The world of work is changing at unprecedented rates. Although “digital transformation” has become a buzzword, new technology calls for updated skills and creates unique challenges for managing a virtual, global workforce. In the recent Society for Industrial and Organizational Psychology Top 10 Workplace Trends for 2020 survey (SIOP, 2020), nearly 1,000 industrial-organizational psychologists voted “The Changing Nature of Work” as the #5 trend that organizations are likely to face in 2020. Klaus Schwab, founder and executive chairman of the World Economic Forum, has called this era the Fourth Industrial Revolution: “characterized by a range of new technologies that are fusing the physical, digital and biological worlds, impacting all disciplines, economies and industries, and even challenging ideas about what it means to be human” (World Economic Forum, n.d., para. 3). This revolution coincides with an aging workforce, creating a dynamic context for person–environment (P–E) fit in the workplace.
Through the lens of Kooij et al.’s (Reference Kooij, Zacher, Wang and Heckhausen2020) conceptualization of aging at work, we share broad insights in this commentary from a recent research study on age-related differences in perceptions of the talent profiles required by the digital work environment and the competency potential of younger versus older individuals in the labor market. We then reflect on how those findings apply to their proposed process model. We discuss how the interface between perceived importance of competencies for specific jobs and actual competency potential scores of workers in these jobs may affect ability and motivation across both younger and older workers with respect to P–E fit, and we describe practical implications for organizations based on our research findings.
Research study overview
Our research study originated with the goal of better understanding the digital world of work such that we would be able to forecast the skill needs that will be required for the 21st century workforce while identifying the skill gaps in the available talent pool. As we analyzed the data, we realized that some of the most interesting insights were found when looking at generational differences, which we will briefly explain in this commentary. Two separate data sources were used to address our research questions.
First, using historical job analysis questionnaires administered over the last 10 years, we examined the nuances in how the critical skills required for successful job performance are evolving over time, specifically with respect to the differences in the perceptions of these critical skills by younger workers (defined as under 40 years old) compared with older workers (defined as 40 years and above). The data consisted of individual importance ratings of a variety of work behaviors that correspond to the Universal Competency Framework (UCF; SHL, 2019). This data source included 12 million data points from more than 800 separate job analysis projects, across more than 300 client companies.
After understanding differences in the perceptions of critical skills by age group, we complemented those findings by comparing competency potential scores across age groups in the same competency areas. Using the Occupational Personality Questionnaire (OPQ; SHL, 2018), a well-established personality instrument completed by over 1 million people each year, we investigated how competency potential scores differ across younger workers (under 40) and older workers (40 and above). The OPQ measures a broad-spectrum, trait-based occupational model of personality, which describes 32 characteristics of an individual’s preferred or typical style of behaving, thinking, and feeling at work. The OPQ uses Thurstonian item response theory with a multidimensional forced-choice item format. Competency potential scores were calculated from the 32 OPQ personality scales using standard equations mapped to the UCF that have been proven to predict performance in the workplace (Bartram, Reference Bartram2005). These competency potential scores are typically used as predictors of supervisor ratings of competency performance areas, with both the predictor and criterion measures mapped to the UCF. Using the standard equations to convert personality scores on the OPQ to competency potential scores allow the UCF to serve as the organizing framework for interpreting predictor–criterion relationships. Eight years of assessment data were included in this analysis, including 4.63 million candidates from nearly 6,000 client companies across more than 200 countries.
When aligning these two sources of data, an interesting picture emerged. We identified slight but consistent trends that illuminate the challenges and successes for older individuals in the workplace. Interestingly, the findings from the job analysis and assessment data sources yield somewhat conflicting conclusions but, when considered together, provide valuable insights for understanding the abilities and motivations of both younger and older individuals in the workplace.
Perceived importance of competencies can be considered analogous to the motivational aspect to continue working, as described in the process model proposed in the focal article. From the review of the job analysis data, there is a trend over the last 4 years toward younger individuals consistently viewing the competencies that are required for performance in the digital work environment as more important to job performance than do their older counterparts. Examples of these competencies include adaptability, resilience, creativity and innovation, and applying expertise and technology. This finding suggests that younger workers are more in tune to the demands of the digital work environment and suggests support for common stereotypes that younger generations are better suited to perform in the digital work environment. The observed gaps in importance ratings across age groups for these competencies are illustrated below in Figure 1.
