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White collar productivity.

Concern with the productivity of the white-colar work force has intensified over recent decades. Industries staffed principally by white-collar employees have expanded more rapidly than others. Between 1973 and 1983, employment in commercial banking gained 41 percent; in finance, insurance, and real estate exclusive of banking, 32 percent; in State and local administration, and legislative and judicial branches, 29 percent, in contrast to a 17-percent rise in total payroll employment. In manufacturing, the number of production workers declined 14 percent over the decade, but that of nonproduction workers--mostly white-collar staff--increased 12 percent. The expansion of white-collar work has insistently raised questions of how productively white-collar workers are employed. In turn, such questions have generated efforts to measure the productivity of white-collar workers.

The book, White Collar Productivity, features essays on a wide range of topics bearing on white-collar productivity. The authors address the problems and practices of measuring office productivity and office work, as well as management by objectives, control of overhead, human resource planning, paperwork reduction, and work unit analysis. They are concerned, then, primarily with the organizational and managerial foundations upon which efforts to improve productivity must build. They leave aside larger questions, such as the economic significance of growth in the white-collar work force, and the possible employment impacts of office technology. The relation of office productivity to office technology receives but cursory treatment. This review will focus upon some productivity issues raised by the book.

One of the chapters, written by Carl G. Thor of the American Productivity Center, deals with productivity measurement in white-collar groups. Two basic problems are addressed--the definition of output, and the acceptance of measuring productivity by "knowledge" workers (that is, professional and technical personnel). Output here is not construed as the final production or service of a firm. Instead, it is an intermediate activity. It relates to the work process or activity in which the white-collar employee is engaged. The relation between input processes and this intermediate output must be homogeneous, writes Thor. The work of typists in a steel mill cannot or should not be measured in terms of the steel tonnage the mill fabricates. Measurement of the typists' work must be linked to the process of typing by which a certain quantity of documents is produced.

Determining the productivity of an establishment's intermediate activities is akin to the measurement of the productivity of higher economic aggregates in that it may reflect changes in underlying factors--for example, a switch from manual to electric typewriters or word processors. Yet, reading Thor, the measurement of white-collar productivity seems basically to prepare for the formulation of work standards. This is implied by his discussion of task analysis of "knowledge" work, as well as of performance measures in a computer center. Task analysis requires the breakdown of given jobs, which may then be simplified and standardized for work measurement. Performance (or work) measures assume standards linked with a given technology; they are changed when the technology changes. Thor's productivity concept comes close to, although it is not identical with, work measurement. The book includes a chapter on work measurement, and more will be said about it further on.

A broader question might be raised here. Productivity measurement has traditionally had a variety or purposes, but these have differed in importance. central to government and academic measurement efforts of the post-World War II ear has been "to learn something of the process by which production is raised," as Solomon Fabricant put it in "Meaning and Measurement of Productivity." (John T. Dunlop and Vasilii P. Diatchenko, eds., Labor Productivity New York, McGraw-Hill, Inc., 1964, p. 20.)

This means that the host of factors that underlie productivity growth must be analyzed. A productivity measure may be based on one or more inputs--for example, labor, capital, materials. But also it is bound to reflect factors which affect input use, such as the way resources are combined, organizational changes, advances in knowledge, and knowhow. For such factors to be properly evaluated, output must be defined at a reasonably aggregative level, such as an industry, or even an establishment, producing a group of cognate products or services. Otherwise, the processes by which productivity--or "the power to produce"--is raised (or retarded) do not fully come into play. This also means that homogeneity of input processes with output is not a prerequisite for productivity measurement. Such homogeneity has only technical meaning, in the sense that workers in a given field depend upon specific tools and materials to produce an output. Their productivity hinges to a large extent upon nontechnical factors, such as the ones mentioned, and on developments in unrelated fields.

When such broader questions are addressed, output defined at highly disaggregated levels cannot yield productivity measures that are economically meaningful (although for purposes of work measurement such definitions may be serviceable). Let us again look at the example of typists at a steel mill. Does their work have meaning without the steel that the mill produces? No. Can the steel be made and marketed without the overhead represented in part by the typists? No. Overhead embodies the social nexus of production--payroll, marketing, purchasing, and accounting. Production cannot be carried on without the overhead activities, and overhead activities are meaningless without the production with which they are linked. The output of an economic unit results from combining the resources and operations of the two entities.

