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Building a Workforce for the Information Economy 2 Understanding the IT Workforce 2.1 WHO IS AN IT WORKER? As noted in Chapter 1, “information technology” is a broad term encompassing computer and communications technology. For purposes of this report, the committee is concerned about IT workers based on what they do. Specifically, IT workers are those persons engaged primarily in the conception, design, development, adaptation, implementation, deployment, training, support, documentation, and management of information technology systems, components, or applications. In addition to “computer occupations” described by the (mostly software) job categories of the Bureau of Labor Statistics (i.e., computer programmers, computer scientists, and systems analysts), this definition includes: Persons who design, install, upgrade, or maintain and support IT hardware, including computers, switches, routers, and chips with a digital aspect to their operation; Persons who design, author, adapt, test, implement, maintain, or support software or databases; Persons who install, configure, support, maintain, or utilize “back office” systems and applications for use by those who interact directly with these systems for business purposes; Persons who design, develop, document or train on, or implement computer-based business solutions for clients;
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Building a Workforce for the Information Economy Persons undertaking software-based enterprise resource planning or just-in-time inventory control and systems integration; Persons who write software code for embedded systems such as hand-held, palm-top devices or equipment controllers; Persons who develop design tools, simulation, and IT-intensive systems for the delivery of electronic content; Persons who are responsible for testing, documentation, or configuration management; and Persons who directly manage IT workers. Box 2.1 lists some sample titles of IT workers. Excluded are persons who work primarily with “front office” or end-user applications that are necessary to job functions not included in the above definition. For example, most office workers use word processors and spreadsheets, but they would not be considered IT workers in this definition.1 Help-desk personnel and technicians who install the PCs, networks, and software applications would be included. The committee has a number of reasons for choosing a definition based on what people do. To the extent that IT is a pervasive enabling technology that requires expertise to implement or to apply to specific business problems, IT workers are necessarily found in all sectors of the economy, not just the industries responsible for creating and developing IT. Thus, a definition based solely on industry of employment is inappropriate. 1 The reason for such an exclusion is that “users” of IT even heavy users—use IT for purposes that are secondary to their jobs. In other words, users of IT generally use IT in support of other job functions that are not related to IT per se. The business manager of an office may use spreadsheets in an extremely sophisticated manner, and the intellectual skills used may be those that characterize highly skilled programmers, but the primary purpose of his or her use of spreadsheets is to manage budgets in support of an office. By contrast, a Web page designer is included, even though his or her work relies in a similar way upon the use of Web authoring tools, because the primary purpose of the job is the management of IT-enabled electronic content. Also, workers such as the business manager described above are not generally the focus of concern that led to the commissioning of this report. Nevertheless, it must be acknowledged that distinguishing between the class of workers instantiated by business managers (excluded from the definition of “IT workers”) and the class instantiated by Web page designers (included in the definition of “IT worker”) is somewhat arbitrary. An additional complication arises when dealing with IT hardware. A semiconductor firm manufactures chips and integrated circuits for others to integrate into finished IT hardware systems. But a semiconductor manufacturing plant requires chemical engineers and process control engineers and materials scientists to design and maintain the production line. Such individuals are as critical to the semiconductor industry as are the designers of integrated circuits and microprocessors, but they are not what one might usually imagine when considering the term “IT worker.” The committee had no access to data relevant to such ambiguities, and thus such individuals are omitted from the analysis.
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Building a Workforce for the Information Economy BOX 2.1 Sample Titles of IT Workers Analyst Animator Applications analyst Applications developer Circuit design engineer Communications engineer Computer-aided design specialist Computer hardware engineer Computer operations manager Computer programmer Computer science teacher, postsecondary Computer security specialist Computer software engineer Computer systems analyst Data analyst Data warehouser Database administrator Database manager Design engineer Document specialist Help desk technician Integrated circuit design engineer Media specialist Microprocessor design engineer Network administrator Network engineer Network technician PC support specialist Program manager Programmer/analyst Project manager Software developer Software engineer Software quality assurance specialist System architect Systems administrator Systems analyst Systems engineer Systems integrator Technical writer Telecommunications systems engineer Telecommunications technician Two-dimensional/three-dimensional artist Web manager and Web administrator Web page developer
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Building a Workforce for the Information Economy To the extent that IT work does not require a formal background in information technology or computer science (and this extent is considerable), IT workers have a wide variety of educational backgrounds. Thus, a definition based solely on educational pedigree is inappropriate. To the extent that job titles do not reflect what IT workers actually do from day to day, job titles are inadequate. Indeed, IT work in the IT sector and in IT-intensive firms is much more varied for a given job title than in some other sectors such as construction or manufacturing. Thus, a definition based solely on job titles may not fully capture all IT workers of interest to the committee. Unfortunately, however, there do not exist data that identify workers based on what they do, although data do identify workers' industry, education, and/or job title. For this reason, and because job titles are developed as an attempt to capture what workers do, IT workers are in this report identified primarily based on their job title or occupation. Nevertheless, the committee recognizes that job titles often mask wide variation in what actually happens on the job for many workers. 2.2 THE NATURE OF IT WORK The nature and scope of IT work are highly diverse. All IT work draws to some extent on core or foundational knowledge, acquired either formally through classroom training or circumstantially through contextual application. Future development of IT workers at every level requires mastery of this core knowledge, often referred to as “IT literacy ” or “IT fluency.” For example, IT workers must generally have some facility with applications programs such as word processors, e-mail, Web browsers, and spreadsheets. They must also understand the basic purpose or application of algorithms, digital representation of information, and the basic technical aspects, features, and limitations of information technology systems. Most IT jobs require a mix of conceptual ability, knowledge of theoretical IT constructs and frameworks, and applied technical skills. The mix depends on the extent to which the job requires creativity and the invention of original work as compared to application of previously developed skills in typical situations. 2.2.1 Category 1 Work It is helpful to distinguish between two different types of IT work.
