Emerging Needs and Opportunities for Human Factors Research (1995)

Paul S. Goodman Douglas H. Harris

This chapter identifies specific opportunities for research on productivity in organizations in the following four areas: implementation of effective change within the organization; integration of individual productivity into organizational productivity; congruence of technology, people, and organizations; and integration of the enterprise. Our focus is on new research to be conducted by human factors specialists. We also recognize the need for coordination and cooperation with researchers in other disciplines who are involved in addressing issues in organizational productivity. Consequently, this chapter is for all researchers interested in gaining a better understanding of productivity in organizations. We believe it is also relevant to policy makers and research planners with needs and interests in this area.

An enterprise consists of technology and people organized to accomplish some purpose. The success of an enterprise can be assessed on the basis of its output and/or the processes and inputs that produce this output. Productivity, in general terms, is the ratio of the output of the enterprise to the inputs. We consider both total factor productivity and labor productivity (see Mahoney, 1988, for a more intensive discussion of productivity). In some of the research we review in this chapter, the criterion variable is

performance, not productivity. Other measures, such as quality, timeliness, and profitability, will also be considered in this analysis. To simplify the exposition, however, we will focus primarily on productivity.

The important questions we must now answer are the following: How do we identify the major conditions and processes that cause variation in organizational productivity? How do we address these factors to increase organizational productivity?

The main focus of human factors research has been on improving individual task performance. Researchers have obtained measures of individual performance, such as speed, accuracy, and time needed to learn, and have used these to estimate individual productivity. In some cases they have measured productivity directly. The implicit or explicit assumption underlying these efforts has been that increased individual productivity will increase organizational productivity. However, very little research evidence is available to support this assumption. Improvements in individual productivity may not add up to improvements in organizational productivity because a variety of variables may moderate the effects of the individual improvements and because the various productivity increases that occur on an individual level can interact in a complex way.

We need to understand the factors that drive organizational productivity. If the human factors researcher intervenes at the individual or group level to increase productivity, we need to learn whether these changes affect productivity at the organizational level. If researchers intervene at the organizational level with new technology, decision-making aids, training, and so on, we still must identify the conditions under which these changes lead to improvements in organizational productivity.

We live in an increasingly competitive global economy. The ability of companies and countries to enhance the productivity of their resources is critical for remaining competitive in this environment and, on a national level, for enhancing the standard of living.

The United States has been introducing advanced technologies to enhance productivity and, hence, our competitive position (National Academy of Engineering and National Research Council, 1991; National Research Council, 1986). The returns from some of these investments, however, appear to be relatively small. For example, the data-processing budgets for corporations in the United States have reportedly been increasing about 12 percent per year. Productivity increases, however, have been averaging no more than 2 percent per year (Weiner and Brown, 1989). Other investigations of the impact of information technology on productivity have failed to

find any increase at all from the more than $100 billion per year that is spent on hardware, software, and computer services (Attewell, 1994).

Enhancing productivity is clearly a major national challenge. As competition increases in the global economy, we need to find new ways to improve organizational productivity. The role of researchers is to understand more about the inhibitors and facilitators of organizational productivity. As we develop new knowledge in this area, we will be better able to link new innovations, technologies, organizational structures, and capital to enhance organizational productivity.

We begin our discussion with a review of past research on organizational productivity. We then describe the 4 areas that need further research and identify 15 research opportunities within these areas.

The purpose of this section is to give the reader a selective review of productivity research in organizations. We draw primarily from the behavioral science literatures (e.g., human factors, industrial psychology, organizational psychology). Research that has been generated from the fields of economics and technology are outside this review. We have also omitted the methodological issues of productivity measurement and analysis (see Mahoney, 1988, for a discussion of these issues).

The bulk of the research completed by industrial/organizational psychologists and human factors specialists has focused on interventions designed to increase individual performance or productivity (Campbell et al., 1988; Pritchard, 1991). Examples of interventions include training, measurement and feedback of performance, goal setting, work design, and human-equipment interface design. Guzzo (1988) assessed what we know from psychological research about productivity and its improvement and identified training as the most powerful way to increase individual productivity. He further stated that the effect of training was strongest on output measures of productivity. Locke and Latham (1990) have provided some convincing evidence of the positive effects of goal setting on individual performance. Research (Guzzo, 1988) has indicated that changes in work design have improved individual productivity. What we do not know, however, is whether or not these individual increases are linked to productivity increases of the organization.

