Strah et al. (Reference Strah, Rupp and Morris2021) discuss the role of job analysis and job classification as a method for helping organizations in the systematic determination of equivalent jobs per legal standards. It is presumed that they make these recommendations with a goal of less gender-based pay discrimination in the workplace. The purpose of the commentary is to address the practical applicability of the recommendations of Strah et al. from a legal, societal, and corporate perspective using the authors combined professional experiences as a lawyer/judge, job analyst, corporate human resources (HR) professional, and senior corporate executive. We finish with a discussion on the current state of work and work locations, addressing challenges of implementing job analysis in remote work contexts.
Legal perspective
Strah et al. (Reference Strah, Rupp and Morris2021) provide a solid but very basic overview of the federal legislation and current case law protecting against pay inequality. From a practical standpoint, however, most cases in this arena are advisory only because the nature of our legal system encourages settlement between the parties to mitigate potentially lengthy legal battles that would place a strain on the courts. On its face, this arena of law is well settled; however, this assumes that (a) judicial interpretations always neatly fall in line with existing law and (b) employer job descriptions/analysis are equally infallible.
Judges are often called upon to tailor legal opinions using broad interpretations of the law that may attempt to fit into a case that is not directly on point. Similarly, those judges will interpret job descriptions that are often written by employers to serve employees who might be doing a variety of things listed that are not always a part of every employees’ role in that defined job’s requirements.Footnote 1 Job content is much more important today than a job’s listed requirements, as content addresses what you actually do rather than what you could be called to do.Footnote 2
Additionally, wage discrimination lawsuits are typically far less likely to be successful than the average tort claim.Footnote 3 Roughly 50% of tort cases are successful, whereas cases filed with the EEOC that have illustrated a finding of wage discrimination have hovered only between 4.5% and 7.5% percent over the past 10 years, despite a steady pace of filed cases.Footnote 4 The majority of these “successful” cases will result in consent decrees, or legal settlements that typically are not published legal precedent that can be relied upon for future filings.
Bias judgements
As discussed by Strah et al. (Reference Strah, Rupp and Morris2021), the perpetuation of the gender–wage gap likely stems from confusion/ignorance surrounding the notion of “equal” and/or “equivalent” work, as there are no criteria or processes set forth to determine the equivalencies of jobs. Strah et al. suggest that job analysis and job classification methods can be used in the setting of equivalent jobs as well as to assess job equivalency in a legal context. Although we agree with the notion of Strah et al.’s arguments in theory, in practice we suggest caution in sweeping adherence and application of such methods as a solution or tool for determining job equivalency. Job analysis as a technique relies on judgments that are made by subject matter experts (SMEs; Goldstein et al., Reference Goldstein, Zedeck, Schneider, Schmitt and Borman1993; e.g., job incumbents, supervisors, etc.), and human judgment has long been demonstrated to be fallible and subject to bias. The fallibility of human judgments in job analysis can have profound effects on the accuracy of the data that are used to make judgments about the classification of jobs vis à vis interrater reliability, interrater agreement, discriminability between jobs, dimensionality of factor structures, mean ratings, and completeness of job information (Morgeson & Campion, Reference Morgeson and Campion1997). Although the authors suggest the use of statistical techniques to determine the common core of tasks or work behaviors, the data being used are likely flawed by said bias.
Strah et al. (Reference Strah, Rupp and Morris2021) also suggest that organizations can use existing inventories such as the Position Analysis Questionnaire, the Job Element Inventory, and O*NET GWAs for use in determining generalized work activities, as they may be more cost effective than the in-house development of tasks, these tools also rely on subject-matter-expert ratings. Moreover, the potential for bias and use of stereotypical heuristics when making decisions are not the only issues with respect to the use of job analysis in the context of job classification. The use of these validated measures could compound the implicit bias in the data, as the measures suggested were developed in the mid-1900s when the United States and the world’s economy reflected industrialization and the majority of the workforce was male, thus they could also contain implicitly biased questions. Taken together, reliance on methodologies such as traditional job analyses to determine equivalencies in organizations could result in the adoption of the wrong factors, wrong weights, and wrong methodology, and could ultimately exacerbate the problem.
