the sales unit meet its objectives more effectively can, in fact, reduce how well the broader organization performs on its measures of return on investment and immediate profits.

This phenomenon leads to the following hypotheses:

  • Improving the ability of one subsystem to achieve its objectives will result in improvement in measures of broader organizational functioning only if that subsystem's objectives are consistent with the broader organization's objectives.

  • The greater the inconsistency in the objectives of units in a hierarchical relationship to each other, the greater the possibility of a productivity paradox.

POTENTIAL SOLUTIONS TO THE PARADOX

Given the above explanations for why the paradox occurs, what implications do the explanations have for how the paradox and the linkage

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

issues it highlights should be dealt with? In this section I suggest some solutions.

The basic approach to understanding what to do about the paradox problem is to look at the causes of the problem. Several groups of possible causes were discussed above, and the solution depends on the particular cause. Table 7-1 summarizes the causes discussed and indicates the solution to each.

Structural Factors and Intervention Side Effects

The first set of causes in Table 7-1 is structural factors. Recall that these are factors such as time lag, slack, and bottlenecks. To the extent that structural factors are producing the paradox, the solution is to measure those factors directly. This means directly tracking what happens to the output of one subsystem as it is combined with that of other subsystems. If an increase in output occurs across individuals, it might take some time before an increase occurs in the unit's outputs. Being aware of this lag and measuring appropriately could cause the apparent paradox to disappear. Measuring factors such as slack and bottlenecks would be done in a similar fashion. Thus, when an intervention occurs, the effects of the change in performance must be measured more broadly and more carefully.

The second set of causes is the side effects of an intervention. These occur when the intervention improves some aspects of performance but decreases performance in other parts of the subsystem. To assess these causes of the paradox, it is also necessary to measure the effects of the intervention more broadly. That is, one must not only measure aspects

TABLE 7-1 Causes and Solutions to the Productivity Paradox

Cause

Solution

Structural Factors

Measure Intervention Effects More Carefully

Intervention Side Effects

Measure Intervention Effects More Broadly

Measurement Effects

 

 

Different Measurement Purposes

Aggregate Consistent Measures

 

Measurement Conflicts

 

 

Conflict between Local Objectives

Resolve Conflicts and Replace Measures

 

Inconsistency Across Organizational Levels

Resolve Conflicts and Replace Measures

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

of performance that should be directly affected by the intervention, but also measure other aspects of the functioning of the broader subsystem that could be affected. For example, if a new CAD system is introduced, one should not only measure the quantity and quality of designs produced by the individual and groups using the new equipment, but also measure the overall outputs of the broader design unit.

Measurement Effects

The next major set of causes comprises direct measurement effects that could produce the paradox. This set of effects stems from the way productivity is measured. The first effect discussed is the natural phenomenon of measuring for different purposes.

Measuring for Different Purposes

The primary problem here is that improvements in measures taken for one purpose will not necessarily produce improvements in measures taken for another purpose. As measures are taken at higher and higher levels in the organization, more and more causal factors are being included in the measures that are not affected by lower levels in the organization. Thus, one should not expect much of a correspondence.

The solution to decomposing this aspect of the paradox is to aggregate measures that include the same causal factors. That is, one should not add new causal factors to the measures in aggregating up the organization. Consider the case of measuring for the motivational purpose. The organization's executives may want to know how well the personnel are doing the organization's work (i.e., producing their outputs). They can measure this in a particular unit but when they aggregate it, they should aggregate it with measures from other parts of the organization that reflect how well those personnel are producing their outputs. When the aggregation is complete, they have a measure of how well the personnel in this broader section of the organization are performing their work. If an organization introduces computer technology and expects it to improve how well people are producing their outputs, that is the measure it should use to evaluate the intervention. If the intervention is evaluated using traditional measures of overall organizational functioning, the organization is making the tacit assumption that factors such as economic conditions, actions of competitors, effectiveness of resource acquisition, coordination of units, and quality of supervision should also be affected by the introduction of computer technology.

