Job analyses typically generate “snapshots” of a profession at a single point in time—yet work demands are constantly changing. We’ve pioneered the use of new methods, including AI-based approaches, that are helping address this challenge.
February 19, 2020 – Ironically, the ancient Greek philosopher Heraclitus may have captured the essence of 21st century work best with his pithy quote that “Change is the only constant.” From technological innovations and automation to the gig economy and shifting labor trends, myriad forces are collectively transforming the way work is performed and the knowledge, skills, and abilities (KSAs) workers need to be successful. From within this dynamic environment, a critical challenge emerges: How do organizations map the requirements of jobs that may be constantly evolving?
Despite their rigor, typical job analytic (JA) methods may provide an incomplete answer to this question. Though they clearly generate a wealth of useful information, the picture that most JAs paint reflects “one moment in time”—and even in relatively stable industries, that picture can quickly become outdated. Recognizing this dilemma, talent management professionals often ask another critical question: How often should JA information be updated to keep up with the “pace of change”?
There have been some valiant attempts to answer this question, with a recommendation emerging from them to update JA information every five to seven years. This may not be an optimal strategy in all cases, though, because the pace of change can vary quite dramatically across jobs—and even within a job’s various duties. Recognizing this nuance and complexity, we have employed several innovative methods to map the pace of occupational change that fall largely within two domains: 1) Tracking emergent job changes through AI-based methods, and 2) Forecasting how changes may differentially impact certain aspects of a job.