Human factors specialists and industrial engineers have reported numerous instances in which the application of appropriate behavioral principles

to the design of workplaces and human-equipment interfaces resulted in increases in individual productivity. For example, Harris (1984), in his presidential address to the Human Factors and Ergonomics Society, described 30 human factors projects, many of which involved increases in individual productivity in organizations. Examples included production of microelectronic devices, maintenance of army tanks, investigation of criminal activity, purification of water, on-the-road detection of drunk drivers, and military mission planning. In most cases, however, there was no attempt to study whether the positive effects of these increases in individual productivity affected group or organizational productivity.

Over the last decade, there has been a renewed research interest in groups. Particular attention has been paid to the role of autonomous or self-managing groups. The findings emerging from this research (Goodman et al., 1988; Hackman, 1990) are that self-managing teams can increase productivity, quality, and worker satisfaction. However, most of this research has not conceptually or empirically considered whether increases in group or team productivity produce increases in organizational productivity.

Another source of studies on productivity in organizations comes from researchers interested in how the interaction of environment, technology, organization, and people variables affects organizational productivity (Lawrence and Lorsch, 1969; Scott, 1987; Thompson, 1967). Socio-technical analysis (Trist et al., 1963) provided the early intellectual underpinnings of this work.

One study (MacDuffie and Krafcik, 1990) sought to explain productivity differences in a worldwide sample of automobile assembly plants. The critical findings of this study were that the plants with the highest level of automation were not the most productive. The most productive plants introduced congruent organizational changes as well as technological changes. In general, congruency refers to the fit between the type of technology, specified in this case by levels of interdependence, and the nature of the organizational arrangements, specified by the flexibility in organizational arrangements. Better fit means higher scores in productivity or effectiveness.

Studies in the shipping industry (Walton, 1987) and coal industry (Goodman, 1979) also show that high organizational productivity is associated with congruency among innovation in technology, organizational arrangements, and people factors.

We know something about how to increase individual and group productivity. However, there is no compelling research evidence that these changes lead to changes in organizational productivity. We also know that congruency among technological, organizational, and people factors can contribute to organizational productivity.

Yet we do not know how changes at the organizational level are related to changes in individual or group productivity. Also, the systems perspective does not inform us ahead of time how conditions of congruency will be determined. There are many gaps in our knowledge of how new forms of technology, new organizational forms, and changes in a competitive environment will impact on rates of changes in a organizational productivity. Although we have made progress in understanding organizational productivity, we need to address some of these gaps with new theories and new methods.

We will outline the research that is needed to define the processes and conditions that will facilitate this transformation. Our focus, then, is not on productivity per se, but on how human factors and other organizational researchers can develop theories and methodologies to understand the link between changes in individual, group, and organizational productivity.

We organize our discussion of research in terms of four opportunity areas. We describe the problem and rationale for each of these areas, along with specific research needs. Throughout this analysis we consider productivity a multilevel and multidimensional concept.

Billions of dollars have been spent introducing new forms of organizational and technological change in organizations (Bikson et al., 1987; Leonard-Barton, 1988; National Academy of Engineering/National Research Council, 1991). Implementation deals with the process of effectively introducing changes in organization. There is a growing body of evidence (Goodman and Griffith, 1991) to show that many organizational and technological interventions, which should inherently improve organizational productivity, are not successfully implemented. This means the interventions are rejected, resisted, only partially accepted, or only temporarily adopted and then rejected.

If technological and organizational interventions have clear objectives or inherent benefits but cannot be successfully implemented, then they will

not improve individual or organizational productivity. Indeed, successful implementation is key to our analysis of organizational productivity. For example, we recently studied the introduction of a vision system into a sophisticated computer-integrated manufacturing environment (Goodman et al., 1990). The purpose of this vision system was to enhance quality through new forms of monitoring. By most objective measures, the new technology dominated current technology for monitoring and improving quality. However, the vision systems remained basically unused two years after their introduction.

If we cannot establish improvements through successful implementation at the individual, group, or organizational level we cannot expect to see productivity gains at the organizational level. Understanding the process of successful implementation is therefore the starting point in our analysis of research opportunities.

Over the last decade there has been an increasing body of research on the process of implementation. In much of that work, researchers have examined how technological-, organizational-, and individual-level variables affect the implementation of new technologies. They have paid less attention to identifying underlying explanatory mechanisms. Thus, there are frameworks but no well-defined theories. Despite the large number of possible predictor variables, there have been few multivariate studies and few longitudinal designs to capture implementation over time.