One difficulty with this solution to the paradox is that of finding

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

measures that can be aggregated across different types of units. That is, the measures must be on some common metric that can be combined. This is a challenge, but it can be done. Later in the chapter I summarize a technique that allows for this.

Conflict between Objectives

The next two measurement effects deal with linkage/paradox problems that come about because of differences in objectives either (1) between subsystems that must coordinate with each other or (2) across organizational levels. If such differences exist, some of the outputs of one subsystem are in essence lost or wasted because they are not needed or valued by other subsystems. If the design unit produces elegant designs and the manufacturing unit requires simple, easy-to-make designs, some effort is going to be lost. This is an example of a conflict among coordinating subsystems. A conflict across levels would occur if the marketing division wanted to build a stable customer base over time and top management wanted immediate revenues.

Both of these situations are quite common. Sometimes there is a clear, openly acknowledged conflict in objectives. However, more typically, people recognize there is a problem, but they do not realize that it involves a conflict in objectives. The solution to this situation is to resolve the conflict in objectives and then develop new measures of organizational performance that are consistent with the agreed objectives. Such a solution is easy to propose but more difficult to implement. Essentially what is required is the development of a good performance measurement system. Below, I describe one such system in some detail because it offers a methodology for dealing with these measurement factors.

Developing a Performance Measurement System

A number of performance measurement systems have been proposed over the years (e.g., Craig and Harris, 1973; Kendrick, 1984; Mali, 1978; Riggs and Felix, 1983; Tuttle and Weaver, 1986). The system described here is called the Productivity Measurement and Enhancement System, or ProMES (Pritchard, 1990; Pritchard et al., 1989). (Note that for this system the term productivity is used in the broader sense. It encompasses the seven performance criteria discussed in Chapter 6.) The major conceptual base for this system is Naylor et al.'s (1980) view of behavior in organizations. When Pritchard and his students (Pritchard et al., 1988) applied this theory to the problem of measurement productivity, a new approach was developed. The new ProMES method not

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
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only produces a way to measure performance, it suggests ways that the information can be optimally fed back to employees so as to help improve their performance. The approach is designed primarily to be used for the motivational purpose in measuring performance or productivity.

The development of ProMES is done in a series of steps that start with identifying the primary objectives and end with providing performance information to the group in the form of a written feedback report that the group uses to improve its performance. To illustrate the steps, I use the example of a manufacturing setting in which a team of four or five persons assembles electronic printed circuit boards of the type found in computers. Each step in the process of developing ProMES is done by a design team composed of three to five job incumbents, one or two supervisors, and one or two facilitators who are familiar with the process and guide the group's activities. A more detailed description of the process can be found in Pritchard (1990, 1995).

Step 1: Develop Products

First, the unit's products must be identified. Products are the important objectives that the group is expected to accomplish. Products may consist of services, tangible items, or a combination of the two. The ProMES design team meets and, through a process of group discussion and consensus building, develops the list of products. Assume that the design team identified the following products for the assembly group: (1) maintain high production, (2) make high-quality circuit boards, and (3) maintain high attendance.

Step 2: Develop Indicators

The next step is to determine a method for measuring how well each objective is being accomplished. These measures are called indicators. They are typically quantitative, objective measures, but they can also be other types of measures, such as customer attitudes. Each product must have at least one indicator. The same design team identifies the indicators through group discussion and consensus. Assume that the design team developed the following list of indicators for the three products:

  1. Maintain high production

    • percentage of boards completed: number of boards completed divided by number of boards received

    • meeting production priorities: number of high-priority boards completed divided by the number needed

  1. Make high-quality boards

    • inspections passed: percentage of boards passing inspection

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×
  1. Maintain high attendance

    • attendance: total hours worked out of the maximum hours possible

In an actual ProMES system there are typically 4 to 6 products and 8 to 12 indicators. The example here is abbreviated to simplify the explanation.