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Building a Workforce for the Information Economy Category 1 work involves the development, creation, specification, design, and testing of an IT artifact, or the development of system-wide applications or services; it also involves IT research. Such work involves conceiving of and sketching out the basic nature of a computer system artifact, or conducting research and development leading to new approaches to hardware and software. Category 1 work relies heavily on conceptual ability and theoretical knowledge, and also involves high creativity, self-discipline, and logical thinking, and often the ability to translate business and organizational needs to hardware and software systems specifications. Some job titles associated with primarily Category 1 work include computer scientist, entrepreneur, product designer, research engineer, systems analyst, computer science researcher, requirements analyst, system architect, system designer, programmer, software engineer, tester, computer engineer, microprocessor designer, and chip designer. Category 1 work results in the creation of a new product, service, or application, or even a new technology. But creation of new products, services, and applications has aspects of both conceptualization and implementation. For conceptualization, cognitive skills of evaluation, judgment, and synthesis are crucial. The conceptualization of an IT product or service is dependent on human insight and understanding, and the constraints within which a conceptualizer must work are limited only by imagination and the understanding of the problem to be solved. Category 1 work is often too complex to be performed by one person. Also, the path from determining a requirement to developing a product or service is not entirely sequential, and the events are not independent. An apparently small change in a functionality requirement, for instance, may result in big performance penalties. Providing more convenience features for users might create inadvertent security issues. Therefore, the ability of Category 1 people to work in teams, develop appropriate specifications, communicate effectively, visualize and anticipate, develop creative and original solutions to unique problems, and produce to specification in a timely manner in a rapidly changing technical environment is paramount. Category 1 work is therefore sometimes likened to playing music in ensemble. Not only must each person be extremely competent in his or her own right, but each must also understand the work of the other members of the team, and all must “play together. ” Finally, Category 1 work usually requires an individual to be able to manage complexity well. Today's IT systems are very complex artifacts, involving large amounts of highly sophisticated code, and the ability to maintain a good mental model of the relevant parts of a system —and how they interact with each other—is highly valued.
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Building a Workforce for the Information Economy 2.2.2 Category 2 Work By contrast, Category 2 work primarily involves the application, adaptation, configuration, support, or implementation of IT products or services designed or developed by others. In general, Category 2 work also requires the ability to support technical systems and to communicate with both equipment vendors and system users. Category 2 work relies heavily on technical skills related to specific platforms or applications software, and the ability to do Category 2 work depends on high levels of technical knowledge especially in areas of configuration, maintenance, installation, functionality, and system capabilities or constraints. Category 2 work entails an understanding of how applications are used, what conflicts might arise from coexistent applications, and how to work around systemimposed limitations and the capabilities of users. Category 2 work may entail the ability to use the end-user programming capabilities provided by the IT artifacts in question. And Category 2 work requires a knowledge of the business context in which the work is done. Some job titles associated with primarily Category 2 work include system consultant, documentation writer, customer support specialist, help desk specialist, hardware maintenance specialist, network installer, and network administrator.2 Category 2 work often demands well-developed problem-solving and troubleshooting capabilities. Individuals doing Category 2 work are the first (and often the only) resource when users have problems with applications or hardware. They are expected to size up the problem quickly, make correct judgments about the set of most likely solutions, and help test these solutions systematically until the problem is remedied. Hypothesis development and testing, good interpersonal skills, and excellent communication skills are a must for this work, and a well-developed understanding of and experience with typical problems and likely problem fixes enhances the value and productivity of Category 2 workers. 2.2.3 The Interaction Between Category 1 and Category 2 Work Both IT-sector and IT-intensive firms require employees who do both kinds of work, although the mix may differ. For example, software-producing companies would be expected to employ individuals doing a great deal of Category 1 work—senior-level programmers, applications 2 In addition to the technical support they provide, these individuals are often the point of contact for management on IT issues because they have day-to-day exposure to an organization's information technology infrastructure. Thus, they may find themselves part of the decision process, helping to determine whether, when, and how new applications are to be deployed. As a result, they can be important conduits for organizational learning.