Figure 1.
Mean importance ratings of competencies, younger versus older workers.
On the other hand, from the review of the assessment data, there is a trend over the last several years that older workers show slightly greater potential in those same competency areas (adaptability, resilience, creativity and innovation, and applying expertise and technology), suggesting that the older workers are actually somewhat more likely to be successful in the digital work environment than are their younger counterparts. Competency potential scores can be likened to the ability aspect to continue working, as described in the process model proposed in the focal article. The gap between competency potential for older and younger workers is greatest in two competencies (adaptability and resilience), both of which are listed among the Top 10 21st Century Skills by the New World of Work organization (2015). The observed gaps in competency potential scores, illustrating how much higher older workers scored in competency potential scores compared with younger workers on adaptability and resilience, are shown in Figure 2.
Figure 2.
Percentage of older workers who scored higher than younger workers on mean competency potential scores for adaptability and resilience.
Discussion of findings
The finding that older workers are more adaptable than younger workers seems to go against the common stereotype, but it is consistent with previous research. Kunze et al. (Reference Kunze, Boehm and Bruch2013) found that, contrary to popular belief, older workers are less resistant to change. Our study found that older workers demonstrate higher potential on creativity and innovation as well. Again, the general belief is that younger generations are more innovative, but previous research has also failed to find any evidence that older workers are less innovative than younger workers (Ng & Feldman, Reference Ng and Feldman2013). These are a few examples of misunderstandings that perpetuate stereotypes against older workers (SHRM, n.d.), potentially making it more difficult for these older workers to be successful. Older workers may need to overcompensate by engaging in proactive goal engagement to overcome these types of stereotypes in an effort to engage in the self-regulation behaviors required to achieve P–E fit (Kooij et al., Reference Kooij, Zacher, Wang and Heckhausen2020) and perform successfully in the digital work environment.
A potential explanation of our findings is that the older workers surveyed in our study achieved higher scores on the competencies known to be critical for the digital work environment because those who were lower in those competency potential areas were not able to maintain the levels of ability required to age successfully at work and self-selected out of the workforce through natural attrition. Although those older workers who are skilled in areas such as adaptability, resilience, creativity and innovation, and applying expertise and technology are likely to achieve the level of ability required to thrive in the digital work environment, their colleagues who have lower potential in these areas may struggle to engage in the self-regulatory behaviors necessary to achieve P–E fit. Through the self-regulatory process of adaptive goal disengagement described in the process model proposed in the focal article, some older workers might have decided to seek out new employment alternatives after experiencing misfit with their work environment as they gradually transition to retirement. This is likely to be a new phenomenon and may continue to increase in the future, as nontraditional employment arrangements are abundant with the recent rise of the gig economy. It is possible that older workers who experience misfit with their work environment are more likely to take advantage of these alternative employment opportunities, therefore leaving only the workers who are best fit for the digital work environment to remain in the older age group of the traditional workforce.
Practical implications for organizations
Based on our findings, we offer a few practical implications for organizations to facilitate P–E fit and help older workers age successfully in the workplace. These recommendations fall under the “meso level” of organizational factors in the model, as presented in the focal article (Kooij et al., Reference Kooij, Zacher, Wang and Heckhausen2020). By manipulating certain organizational factors (e.g., HR practices), organizations can influence employees’ perceived fit between the demands and needs of the workplace and what they have to offer the organization, ultimately helping employees maintain the ability and motivation to continue to make productive contributions to the success of the organization as they age.
The findings of our study suggest that older workers are more adaptable and resilient than they are generally believed to be. Research has shown that older workers are also more engaged and committed, leading to better business outcomes including improved performance and reduced turnover (AARP, 2015). These findings highlight the strengths of an aging workforce. Given these benefits, organizations should not overlook the advantages of an older workforce out of fear that this will cause misfit with the rapidly evolving work environment. Rather, organizations should actively work to discredit the stereotypes within the organizational culture, to remove potential barriers for older workers to be successful, and to clearly communicate that workers of all ages are valued.