When the design team reaches agreement on a unit's products and indicators, it presents the list to upper management for review and approval. Once approval is obtained, the design team can begin the next step.

Step 3: Develop Contingencies

The next step is to determine the contingencies, or the relationships between the amount of the indicator and how that amount will be evaluated. Figure 7-4 shows the general form of a contingency. The horizontal axis represents the amount of the indicator, ranging from the worst possible level likely to occur to the best possible level. The vertical axis depicts the different levels of effectiveness for the indicator. This scale ranges from +100 (maximum effectiveness) to -100 (minimum effectiveness). The zero point repre

FIGURE 7-4 General form of a contingency.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

sents the expected level of effectiveness. It is defined as the level of the indicator that is neither good nor bad. The basic idea of developing an indicator is to identify the function that defines what level of the indicator it takes to achieve what level of effectiveness.

A series of specific steps is used to develop each contingency. Through a process of group discussion and consensus, the design team identifies the end points of the indicator, determines the effectiveness scores for those end points, determines the zero point (expected level), and then completes the other points in the function. The process is somewhat complex conceptually, but in practice it is fairly easy. It also seems to produce contingencies that are reliable and useful over time (Pritchard et al., 1989).

In the example contingency, the design team determined that the best possible amount of boards passing inspection is 100 percent. This indicates that the team believes it is realistically possible for all the boards to pass inspection. The minimum, or worst feasible level of the indicator, was set at 99 percent of the boards passing inspection. Performance at or near this level was seen by the design team as a major production problem. The zero point, the expected level of the indicator, is 99.4 percent passing inspection. The effectiveness values that correspond to the maximum and minimum indicator levels are +70 and-80. The other values of the function are then determined.

This scaling process is done for all indicators so that each indicator has a contingency. Completed contingencies for all the indicators in the example are shown in Figure 7-5. Next, the contingency set is presented to higher management for approval. Frequently, disagreements arise about some of the contingencies; they are discussed and a compromise is reached. Once all the contingencies are approved by higher management, the contingency set is complete.

There are two particularly important aspects to note about contingencies. First, the overall slope of the contingency expresses the relative importance of the indicator. Steep slopes are produced for indicators that are very important to the functioning of the unit. Indicators with flatter slopes are less important to the functioning of the unit in that variations in these indicators will have a lesser impact on total effectiveness. Thus, the differential importance of the indicators is captured by the slope of the contingencies.

The second important aspect of contingencies is their nonlinearity. This is reflected in the completed contingency in Figure 7-5A. It shows that when the number of boards passing inspection is above the neutral point of 99.4 percent there is a large increase in effectiveness. However, once the passing rate reaches 99.7 percent, further increases do not represent as great a change. This nonlinearity is important be-

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

FIGURE 7-5 Completed contingency set.

cause a given amount of improvement at the low end of the measure may not have the same effect at the high end of the measure. It is quite common for improvements in the middle range of the indicator to result in large improvements in effectiveness, while improvements at the high end of the indicator result in smaller improvements in effectiveness. In other words, a point of diminishing returns is reached.

Put another way, once a certain level of effectiveness is reached, it may be more beneficial to focus on improving another area than to continue working on an area of performance that is already very good. For instance, if the unit producing circuit boards has completed a very high percentage of boards, it may be better to work on improving its only modest attendance even though attendance is not as important overall.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
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Step 4:
Create the Feedback Report

The fourth step in developing ProMES is to create a formal feedback report. Once indicator data are collected, effectiveness scores can be determined based on the contingencies for each indicator. As can be seen in Figure 7-5, if 99.8 percent of the group's boards pass inspection, it would achieve an effectiveness score of +62.

Continuing this process would result in an effectiveness value for each indicator. Once effectiveness values for each indicator are determined, they can be summed to determine the overall effectiveness score for that particular work group. This score represents the group's level of overall performance. A score of zero means that the group is meeting expectations; the higher the score is above zero, the more the unit is exceeding expectations. This information is presented to the unit in a formal written feedback report on a regular basis. Figure 7-6 shows an example of such a report.

