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Managing White-Collar Work: an Operations-Oriented Survey

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Managing White-Collar Work: an Operations-Oriented Survey PRODUCTION AND OPERATIONS MANAGEMENT POMS Vol. 18, No. 1, January–February 2009, pp. 1–32 DOI 10.3401/poms.1080.01002 ISSN 1059-1478|EISSN 1937–5956|09|1801|0001 r 2009 Production and Operations Management Society Managing White-Collar Work: An Operations-Oriented Survey Wallace J. Hopp Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109, [email protected] Seyed M. R. Iravani Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208 [email protected] Fang Liu Management Science Group, Merrill Lynch, Global Wealth Management, Pennington, NJ 08534, [email protected] lthough white-collar work is of vast importance to the economy, the operations management (OM) literature A has focused largely on traditional blue-collar work. In an effort to stimulate more OM research into the design, control, and management of white-collar work systems, this paper provides a systematic review of disparate streams of research relevant to understanding white-collar work from an operations perspective. Our review classifies research according to its relevance to white-collar work at individual, team, and organizational levels. By examining the literature in the context of this framework, we identify gaps in our understanding of white-collar work that suggest promising research directions. Key words: white-collar work; operations management; survey History: Received: July 2006; Accepted: May 2008, after 2 revisions. 1. Introduction and 21.2%, respectively, from 2004 to 2014, which Operations management (OM) is concerned with the ranks them as the third and first fastest growing processes involved in delivering goods and services occupation categories.1 This trend suggests that future to customers (Hopp and Spearman 2000, Shim and economic growth will depend much more on improv- Siegel 1999). At the core of many of these processes is ing productivity of white-collar work than on the work of human beings. Indeed, the field of OM achieving further improvements in blue-collar work has its roots in the labor efficiency studies of Frederick productivity. W. Taylor and other champions of the Scientific Man- Despite the obvious importance of white-collar agement movement of the early 20thcentury. Because work to the economy, it is much less understood these early studies focused on the physical tasks in in an operations sense than is blue-collar work. manufacturing, construction, and other industries, the Well-known principles of bottleneck behavior, task OM field developed a tradition of studying what sequencing, line balancing, variability buffering, we colloquially call ‘‘blue-collar’’ work. The dramatic and many others (Askin and Goldberg 2002, Hopp improvements in direct labor productivity over the and Spearman 2000) help us evaluate, improve, and past several decades suggest that this line of research design systems involving blue-collar work. But in has been highly effective. systems where white-collar work predominates, in However, in recent years, the US economy has which tasks are less precisely defined and controlled steadily shifted toward service and professional jobs than in blue-collar systems, we do not yet have prin- that we associate with ‘‘white-collar’’ work (Spohrer ciples for guiding operations decisions. Fundamental and Maglio 2008). Workers in such jobs now constitute questions remain unanswered. For example: What is 34% of the workforce according to the Bureau of the bottleneck of a white-collar work system? What Labor Statistics (BLS) (Davenport et al. 2002). Further- are appropriate measures of productivity? How do more, according to the BLS, workers in ‘‘management, learning and collaboration affect performance? To an- business, and financial occupations’’ and in ‘‘profes- swer these and many other questions, the OM field sional and related occupations’’ will increase by 14.4% needs to expand its scope and methods to facilitate 1 Hopp, Iravani and Liu:: Managing White-Collar Work 2 Production and Operations Management 18(1), pp. 1–32, r 2009 Production and Operations Management Society operations analyses of systems in which white-collar To do this, it is important to recognize that all work is an essential component. individuals do many types of work. Indeed, some A variety of fields, beyond OM, including Econom- researchers have argued that new technologies have ics, Sociology, Marketing, and Organizational Behavior, transformed work in such a way that traditional have produced streams of research relevant to white- distinctions between white- and blue-collar workers collar work. While these have not focused on opera- have been rendered obsolete (Barley and Kunda tions issues directly, research in