Small and medium sized enterprises
Although job analysis might be the possible solution, despite the potential for bias, in terms of administration of such process, we must consider the feasibility of use across a variety of organizations. Twenty-nine million small- and medium-sized enterprises (SMEs) in the United States constitute 99.7% of all U.S. businesses and approximately half of the total private-sector employment (O’Mahony & Ma, Reference O’Mahony and Ma2017). These businesses, including family-owned operations, do not often have formalized HR procedures or professionals to help guide organizational decision making in any area of HR (Wapshott & Mallett, 2015). Additionally, research in this area is limited (Cruz et al., Reference Cruz, Firfiray, Gomez-Mejia, Joshi, Liao and Martocchio2011) and relevant literature related to SMEs and compensation has focused on executive pay and pay at individual levels rather than the development and consideration of compensation systems (Michiels, 2017).
It is not surprising, given that the lack of basic HR resources in SMEs, that these firms do not have the ability or knowledge to conduct thorough job analyses and job evaluation processes internally. Additionally, external consultation for job analysis and job evaluations can be cost-prohibitive, leaving only limited nonspecific information from government sources available to SMEs, (Pynes, Reference Pynes2008; e.g., Bureau of Labor Statistics) without the benefit of knowledgeable professionals who could evaluate the wage surveys. This lack of resources and knowledge in SMEs related to compensation system development puts these organizations at risk for compliance issues. Although the job analysis, job classification, and compensation plans outlined by Strah et al. (Reference Strah, Rupp and Morris2021) are advisable and applicable among larger firms with specialized HR services, such is not the case for SMEs.
Job analysis and the remote worker
Continuing our position of concerns with job analysis and job classification based on Strah et al. (Reference Strah, Rupp and Morris2021), we believe the present influx of remote work arrangements adds credibility to our view. Extensive research by Kamouri and Lister (Reference Kamouri and Lister2020) shows that remote work arrangements have grown over 216% from 2005 to 2019. Interestingly, they found that 69% of 2,500 U.S. employees worked from home at the pandemic peak. This trend is expected to continue. Early research reported by Senz (Reference Senz2020) indicates that at least 16% of “pandemic-induced remote workers” will remain working remotely long after the COVID-19 crisis is over (Bartik et al., Reference Bartik, Cullen, Glaeser, Luca and Stanton2020). As remote work becomes more ubiquitous, traditional job analysis and work redesign may be impossible and could quite possibly increase the existing pay gap. This is not surprising for two reasons, first, remote work environments are out of the control and sight of the employer, making them more ambiguous (Allen et al., Reference Allen, Golden and Shockley2015). Ambiguity in the context of work induces reliance on inherent biases and heuristic decision making; this is problematic, per our previous argument, if we rely on individual-level judgments on task and performance as the basis of our job analytic data. Given this, we argue that statistically analyzing core work behaviors, clustering, and skill/effort assessments are inadequate to derive job analysis in one of the fastest growing worker segments.
Second, Rudolph et al. (Reference Rudolph, Allan, Clark, Hertel, Hirschi, Kunze, Shockley, Shoss, Sonnentag and
Zacher2021) suggest that although job duties may remain the same, the nature of how the job is done will vary (e.g., task interdependence, task frequency, communication, etc.) perhaps more frequently than with other nonremote work. Thus, although job duties appear equivalent, the nature of the job has become more dynamic making job analysis a less amenable choice. Therefore, we call for a rethinking of the focal article contribution in this area relative to such work arrangements.
Future research
Developing employees to engage in proactive job crafting may work when traditional work job analysis is impractical or unaffordable. Job crafting is defined as “the physical and cognitive changes individuals make in the task or relational boundaries of their work” (Wrzesniewski & Dutton, Reference Wrzesniewski and Dutton2001, p. 179). It involves the employee engaging proactively in a process of adjusting boundaries, conditions of the job’s tasks, relationships with people associated with the job, and the meaning of the work conducted in the job (Wrzesniewski & Dutton, Reference Wrzesniewski and Dutton2001). Rather than focusing on the duties or tasks of the job (which are now ever evolving), job crafting focuses on five dimensions: increasing challenging demands, decreasing social demands, increasing social job resources, increasing quantitative demands, and decreasing hindrance demands (Nielsen et al., Reference Nielsen, Antino, Sanz-Vergel and Rodríguez-Muñoz2017). Job crafting provides perhaps a better way to incorporate both organizational policy and values with a methodical system for identifying dimension of jobs (Dierdorff & Aguinis, Reference Dierdorff and Aguinis2018). Further, it provides an alternative approach to evaluating and/or differentiating “substantially equivalent jobs” based on the dimensions listed above.