Research needs include the following:

• Developing better conceptualizations and measures of implementation success. Many studies focus on user satisfaction and frequency of use. There has been little attempt to link individual and organizational dimensions of implementation success.

• Developing more parsimonious theory. Much of the research has used a contingency theory approach. That is, researchers have tried to identify a contingent set of variables or conditions (e.g., top management support or participation) under which technologies will be more effectively implemented and conditions under which implementations will be less effective. Because of the large number of variables that might affect implementation success, such an approach has great limitations. Recently, there has been movement toward a process-oriented theory (Goodman and Griffith, 1991). The key idea is to develop a better understanding of the mechanisms that lead to successful implementation.

• Assessing the value of alternative forms of training and learning. Training is an important part of the implementation process. It is clear that

formal classroom training plays an important role in the successful implementation of new technology. It is also true that other forms of learning, such as observation, modeling, and apprenticeship, bear on successful implementation of new technology or organizational arrangements. We have little systematic knowledge of how and under what conditions these alternative forms of learning affect implementation success.

• Studying the effects of alternative forms of commitment. Participation is a common prescription in implementing new changes successfully. However, the empirical evidence on the effectiveness of participation is quite mixed (Goodman and Griffith, 1991). Perhaps we should explore other ways to enhance commitment: for example, fostering recognition of the inherent benefits of the new technology or a normative consensus about the new technology. Alternatively, we could explore the specific mechanisms evoked by different forms of participation and how they bear on changing levels of commitment.

• Studying adaptation and redesign. A significant finding (Leonard-Barton, 1987) in recent implementation studies is the importance of a redesign function. That is, as a piece of technology is introduced into an organization, one needs a mechanism to adapt the technology to changing user needs and organizational contexts. We know little about how to design alternative forms of adaptation mechanisms or the effectiveness of these mechanisms in different contexts. This is important if we are going to understand the successful implementation of new technology and organizational arrangement.

Although there has been considerable research on productivity at the individual, group, and organizational levels, we know little about how changes in productivity at one level affect changes in productivity at another level.

Research opportunities for examining the linkages between individual and organizational productivity are relatively unlimited, given the paucity of studies in this area. We recommend examining the different types of linkages to discover whether increases in individual productivity inhibit or facilitate increases in organizational productivity.

Research needs include the following:

• Studying productivity linkages within jobs. Jobs are bundles of linked activities. Most interventions to improve productivity focus on specific

sets of activities. There is some evidence that increasing the productivity of certain sets of activities within a job can reduce the productivity of other job activities. For example, Kraut et al. (1989) examined the impact of a new computerized information system on the productivity of customer service representatives. They learned that productivity increased for routine tasks, but dropped for nonroutine tasks. So the net increase in productivity of that job may be close to zero. Similarly, increases in productivity in certain job activities can simply create additional slack, which does not enhance productivity for the total job or for the organization. Furthermore, some job activities are central to core production activities, while others (e.g., recordkeeping) are more peripheral. Improving productivity in peripheral activities is less likely to affect organizational productivity. We do not understand the linkages between different activities within a job. When will productivity changes in certain activities stimulate positive changes in other activities? When will the opposite occur? We also do not understand when slack will be generated, when slack can have a positive effect on productivity, and when slack will mitigate any greater effects of productivity, given increases in certain job activities.

• Studying productivity linkages between jobs or units. Jobs in organizations are interdependent in varying degrees. Most research has focused on increasing productivity in individual jobs, but not on the consequences of this productivity for jobs horizontally or vertically linked to them. There is some evidence that productivity increases in a particular job may (1) reduce productivity in other jobs, (2) simply create slack that does not lead to productivity in other jobs, or (3) encounter constraints in interdependent jobs that prevent the productivity increases from having an impact on any other part of the organization. The situation is analogous to what occurs among activities within a job. Thus, increases in productivity in one job may decrease productivity in other jobs, leading to a net productivity gain of zero. The basic research question is, how do changes in one job positively or negatively affect other linked jobs? There is a need for a well-developed theory or research paradigm to help us predict when increases in productivity in one job would enhance the productivity in a horizontally, or vertically, linked job.