Another overall measure that can be derived from the system is the group's percentage of maximum effectiveness, that is the overall effectiveness score the group would receive if it was at the highest possible level on every indicator. The unit's actual overall effectiveness score for the period can then be expressed as a percentage of this maximum. For example, summing the maximum values for each of the indicators in the example yields a total possible score of 300. The example unit received a monthly score of +97. Thus, its percentage-of-maximum score was 97/300, or 32.3 percent. The closer the unit is to 100 percent, the

Circuit Board Manufacturing Unit

Date: July 19xx

I. Production

 

A. Percentage of Boards Completed

98%

+40

 

B. Percentage of High-Priority Boards Done

85%

-5

 

Total Effectiveness: Production = +35

 

 

II. Quality

 

Percentage Passing Inspection

99.8%

+62

III. Attendance

 

Percentage of Maximum Hours Worked

97%

0

 

Overall effectiveness = +97

 

 

FIGURE 7-6 Sample feedback report.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

closer it is to performing at the maximum performance level. If the unit's overall effectiveness is negative (i.e., below expectations), a negative value of the percentage-of-maximum score is calculated.

The advantage of the percentage-of-maximum index is that it allows the performance of groups doing very different things to be compared. The group with the highest percentage-of-maximum score is the highest-performing work group. This comparison is valid even if the groups have different indicators because the contingency process scales all indicators on a common metric, overall effectiveness. The comparison between different groups is then based on this common metric.

The ProMES methodology was first developed and evaluated in five units of an Air Force base (Pritchard et al., 1989). It resulted in large gains in productivity, and those gains were maintained for the entire time of measurement—at least 20 months. The methodology has also been successfully implemented in other organizations in the United States and Europe (Janssen and van Berkel, 1991; Jones, 1995; Kleinbeck et al., 1991; Kleingeld et al., 1991; Roth et al., 1995; Hedley et al., 1995; Schmidt, 1991; Stout and Jones, 1989; Thierry and Miedema, 1991; van Tuijl, 1991).

ProMES and Linkage Issues

ProMES is one methodology that can be used for dealing with conflicts in objectives that can produce the productivity paradox. The technique can be seen as a way of formally identifying organizational policy. Products, indicators, and contingencies reflect what the objectives of each subsystem are, what measures will communicate how well the subsystem is fulfilling those objectives, the relative importance of each measure, what is expected on each measure, and what level of output is defined as good or bad. This is a statement of policy. It is developed subjectively, but policy is by nature subjective. What ProMES does is to give organizational personnel a methodology with which to define policy in a way that people can understand, that people can agree with or not, and that can be communicated clearly.

By going through the process of developing the system, incumbents, supervisors, and managers can come to terms with the fact that there are disagreements in policy. These disagreements almost always occur somewhere in the development of a system. However, because the system gives personnel a structured method for dealing with the disagreements, it can make reaching a satisfactory compromise easier. This approach can be used across organizational levels and at the same level. Through the process of getting incumbents and supervisors to agree on the elements of the system and then presenting those elements to higher management and gaining approval, disagreements in objectives and

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

policy across levels are made clear. Where possible, they are resolved and a new, more congruent policy is developed. If agreement is not possible, at least people know where the disagreements are and why they exist. This seems to make it easier to cope with the conflict.

The process of developing the system also helps resolve conflicts between units that must coordinate with each other. When the system is developed, it becomes clear where objectives are not consistent. In the design and manufacturing units in the example above, it would be clear from an examination of each unit's products and indicators that the two units are evaluating themselves differently. It then becomes the responsibility of higher management to work with the two units to bring products and indicators more in line with the objectives of the broader organization. One way this can be done is for each unit to have its own products, indicators, and contingencies as usual, but to have additional indicators that are a function of the joint efforts of the coordinating units. In the example, the common measures could be time to complete the final prototype, number of changes in the original design, and number of prototypes needed. These measures can only be highly favorable when the two units work closely together in developing the new product. These common measures would be added to the measurement system of each unit. If the two units want to look good on their measures, they must work together effectively.