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Building a Workforce for the Information Economy developers, software designers, and testers, all of which are critical to their core mission. However, they might outsource maintenance of their computers or administration of their corporate Web site to a third-party service provider, who would employ many individuals doing Category 2 work. Both Category 1 and Category 2 work are themselves highly differentiated. In Category 1, for example, development of software tools (e.g., programming language environments) that will be used by others to develop their own applications is different from the development of those applications themselves. Category 2 work also covers a wide range of work, and so, for example, troubleshooting a new network installation with hubs, routers, and servers requires significantly more technical knowledge and problem-solving ability than does stepping a user through a flowchart to figure out why a PC modem won't dial. As a general rule, two individuals with the same job title may well require different skill sets and background knowledge. Implementation is an aspect of IT work that straddles the border between Category 1 work and Category 2 work. As described above, Category 1 work involves the specification of performance requirements that reflect an understanding of what an IT artifact is supposed to do. Implementation, which can be regarded as work that simply creates an IT artifact designed by another party, thus is arguably Category 2 work. Implementation is also medium-dependent. For example, implementation of an IT artifact may need to be done in a specific programming language or for a particular database management system. Thus, implementation-related skills change as rapidly as the implementation medium changes, i.e., as fast as the underlying information technology evolves. And it is the case that exceptional technical knowledge is often needed for implementation. The development of new or faster operating system kernels, for instance, must occur with detailed knowledge of the architecture of the microprocessor on which the system will run. New processor design must occur in the context of the applications for the device. New applications must be developed with very detailed knowledge of user requirements, platform capabilities, and functionality issues. Systems integration work requires the ability to form clear pictures of how different components could fit together, the ability to anticipate what the interface issues might be, and knowledge of what the possible benefits or penalties of different options might be. To the extent that the underlying information technologies are “backwards-compatible,” learning of new skills is not especially necessary to implement the same product conceptualizations in the same way. But learning of new skills is always needed to take advantage of new features or capabilities enabled by improvements in IT. For example, the
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Building a Workforce for the Information Economy speed of microprocessors has increased by an order of magnitude over the past several years. Faster microprocessors enable new applications and functionality (e.g., speech recognition). Developers who wish to take advantage of newly available speech recognition capabilities enabled by faster microprocessors must clearly learn new skills. And, as the disparity between processor speed and secondary memory speed has increased, the consideration of techniques to lessen memory access and to manage and exploit memory hierarchies has become much more important and has made many software system design problems much more difficult. Because the skills needed for implementation can change with the technology, implementation can seem like Category 2 work. At the same time, the implementation of an IT product or service can require creativity and innovation. A variety of ways of implementing a given concept are possible, and these possible implementations differ considerably with respect to various dimensions of quality (Box 2.2), leaving a wide variation in the range of solutions that individual implementers will develop. In general, a very productive implementer is probably able, in the same amount of time as a less productive worker, to develop an implementation that is more robust, has more functionality, is easier to change and evolve, and overall embodies more of the “ilities” (e.g., flexibility, reliability, security). Furthermore, requirements specification and implementation do not necessarily proceed sequentially. Indeed, for the most part they do not proceed sequentially, but are rather highly intertwined. Nor are they independent of each other; sometimes, a small change in performance requirements can have a large impact on the ease or difficulty of implementation. And finally, because there are in general many different ways to implement a given specification, implementation can also involve considerable technical judgment and creativity. In this way, it is more like Category 1 work. 2.2.4 Category 1 and Category 2 Workers Any given IT worker is likely to do work that involves a mix of Category 1 work and Category 2 work. A good example is individuals who can be characterized as modifiers or extenders (e.g., maintenance programmers, programmers, software engineers, computer engineers, database administrators), who modify or add on to existing information technology artifacts. In the software domain, they write code based on design created by others, and they modify or tailor software to meet specific user needs. Note also that Category 1 work and Category 2 work both entail a need for skills in problem solving, time management, and interpersonal relationships.