We admit, the conversation of gender relative to job crafting is still somewhat in infancy but important per early calls to research by Sanchez and Levine (Reference Sanchez and Levine2012). We suggest future research explore the viability of job crafting as a method for classifying equivalent jobs and how it will withstand the scrutiny of the EEOC evaluation of equivalent jobs. In other words, do “substantially equivalent jobs” have gender pay differences in either traditional or alternative (remote/hybrid) work arrangements? A recommended start to our proposition is to review the Social Impacts on Job Crafting meta-analysis by Wang, Li, and Chen’s (2020). Their work sheds light on a current conversation taking place in this space. Furthermore, research by Daly (Reference Daly2019) may be useful because it focused on constructed gender, gender social role differences, and gender motivation differences relative to job crafting.
We present avenues and ideas as preliminary steps before exploring how and why compensation inequality is a factor or not in job crafting. Arguably, before pay inequality is investigated, a focal point of gender linked to the job-crafting space needs to be more fully developed and understood.
Concluding thoughts
Strah et al.’s (Reference Strah, Rupp and Morris2021) discussion of pay inequality relative to federal legislation and current case law is timely and appropriate. We felt the conversation they started afforded us an opportunity to expand the discussion with expertise in legal scholarship, especially because one of us is a judge. Furthermore, advancing the topic of job analysis/classification while considering equal pay is complex. Our contribution to this topic was to provide insights as to why it is complex, specific to bias judgements and limitations of SMEs. To illustrate our position, we discussed our concerns of job analysis/classification with an application to remote work because this arrangement is current and relevant to many workers due to the COVID-19 pandemic. Furthermore, we offered several suggestions for future research to expand the work of Strah et al. Although there are many paths our discussion could have taken, we intentionally chose to keep it focused and limited to pertinent points to advance both the scholar and practitioner communities.
Strah et al. (Reference Strah, Rupp and Morris2021) discuss the role of job analysis and job classification as a method for helping organizations in the systematic determination of equivalent jobs per legal standards. It is presumed that they make these recommendations with a goal of less gender-based pay discrimination in the workplace. The purpose of the commentary is to address the practical applicability of the recommendations of Strah et al. from a legal, societal, and corporate perspective using the authors combined professional experiences as a lawyer/judge, job analyst, corporate human resources (HR) professional, and senior corporate executive. We finish with a discussion on the current state of work and work locations, addressing challenges of implementing job analysis in remote work contexts.
Legal perspective
Strah et al. (Reference Strah, Rupp and Morris2021) provide a solid but very basic overview of the federal legislation and current case law protecting against pay inequality. From a practical standpoint, however, most cases in this arena are advisory only because the nature of our legal system encourages settlement between the parties to mitigate potentially lengthy legal battles that would place a strain on the courts. On its face, this arena of law is well settled; however, this assumes that (a) judicial interpretations always neatly fall in line with existing law and (b) employer job descriptions/analysis are equally infallible.
Judges are often called upon to tailor legal opinions using broad interpretations of the law that may attempt to fit into a case that is not directly on point. Similarly, those judges will interpret job descriptions that are often written by employers to serve employees who might be doing a variety of things listed that are not always a part of every employees’ role in that defined job’s requirements.Footnote 1 Job content is much more important today than a job’s listed requirements, as content addresses what you actually do rather than what you could be called to do.Footnote 2
Additionally, wage discrimination lawsuits are typically far less likely to be successful than the average tort claim.Footnote 3 Roughly 50% of tort cases are successful, whereas cases filed with the EEOC that have illustrated a finding of wage discrimination have hovered only between 4.5% and 7.5% percent over the past 10 years, despite a steady pace of filed cases.Footnote 4 The majority of these “successful” cases will result in consent decrees, or legal settlements that typically are not published legal precedent that can be relied upon for future filings.
