Use of generational labels is spreading, as the temptation to lump vast numbers of individuals into categories based purely on birth year apparently proves too difficult to resist. The Army is unfortunately not immune. For all its recent progress toward more evidence-based approaches to talent management, defense leaders seem to accept and repeat myths about generations in the workforce. Baby boomers, Generation X, millennials, Generation Z, and now Generation Alpha—all of these allegedly have distinct characteristics associated with a window of birth years, known in scientific literature as cohort effects. Despite having captured the popular imagination since at least the 1960s, generations can be a misleading concept and do not provide a sound basis for shaping military personnel policy. Mismanaging age diversity puts the military services at risk of falling behind in the competition for talent, with recruiting shortfalls consequently creating secondary pressures to promote some young leaders too early. Defense leaders should avoid using generations as a shortcut for thinking about age and instead rely on more data-informed approaches to recruiting and talent management.

Shortfalls in recruiting understandably prompt leaders to look to social science to inform solutions to organizational problems, and generational concepts find a receptive outlet in the limits of human cognition. Although humans’ long-term memory capacity is expansive, working memory capacity is limited. Since cognition can only actively retrieve and operate with a limited set of information at any one time, grouping into categories is helpful. People routinely rely on categories and groupings to process more information, but this is beneficial only if the categories reflect meaningful commonalities in the real world. When the categories do not correspond to real shared characteristics, relying on them for management and decision-making can lead to systematic bias and predictable errors. Generations are one such grouping that serve as a shortcut in communication, even while they mislead and conceal.

The National Academies of Sciences, Engineering, and Medicine has extensively documented the limitations of scientific research on generations, demonstrating that most of the research cannot distinguish “generation effects” from age effects (i.e., developmental influences common during specific age periods, like young adulthood) or societal period effects (i.e., social influences common during, for example, a postwar period). Furthermore, researchers David Costanza and Cort Rudolph have identified how generational labels have spawned myths affecting workforce planning and management. For example, the notion that generations require unique management practices, or the notion that the millennials or Gen Z are uniquely disrupting work norms creates inaccurate expectations and potentially ineffective management practices.

Research indicates four hazards associated with generations as a construct for decision makers:

1. Generations obscure. The concept of generations implies that the categories are precise, when in fact they are not consistently distinguishable. Researchers are inconsistent in identifying where the cutoffs should be. Did Generation X start in 1961 or 1965? Does it include individuals born in the 1980s or not? When did the millennial generation start? Even as the Pew Research Center advocates using generations as an analytic tool, they acknowledge that “generations are often considered by their span, but again there is no agreed upon formula for how long that span should be.”

In addition, social science concepts of generations do not correspond to biological concepts of generations. In popular dialogue and in social science, generations are not genetically derived, but rather are socially constructed. If derived from genetics, they would likely be longer than they are defined by social scientists, differing by sex and over time. Further, defining a twenty-year age span as a generation obscures the maturation of the generation through multiple age groups at any given time, a current problem with understanding millennials who now span both young adulthood and middle age.

2. Generations oversimplify. Using generational groupings misleads by converting numerical continuity into discrete categories. Simplifying to generational labels, rather than understanding age to be a continuous variable, offers simplicity for convenience rather than accuracy. Defense leaders often use a generational label when they are really referring to age effects. When they say that Generation Z seeks purpose at work, do they mean that members of that generation will prioritize purpose over other features, like pay and predictability, for the rest of their working lives? Or do they just mean that young people prioritize purpose right now, as they are just starting their careers and may not yet have long-term financial commitments, like mortgages or children? This distinction is important because it shapes policy and resource decisions regarding compensation, assignments, and occupation choices.

3. Generations overgeneralize. Many generational analyses are simply socially endorsed stereotypes, disregarding the amount of variation within an age group. For example, one analysis by CNA identified characteristics of millennials as a distinct group, but also acknowledged that their technology exposure varied widely within the generation, countering the popular idea that people in this age group can uniformly be considered digital natives. These generalizations may encourage leaders to see members of a particular generation as more homogenous than they actually are, and risk becoming normative rather than merely descriptive. Younger members of the workforce may infer that they should behave according to a reported trend, such as that younger people are more narcissistic or more likely to switch jobs.

4. Generations overlook the impact of cultural shifts across the workforce, not just on young people. Major societal events broadly impact the population, something known as period effects, and singling out their impact on distinct generations neglects how these events affect the entire workforce. For example, young people may expect more flexibility in work hours and location following their experiences with online education and remote work during the COVID-19 pandemic. But older workers now similarly expect more opportunities for remote and hybrid work.

Generations provide a shorthand for talking about age, but they may harm more than they help. And they are unnecessary. There are at least three ways leaders can better deal with age differences in the workforce. First, they can simply talk about age, treating age as the continuous variable that it is. This approach allows for the possibility that young people may mature out of certain preferences and tendencies, whereas generational labels imply static characteristics unlikely to change over time.

Second, leaders and talent management practitioners can focus on the shared experiences that result from societal change and how those experiences affect the workforce. There may be differences in how age groups experience these events, but a focus on the events and experiences allows for variation within age groups and acknowledges change over time. Some events, like the widespread availability of generative artificial intelligence, will impact multiple age groups and multiple stages of the human capital life cycle—not just young workers, and not just one human resource function like recruiting or selection.

Third, incorporating behavioral science will help provide data-informed foundations for shaping talent management. As the National Academies of Sciences, Engineering, and Medicine report advocates, more rigorous research designs can help human resource and talent managers better distinguish age and cohort effects. These differences are important in providing enterprise leaders with appropriate policy recommendations for the challenges of a dynamic talent marketplace.

The Army has embraced simple typologies in the past, but, in recent years, has shown an ability to adopt more evidence-based talent management practices. For example, the Army used the Myers-Briggs Type Indicator in leader development for many years, in spite of more valid models of personality being available. However, more recently, the Army’s assessment programs have adopted instruments that more accurately capture individual variation in personality traits, rather than types of personality. Adopting more scientifically valid approaches for understanding age diversity will similarly help advance the Army’s goals of modernizing talent management. Although recent recruiting reforms are showing promise, further innovation will depend on an accurate understanding of age and other demographic characteristics, employing evidence-based approaches instead of generational stereotypes.

Allison Abbe is professor of organizational studies at the US Army War College and the Matthew Ridgway chair of leadership studies. Her research focuses on the development of leadership and intercultural skills in national security personnel. She has previously worked as a research psychologist and program manager in defense and intelligence organizations and holds a PhD in social and personality psychology.

The views expressed are those of the author and do not reflect the official position of the United States Military Academy, Department of the Army, or Department of Defense.

Image credit: Nathan Clinebelle, US Army (adapted by MWI)