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Building a Workforce for the Information Economy BOX 2.2 Productivity Variations in Software Developers In the software domain, there appears to be considerable variation in the productivity of software developers, The landmark study in this area, published in 1968,1 showed variations of more than 20 to 1 in the time required of programmers to solve particular programming problems, In addition, the fastest programmers developed programs that had fewer errors and were more efficient in both running time and utilization of memory than those of their counterparts. Thus, the fastest programmers were arguably more effective than would be indicated by their problem-solving speed alone, The results of other, more recent studies2 are consistent with the results of the Sackman study. Some detailed insight is provided in a study by Lutz,3 who found that the median program written by the top half of a group of graduate student programmers was 30 times as efficient as the median program written by the bottom half of the group (as measured by run time and memory use; the programming problem involved the conversion of telephone numbers into word strings). Further: The time used by the various programmers to code the programs varied by a factor of 20. The quality of a program was far more dependent on who coded the program than on the language in which it was implemented. Findings such as these—quite consistent over a wide range of studies—suggest that employers of IT workers have considerable incentives to find the most productive personnel. Measuring the quality of software produced can be problematic. One key reason is that such measures can generally account only for how a given set of requirements has been implemented in software—and not for whether those requirements capture any kind of functionality that is useful or helpful to users. Related is the fact that systems that have been tightly optimized for performance are often very difficult to change. Conversely, systems designed in a flexible manner almost always exhibit suboptimal performance. A second reason is that some measures of program quality may not be particularly valuable in the marketplace. For example, run time or resource usage may be less significant when the hardware on which programs run can provide rapidly growing increases in speed and resources such as memory. At the same time, software producers who wish to develop products that will run on a large installed base of hardware cannot exploit such growing resources fully, simply because many of their target platforms will not be new. 1 Sackman, H., W.J. Erikson, and E.E. Grant. 1968. “Exploratory Experimental Studies Comparing On-line and Off-line Programming Performance,” Communications of the ACM 11 (1):3-11. 2 Bryan, G. Edward, 1997, “Not All Programmers Are Created Equal,” in Richard Thayer, Software Engineering Project Management (second edition), IEEE Computer Society; Curtis, William, 1981, “Substantiating Programmer Variability,” Proceedings of the IEEE, July; DeMarco, Tom, and Timothy Lister, 1985, “Programmer Performance and the Effects of the Workplace,” pp. 268-272 in Proceedings of the 8th International Conference on Software Engineering, IEEE Computer Society Press, August. 3 Prechelt, Lutz. 1999. “Comparing Java vs. C/C++ Efficiency Differences to Interpersonal Differences,” Communications of the ACM 42(10).
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Building a Workforce for the Information Economy The fact that most IT workers engage in a mix of Category 1 work and Category 2 work means that the boundary between Category 1 and Category 2 workers is fluid. Category 1 work and Category 2 work are differentiated by the amount of formal education required, the degree to which conceptualization and invention apply to the core tasks, and the complexity of the tasks or the number of system components to be integrated. But people entering IT through Category 2 work have opportunities to acquire the additional higher education (through evening, weekend, and online courses) and experience to qualify for Category 1 jobs. Furthermore, the culture of IT work is one in which education and training, as well as experience, are richly valued intrinsically and well rewarded monetarily. For example, a small company with straightforward networking requirements would usually be able to meet its needs for the design, installation, and administration of a local area network (LAN) with workers who do primarily Category 2 work, because the requirements would fall within the conventional application parameters already anticipated and set forth by the hardware and software providers. However, expertise with such Category 2 work would provide a foundation for such workers to move to the design and management of enterprise-level LAN/WAN (wide area network), Web, or e-business applications that involve a large number of system components, a high level of risk, a large number of users, high data volumes, and a number of mission-critical and specialized applications. Such endeavors would naturally entail a greater degree of Category 1 work. A similar situation might pertain to programming and software engineering. Category 2 work in this area would typically involve the routine job of writing code to specifications developed by designers, or modifying existing code to fix bugs in the software. Expertise in such work would provide a good foundation on which to develop further expertise with Category 1 work in this area, which might entail developing the specifications for the program itself, or authoring software tools for other programmers to use in producing end-user applications. The close coupling of innovation and application is common in IT. The constant drive on the part of IT users to exploit new applications, or upgrade to the latest version of current applications, constantly challenges individuals doing Category 2 work, and staying current technically on the new features and attributes of applications software and network operating systems is important to such individuals. Thus, the coupling between innovation and application creates a robust array of career pathways that can lead to rapid advancement. For ease of discussion, this report defines Category 1 workers as individuals whose responsibilities involve a greater amount of Category 1 work relative to Category 2 work, and Category 2 workers in the opposite
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Building a Workforce for the Information Economy manner. Both are essential to the IT sector and IT-intensive firms. Category 2 workers, who work primarily at the applications and user level, would have nothing to apply if there were no software developers or engineers, no system integrators or analysts, no one to develop new hardware, or no one to pioneer new languages or applications. (One need only look at the boost Java has given the Web applications for proof of this.) Commensurately, there would be little economic justification for investing in the Category 1 work if new developments could not be moved rapidly to users and effectively applied—the purview of Category 2 workers. 2.3 INTELLECTUAL AND KNOWLEDGE REQUIREMENTS 2.3.1 Formal Education and Type of IT Work3 Category 1 work generally requires more years of formal education in IT-related disciplines than does Category 2 work. Some Category 1 work (algorithm design, for example) requires mathematical concepts and skills. Research on and development of new technologies and new products require a high level of specialized technical knowledge and skills, grounding in research methods, and access to research facilities. Other Category 1 work needs people with well-developed conceptual and abstract reasoning ability. Systems integration, systems analysis, and network design, for instance, require persons who can visualize outcomes, anticipate problems, and manage projects, budgets, and people. Historically, different kinds of formal education have been needed for different kinds of Category 1 work. Research in IT generally requires post-baccalaureate degrees in an IT-related field, as do certain types of development work (e.g., the development of software tools for use by others doing Category 1 work. But the general benefits of higher education (systems thinking, ability to generalize, abstract reasoning) have often enabled persons with baccalaureate degrees in disciplines ranging from mechanical engineering to music to be effective in many areas of Category 1 work, especially in IT-intensive firms. (The extent to which this historical trend will continue into the future is discussed in Chapter 7.) Category 2 work involving installation, maintenance, repair, or modification of an IT artifact generally requires skills that are based more on the specific characteristics of the particular software or hardware than on 3 This subsection draws on information in Freeman and Aspray (Freeman, Peter, and William Aspray. 1999. The Supply of Information Technology Workers in the United States. Washington, D.C.: Computing Research Association. Available online at <www.cra.org./reports/wits/>) and in NWCET materials.