Establishing mentoring relationships between older and younger employees is one way to communicate value as it demonstrates that the organization is invested in their employees (Hirsch, Reference Hirsch2017). Establishing a mentoring culture may prove to be beneficial to both older and younger workers. Younger workers can help to enlighten older workers about the changing demands of the digital work environment to help them better understand the needs or demands and increase their motivations to continue working, whereas older workers can help younger workers better prepare their abilities or supplies in the competency areas that are critical for success by sharing their practical tips that can only be gathered through long-tenured work experience. Creating or restoring a match between the understanding of needs and demands (where the older workers may be deficient) and availability of abilities or supplies (where the younger workers may be deficient), as detailed in the process model of successful aging at work (Kooij et al., Reference Kooij, Zacher, Wang and Heckhausen2020), can help workers of all ages achieve P–E fit.
Finally, organizations should seek to clearly understand and communicate the evolving expectations for performance in the new world of work. This may be particularly useful to older workers, who may not be as aware as are younger workers about what it takes to be successful in the digital work environment. Organizations can engage workers of all ages in current and future-oriented job analysis exercises and actively communicate the results, supported by an interpretation of how the needs and demands of the work environment have changed and how they are projected to evolve further in the future. If older workers can understand and anticipate changes to the work environment and the related expectations, they have a better opportunity to understand how they can serve those needs and demands and be active in self-regulation behavior to establish or restore P–E fit as the individual and the organizational environment both continue to evolve. This example is one possible practical application of the interplay between the work environment and personal factors that is integral to the process model of successful aging at work.
Conclusion
The process model presented in the focal article is a useful lens through which to conceptualize successful aging at work. Understanding the differences across younger and older workers in terms of both perceptions of performance expectations in the digital work environment and competency potential underscores the importance of both ability and motivation to continue working, as specified by the authors of the focal article, and extends this framework to shed further light on potential interventions for organizations to support workers of all ages in achieving P–E fit.
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The world of work is changing at unprecedented rates. Although “digital transformation” has become a buzzword, new technology calls for updated skills and creates unique challenges for managing a virtual, global workforce. In the recent Society for Industrial and Organizational Psychology Top 10 Workplace Trends for 2020 survey (SIOP, 2020), nearly 1,000 industrial-organizational psychologists voted “The Changing Nature of Work” as the #5 trend that organizations are likely to face in 2020. Klaus Schwab, founder and executive chairman of the World Economic Forum, has called this era the Fourth Industrial Revolution: “characterized by a range of new technologies that are fusing the physical, digital and biological worlds, impacting all disciplines, economies and industries, and even challenging ideas about what it means to be human” (World Economic Forum, n.d., para. 3). This revolution coincides with an aging workforce, creating a dynamic context for person–environment (P–E) fit in the workplace.
Through the lens of Kooij et al.’s (Reference Kooij, Zacher, Wang and Heckhausen2020) conceptualization of aging at work, we share broad insights in this commentary from a recent research study on age-related differences in perceptions of the talent profiles required by the digital work environment and the competency potential of younger versus older individuals in the labor market. We then reflect on how those findings apply to their proposed process model. We discuss how the interface between perceived importance of competencies for specific jobs and actual competency potential scores of workers in these jobs may affect ability and motivation across both younger and older workers with respect to P–E fit, and we describe practical implications for organizations based on our research findings.
Research study overview
Our research study originated with the goal of better understanding the digital world of work such that we would be able to forecast the skill needs that will be required for the 21st century workforce while identifying the skill gaps in the available talent pool. As we analyzed the data, we realized that some of the most interesting insights were found when looking at generational differences, which we will briefly explain in this commentary. Two separate data sources were used to address our research questions.
First, using historical job analysis questionnaires administered over the last 10 years, we examined the nuances in how the critical skills required for successful job performance are evolving over time, specifically with respect to the differences in the perceptions of these critical skills by younger workers (defined as under 40 years old) compared with older workers (defined as 40 years and above). The data consisted of individual importance ratings of a variety of work behaviors that correspond to the Universal Competency Framework (UCF; SHL, 2019). This data source included 12 million data points from more than 800 separate job analysis projects, across more than 300 client companies.