these fields has yielded 2001, Zuboff 1988). Management practices, such as useful insights that could be useful in operations con- empowerment and self-directed teams, have given texts. In this paper, we survey a wide range of research even the most basic physical workers decision making that offers promise for understanding the operations of responsibility, while information technology (IT) has white-collar work. Our objectives are to bring together given virtually every job an element of knowledge these disparate threads, provide a framework for or- work. However, while it may no longer make sense to ganizing them, and identify needs and opportunities classify workers as blue and white collar, we believe for developing a science of white-collar work. there remains a fundamental distinction between the two types of work at the task level. The routine, repet- 2. Definition of White-Collar Work itive, largely physical tasks that were the basis of To achieve these objectives we must first define what traditional blue-collar work are still essentially differ- we mean by white-collar work. Historically, the term ent from the non-routine, individual, heavily ‘‘white collar’’ has been used loosely to refer to knowledge-based tasks we associate with traditional salaried office workers, in contrast with hourly white-collar work. Consequently, we focus on the ‘‘blue-collar’’ manual laborers (Shirai 1983).2 Other tasks involved in the work (e.g., financial consulting, definitions of white- and blue-collar work are based operating machine tool) rather than on the workers on whether the worker performs manual work. For (e.g., financial advisors, machine tool operators). example, Prandy et al. (1982) used the term ‘‘white Viewed in this way, someone we customarily think collar’’ to refer to non-manual labor, e.g., supervisors, of as blue-collar worker may perform white-collar clerks, professionals, and senior managers. Still other tasks (e.g., a machinist brainstorms methods for definitions of white-collar work have focused on job improving the yield of his operation). Conversely, categories. For example, Coates (1986) divided white- someone we normally think of as a white-collar collar work into three categories: clerical, professional, worker may perform blue-collar tasks (e.g., a profes- and managerial. Because of the nature of the work, sor makes her own photocopies). Hopp and Van Oyen some scholars have equated white-collar workers with (2004) defined a task as a process that brings together knowledge workers (McNamar 1973, Ramirez and labor, entities, and resources to accomplish a specified Nembhard 2004). In this vein, Stamp (1995) summa- objective. In this very general definition, labor refers rized eight important aspects of white-collar work: (1) to workers (e.g., machinist, doctor, cashier, banker). surfacing and aligning values and vision, (2) thinking An entity represents the job being worked on (e.g., strategically, (3) focusing key resources, at the same part, patient, customer, financial transaction). Re- time maintaining flexibility, (4) managing priorities, (5) sources include anything used by labor to carry out measuring performance, (6) accepting ownership, re- the activity of the task, such as equipment (e.g., sponsibility, and accountability, (7) influencing, while machines, computers), technology (e.g., algorithms, maintaining interpersonal awareness, and (8) contin- systems infrastructures), and intellectual property ually improving people, products, and processes. (e.g., books, reports, outside expertise). Although these definitions give a general sense of A task is defined by these three elements – labor, what constitutes white-collar work and how it differs entities, and resources – as well as the processes that from blue-collar work, they do not provide a precise or describe how they are brought together. For our consistent statement that we can use to focus research purposes, whether a task is classified as blue or on the operations of white-collar work. For example, white collar depends on how it is characterized along Coates (1986) classified clerical work, such as typing, as two dimensions: white-collar work. However, typing does not have any of the eight features of white-collar work as defined in 1. Intellectual vs. Physical: White-collar tasks involve Stamp (1995). Moreover, from an operations perspec- significant use of knowledge in generating ideas, tive, typing has much more in common with machining processes or solutions (Davenport and Prusak (commonly thought of as ‘‘blue collar’’) than with 2002), while blue-collar tasks consist primarily of management (commonly thought of as ‘‘white collar’’). physical transformations or transactions. In these To study the operations aspects of white-collar work, terms, a data analysis task is intellectual
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