ProMES and Aggregation

The point has been made that one way of avoiding the productivity paradox is to aggregate only measures that are influenced by the same set of causal factors. The ProMES methodology offers a way to do this through the percentage-of-maximum measure. This is the index that is the unit's actual overall effectiveness divided by the maximum possible effectiveness for that unit. It is a metric that is common across all types of units, no matter what work they are doing.

One could calculate the percentage of maximum for a variety of different units. The mean percentage of maximum across the units would be the overall index of how well personnel are performing the organization's work.

TOWARD A COMPOSITION THEORY OF LINKAGES

While it is important to decompose the productivity paradox and suggest solutions for dealing with it, the larger objective must be kept in sight: learning about productivity linkages. The paradox is only an example of the importance of studying and understanding linkages between organizational subsystems. What is really needed is greater

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

awareness and understanding of how outputs get combined and transformed across organizational levels.

The solutions to decomposing the paradox suggested above are a start in this direction, but they are just partial solutions. What is needed in addition is more conceptual work that will enable researchers and practitioners to understand better the nature of organizational linkages. Specifically, a sound theory of aggregation is needed, that is, a theory for how organizational levels are related to each other and how that affects organizational productivity.

Rousseau (1985) has cogently made the same point, arguing that when aggregation is done, what she calls a ''theory of composition" is necessary. A composition theory specifies what the relationship is between the variables of interest at each level of aggregation. In the case of productivity, the composition theory would describe conceptually how productivity at the individual level is combined to produce productivity at the group level, and how the productivity of the groups are combined to produce divisional and organizational productivity.

A simplified example of such a composition theory is shown in Figure 7-7. The darker boxes in the middle of the figure show the linkages going from the individual to group to organizational level of analysis. Other levels would be needed for a complete theory, but the three depicted make the point. Above and below the middle of the figure are causal factors that will influence the transformation of outputs (i.e., linkage) from one level to the next.

The theory might suggest that an individual's output is a function of abilities, knowledge gained through training and experience, motivation, and availability of materials/resources to do the work. These variables combine to produce individual output, the first box in the figure. However, since the individual's efforts must be combined with those of others, how well individuals work together will influence how well the individuals' outputs are translated into group outputs and, ultimately, group performance. In addition, if the supervisor does not provide sufficient materials and information and does not handle intergroup and intragroup relations well, group performance will be affected. Thus, the quality of supervision is also involved in the translation of individual to group performance.

Another variable in this composition theory is the degree of interdependence of the individuals in the group. If each person works completely independently, moving to a higher level of analysis is more straightforward. Individual measures can be more easily aggregated because the work of one individual has little impact on the work of the others. If, however, there is a great deal of interdependence in the work, the situation is much more complicated. In this case, it is inap-

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

FIGURE 7-7 Simplified model of composition theory.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

propriate simply to sum individual measures. Specific group-level measures that will capture the interdependencies would be needed.

Role accuracy is another variable that influences the translation of individual output to group performance. This variable is conceptualized as the accuracy of the match between what the individuals see as important in expending their time and effort and what is important to the broader group.

Other variables influence the translation of group-level performance to organizational performance. Inputs from other units are the outputs of other units that are needed to translate group-level performance to organizational performance. They could include other components of the final product, direct services (e.g., marketing), or staff functions of various types. Match of group to organizational objectives is analogous to role accuracy, but at the group level. It is the degree of match between group objectives and organizational objectives. Factors outside the organization include the economy and government regulations.

