Already replacing human labor in many factories, automation--machinery and management systems controlled and integrated by computers--is on the verge of reshaping the workplace.
But even after years of study, the effects of automation on work are not well understood. Indeed, debates still rage between enthusiasts and critics: Advocates argue that it will free workers from repetitive, heavy, and dangerous assignments to undertake more creative work, while opponents believe that it will de-humanize work, enslaving operators with tight control and low wages.
Faced with the contrasting implications of these views, educators do not know how to respond to automation. Does operating a computer-controlled machine require more skills or fewer? Breadth of scope or depth of knowledge? With little information and less agreement on the answers, educators often react in the easiest manner--by purchasing computers and advanced automated equipment and teaching students how to use them.
But that response begs the question of how automation affects work. It treats automation as an extension of mechanization that can be addressed by adjustments in the acquisition of skills--when in fact it often produces a fundamental change in relationships among employees, employers, and machines. To accommodate such a change, educators must consider a restructuring of curricula and educational philosophy, not just added courses.
Indeed, firms using new technologies want a different type of worker--and an education appropriate for the automated system. The spread of automation requires turning the most job-specific forms of education back to the company and concentrating in schools on broader skills and knowledge.
To better understand the effects of automation on work and their significance for education, the Southern Technology Council--formed by the governors of 12 Southern states to address issues of science and technology--conducted a study of manufacturers in the rural South. A questionnaire sent to businesses sought information about factors affecting decisions to automate and about changes in the workplace resulting from such shifts. Follow-up case studies were conducted in eight of the sites, including two Japanese-affiliated companies.
The study found that the impact of automation for workers cannot be discussed simply in terms of their needing fewer--or more--skills. Automation does simplify some functions and add complexity to others. But more important, the automated workplace requires qualitatively different skills and behaviors.
A common mistake is to view automated processes merely as new ways to alter the form of matter. “Hard’’ technology is not the only important addition to the workplace. In fact, new skills are more apt to be attributable to “soft’’ technologies--innovations in organizing and managing business, often influenced by the success of Japanese manufacturing and by global competition. Examples include “just in time’’ inventory methods for reducing the need to maintain stock, statistical process control for sampling products and understanding variations in quality, participatory management, and customized production.
The need for new skills, the study found, arises from a variety of technological factors. First, businesses are seeking greater flexibility as they move toward customized manufacturing. Whereas the most progressive manufacturers once aimed for large production runs to achieve economies of scale and lower unit costs, their goal now is small runs to gain economies of scope and greater responsiveness to market demand. To attain the needed flexibility with computer-integrated production, they reduce the number of job classifications and organize production around teams responsible for a product--not around the sequential, independent tasks of the past.
Operators of automated processes are expected to perform more varied tasks, including work previously done by several employees holding a range of different job classifications. In an automated factory, a single worker might set up a machine, monitor quality, and make adjustments, as well as operate the equipment. Rather than being controlled by rates of production--as in the traditional factory--the operator, within limits, controls production.
In one rural county where, according to the 1980 census, more than three out of every five adults had less than eight years of education, a new plant trained prospective employees to “know the entire operation, even if the problem is somebody else’s operation, ... [to] have a basic understanding of how everything works.’' The company’s training began with remedial math and did not end until the employee was proficient in statistical methods and was able to interpret control charts.
A second factor dictating the development of different skills is the necessity of workers’ understanding how to respond quickly to errors in a computer-integrated system and how to predict their impacts downstream.
Despite the glowing promises for new technologies made in trade journals and marketing brochures, automated equipment rarely works as well on the factory floor as it does in the vendor’s showroom. Adjustments to the programming must be made routinely.
One company, for example, introduced welding robots--assuming that they could just be monitored by employees with little education. It quickly discovered, however, that the welding programs required frequent adjustments, and that the only way it could maintain production rates was to employ operators who could analyze problems and edit programs themselves.
Third, successful businesses are beginning to realize the degree to which an employee’s knowledge and experience can contribute to innovation. In fact, most gains in productivity are not the result of introducing new automation but of improving the use of technology already present. Such refinements are as likely to come from an operator or technician as an engineer or manager.
The quality circles observed at most of the sites attempted to systematically incorporate the knowledge of workers in planning production.
The results of the council’s examination of the automated workplace were overwhelmingly positive. The survey of more than 50 production managers indicated that work with new technologies requires more high-order skills and flexibility, and provides more participation in operating decisions than does work in traditional manufacturing.
The new roles for workers have changed businesses’ expectations of the schools: They want graduates with a solid grounding in the basics.
Reinforcing the recent calls for reform by corporate heads, this thinking is hardly a major surprise. What is new, however, is that the requests are coming not only from enlightened leaders but also from personnel managers and first-line supervisors at the plant level, who in the past asked for--even demanded--job-specific training.
In the automated plant, supervisors no longer expect a new worker to be able to operate specific equipment. They rely on their vendors (84 percent of the firms in the study) and in-house training (98 percent) for developing skills.
Instead, managers in the study asked for “that intangible ability to learn,’' “people who demonstrate a thinking process,’' and “a willingness to learn.’' According to one supervisor, 95 percent of the job-specific skills have to be learned on the job. It is up to the schools, he said, to provide the fundamental knowledge and the ability to learn on the job.
In part, the return to basics reflects the frustration of managers in their efforts to retrain present employees to work with new technologies. Companies found that most workers lacked the mathematical and scientific skills to be taught, for instance, statistical process control.
Seven of the eight visited sites had to teach remedial math--simple operations in fractions and decimals--before they could begin retraining. This may not be surprising, given that in 1984 only 1 in 4 high-school vocational-education graduates had taken geometry, and less than 2 in 100 had taken trigonometry or physics.
Companies, of course, expect much more than the basics. As desirable background for employees, nearly all those interviewed listed statistics and process control, manufacturing concepts, including micro-economics, basic electronic theory, and communications. They also valued willingness to accept responsibility, ability to solve problems, and readiness to take initiative.
Most of the firms, however, did not feel the schools understood these needs well enough or had the capability to meet them. Only two of the eight sites visited had strong ties to local vocational schools, and only 30 percent of those surveyed rated public schools as important factors in their decisions about automation.
Greater responsibilities for workers indicate the need for a less structured educational environment. For example, fewer job classifications in the factory ought to lead to fewer classifications of vocational programs. Schools must place more emphasis on the learning process and on leadership. And increased requirements in industry for math, English, and science suggest that high schools must devote more time to these disciplines, and that technical proficiency in manufacturing necessitates postsecondary vocational education.
Innovation is the key to the success of American industry. Yet too many high-school graduates today are ill-equipped to function confidently in an automated workplace. Educating for the factory of the future will give technical graduates the opportunity to be innovators--to make increasingly effective use of technology, rather than merely react against it.