Bias judgements
As discussed by Strah et al. (Reference Strah, Rupp and Morris2021), the perpetuation of the gender–wage gap likely stems from confusion/ignorance surrounding the notion of “equal” and/or “equivalent” work, as there are no criteria or processes set forth to determine the equivalencies of jobs. Strah et al. suggest that job analysis and job classification methods can be used in the setting of equivalent jobs as well as to assess job equivalency in a legal context. Although we agree with the notion of Strah et al.’s arguments in theory, in practice we suggest caution in sweeping adherence and application of such methods as a solution or tool for determining job equivalency. Job analysis as a technique relies on judgments that are made by subject matter experts (SMEs; Goldstein et al., Reference Goldstein, Zedeck, Schneider, Schmitt and Borman1993; e.g., job incumbents, supervisors, etc.), and human judgment has long been demonstrated to be fallible and subject to bias. The fallibility of human judgments in job analysis can have profound effects on the accuracy of the data that are used to make judgments about the classification of jobs vis à vis interrater reliability, interrater agreement, discriminability between jobs, dimensionality of factor structures, mean ratings, and completeness of job information (Morgeson & Campion, Reference Morgeson and Campion1997). Although the authors suggest the use of statistical techniques to determine the common core of tasks or work behaviors, the data being used are likely flawed by said bias.
Strah et al. (Reference Strah, Rupp and Morris2021) also suggest that organizations can use existing inventories such as the Position Analysis Questionnaire, the Job Element Inventory, and O*NET GWAs for use in determining generalized work activities, as they may be more cost effective than the in-house development of tasks, these tools also rely on subject-matter-expert ratings. Moreover, the potential for bias and use of stereotypical heuristics when making decisions are not the only issues with respect to the use of job analysis in the context of job classification. The use of these validated measures could compound the implicit bias in the data, as the measures suggested were developed in the mid-1900s when the United States and the world’s economy reflected industrialization and the majority of the workforce was male, thus they could also contain implicitly biased questions. Taken together, reliance on methodologies such as traditional job analyses to determine equivalencies in organizations could result in the adoption of the wrong factors, wrong weights, and wrong methodology, and could ultimately exacerbate the problem.
Small and medium sized enterprises
Although job analysis might be the possible solution, despite the potential for bias, in terms of administration of such process, we must consider the feasibility of use across a variety of organizations. Twenty-nine million small- and medium-sized enterprises (SMEs) in the United States constitute 99.7% of all U.S. businesses and approximately half of the total private-sector employment (O’Mahony & Ma, Reference O’Mahony and Ma2017). These businesses, including family-owned operations, do not often have formalized HR procedures or professionals to help guide organizational decision making in any area of HR (Wapshott & Mallett, 2015). Additionally, research in this area is limited (Cruz et al., Reference Cruz, Firfiray, Gomez-Mejia, Joshi, Liao and Martocchio2011) and relevant literature related to SMEs and compensation has focused on executive pay and pay at individual levels rather than the development and consideration of compensation systems (Michiels, 2017).
It is not surprising, given that the lack of basic HR resources in SMEs, that these firms do not have the ability or knowledge to conduct thorough job analyses and job evaluation processes internally. Additionally, external consultation for job analysis and job evaluations can be cost-prohibitive, leaving only limited nonspecific information from government sources available to SMEs, (Pynes, Reference Pynes2008; e.g., Bureau of Labor Statistics) without the benefit of knowledgeable professionals who could evaluate the wage surveys. This lack of resources and knowledge in SMEs related to compensation system development puts these organizations at risk for compliance issues. Although the job analysis, job classification, and compensation plans outlined by Strah et al. (Reference Strah, Rupp and Morris2021) are advisable and applicable among larger firms with specialized HR services, such is not the case for SMEs.