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Building a Workforce for the Information Economy TABLE 2.4 New Students Entering Computer Science and Computer Engineering Departments in U.S. Institutions Awarding Doctoral Degrees in These Fields, 1995 to 1999 New Students 1995 1996 1997 1998 1999 Undergraduate 8,207 11,972 16,197 16,075 16,605 Master's 1,191 3,101 3,085 3,955 4,862 Doctoral 992 1,283 1,354 1,697 1,808 SOURCE: See source line, Table 2.2. TABLE 2.5 Degrees Granted in Computer Science and Computer Engineering in U.S. Institutions Awarding Doctoral Degrees in These Fields, 1995 to 1999 Degree 1995 1996 1997 1998 1999 Undergraduate 7,561 8,411 8,063 10,161 12,692 Master's 4,425 4,260 4,443 4,934 5,579 Doctoral 1,006 915 894 933 852 SOURCE: See source line, Table 2.2. (Figure 2.18). Based on the Taulbee data for 1996 to 1999 and the fact that about one-third of all 4-year computer science students attend institutions that offer advanced postgraduate study leading to a Ph.D.,27 the committee estimates that the total number of bachelor's degrees may increase to about 36,000 entering 2000. Table 2.4 also shows significant increases over the period from 1995 to 1999 in the number of new entrants into master's and Ph.D. programs in CS&E, with nearly a fourfold increase at the master's level and a doubling at the Ph.D. level. Data on total enrollments at the master's level, available only for 1998 and 1999, indicate that about 12,200 were enrolled for 1998 and 13,800 for 1999. According to the Taulbee data, the actual number of master's degrees awarded was constant at about 4,400 to 1997 27 The Taulbee surveys are taken from various issues of Computing Research News, published by the Computing Research Association (available online at <www.cra.org>). The 1995 CRA Taublee survey can be found in the March 1996 issue (Vol. 8, No. 2); the 1996 survey, in the March 1997 issue (Vol. 9, No. 2); the 1996-1997 survey, in the March 1998 issue (Vol. 10, No. 2); the 1997-1998 survey, in the March 1999 issue (Vol. 11, No. 2); and the 1998-1999 survey, in the March 2000 issue (Vol. 12, No. 2).
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Building a Workforce for the Information Economy FIGURE 2.18 Bachelor's and associate's degrees awarded in computer science, 1980 to 1996. SOURCE: NRC staff analysis. and then increased significantly in the next 2 years, to about 5,600 in 1999 (see Table 2.5). Such increased enrollments may indicate additional increases in degree production at those levels in the coming years. The picture at the Ph.D. level, however, is very different, as indicated by the declining number of doctorates awarded from the mid-1990s to 1999 (see Table 2.5). Total enrollment has also declined over the same period, from about 7,900 full- and part-time students in 1995 to about 7,100 in 1999 and a low point of 6,800 in 1997. Although the disparity between new enrollments and the number of Ph.D. degrees awarded may simply reflect the time required to earn a doctorate, it might also indicate that students are dropping out of Ph.D. programs to take employment in a very good job market. Across all institutions the number of degrees awarded in the mid-1990s was constant at about 10,000 for master's degrees and 1,100 for doctorates. If the Taulbee data on computer science and engineering enrollments can be extrapolated to enrollments across all institutions, then growth at the master's level to about 12,500 by the end of the 1990s might be anticipated. However, significant increases at the doctoral level in the late 1990s are unlikely, given that the Taulbee and the National Science Foundation data show no increases. It is possible, then, that at the start of the 21st century, the number of trained computer scientists added to the workforce yearly may stand at 36,000 with bachelor's degrees, 12,500 with master's degrees, and 1,100 with doctorates.
