a structure that works effectively across levels, functions, and jobs, as well as two of the common applications for talent management frameworks in recruitment and development.
I aim to demonstrate that there exists an inherent tradeoff between defining a framework that accounts for the intricacies between jobs and its usefulness for making sound talent management decisions. The role of the practitioner is to use his or her best judgment in weighing the pros and cons of each alternative, settling on the framework that will have maximum utility for the organization at this specific point in time. Right now, I believe that the pendulum has swung too far, with frameworks accounting for only a fraction of the employment relationship (focusing excessively on behaviors) and applying generic language across highly divergent roles. Together, these trends provide practitioners with the greatest opportunity to help their organizations reframe what top talent looks like.
Origins of Job Analysis
Modern day practitioners are not the first to be interested in the content and structure of jobs. The origins of job analysis are evident with the development of more complex and interdependent civilizations. For example, Imperial China had a long-standing tradition of regularly testing the worthiness of government officials. In 1115 BCE, six skill sets were defined as part of this testing regime, specifically writing, arithmetic, music, archery, horsemanship, and ceremonies and rites. As a second example from the other side of the world, Socrates in the 5th century BCE mused about the allocation of work in his description of the ideal state.
The first major work that can be considered a precursor to job analysis was completed in 1747. Diderot, busily writing his encyclopedia, was so disturbed by the lack of clarity around how jobs were defined in the trades, arts, and crafts that he took it upon himself to create a job classification system. Diderot kicked off a trend that would continue in France for nearly a century. Between 1780 and 1830, France defined an encyclopedia of occupations and the basic qualifications required for civil service, implementing bureau examinations to select the most suitable candidates. The British Empire was quick to follow, similarly focused on the civil service and the challenge of effectively managing colonies located around the world.
The late 19th century witnessed reform in the United States, initiated by Lincoln voicing his displeasure at the “inefficient and wasteful results of political appointments.” A firm tradition of assessing abilities and skills was thus established. The full potential of job analysis was not realized until it was applied beyond the civil service, coinciding with the establishment of Industrial Psychology as something different than other psychological disciplines. Early pioneers include Frederick Taylor, who relied on job analysis to fuel his principles of Scientific Management; Hugo Munsterberg and his quest to identify worker characteristics that would result in greater job fit; and Frank and Lillian Gilbreth with their development of time and motion studies (see Figure 1.1).
Figure 1.1 Image from Frank and Lillian Gilbreth’s 1918 Ball Brothers Mason Jar Study That Targeted How to Improve Worker Efficiency by Reducing Motion
A huge amount of momentum for job analysis was gained as an outcome of the First World War. The U.S. Army was keen to improve how soldiers were selected and placed into service (Figure 1.2). When the Great Depression hit, attention turned to utilizing worker abilities and getting the great masses of civilians back to work. The Social Science Research Council and the National Research Council sought to utilize job analysis to identify the core characteristics of jobs and how they differ by vocation. This work led the U.S. Employment Service to establish the Occupational Research Program in 1934, which sought to draft a Dictionary of Occupational Titles (DOT) and create a taxonomy of worker characteristics that could be used to select candidates. The program resulted in a taxonomy of forty-five characteristics used by states to hire and relocate staff, with the DOT itself published in 1939.
Figure 1.2 Image of U.S. Army Air Corps Cadets in 1942 Taking a Group Test to Help Determine Their Proficiency as Pilots, Navigators, or Bombardiers
Although interest in job analysis has remained steady, especially in light of Equal Employment Opportunity legislation, a major overhaul of the DOT did not occur until 1995, with the creation of O*Net. A consortium of prominent psychologists was hired by the U.S. Department of Labor to replace the DOT with a new classification of jobs that were representative of the U.S. economy. In addition to basic labor market information, O*Net provides a breakdown of each job by four categories.
● Worker Characteristics: Abilities, Interests, Values, and Styles held by the employee that are considered enduring and likely to influence their performance and acquisition of skills.
● Worker Requirements: Skills, Knowledge, and Education that are gained by the employee by either doing their jobs or in preparing for a career.
● Occupational Requirements: Tasks required by the employee and the Tools and Technology that he or she will likely utilize on the job.
● Occupation-Specific Information: Work Activities describing the behaviors expected from employees and the Work Context (aka environment) that they are likely to experience.
O*Net was an ambitious project and the final product contains 571 job elements across 821 detailed occupations. Such an array of job elements provides a mindboggling number of potential combinations, and practitioners are well aware of the value O*Net brings to their toolbox.
I have had the pleasure of working alongside one of the creators of O*Net. Wally Borman is an expert practitioner, having a résumé that would make anybody deeply envious. Wally is the “chief scientist” at PDRI, as well as a professor of IO psychology at the University of South Florida. He has penned over 350 publications, served as president for the Society for Industrial and Organizational Psychology, edited four professional journals, and above all, is one of the most genuine and supportive people I have worked with.
When writing this chapter, I arranged some time to speak with Wally about the creation of O*Net and what it strove to achieve. According to Wally, the motivation for O*Net was to get beyond the DOT, which had a clumsy underlying framework that failed to provide a true comparison between jobs and did little beyond providing generic job descriptions. True comparison between jobs, with rich and thorough taxonomy, was beyond the DOT and required a major rework.
To create the content used across worker characteristics, worker requirements, occupational requirements, and occupation-specific information, the O*Net designers relied on a combination of existing theory, logic, and their extensive practical experience working in the field performing job analysis. For example, O*Net’s taxonomy for work styles is based on the Big 5 personality model, which is the most highly researched and validated personality structure available today. Moreover, Wally was keen to point out that O*Net has a hierarchical structure that extends beyond the categorization of jobs. The hierarchy applies at a lower level to the work activities that drive these distinctions, accomplished by looking at differences among task complexity, importance, and frequency.
According to Wally, the greatest challenge in creating O*Net was not in drafting the content, but in gaining enough data to validate what was written. Realizing how enormous the task was of surveying job incumbents from each of the 821 jobs included in O*Net, the designers decided instead to opt for a practical approach. The designers targeted eighty jobs, which, surprisingly, made up 80 to 90 percent of people employed in the U.S. economy at the time. The design team went out to organizations with significant populations of employees working in these occupations and was warmly welcomed.
But the designers hit a roadblock. Despite a resounding initial interest from employers to participate, the response rate was shockingly poor, and solid data was captured for only thirty-five of the jobs. The design team went to Plan C and used other industrial psychologists to validate O*Net’s content.