Job analysis and the remote worker
Continuing our position of concerns with job analysis and job classification based on Strah et al. (Reference Strah, Rupp and Morris2021), we believe the present influx of remote work arrangements adds credibility to our view. Extensive research by Kamouri and Lister (Reference Kamouri and Lister2020) shows that remote work arrangements have grown over 216% from 2005 to 2019. Interestingly, they found that 69% of 2,500 U.S. employees worked from home at the pandemic peak. This trend is expected to continue. Early research reported by Senz (Reference Senz2020) indicates that at least 16% of “pandemic-induced remote workers” will remain working remotely long after the COVID-19 crisis is over (Bartik et al., Reference Bartik, Cullen, Glaeser, Luca and Stanton2020). As remote work becomes more ubiquitous, traditional job analysis and work redesign may be impossible and could quite possibly increase the existing pay gap. This is not surprising for two reasons, first, remote work environments are out of the control and sight of the employer, making them more ambiguous (Allen et al., Reference Allen, Golden and Shockley2015). Ambiguity in the context of work induces reliance on inherent biases and heuristic decision making; this is problematic, per our previous argument, if we rely on individual-level judgments on task and performance as the basis of our job analytic data. Given this, we argue that statistically analyzing core work behaviors, clustering, and skill/effort assessments are inadequate to derive job analysis in one of the fastest growing worker segments.
Second, Rudolph et al. (Reference Rudolph, Allan, Clark, Hertel, Hirschi, Kunze, Shockley, Shoss, Sonnentag and Zacher2021) suggest that although job duties may remain the same, the nature of how the job is done will vary (e.g., task interdependence, task frequency, communication, etc.) perhaps more frequently than with other nonremote work. Thus, although job duties appear equivalent, the nature of the job has become more dynamic making job analysis a less amenable choice. Therefore, we call for a rethinking of the focal article contribution in this area relative to such work arrangements.
Future research
Developing employees to engage in proactive job crafting may work when traditional work job analysis is impractical or unaffordable. Job crafting is defined as “the physical and cognitive changes individuals make in the task or relational boundaries of their work” (Wrzesniewski & Dutton, Reference Wrzesniewski and Dutton2001, p. 179). It involves the employee engaging proactively in a process of adjusting boundaries, conditions of the job’s tasks, relationships with people associated with the job, and the meaning of the work conducted in the job (Wrzesniewski & Dutton, Reference Wrzesniewski and Dutton2001). Rather than focusing on the duties or tasks of the job (which are now ever evolving), job crafting focuses on five dimensions: increasing challenging demands, decreasing social demands, increasing social job resources, increasing quantitative demands, and decreasing hindrance demands (Nielsen et al., Reference Nielsen, Antino, Sanz-Vergel and Rodríguez-Muñoz2017). Job crafting provides perhaps a better way to incorporate both organizational policy and values with a methodical system for identifying dimension of jobs (Dierdorff & Aguinis, Reference Dierdorff and Aguinis2018). Further, it provides an alternative approach to evaluating and/or differentiating “substantially equivalent jobs” based on the dimensions listed above.
We admit, the conversation of gender relative to job crafting is still somewhat in infancy but important per early calls to research by Sanchez and Levine (Reference Sanchez and Levine2012). We suggest future research explore the viability of job crafting as a method for classifying equivalent jobs and how it will withstand the scrutiny of the EEOC evaluation of equivalent jobs. In other words, do “substantially equivalent jobs” have gender pay differences in either traditional or alternative (remote/hybrid) work arrangements? A recommended start to our proposition is to review the Social Impacts on Job Crafting meta-analysis by Wang, Li, and Chen’s (2020). Their work sheds light on a current conversation taking place in this space. Furthermore, research by Daly (Reference Daly2019) may be useful because it focused on constructed gender, gender social role differences, and gender motivation differences relative to job crafting.
We present avenues and ideas as preliminary steps before exploring how and why compensation inequality is a factor or not in job crafting. Arguably, before pay inequality is investigated, a focal point of gender linked to the job-crafting space needs to be more fully developed and understood.
Concluding thoughts
Strah et al.’s (Reference Strah, Rupp and Morris2021) discussion of pay inequality relative to federal legislation and current case law is timely and appropriate. We felt the conversation they started afforded us an opportunity to expand the discussion with expertise in legal scholarship, especially because one of us is a judge. Furthermore, advancing the topic of job analysis/classification while considering equal pay is complex. Our contribution to this topic was to provide insights as to why it is complex, specific to bias judgements and limitations of SMEs. To illustrate our position, we discussed our concerns of job analysis/classification with an application to remote work because this arrangement is current and relevant to many workers due to the COVID-19 pandemic. Furthermore, we offered several suggestions for future research to expand the work of Strah et al. Although there are many paths our discussion could have taken, we intentionally chose to keep it focused and limited to pertinent points to advance both the scholar and practitioner communities.