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Building a Workforce for the Information Economy 2.4.6 Distribution of Category 1 IT Workers by Size of Employer In 1997 in all industries, almost one-half of the Category 1 IT workforce (44.7 percent) was employed in large companies (more than 5,000 employees), and only 18 percent worked in small companies (fewer than 100 employees), as noted in Table 2.6. By contrast, about 36.6 percent of Category 1 IT workers working in companies that produce information technology or provide computer services are employed in large companies, and 26.9 percent are employed in small companies. As indicated in Table 2.6, in 1997 well over one-half of Category 1 IT workers (63.8 percent) were employed in companies with over 1,000 employees that were not IT companies such as Intel or Cisco, but were large product- or service-oriented companies. At the other end of the spectrum, small companies with fewer than 25 employees account for a substantial percentage of Category 1 IT employment (16.9 percent). Table 2.6 also shows that in 1997 the distribution of Category 1 IT workers in IT industries was very similar to that for all workers across all U.S. industries. TABLE 2.6 Number of Category 1 IT Workers and All Workers in Industrial Employment by Size of Company, 1997 Category 1 IT Workers Size of Company In All Industries (% of total) In IT Industries (% of total) All Workers in All Industriesa (% of total) Under 10 employees 68,416 (6.3) 58,871 (11.3) 775,727 (13.1) 10–24 employees 36,040 (3.7) 29,097 (5.6) 442,816 (7.5) 25–99 employees 72,361 (8.0) 52,369 (10.0) 654,231 (11.1) 100–499 employees 126,841 (12.3) 77,356 (14.8) 856,354 (14.5) 500–999 employees 56,344 (6.0) 31,014 (5.9) 340,300 (5.8) 1,000–4,999 employees 167,979 (19.1) 82,685 (15.8) 841,662 (14.2) 5,000 plus employees 446,585 (44.7) 191,332 (36.6) 1,999,429 (33.8) Total 974,566 (100.0) 522,724 (100.0) 5,910,519 (100.0) a“All workers” includes only those with bachelor's and higher degrees from U.S. educational institutions; the “industries” category does not include government or nonprofit employing institutions. SOURCE: See source line, Table 2.2.
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Building a Workforce for the Information Economy 2.4.7 Unemployment of Category 1 IT Workers According to the SESTAT data set, the rate of unemployment for graduates of computer science and computer engineering programs declined from 2.7 percent in 1993 to 1.2 percent in 1997. This low level of unemployment was comparable to that for all graduates—2.8 percent in 1993 and 1.4 percent in 1997. The data also indicate essentially no difference in unemployment among Category 1 IT workers of different age cohorts. However, the percentage of computer science and engineering degree holders who are unemployed and not seeking employment has been consistently held at 4 percent but has stood closer to 7 percent for all graduates. This lower rate for CS&E degree holders may imply that there is a smaller proportion of the unemployed computer science and computer engineering graduates who have given up looking for work and hence, a greater demand for such graduates than for others. Because BLS-measured “unemployment rates” count only unemployed individuals who are seeking work, they set a floor on the number of individuals who would be available to take IT work. Other categories of individuals who might be available for IT work include those with previous work experience in IT who currently hold jobs in other, non-IT fields that pay less than their previous job in IT and those who have become “discouraged” and are no longer (technically) looking for work and thus are not counted in official unemployment statistics. An examination of the SESTAT database in the period from 1995 to 1997 indicates that the number of Category 1 IT workers who took jobs in non-IT occupations is approximately twice the number of unemployed Category 1 individuals. 2.4.8 A Note About the Hardware Subsector Within Information Technology Although this report comments on workforce needs in hardware when possible, it devotes more attention to the software side of the IT sector. One reason is that the data sources available to the committee largely focus on aspects of the software and applications workforce. A second reason is that while IT hardware provides the platforms on which software and applications build, a very large number of different kinds of software and applications can be built upon a much smaller number of hardware platforms. Finally, many firms whose product lines were originally dominated by hardware production are increasingly involved in providing IT-related services. For example, Dell, originally a company that derived most of its revenues from hardware sales, is now beginning to provide Internet-based IT services. Thus, it is not surprising that the
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Building a Workforce for the Information Economy number of people engaged in software and applications work is significantly larger than the number engaged in hardware work. See Box 2.4 for more commentary. 2.4.9 Characteristics of the Category 2 IT Workforce Occupational clusters developed by the Northwest Center for Emerging Technologies (NWCET)28 provide a broad, up-to-date list of occupations that generally map the expansive territory of the Category 2 IT workforce. These clusters include occupations in database development and administration, digital media, enterprise systems analysis and integration, network design and administration, programming and software engineering, technical support, technical writing, and Web development and administration (Table 2.7). Unfortunately, it is almost impossible to try to map the list of NWCET occupations onto the occupational categories covered in the large, government data sets, such as the CPS, that provide demographic information about the U.S. workforce. The data illustrate the widely varying characteristics of individuals in a small set of CPS occupations who hold Category 2 jobs, although the committee emphasizes that generalization to the overall Category 2 IT workforce is not necessarily possible based on these data. Technical writers and data-processing equipment repairers are rapidly growing occupational groups. The number of technical writers, a group that includes both IT and non-IT workers, grew at a rate of 13.3 percent per year, from 33,000 in 1992 to more than 78,000 in 1999. The rate for data-processing equipment repairers was 12.6 percent annually, with an increase from about 146,000 in 1992 to more than 335,000 in 1999. Computer operators, by contrast, are a rapidly shrinking occupational group, with a decrease from about 641,000 in 1992 to 340,000 in 1999. The number of electrical and electronic technicians grew at a rate of 5.5 percent per year, from 316,000 in 1992 to 461,000 in 1999. Technical writers are well educated. In 1999, 59 percent held a bachelor's degree and 23 percent held master's degrees. By contrast, 76 percent of data processing equipment repairers and 86 percent of both electrical and electronic technicians and computer operators had less than a bachelor's degree. 28 Based at Bellevue Community College in Washington State, the mission of the North-west Center for Emerging Technologies is to advance information technology (IT) education to improve the supply, quality, and diversity of the IT workforce by preparing and educating versatile knowledge workers of the future. As part of this work, it has developed comprehensive skill standards designed in part to ensure that current 2-year IT education matches the requirements of the labor market. These are discussed at greater length in Chapter 7.