Thor briefly addresses the "sensitivity" of professional and technical workers to productivity measurement at the intermediate level. He recognizes that blue-collar workers may be equally sensitive. But blue-collar workers' output, Thor says, unlike white-collar workers', is "tangible," easily countable. Moreover, blue-collar workers have long experienced productivity measurement, they are accustomed to it. Thor does not tell us why blue-collar workers have indeed been so sensitive to productivity measurement, and why white-collar workers may be equally or even more sensitive to it. The reasons have been discussed in the industrial relations literature; they relate to fear of job loss if the standards which productivity measurement generates are not met; the frequent downgrading of jobs where jobs have been simplified; and the pressure to perform beyond specified standards. Productivity measurement and the task analysis to which, according to Thor, it gives rise, thus promotes the industrialization of white-collar work. "In countless banks and insurance companies a traditional clerical job with some variety--typing, correspondence, scheduling, filing, phoning--is broken down into its smallest component parts. One person then performs one small task over and over, often at a pace set by the computer and monitored electronically," writes Karen Nussbaum of the National Association of Working Women (In These Times, May 24-30, 1983). Similarly, A. B. Cherns, writing in the International Labour Review (December 1980) on the social effects of microelectronic technology, states that "Banks, insurance companies, and government offices, and many other organization have . . . used [the computer] in such a way as to fragment jobs and reduce the comployee's autonomy." It is not surprising then that white-collar employees may be quite as "sensitive" to productivity measurement of disaggregated activities as blue-collar workers.

Some writers see diseconomies in the office organized along industrial lines. Workers are dissatisfied, they become bored and tire easily; absenteeism and quit rates rise. In "Mechanization of Office Work" (Scientific American, September 1982), V. Giuliana urges that the "information office," with work stations where workers handle all aspects of accounts, replace the "industrialized" office. He would measure productivity in terms of worker effectiveness in satisfying customers. This approach does not seem to be the prevailing trend in the work organization of offices. But in the chapter on work measurement in White Collar Productivity, Robert E. Nolan appears to suggest this approach.

It seems puzzling why, when technology changes rapidly and chiefly in the direction of saving labor, work measurement remains so prominent a tool of productivity improvement. However, work measurement conceptually abstracts from changes in technology and other factors underlying productivity change. These engender new work standards, and work measurement is the means by which these standards may be implemented. The spread of work measurement to white-collar work has been spurred by the diffusion of data processing by computer. The computer can be keyed to generate performance data and to monitor adherence to performance standards. Nolan claims that the state of the art of white-collar work measurement is now such as to make it possible "to establish a form of accountability for virtually every job in the office," including jobs at technical and professional levels.

Does work measurement improve white-collar productivity? We cannot be sure. Office efficiency has been estimated to be as low as 50 percent by some industrial engineers (Delmar Karger and Franklin Bayha, Engineered Work Measurement, 3d ed., New York, Industrial Press, 1977, p. 739), hence even if work standards are not fully met, productivity gains result as performance approaches standards. (Nolan claims that costs may be reduced "to the tune of 20-40 percent of payroll costs.") However, efficiency gains from the elimination of slack cannot be repeated. Furthermore, problems associated with work measurement assert themselves. Nolan writes, "There are negative connotations . . not the least of which is getting people to work harder, [or] getting more work out of fewer people. Positive aspects are that work measurement is esential to high performance and high productivity."

Thus, there is a disjunction between the interest of employees and the interest of management. Nolan would overcome this disjunction by involving employees in setting standards. He is emphatic about this in discussing standards for the work of technicians and professionals who, he suggests, should set their own standards rather than have them set by specialists. However, work measurement inherently contributes to the routinization of work; and routinization is like a railroad tract, tolerating no deviation from gauge. This tendency is reinforced by Nolan's advocacy of the Methods-Time-Measurement System--a procedure which, as defined by its originator, "analyzes any manual operation or method into the basic motions required to perform it, and assigns to each motion a predetermined time standard, which is determined by the nature of the motion and the conditions under which it is made." Such a system leaves little discretion to the worker whose output is thus paced.

Work measurement systems have since their inception aroused the resistance of organized labor. In significant instances, unions have declined to recognize management prerogatives in this area, and insisted upon the cooperative setting of work standards and methods. The setting of work standards has been implicity if conditionally accepted by labor, but work measurement has almost invariably remained a controversial practice, whose scientific value, where claimed, has been persistently questioned. Nolan deals with this problem quite gingerly, pointing to first-line supervisors rather than to rank-and-file workers as displaying "poor attitudes" in respect to work measurement, and presenting obstacles to installing work measurement systems. He writes that these supervisors do not wish to be burdened with the recordkeeping tasks such systems require. It seems likely, however, that supervisors are less concerned with the paperwork than with employee resentment and the deterioration in the ambiance of the workplace which work measurement systems may bring on. Quantity of white-collar output may rise at the expense of quality of service and of a spirit of teamwork and cooperation. To paraphrase Cherns, work measurement fragments tasks to a degree that any imbecile can perform them; it should then not be surprising that only an imbecile will be happy performing such tasks.

The book is a valuable practical guide to current management thinking about how to deal with problems of white-collar output and productivity. But its approach is narrow in that it fails to deal with the broader meaning of productivity. It does not examine the effect of changes in white-collar technology on employment and productivity. Most important in terms of its frame of reference, it fails in pointing to ways of involving white-collar workers in structuring their own work and in initiating their own paths to higher productivity.
COPYRIGHT 1984 U.S. Bureau of Labor Statistics
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Author:Brand, Horst
Publication:Monthly Labor Review
Article Type:Book Review
Date:Sep 1, 1984
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