• Studying linkages and organizational type. Organizations differ in the interdependence and complexity of their linkages. Some organizations, for example, have pooled interdependence: different departments are fairly independent, but the products of all these departments need to be pooled together to achieve an organizational product. A department store is an example of pooled interdependence. Some organizations have other forms of interdependence: an assembly line is a form of serial interdependence; a hospital might illustrate reciprocal interdependence. Even organizations with the same type of interdependence may vary in complexity or simply in

the number of different linkages. Linkages between individual, department, and organizational productivity in pooled interdependence differ from the linkages in serial or reciprocal interdependence. For example, because department store units are relatively independent, increasing productivity in one unit should contribute fairly directly to increases in organizational productivity. In contrast, the effect of productivity increases in any unit of an assembly line depends, to a large extent, on what happens in the other interdependent units and, hence, will condition the impact of that unit on organizational productivity (see National Research Council, 1994). We need to understand how the mechanisms that translate changes in individual-level productivity to organizational-level productivity differ by organizational type. These comparative organizational analyses should provide new ideas about and new insights into the relationship between individual and organizational changes in productivity. Although we have defined organizational type in terms of the form of interdependence, other measures such as size may be relevant.

A growing body of literature indicates that the fit or congruency among technological, organizational, and people factors is the key to understanding differences in organizational productivity (Goodman, 1979; Walton, 1987). For example, in a study of auto assembly plants, MacDuffie and Krafcik (1990) observe that the most productive plants, identified as ''lean production systems," have (1) a technological system characterized by highly interdependent technology, no buffers, a mechanism that immediately stops the system when downtime occurs, and no repair areas and (2) an organizational system characterized by fewer job classifications, workers with multi-job skills, intensive training in problem solving, teams, fewer status barriers, and contingent reward systems.

The critical research question is, why does this configuration of technological and organizational arrangements lead to high productivity? What does congruency or fit mean? An increasing number of studies indicate that fit makes a difference. However, we need some before-the-fact explanations for what fit among technology, organization, and people factors means. This becomes particularly important as new technologies proliferate and new organizational arrangements evolve.

The importance of this research area should be clear. The future will bring rapid changes in both technology and organizational arrangements, as well as new demographic characteristics. We need to develop theories and bodies of research findings that will help us understand and predict how different combinations of these factors will affect organizational productivity.

There are important, exciting research opportunities concerning the congruency among technological, people, and organizational factors as drivers of organizational productivity.

Research needs include the following:

• Identifying the critical processes or mechanisms that explain why certain configurations among technology, organizations, and people lead to higher organizational productivity. Goodman et al. (1994) identify five critical processes underlying the congruency question: coordination, problem solving, focus of attention, organizational evolution or redesign, and motivation. Are there other processes? Should some of these be combined? To what extent are the processes independent explanations and to what extent do the processes reinforce one another? Reward systems at the organizational level both improve motivation and focus attention on organizational-level outcomes. How do these processes function under different technological and organizational arrangements?

• Connecting the issues of linkage and congruency. A central question in this chapter is, how do changes in individual-level productivity lead to changes in organizational productivity? This is an important and relatively unresearched area. Although, as noted above, there is a body of literature supporting the importance of congruency among technology, organizations, and people to enhance productivity, there is little theory or evidence to explain when, how, and why this congruency functions. Research is needed to integrate the theoretical work on linkages and congruency in some empirical context. Are there common processes that enhance both linkages and congruency among technological and organizational systems? How do they function? Where is the synergy? Research in this area might, for example, focus on redesign. The implementation literature points out that redesign is necessary to adapt new technology to changing organizational factors and user needs over time. If a successful redesign process is in place, there is a higher probability that individual productivity can be sustained and, therefore, a greater opportunity to contribute to organizational productivity. Without a redesign process, there is a much lower probability that individual productivity will affect organizational productivity. The redesign process also appears in the literature about highly productive, congruent systems. In the high-productivity, lean production systems discussed above, there was a continuous process of redesigning the organizational and technological systems to ensure better fits and higher productivity. It is important to note that the redesign process is central to both explanations (linkage and congruency) for higher productivity.

• Studying the effects on productivity of dramatic changes in technology,

organization, and the workforce. Over the next decade, we expect to see rapid and dramatic changes in all three areas. New forms of technology will proliferate as tools are created for decision making, communication, and working across space and time. On an organizational level, there will probably be a continuation of the movement toward smaller and more autonomous units, the structuring of organizations around processes rather than functions, and increased interest in such processes as organizational learning. The characteristics of the workforce will also continue to change, possibly altering the "contract" between the employees and the organization. We need research on how changes in each of three areas—technology, organization, and the workforce—affect productivity in the other two. It may be helpful to do some of this research in different national contexts.