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Building a Workforce for the Information Economy BOX 2.4 Size of the Hardware IT Workforce The number of people working in hardware in the IT sector is much more difficult to estimate than the number working in software. The Bureau of Labor Statistics (BLS) captures software workers as “computer scientists, systems analysts, and computer programmers,” all of whom can work for software vendors or other IT-intensive firms that make use of software. IT does not, however, capture any IT occupations that are unique to IT hardware. The National Science Foundation's SESTAT database does include the category “computer hardware engineer,” but that category does not necessarily include the circuit and chip designers, manufacturing engineers, process control specialists, and other professionals who fabricate the components of IT hardware systems and integrate them into computer and telecommunications systems. Nor does it include any of the important support occupations associated with installing and maintaining hardware. SESTAT data on the number of individuals employed in this category in the mid-1990s are given in Table 2.4.1. Because IT-intensive firms generally do not produce hardware, professionals whose occupations are associated with hardware are generally found in IT-producing firms; these are generally Category 1 workers. But IT-intensive firms do employ many individuals whose role is to support hardware deployments (Category 2 workers). An upper bound on Category 1 workers in hardware is provided by BLS statistics on total employment in the semiconductor, telecommunications equipment, and computer equipment sectors (Table 2.4.2); however, these figures include lawyers and janitors and administrators as well as the technical workers who are the primary focus of this report. Informal estimates from senior industry executives in the semiconductor industry indicate that the fraction of technical professionals is about 22 percent, and the fraction of technical support workers about 44 percent. Estimates of the distribution for the telecommunications and computer equipment sector were unavailable, but if the fractions are comparable, a rough estimate as shown in the two right-hand columns of Table 2.4.2 can be made of the size of the hardware workforce. However, the Category 2 column total almost certainly understates the total number of workers with hardware support responsibilities, because the BLS baseline “total employment” figures shown do not include employees in IT-intensive firms. Clearly, Category 1 workers in hardware constitute a much smaller group than the Category 1 workers in software (among IT vendors) and applications (among IT-intensive firms). And it is likely, though less certain, that the Category 2 workers in hardware are similarly outnumbered by their counterparts in software and applications. TABLE 2.4.1 Employment in the Category “Computer Hardware Engineers” Year 1993 1995 1997 Total 44,970 47,799 47,368 SOURCE: National Science Foundation SESTAT data, 1993, 1995, 1997. TABLE 2.4.2 Estimating the Size of the Hardware Workforce Sector Upper Bound, BLS Data on Total Employmenta (June 2000) Category 1 IT Estimateb Category 2 IT Estimateb Semiconductors and related devices (SIC code 3674) 282,400 62,100 124,300 Telephone/telegraph apparatus (telecommunications equipment) (SIC code 3661) 123,000 27,000 54,000 Computer equipment (computers, storage devices, computer peripherals) (SIC codes 3571, 3572, 3577) 305,300 67,200 134,300 Total 710,700 156,300 312,600 aIncludes administrators and nontechnical personnel; figures are not seasonally adjusted and can be obtained from <http://stats.bls.gov/ceshome.htm>. bEstimates derived by the method described in the text. In 1999, technical writers and computer operators were relatively older, with each group having a median age of 44 years. The median age of electrical and electronic technicians was 35 and that of data-processing equipment repairers was 31.
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Building a Workforce for the Information Economy In 1999 in each of the above four occupational groups, fewer than 10 percent of the workers were foreign-born. By contrast, 17 percent of individuals in Category 1 occupations were foreign-born. For each of the above four occupational groups, the large majority of individuals are also white, but the percentage varies widely by group. In 1999, 96 percent of technical writers, 82 percent of data processing equipment repairers, 78 percent of computer operators, and 69 percent of electrical and electronic technicians were white.