Once the variables in the theory of composition are identified and defined unambiguously, the next step would be to develop quantitative operationalizations of each variable. For example, degree of interdependence could be operationalized as the correlation of mean individual output and total group performance over time. If personnel in the group are truly independent, their individual outputs can simply be summed to arrive at total group output. In this case, if one calculated the correlation between mean individual output and group output over time periods, the correlation between the two measures over time would be 1.0. Thus, if this correlation is close to 1.0, the individuals are highly independent. If there is dependency between group members, the outputs of one individual influence the outputs of others. In a case of interdependence like this, the mean outputs of the individuals cannot simply be added to get total group output. Consequently, the correlation between mean individual output and total group output over time will decrease from 1.0. The greater the interdependency, the greater the decrease from 1.0 toward 0.

Once the operationalizations have been developed, the next step would be to estimate mathematical functions that capture how the separate variables are related to each other. For example, the interdependence coefficient, which ranges from 0 to 1.0, could be a multiplier between total individual output and group performance. An interdependence coefficient of, for example, .50 would mean that increasing individual output would improve group performance, but not as much as when interdependence is lower (e.g., a coefficient of .8).

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

Advantages of a Theory of Composition

While this theory of composition and the example functions are simplistic, they illustrate what a theory of composition for productivity linkages might be like. A great deal of work would be needed to develop a comprehensive theory, but the work would be well worth it because of the advantages of such a theory.

One major advantage of such a theory would be that it would enhance understanding of productivity linkages and cross-level organizational analyses in general. Researchers and practitioners have been very naive in their approach to organizations, assuming that changes in one level of the organization will automatically be apparent at higher levels of the organization. It is commonly implied, for example, that better selection of entry-level personnel will improve organizational productivity. The argument is that if the mean productivity of individuals is improved by, for example, 10 percent, the productivity of the unit will improve by 10 percent. This sort of argument ignores all the factors that the theory of composition indicates influence the translation of individual to group productivity. If the output of a group of programmers is increased by 10 percent through better selection, but the work flow between programmers is not managed so as to utilize the improved individual performance, the increase could easily be lost. A clear theory of composition would make the fallacy of the assumption very clear and indicate the factors that intervene in the linkages.

Once there is even a basic mathematical model of the linkages, several other benefits become possible. One advantage will be the ability to predict the relationships between components of the theory. Not only will this allow the theory to be tested, but once supported, the theory can then be used to predict what to expect when components of the model are changed.

One application of this capability of the model is to predict whether productivity gains at one level will be lost or wasted in their translation to higher levels. For example, it may be possible to predict that with the level of slack that exists in a given unit, improving the efficiency of one group will simply increase the amount of slack, not improve the broader unit's performance.

Another application is to do "what-if" and sensitivity analyses to compare productivity improvement strategies. For example, one could compare the expected gain in performance at the group and organizational levels from (1) improving personnel selection, (2) clarifying roles, and (3) changing technology. Being able to approximate the gains that would occur with different strategies could be of great benefit in deciding among alternatives.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

DIRECTIONS FOR FUTURE RESEARCH

Attempting to understand linkage issues leads to a series of ideas for needed research. First, the most general need is for research that further explains the importance of linkages and the impact they have on attempts to improve organizational performance. It is easiest just to focus on a single intervention at a single level of analysis, but as this report makes very clear, such a strategy is overly simplistic.

Second, future researchers need to avoid the temptation to try to identify the "proper" criterion for assessing organizational performance. It make no sense to talk about organizational performance or effectiveness as if it is a concept that has a universal meaning. It is like asking whether an individual is a good performer. The obvious answer is a good performer at what? What constitutes organizational performance is what the measurer wants to assess the organization on. Researchers must be very careful that they do not fall into the trap of assuming that there is a set of agreed measures or even that one set of measures is somehow better than another.

Third, in order to attack the linkages problem in a systematic fashion, researchers should develop a master list of variables that could influence the translation of outputs across linkages. The chapters in this report are an excellent source for such a taxonomy. Such a listing could group the factors by type. For example, this chapter breaks down factors into structural effects, intervention side effects, and measurement effects. Within each type, the factors could be grouped by the type of solution needed to address the linkage issue. For example, variables that are the natural consequence of organizational structure (e.g., slack), which cannot and should not be considered problems, would be grouped together.

