All too often, new technologies are introduced into the workplace without sufficient planning for their implications for the workforce. To the extent that businesses do plan for these implications, their approach is often governed by two related myths—the idiot-proofing myth and the deskilling myth. In each, technology plays a heroic role, rescuing efficiency from a workforce presumed to be unreliable. In the idiot-proofing myth, the hero is a machine so perfect that it is immune from the limitations of its users. System design based on this perspective is more concerned with how to keep operators from creating errors than with enabling operators to deal with the inevitable contingencies of the work process. The deskilling myth extends the idiot-proofing myth, offering a system so idiot-proof that the business can presumably get along not only with proportionately fewer workers, but also with workers who are on average less skilled and less expensive. Contradicting these myths, an emerging body of research suggests that in the vast majority of cases, new technologies will be more effective when designed to augment rather than replace the skills of users.

                        The key challenge in designing new technologies is how best to take advantage of users’ skills in creating the most effective and productive working environment. We call this the usability challenge. To meet the usability challenge, industry needs to develop more appropriate usability criteria and to implement more effective processes to assure usability. This book provides a background of concepts and experiences that can offer insight into defining these criteria and processes. This introductory chapter situates the usability challenge in its organizational context, develops some core concepts of usability, and outlines the subsequent chapters’ contributions. Our first task is to articulate more clearly what we mean by usability.


                          The design of systems for human use has long been associated with the discipline of “human factors,” in which the operator is seen as a component of a larger system, and the job of the designer is to produce an “interface” that ensures the most efficient fit of this component into the system. The premise of this volume is that we need a concept of usability that goes beyond the traditional model because this model suffers from at least four interrelated limitations. First, the traditional model treats the user primarily from a physical/ mechanical point of view. While physiological issues will always be relevant, the development of new technologies has forced us to focus on the cognitive and social aspects of users when designing equipment. As work has become less physical and more mental, the key criteria of effective worker performance have shifted from the speed or range of motion of their limbs to the quality and flexibility of their thinking. 

                             Unfortunately, the cognitive theories used in most human factors work focus on the lower levels of cognitive functioning— such as character recognition and mnemonic abbreviations—and are ill suited to understanding the higher cognitive functions of complex reasoning processes and social interaction. Second, the perspective usually adopted in human factors practice is one in which the human is viewed as a system component with a particular repertoire of actions and potential for breakdown. This view conceals the active role that people take in interpreting situations, in learning and adapting in their work, and generally in performing higher-level functions of monitoring and changing the system.

                           Design techniques suited to maximizing the throughput of a speed-limited processor are simply irrelevant to the task of augmenting the capacities of the worker to act as an observer and designer of actions. While the first two limitations constrain our understanding of the usability objective, the third and fourth limitations of traditional human factors pertain to processes for ensuring usability. The traditional human factors approach takes as given the basic form of the technology and asks how the details of a device can be modified to fit better the limits of human function. As a result, the typical human factors effort is given low priority among a design team’s objectives. Usability issues are often left to the latest possible date, by which time modifications are more expensive to make. This traditional industrial practice has shaped the human factors field: human factors engineers are more at ease in responding to a proposed design than in articulating usability criteria for, and contributing directly to, the initial design concepts. Finally, the human factors process has typically accorded the central role to engineering experts. 

                        The expertise of human factors engineers is seen as necessary to predict operating difficulties of which users may not even be aware, such as the long-term effects of poor posture. Users appear in such a usability process only as parameters of human performance identified in laboratory studies and summarized in handbook tables.

The traditional approach allows that, in extreme cases, the technical novelty of the system being designed might take the engineer beyond the envelope of prior research. In such cases, some user testing might be required to ensure usability. These expert-centered approaches may have made sense when the key usability issues were primarily physiological and lower-order cognitive ones. But when the effectiveness of a system depends on how well it supports higherorder cognitive activities and social interaction, there is often no substitute for direct user participation in the design process. The traditional criteria and processes may have sufficed at lower levels of automation, when there were often only a few ways to implement a given capability. With computer-based systems, however, usability is often the primary consideration in whether the design will be effective in use. For companies whose business is designing and selling new equipment, usability often determines market success or failure; for departments designing equipment for in-house use, efficiency and quality of use can have important competitive repercussions. By relegating usability to its traditional place, the conceptual design effort fails to come to grips with key issues that will govern the ultimate success of the equipment being designed.

                                     It is thus hardly surprising that seventy-five percent of companies that implement advanced manufacturing technologies do not achieve the performance they anticipated because of unforeseen problems with the interaction of human and machine (Corbett, Chapter 6 of this volume, citing Majchzrak, 1988). The pace of technological change today makes usability assurance both more important and more difficult. The expanding functionality of new generations of systems—especially computer-based systems—widens the gap between the performance of well-designed systems and that of poorly designed systems. At the same time, the increasing complexity of the new systems reveals the limits of our current understanding of what constitutes usability and how to design for it. USABILITY AND USE: THE LINK BETWEEN EQUIPMENT DESIGN AND WORK DESIGN Industrial practice in the area of equipment design has been hobbled not only by the narrow views of usability discussed in the previous section, but also by some invisible assumptions about the ultimate goal of equipment design. Designers have long been encouraged to assume that the most effective designs 6 USABILITY will be those that minimize reliance on users’ skills and users’ involvement in the production process. This belief is encouraged first by its consistency with the widespread deskilling myth, and second by the sociopolitical pressures that shape design.

                       First, viewed as an engineering and economic problem, this idiot-proofing approach reflects a commitment to the deskilling myth. It heels to the belief that automation will typically reduce not only the number of employees per unit of output, but also the average level of skill required of the users, and thus reduce the average per-hour labor cost. Although such a double gain can be obtained in a small minority of cases, a growing body of research shows that, in the majority of cases, the effective use of new technologies requires a workforce that is more skilled, not less (Adler, 1991). The most profitable way to use most new technologies appears to be two-pronged: invest in user training and broaden job responsibilities. The resulting improvements in productivity and quality greatly outweigh the added per-hour labor cost. Second, viewed as an organizational problem, the design of work and equipment is strongly influenced by the sociopolitical realities of industrial life. In practice, involving users in the design process is difficult: It takes time, and users’ input is often contradictory.

                  Moreover, as argued by an important stream of research following from Braverman’s seminal book (1974), asymmetric distribution of economic rewards, status, and power between managers and employees creates great tension in all aspects of job and equipment design. For research on designing for usability to benefit industrial practice, we must be sensitive to the organizational context in which the research results might be implemented. In order to better understand the forces shaping this context, let us describe a prototypical situation—one that is depressingly common—in which employees resist and even sabotage the implementation of new technology, and managers insist that work design and equipment design minimize user skill requirements and job responsibilities.


                    In this hypothetical situation, managers see employees as recalcitrant and unreliable. Whatever the accuracy of this perception, it leads to a self-fulfilling prophecy. Managers adopt policies and behaviors that give employees every reason to act in recalcitrant and unreliable ways, thus confirming managers’ beliefs (Walton, 1990). Managers’ distrust of employees is mirrored in employees’ distrust of managers. Employees contribute to tensions when they fear that their work will be deliberately regimented by new technologies and that they may be laid off as a result of investments in automation. Managers fear that any guarantees to protect workers against layoffs will weaken the effectiveness of the sanctions they use to buttress their managerial authority. Without such protection, employees become very reluctant to accept flexibility in job assignments. The union, on the defensive, therefore clings to existing job definitions and skills and opposes reorganization.

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