Developments since the late 1980s point to the need to integrate organizational processes better, for example, by computer-integrated manufacturing. At the same time, there has been a push to integrate external constituencies such as customers and suppliers. One important question in the 1990s is how to integrate these external activities to improve organizational productivity. The broader question is how to integrate internal and external activities into a total enterprise to improve overall productivity and effectiveness.

The design process is a good exemplar of this issue. Traditionally, the design process was a serial activity with primarily an internal focus. It went from product conception to the design, manufacturing, and marketing of the product. Now, the importance of integrating customer needs into the design process is well understood, and the necessity of moving away from serial interdependence to a more simultaneous consideration of customer, designer, and manufacturing needs is becoming more apparent (Clark, 1991). Integration, both internally and externally, is what makes simultaneous consideration of these multiple needs possible. The consequences of good design processes are readily apparent. Producers with better externally and internally integrated design processes get goods to the market faster, are more responsive to customer needs, and produce goods with higher quality and productivity.

Another example of enterprise integration concerns the relationship between an organization and its suppliers and vendors. Traditionally, this was an arm's length relationship. Now, there are major forces to integrate suppliers and customers into the daily operation of the organization. "Just-in-time" environments demand a close association between the suppliers and the focal organization.

If our ultimate objective is to better understand organizational productivity,

we must pay attention to integrating the enterprise. This is not a well-researched area. In the past, much of the work in this area has focused on specific levels of analysis and on interventions to increase productivity at specific levels within the organization. The challenge in the 1990s is to understand the process of integrating external demands into the internal processes of the organization.

Increasing our understanding of the process of integration should increase our knowledge of productivity in organizations. However, this problem is challenging simply because of the scope of the problem statement. Enterprise integration focuses on the totality of the organization and all the relevant constituencies of its environment. Given the paucity of research in this area, we have identified research areas that would inform us about the enterprise integration process.

Research needs include the following:

• Investigating the role and consequences of technology. With the costs of buying and using computers declining and with the levels of computer power and networking capability increasing, technology will be a major factor in the integration process. Much of the early work in enterprise integration focused on internal integration of machines. The new challenges are using technologies to integrate operational planning and strategic decision making into a total operating system. Some of the research on electronic data interchange shows how certain types of external integration can improve organizational performance indicators (Kekre and Mukhopadhyay, 1992; Srinivasan et al., 1991). An important research endeavor will be to document the functional and dysfunctional consequences of this and other technologies in achieving internal and external integration. What types of information and transactions are necessary in this integrated enterprise, and how will electronic communication (versus other forms of communication) contribute to the productivity and quality of these information exchanges?

• Studying the process of coordination. Implicit in the concept of integration is the need to coordinate activities across varied constituencies. The design example, discussed above, involved different groups (customers, designer, manufacturer) who had different goals and interests. The tasks were to identify critical forms of information and to coordinate this information so as to optimize all the relevant processes (design, manufacturing, marketing). New theory and research on negotiation and coordination seem to be critical for understanding the broader question of enterprise integration (Malone and Crowston, 1994).

• Studying the process of developing new partnerships. The concept of enterprise integration is not grounded solely in technological solutions. Customers, suppliers, and firms all have different interests. Entering a collaborative arrangement requires some form of organizational change. These new organizational forms require new forms of reward, commitment, and structural relationship. How to define effective collaboration is an important research question that bears on our broader question of enhancing productivity in organizations (Kanter, 1991).

• Studying the effects of linking external and internal productivity. We have focused on the need for research on how productivity increases at the individual level lead to productivity increases at the organizational level. Our analysis, however, has been within the organization. Another approach would be to examine how productivity increases in the customer's or supplier's organization leads to productivity increases in the focal organization. If the focal organization intervenes in the customer organization to increase productivity, how do these productivity increases link back into the focal organization?

We have identified four broad research opportunity areas, describing each problem area and possible research topics. We believe that understanding these four areas is critical to understanding the general question of productivity in organizations. We think there is important and challenging research to be done in each area. We derived 15 research needs from these 4 opportunity areas. Each research need can be a point of departure for understanding organizational productivity.

Although we have focused primarily on productivity, we could have switched our focus to other criterion variables, such as quality. We also think the research issues generated in this chapter bear equally on many different organizational forms. The research questions are relevant to both manufacturing and service organizations, and to both profit and nonprofit organizations.

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