Fourth, empirical research is needed to identify the major linkage variables and their relative importance. To do such research, multiple units within multiple organizations must be studied in a longitudinal design. As a first step, improvements in outputs at the most molecular level must be shown to have occurred because of an intervention, and then those improvements must be traced through the various organizational linkages to the broadest organizational level. The idea would be to measure each explanatory factor as identified in the linkages taxonomy, along with the amount of loss of output across the linkage. For example, explanatory variables such as slack and conflict in objectives would be measured directly. Then, the importance of each could be assessed empirically. Ideally, the data would be collected so that the variance accounted for by each explanatory factor could be assessed.

The most important types of linkage variables are those that result

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
×

in the actual loss of outputs from one level to the next. This represents waste, and to the extent it exists, its elimination will improve organizational functioning. Thus, the next step in the research program would be to use interventions to change the factors that are decreasing the translation of outputs across levels and assess the effectiveness of the interventions. For example, if conflict in the objectives of different units is causing the linkage loss, interventions to make the objectives consistent would be employed. The evaluation would be to assess the effectiveness of different types of intervention and to determine if the linkage loss can be eliminated.

Finally, a theory of composition is sorely needed. As argued in this chapter, this is a theory that indicates what the major linkage variables are and how they affect the translation of outputs from one level of the organization to the next. This would be a major research program that would take a great deal of work. However, if it could be done successfully, the payoffs would be enormous.

CONCLUSION

It is clear from the issues raised in this chapter that the productivity paradox is of great significance in that it highlights the importance of a much clearer understanding and appreciation of the linkages among levels of the organization. Researchers and practitioners have been very simplistic in thinking that changes at one level in the organization will be translated in a simple manner to higher levels. There are many possible explanations for the paradox, the importance of which is to enhance understanding of organizational linkages. This and other chapters in this report suggest many factors that must be considered in understanding these linkages. The challenge is to use these ideas to further understanding of linkages and, from that, to learn how efforts to improve productivity can be facilitated.

AUTHOR'S NOTE

I would like to thank Margaret Watson for her contribution to an earlier version of this chapter. Steven Worchel suggested several of the ideas in the section on unintended side effects of organizational interventions. I would also like to thank Amie Hedley-Goode, Karlease Clark, and Anthony Paquin for their helpful comments on an earlier draft of the chapter.

Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
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Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
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Suggested Citation:"7 DECOMPOSING THE PRODUCTIVITY LINKAGES PARADOX." National Research Council. 1994. Organizational Linkages: Understanding the Productivity Paradox. Washington, DC: The National Academies Press. doi: 10.17226/2135.
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Next: 8 MODELS OF MEASUREMENT AND THEIR IMPLICATIONS FOR RESEARCH ON THE LINKAGES BETWEEN INDIVIDUAL AND ORGANIZATIONAL PRODUCTIVITY »
Organizational Linkages: Understanding the Productivity Paradox Get This Book
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By one analysis, a 12 percent annual increase in data processing budgets for U.S. corporations has yielded annual productivity gains of less than 2 percent. Why? This timely book provides some insights by exploring the linkages among individual, group, and organizational productivity.

The authors examine how to translate workers' productivity increases into gains for the entire organization, and discuss why huge investments in automation and other innovations have failed to boost productivity.

Leading experts explore how processes such as problem solving prompt changes in productivity and how inertia and other characteristics of organizations stall productivity. The book examines problems in productivity measurement and presents solutions.

Also examined in this useful book are linkage issues in the fields of software engineering and computer-aided design and why organizational downsizing has not resulted in commensurate productivity gains.

Important theoretical and practical implications contribute to this volume's usefulness to business and technology managers, human resources specialists, policymakers, and researchers.

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