After understanding differences in the perceptions of critical skills by age group, we complemented those findings by comparing competency potential scores across age groups in the same competency areas. Using the Occupational Personality Questionnaire (OPQ; SHL, 2018), a well-established personality instrument completed by over 1 million people each year, we investigated how competency potential scores differ across younger workers (under 40) and older workers (40 and above). The OPQ measures a broad-spectrum, trait-based occupational model of personality, which describes 32 characteristics of an individual’s preferred or typical style of behaving, thinking, and feeling at work. The OPQ uses Thurstonian item response theory with a multidimensional forced-choice item format. Competency potential scores were calculated from the 32 OPQ personality scales using standard equations mapped to the UCF that have been proven to predict performance in the workplace (Bartram, Reference Bartram2005). These competency potential scores are typically used as predictors of supervisor ratings of competency performance areas, with both the predictor and criterion measures mapped to the UCF. Using the standard equations to convert personality scores on the OPQ to competency potential scores allow the UCF to serve as the organizing framework for interpreting predictor–criterion relationships. Eight years of assessment data were included in this analysis, including 4.63 million candidates from nearly 6,000 client companies across more than 200 countries.
When aligning these two sources of data, an interesting picture emerged. We identified slight but consistent trends that illuminate the challenges and successes for older individuals in the workplace. Interestingly, the findings from the job analysis and assessment data sources yield somewhat conflicting conclusions but, when considered together, provide valuable insights for understanding the abilities and motivations of both younger and older individuals in the workplace.
Perceived importance of competencies can be considered analogous to the motivational aspect to continue working, as described in the process model proposed in the focal article. From the review of the job analysis data, there is a trend over the last 4 years toward younger individuals consistently viewing the competencies that are required for performance in the digital work environment as more important to job performance than do their older counterparts. Examples of these competencies include adaptability, resilience, creativity and innovation, and applying expertise and technology. This finding suggests that younger workers are more in tune to the demands of the digital work environment and suggests support for common stereotypes that younger generations are better suited to perform in the digital work environment. The observed gaps in importance ratings across age groups for these competencies are illustrated below in Figure 1.
Mean importance ratings of competencies, younger versus older workers.
On the other hand, from the review of the assessment data, there is a trend over the last several years that older workers show slightly greater potential in those same competency areas (adaptability, resilience, creativity and innovation, and applying expertise and technology), suggesting that the older workers are actually somewhat more likely to be successful in the digital work environment than are their younger counterparts. Competency potential scores can be likened to the ability aspect to continue working, as described in the process model proposed in the focal article. The gap between competency potential for older and younger workers is greatest in two competencies (adaptability and resilience), both of which are listed among the Top 10 21st Century Skills by the New World of Work organization (2015). The observed gaps in competency potential scores, illustrating how much higher older workers scored in competency potential scores compared with younger workers on adaptability and resilience, are shown in Figure 2.
Percentage of older workers who scored higher than younger workers on mean competency potential scores for adaptability and resilience.
Discussion of findings
The finding that older workers are more adaptable than younger workers seems to go against the common stereotype, but it is consistent with previous research. Kunze et al. (Reference Kunze, Boehm and Bruch2013) found that, contrary to popular belief, older workers are less resistant to change. Our study found that older workers demonstrate higher potential on creativity and innovation as well. Again, the general belief is that younger generations are more innovative, but previous research has also failed to find any evidence that older workers are less innovative than younger workers (Ng & Feldman, Reference Ng and Feldman2013). These are a few examples of misunderstandings that perpetuate stereotypes against older workers (SHRM, n.d.), potentially making it more difficult for these older workers to be successful. Older workers may need to overcompensate by engaging in proactive goal engagement to overcome these types of stereotypes in an effort to engage in the self-regulation behaviors required to achieve P–E fit (Kooij et al., Reference Kooij, Zacher, Wang and Heckhausen2020) and perform successfully in the digital work environment.
A potential explanation of our findings is that the older workers surveyed in our study achieved higher scores on the competencies known to be critical for the digital work environment because those who were lower in those competency potential areas were not able to maintain the levels of ability required to age successfully at work and self-selected out of the workforce through natural attrition. Although those older workers who are skilled in areas such as adaptability, resilience, creativity and innovation, and applying expertise and technology are likely to achieve the level of ability required to thrive in the digital work environment, their colleagues who have lower potential in these areas may struggle to engage in the self-regulatory behaviors necessary to achieve P–E fit. Through the self-regulatory process of adaptive goal disengagement described in the process model proposed in the focal article, some older workers might have decided to seek out new employment alternatives after experiencing misfit with their work environment as they gradually transition to retirement. This is likely to be a new phenomenon and may continue to increase in the future, as nontraditional employment arrangements are abundant with the recent rise of the gig economy. It is possible that older workers who experience misfit with their work environment are more likely to take advantage of these alternative employment opportunities, therefore leaving only the workers who are best fit for the digital work environment to remain in the older age group of the traditional workforce.
Practical implications for organizations
Based on our findings, we offer a few practical implications for organizations to facilitate P–E fit and help older workers age successfully in the workplace. These recommendations fall under the “meso level” of organizational factors in the model, as presented in the focal article (Kooij et al., Reference Kooij, Zacher, Wang and Heckhausen2020). By manipulating certain organizational factors (e.g., HR practices), organizations can influence employees’ perceived fit between the demands and needs of the workplace and what they have to offer the organization, ultimately helping employees maintain the ability and motivation to continue to make productive contributions to the success of the organization as they age.
The findings of our study suggest that older workers are more adaptable and resilient than they are generally believed to be. Research has shown that older workers are also more engaged and committed, leading to better business outcomes including improved performance and reduced turnover (AARP, 2015). These findings highlight the strengths of an aging workforce. Given these benefits, organizations should not overlook the advantages of an older workforce out of fear that this will cause misfit with the rapidly evolving work environment. Rather, organizations should actively work to discredit the stereotypes within the organizational culture, to remove potential barriers for older workers to be successful, and to clearly communicate that workers of all ages are valued.
Establishing mentoring relationships between older and younger employees is one way to communicate value as it demonstrates that the organization is invested in their employees (Hirsch, Reference Hirsch2017). Establishing a mentoring culture may prove to be beneficial to both older and younger workers. Younger workers can help to enlighten older workers about the changing demands of the digital work environment to help them better understand the needs or demands and increase their motivations to continue working, whereas older workers can help younger workers better prepare their abilities or supplies in the competency areas that are critical for success by sharing their practical tips that can only be gathered through long-tenured work experience. Creating or restoring a match between the understanding of needs and demands (where the older workers may be deficient) and availability of abilities or supplies (where the younger workers may be deficient), as detailed in the process model of successful aging at work (Kooij et al., Reference Kooij, Zacher, Wang and Heckhausen2020), can help workers of all ages achieve P–E fit.
Finally, organizations should seek to clearly understand and communicate the evolving expectations for performance in the new world of work. This may be particularly useful to older workers, who may not be as aware as are younger workers about what it takes to be successful in the digital work environment. Organizations can engage workers of all ages in current and future-oriented job analysis exercises and actively communicate the results, supported by an interpretation of how the needs and demands of the work environment have changed and how they are projected to evolve further in the future. If older workers can understand and anticipate changes to the work environment and the related expectations, they have a better opportunity to understand how they can serve those needs and demands and be active in self-regulation behavior to establish or restore P–E fit as the individual and the organizational environment both continue to evolve. This example is one possible practical application of the interplay between the work environment and personal factors that is integral to the process model of successful aging at work.
Conclusion
The process model presented in the focal article is a useful lens through which to conceptualize successful aging at work. Understanding the differences across younger and older workers in terms of both perceptions of performance expectations in the digital work environment and competency potential underscores the importance of both ability and motivation to continue working, as specified by the authors of the focal article, and extends this framework to shed further light on potential interventions for organizations to support workers of all ages in achieving P–E fit.