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Building a Workforce for the Information Economy TABLE 2.7 NWCET Occupational Clusters and Related Skill Standards Career Cluster Representative Job Titles Sample Critical Work Function Sample Key Activity Sample Performance Indicator Sample Technical Knowledge Sample Skills for Employability Database development and administration Data analyst, database administrator Analyze and design database Perform research and analyze requirements Business objectives and goals for project are well defined Knowledge of basic business objectives and requirements analysis Ability to identify key sources of information Digital media Animator, 2D/3D artist, media specialist Produce visual and functional design Determine media types and delivery platform Chosen media elements and delivery platform support project goals and scope Knowledge of media types and capabilities Ability to present technical information Enterprise systems analysis and integration Systems analyst, systems integrator Define customer requirements Identify and document customer requirements Constraints are properly identified Knowledge of continuous quality improvement tools Ability to compare multiple viewpoints and analyze communication Network design and administration Network technician, network engineer Perform monitoring and management Monitor and report component, security, and connectivity problems System is closely monitored and outages are reported in a timely manner Knowledge of network architecture, topology, hardware, and software Ability to interpret and evaluate data Programming/software engineering Applications analyst, programmer/analyst, software engineer, software QA specialist Implement program Write code Code is developed using efficient software design processes Knowledge of programming language required for application Ability to write simple documents Technical support Analyst, help desk technician, PC support specialist Perform troubleshooting Analyze problem and research solutions Problem is correctly identified Knowledge of troubleshooting methods Ability to analyze and prioritize information Technical writing Technical writer, document specialist Design document Select style and tone Style and tone are appropriate for purpose, medium, and audience Knowledge of different writing styles Ability to present information persuasively and objectively Web development and administration Web page developer, Web site developer Perform content and technical analysis Research content Content is properly indexed and weighted by importance Knowledge of indexing and weighting techniques Ability to interpret communication and compare multiple viewpoints
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Building a Workforce for the Information Economy TABLE 2.8 Annual Rate of Change in Mean Wages for Selected Category 2 Occupations Selected Category 2 Occupation Annual Average Rate of Growth (loss) Technical writer 16.9% Electrical and electronic technician 5.6% Computer operator 4.4% Data processing equipment repairer (−1.6%) SOURCE: Current Population Survey, March Supplement 1996 to 1999. An increasing percentage of technical writers are female, up from 46 percent in 1995 to 62 percent in 1999. The percentages of females among computer operators has been relatively stable and was 63 percent in 1999. Electrical and electronic technicians and data-processing equipment repairers, however, were overwhelmingly male, at 86 and 82 percent, respectively, in 1999. Mean wages (in constant 1999 dollars) in the Category 2 occupations of technical writers, electrical and electronic technicians, and computer operators grew annually by amounts ranging from about 4 percent to 17 percent between 1996 and 1999, while wages for data-processing equipment repairers declined by almost 2 percent (see Table 2.8). 2.5 RECAP “Information technology” is a broad term encompassing computer and communications technology. For purposes of this report, IT workers are those persons engaged primarily in the conception, design, development, adaptation, implementation, deployment, training, support, documentation, and management of information technology systems, components, or applications. IT work is highly diverse. Most IT jobs require a mixture of conceptual ability, knowledge of theoretical IT constructs and frameworks, and applied technical skills. The mix depends on the extent to which the job requires creativity and the invention of original work (Category 1 work) as compared to the extent that it requires application of previously developed skills in typical situations (Category 2 work). Some types of work, such as implementation of a concept, can reasonably be characterized as both Category 1 work and Category 2 work. Furthermore, expertise in IT (as in many other domains) depends on both formal knowledge (that can be
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Building a Workforce for the Information Economy acquired in the context of formal education) and situated knowledge that is specific to a work or problem situation. Because most jobs require a mix of Category 1 work and Category 2 work, the boundaries between Category 1 and Category 2 workers is fluid. That said, Category 1 work tends to require more years of formal exposure to IT-related disciplines than does Category 2 work. This difference suggests that a significant increase in the supply of Category 1 workers is likely to take at least several years (i.e., the time needed for large numbers of these individuals to matriculate), while training efforts for Category 2 workers can—in principle—bear fruit in a matter of months. The size of the IT workforce is difficult to estimate. However, the committee estimates that the overall size of the IT workforce is at least 5.0 million, with approximately 2.5 million Category 1 workers and a number of Category 2 workers that is at least as large. The IT workforce has grown rapidly in the last 8 years, with the “core ” Category 1 workforce nearly doubling. Demographically, the Category 1 workforce is predominantly male, white, and younger than the workforce in general. And theCategory 1 workforce is highly educated, with most Category 1 workers having at least a bachelor's degree (though frequently not in an IT-related discipline). Real wages have grown in Category 1 occupations overall at a rate of about 3.8 to 4.5 percent annually since 1996, although this figure masks much more substantial growth in certain subspecialties and also does not include the impact of stock options and equity stakes on total compensation.
Representative terms from entire chapter: