Keisha Benson Woods
Abstract
The modern workplace is dynamic and diverse, with five generations—Traditionalists, Baby Boomers, Gen X, Millennials, and Gen Z—working side-by-side. Organizations must navigate workforce challenges, including advancing technological skills, addressing generational biases, and promoting diversity, equity, inclusion, and accessibility (DEIA). Reverse mentoring offers a solution by pairing younger employees as mentors to older colleagues, fostering a two-way exchange of knowledge and skills. This article examines how reverse mentoring impacts job satisfaction, employee engagement, and retention among older IT workers. The study evaluates the extent reverse mentoring (affective commitment, continuous commitment, normative commitment) relates to the retention (job satisfaction, intent to leave) of older workers Using theoretical frameworks (Social Exchange Theory (SET), Leader-Member Exchange Theory (LMX), and Perceived Organizational Support (POS)) this research demonstrates reverse mentoring’s ability to bridge generational gaps, promote cross-generational collaboration, and support organizational goals. Key findings highlight that reverse mentoring increases engagement, supports knowledge transfer, and mitigates risks such as turnover and disengagement. Drawing on quantitative analysis, the article offers evidence-based recommendations, including integrating reverse mentoring into DEIA strategies, providing structured training, and leveraging pulse surveys to evaluate program effectiveness. Reverse mentoring emerges as a powerful tool for fostering inclusivity, collaboration, and long-term organizational success.
Introduction
The modern work environment is dynamic, diverse, and continuously evolving, shaped by technological advancements, globalization, and shifting workforce demographics. Organizations must navigate flexible work models, diversity, equity, inclusion, accessibility (DEIA) priorities, and increasing demands for mental health and wellness initiatives, all while addressing sustainability and social responsibility. With five generations working side-by-side—Traditionalists, Baby Boomers, Generation X (Gen X), Millennials (Gen Y), and Generation Z (Gen Z)—developing workforce policies that align with diverse generational norms, values, and beliefs remains challenging.
Reverse mentoring offers a valuable tool for bridging these multigenerational workforce gaps. Reverse Mentoring is a workplace mentoring relationship between a senior manager (the protégé in this relationship) and a junior employee (the mentor in this relationship) to facilitate the learning and development of the protégé (Ballard, 2013; Burdett, 2014; Chaudhuri & Ghosh, 2012; Chen, 2013, 2014; Greengard, 2002; Haggard et al., 2011; Harvey et al., 2009; Leh, 2005; Meister & Willyerd, 2010; Woods, 2022, Woodward et al., 2015). Older workers include Traditionalists and Baby Boomers (Baily, 2009; Boysen et al., 2016; Brummit, 2014a, 2014b; Eversole et al., 2012; Fox, 2011; Jamieson, 2009; Knight, 2014; Pritchard & Whiting, 2014; Wiedmer, 2015; Woods, 2022). Today, the youngest Traditionalists, born between 1928 and 1945, are 79 (Baily, 2009; Boysen et al., 2016; Brummit, 2014a, 2014b; Fox, 2011; Jamieson, 2009; Knight, 2014; Pritchard & Whiting, 2014; Wiedmer, 2015). Baby Boomers, born between 1946 and 1964, are between 60 and 78 (Chaudhuri and Ghosh, 2012; Boysen et al., 2016; Fox, 2011; Wiedmer, 2015). While this research focuses on older workers as a class, studies show that both older and younger workers in a reverse mentoring relationship benefit from the reciprocal exchange of knowledge and skills facilitated by pairing younger employees as mentors to senior colleagues (Browne, 2021; Chaudhuri & Ghosh, 2012; Cismaru & Iunius, 2019, 2020).
The benefits of reverse mentoring for older workers are well-documented and supported by extensive research. A review of approximately 370 research and scholarly articles highlights that reverse mentoring increases engagement among Baby Boomers and Gen Y, correlating with higher retention and job satisfaction while reducing turnover intentions (Benn et al., 2015; Bhattacharya, 2015; Sawatzky & Enns, 2012; Schaufeli & Bakker, 2004). Studies across various industries (e.g., nurses, medical students, teachers, farmers, mechanics, and researchers) and countries like the UK, India, Australia, Canada, and Indonesia emphasize its universal relevance (Curtis, Mozley, Langford, Hartland, & Kelly, 2021; Ellison, 2014; Leh, 2005; Gurchiek, 2018; Sulistiono, Hermawan, & Sukmawati, 2020). This practice empowers older workers to overcome job plateaus, technological skill gaps, and biases while enabling younger employees to develop leadership skills and foster workplace collaboration (Chaudhuri & Ghosh, 2012). Leedahl et al. (2020) demonstrated that reverse mentoring effectively bridges generational gaps, particularly when using technology to teach older adults. Additionally, Cismaru and Iunius (2019, 2020) found that reverse mentoring among senior executives enhances organizational commitment, competency development, and consumer-oriented contributions. Browne (2021), supported by Ropes (2013), noted that reciprocal knowledge transfer in reverse mentoring is only the starting point. Through reverse mentoring, doctoral candidates and junior researchers provide senior academics with awareness and updated knowledge on the topic of research integrity and open science (Pizzolato & Dierickx, 2022). Reverse mentoring motivates older workers, benefiting both individuals and organizations (Woods, 2022).
The literature also demonstrates that the definition of reverse mentoring has evolved (Ballard, 2013; Chaudhuri & Ghosh, 2012; Greengard, 2002; Haggard et al., 2011; Leh, 2005), supporting job satisfaction (Allen et al., 1999; Chaudhuri & Ghosh, 2012; Chen et al., 2011), helping older protégés gain a youthful perspective (Greengard, 2002). Whether applicable to academic (Ballard, 2013; Leh, 2005), government (Burdett, 2014), or industry settings, the subject of the mentoring relationship is no longer just relegated to IT topics. Now, a reverse mentoring relationship can be about anything where the younger mentor has subject matter expertise and the older protégé needs to learn about that subject (Woods, 2022).
Organizations with older IT workers have a vested interest in improving employee engagement and job satisfaction across generational cohorts, including Traditionalists and Baby Boomers (Brummit, 2014a, 2014b; Eversole et al., 2012; Fox, 2011; Pritchard & Whiting, 2014). Since engaged employees report higher job satisfaction (Benn et al., 2015; Bhattacharya, 2015; Dash & Muthyala, 2016; Sawatzky & Enns, 2012; Schaufeli & Bakker, 2004; Yalabik et al., 2017) and lower intent to leave (Agarwal & Sajid, 2017; Benn et al., 2015; Chen et al., 2011; Lo, 2015; Pepe, 2010), reverse mentoring should be considered for improving employee retention of older workers as a class. Engagement also drives emotional and organizational commitment, reducing turnover and improving productivity (Dash & Muthyala, 2016; Shuck et al., 2014), benefiting profitability. Like many other industries, most IT environments include both older and younger workers (Rayome, 2018), thus tools like reverse mentoring should be considered for improving job satisfaction and employee engagement in older IT workers (Woods, 2022).
While younger workers make up the majority of IT workers industry-wide (Loten, 2019) and tend to be more interested in technology jobs (Rayome, 2018), there are specific instances where older IT workers are preferred (Corrigan, 2019; Loten, 2019; Rayome, 2018). This is the case when specialized IT management skills are required (Rayome, 2018), legacy IT systems and critical infrastructure must be maintained (Flinders, 2019; Kelker, 2018; Loten, 2019), for modernizing IT environments via cloud migration (Wu, 2016), and even when preserving national security (Albright & Cluff, 2005; Corrigan, 2019; Wakeman, 2016). Losing these highly skilled older IT workers could hinder businesses and prevent federal agencies like DoD, Navy, NORAD, and DHS from achieving national security missions and ensuring safety at home and abroad (Albright & Cluff, 2005; Wakeman, 2016; Woods, 2022). As a result, IT managers would derive significant value from understanding to what extent reverse mentoring can improve job satisfaction and employee retention in older workers.
Problem or Hypothesis
To help organizations explore the complexities of multigenerational workforces and understand how reverse mentoring influences retention, engagement, and job satisfaction among older workers, Woods’ (2022) study posed the following quantitative research question:
RQ: To what extent does reverse mentoring (affective commitment, continuous commitment, normative commitment) relate to the retention (job satisfaction, intent to leave) of older workers in the IT industry?
leave) of older workers in the IT industry?
H0: Reverse mentoring (affective commitment, continuous commitment, normative commitment) is not significantly related to the retention (job satisfaction, intent to leave) of older workers in the IT industry.
Ha: Reverse mentoring (affective commitment, continuous commitment, normative commitment) is significantly related to the retention (job satisfaction, intent to leave) of older workers in the IT industry.
A quantitative, non-experimental research design was selected for this study to confirm the prediction that reverse mentoring increases job satisfaction in older IT workers, reducing intent to leave, as informed by SET, LMX, and POS theories (Madhavanprabhakaran, Francis, & Labrague, 2022; Gelo et al., 2008). These hypotheses were tested through quantitative analysis, using survey data to measure the relationships between mentoring participation, organizational commitment dimensions, job satisfaction, and retention outcomes (Woods, 2022). This design allows exploration of whether the independent variables, affirmative commitment (AC), continuous commitment (CC), and normative commitment (NC) significantly impact the dependent variable retention (RET), measured by job satisfaction and intent to leave. Inferential statistical procedures, such as MLR analysis, were used to test these relationships (Sekaran & Bougie, 2013). If mean Chronbach’s alpha scores exceed those in Agarwal and Sajid’s (2017) survey, increased organizational commitment may be linked to reverse mentoring relationships.
The target population for this study consisted of older IT workers who have been reverse mentored, specifically those identified as Traditionalists and Baby Boomers. The U.S. IT workforce included more than 4 million professionals across 10 occupational categories in 2018 (Beckhusen, 2016). Convenience, random sampling was employed, utilizing affordable and efficient electronic surveys administered through Qualtrics. A total of 131 participants (N=131), aged 57–100, who had been reverse mentored or managed by younger workers, were surveyed from this population. The study maintained a 95% confidence interval with a 0.05 margin of error.
The study employed comprehensive participant selection, protection, and data collection procedures to ensure accurate and ethical research involving older IT workers reverse mentored by younger colleagues. Using G*Power software with a 0.05 margin of error, 95% confidence interval, and predictors (AC, CC, NC), 129 participants were required (Sekaran & Bougie, 2013). Qualtrics recruited participants using opt-in market research panels, matching candidates based on screening criteria, including birth year and reverse mentoring experience (Qualtrics, 2019). Participants reaffirmed their eligibility before inclusion and were protected through IRB-approved informed consent, ensuring anonymity, voluntary participation, and risk-free engagement. Data was collected from Traditionalists and Baby Boomers using Agarwal and Sajid’s (2017) 48-question survey, which incorporated Meyer and Allen’s (1997) Organizational Commitment Scale, Brayfield and Rothe’s (1951) Index of Job Satisfaction, and Hinshaw and Atwood’s (1980) ATS.
Analysis
A review of descriptive statistics revealed that the variable data had similar means, with minor variance issues addressed through residual analysis under hypothesis testing. Skew and kurtosis scores supported normality, further confirmed by Q-Q plots and histograms. Correlation analysis showed non-significant, weak relationships between AC and RET
(p = 0.320; α = 0.05) and CC and RET (p = 0.374; α = 0.05), while other intercorrelations were significant and strong. Evidence of multicollinearity was not found. Hypothesis testing used MLR, where AC, CC, and NC were independent variables and RET the dependent variable. The model demonstrated a significant, strong relationship (adj r2 = 0.497; p < .001; α = .05), leading to rejection of the null hypothesis in favor of the alternative. Effect size analysis confirmed a strong linear relationship
(adj r2 = 0.497; Gloeckner et al., 2001, p. 227), with significant pairwise relationships for AC and RET (p<.001p < .001p<.001) and NC and RET (p=.007p = .007p=.007), though not for CC and RET (p=.355p = .355p=.355). Residual assessments confirmed normality and linearity assumptions via histograms and P-P plots. These findings addressed the research question, highlighting a robust omnibus hypothesis with minor coefficient exceptions (Woods, 2022).
Solutions
Reverse mentoring is a transformative strategy that enhances older workers’ skills, fosters inclusion, and bridges generational gaps in the workplace. Organizations like IBM, Deloitte, General Electric, and the Wharton School at the University of Pennsylvania have successfully leveraged reverse mentoring to upskill senior employees, improve cross-generational understanding, and boost employee engagement and retention. This approach facilitates critical knowledge transfer, addresses skill gaps, and fosters innovation while creating a culture of mutual respect and collaboration. By integrating reverse mentoring into broader DEIA strategies, organizations can drive inclusion, strengthen retention, and build resilient teams. Structured training programs, feedback systems, and scalability ensure reverse mentoring remains a vital workforce development tool.
Reverse mentoring is not only transformative for enhancing capabilities but also aligns with best practices outlined by Diversity MBA (DMBA, 2023). According to the DMBA Inclusive Leadership Index (ILI), 91% of companies measure inclusion effectiveness through engagement surveys and focus groups. This underscores the importance of reverse mentoring as a feedback-rich initiative to drive inclusion and workforce collaboration. Additionally, pulse surveys combined with participant evaluations—identified by DMBA (2023) as leading tools—can complement reverse mentoring programs by providing real-time insights into their impact. DMBA (2023) also highlights that 48% of companies use participant satisfaction rates as a key inclusion metric, a measure easily applied to reverse mentoring programs to assess participant engagement and program success. Incorporating these tools alongside structured training programs and diversity strategies can further maximize reverse mentoring’s potential for fostering an inclusive and agile workplace.
Results/Outcomes
Reverse mentoring programs provide older workers with opportunities to learn new skills, remain engaged, and mitigate risks of disengagement or job plateaus. These mentoring relationships also enhanced cross-generational understanding and collaboration, breaking down stereotypes and fostering mutual respect. Organizations leveraging reverse mentoring not only retain critical talent but also build inclusive cultures that drive collaboration and innovation. Beyond individual benefits, reverse mentoring facilitates knowledge transfer, strengthens organizational resilience, and enhances workforce agility, ensuring that companies adapt and thrive in dynamic, multigenerational environments. To maximize program effectiveness, training mentors and protégés, setting clear objectives, and implementing regular feedback mechanisms are essential. This aligns with broader organizational trends identified in the DMBA ILI (2023), where 95% of companies prioritize collaboration, resources, and growth as key inclusion outcomes. Reverse mentoring addresses these priorities by fostering critical cross-generational knowledge transfer, enhancing collaboration, and supporting employee growth across all levels of the organization. Additionally, the DMBA (2023) findings reveal that formal mentoring programs remain a cornerstone of leadership development for 89% of companies. Reverse mentoring builds on this foundation by extending its impact to include skill enhancement for senior employees and leadership opportunities for younger workers. Furthermore, integrating metrics like participant satisfaction, as suggested by DMBA (2023), provides a tangible way to evaluate program effectiveness. Using these insights, organizations can optimize mentoring relationships and better align outcomes with strategic goals.
Lessons Learned
Implementing reverse mentoring programs requires careful planning, continuous support, and thoughtful design to maximize their impact. Overcoming challenges such as resistance to role reversal, generational biases, and unclear objectives is crucial. Ongoing support and monitoring through regular check-ins and feedback loops help sustain participant engagement and resolve emerging issues. Matching mentors and mentees based on goals, personalities, and learning styles ensures compatibility, while cultural competency training enhances understanding of communication styles and workplace norms, particularly in global organizations.
Recognizing and rewarding participants’ efforts through public acknowledgment or awards further boosts motivation. For sustainability, reverse mentoring programs should integrate with broader organizational strategies like leadership development and DEIA initiatives. Emphasizing mutual learning from the outset demonstrates the reciprocal benefits, fostering valuable skills and insights for both parties. Confidentiality and psychological safety are critical, with clear guidelines ensuring trust and open engagement.
Feedback mechanisms such as pulse surveys and participant evaluations, recommended by DMBA (2023), provide real-time insights into program effectiveness. These tools, combined with regular progress meetings, can identify areas for improvement and maintain program momentum. Additionally, DMBA highlights exit interviews as a key method for uncovering systemic inequities and micro-aggressions, enabling reverse mentoring to proactively address cultural biases and promote inclusivity. By incorporating these practices, reverse mentoring programs can drive collaboration, foster inclusivity, and prepare organizations for future challenges.
Recommendations
HR leaders can take several steps to enhance the effectiveness and impact of reverse mentoring programs. First, establishing comprehensive training programs is essential to equip both mentors and protégés with the skills needed to navigate generational differences, foster trust, and communicate effectively. Training should include real-world scenarios emphasizing empathy and mutual respect, ensuring participants are prepared to maximize the benefits of mentoring while minimizing potential conflicts or misunderstandings. Alongside training, organizations should create robust feedback and support mechanisms, such as regular check-ins, surveys, and forums, to address challenges in real-time and allow participants to share experiences, further strengthening the mentoring relationships.
Leveraging technology can also enhance the scalability and accessibility of reverse mentoring programs. Digital platforms can facilitate mentor-mentee interactions, track progress, and measure outcomes, particularly valuable for global organizations or those operating in remote work environments. Additionally, integrating reverse mentoring into succession planning provides a dual benefit: preparing younger employees for leadership roles while ensuring that institutional knowledge is retained through meaningful intergenerational exchanges. Aligning reverse mentoring initiatives with broader business objectives, such as addressing skill gaps or supporting digital transformation efforts, ensures that these programs contribute directly to measurable organizational success.
Future research should further refine reverse mentoring practices. Investigating its role in digital transformation could reveal how mentoring accelerates technology adoption and digital literacy among senior employees. Examining psychological safety within mentoring relationships can provide insights into fostering open communication. Research into reverse mentoring’s impact on diversity, equity, and inclusion (DEI) initiatives would highlight its potential to reduce workplace disparities and foster inclusivity. Industry-specific studies could assess how outcomes vary across sectors such as healthcare, finance, and manufacturing, tailoring programs to unique challenges. Longitudinal studies would offer deeper insights into mentoring’s effects on career trajectories, loyalty, and workplace culture.
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