MT304 Unit 9 Generational Workforce Study Example

Tenure, Not Birth Year: An MT304 Unit 9 Workforce Composition Study of Generational Labels at a Claims Office

[Student Name]

Purdue University Global

MT304: Leading the 21st Century Organization

Unit 9 Workforce Composition Study

[Instructor Name]

[Date]

The insurer, its survey, records and staff are composite; the research cited is real.

The Request

The director's email, in part: "We need a Gen Z plan with weekly feedback, since that's what they expect, and a boomer plan that deals with resistance to the photo software. Millennials and Gen X we can probably handle together."

What Research Supports

A 2020 consensus report from the National Academies concluded that generational categories are not a sound basis for workforce management decisions, because the evidence for meaningful differences between generations at work is weak and the boundaries between categories are arbitrary (National Academies of Sciences, Engineering, and Medicine, 2020). Costanza et al. (2012), pooling studies of how satisfied, committed and ready to quit workers of different generations were, found that differences across generations were small and inconsistent, and that most of the variation lay within generations.

Work motives do shift with age. Kooij et al. (2011), in a meta-analysis, found that some motives, such as growth and extrinsic rewards, tend to weaken with age while intrinsic motives and security strengthen. But those shifts are modest and vary more within age groups than between them, and they are about age, not about generations.

Why One Survey Cannot Separate Age From Generation

At any single point in time, a person's age, their generation and the period they are living through are linked. A 25-year-old appraiser surveyed in 2025 is young, a member of a particular cohort and new to the job, all at once. One survey cannot tell which of those explains an answer. A difference that looks generational may simply be what it is like to be new.

Method

Two sources were used. The insurer's 2025 engagement survey received 318 responses from claims staff, including a self-reported caregiving question. Override records from the photo-estimating software show how often each appraiser changed the software's figure in the past year. Both were cut two ways: by birth-year band, under 30, 30 to 44, 45 to 59 and 60 and over, and by tenure band, under 2 years, 2 to 5, 6 to 10 and over 10. All results are reported by group, never by person.

Findings

Table 1: Engagement. Mean engagement on a five-point scale ranged from 3.6 to 3.9 across birth-year bands, a spread of 0.3. Across tenure bands, it ranged from 3.2, for staff with 2 to 5 years, to 4.1, for staff under 2 years, a spread of 0.9. Tenure explained about three times as much as birth year.

Table 2: Overrides of the photo software. If boomers resisted the software, they should override it less. They override it more: appraisers over 60 changed the figure on 9 percent of claims. But so did appraisers aged 30 to 44 with over ten years' tenure, at 8 percent. New appraisers of every age overrode it least, at 2 to 3 percent. Override rates track experience, not age, and veterans of every age override more because they know what the software misses.

Table 3: Intent to leave. Intent to leave in the next year was highest among staff paid below the posted midpoint for their role, 41 percent, and among staff reporting heavy caregiving loads, 38 percent. Within birth-year bands, it ranged from 18 to 26 percent.

The "boomer resistance" in the request is the same behavior the Unit 7 recheck showed was catching the software's mistakes.

Why the Labels Persist

If the evidence is so weak, why did the director ask for generational plans? Part of the answer is that the labels are convenient. They sort a workforce into four groups that are easy to name, and popular writing about each group gives managers a ready explanation for behavior they find puzzling. A new appraiser who asks for feedback every week looks like a Gen Z appraiser; a veteran who changes the software's figure looks like a boomer resisting change. In both cases, the label replaces a more useful question: what about this person's situation, their tenure, their caregiving or their pay, might explain what they are doing? The data here suggest that question has better answers. They also suggest a cost to the labels: a veteran told her override habit was resistance may stop overriding, and the Unit 7 recheck showed what that would cost policyholders.

Implications

The four generational plans the director requested would aim at differences that are small in our data and in the research. The evidence points to three plans aimed at what does differ:

1. A tenure plan. Engagement dips sharply at 2 to 5 years. That is when appraisers have mastered the basics but have not been promoted; the Unit 3 pay transparency analysis showed many applying and being turned down. Clear development paths and feedback after a turned-down application address that dip, for every age.

2. A caregiving plan. Flexible scheduling during surges for staff with heavy caregiving loads, who report the highest intent to leave after pay.

3. A pay placement plan. Staff below midpoint have the highest intent to leave. Adjusting the eleven appraisers identified in Unit 3 is the most direct retention step available.

Weekly feedback may be good for everyone, especially new staff, but it is not a Gen Z need. And the software override behavior should be treated as expertise to spread, not resistance to manage.

What the Director Can Do Next Week

The director does not need to wait for a full program. Three steps are available at once: ask HR for the list of staff below their posted midpoint, ask team leads which appraisers are two to five years into the job and have applied for promotion, and ask the veteran appraisers what they override most often and why. Each answer points to an action that will matter more than a generational plan.

Limits

This is one year of data from one office. The 318 responses are a self-selected group, and caregiving is self-reported. The study cannot separate a cohort effect from the effect of being new, so it cannot prove that generation plays no role. It can show that tenure, caregiving and pay explain more of what the director cares about.

Conclusion

Research and the insurer's own data agree: generational labels explain little about engagement, software use or intent to leave at our claims office. Tenure, caregiving and pay position explain much more. The director's two generational plans should be replaced with plans aimed at those three conditions.

References

Costanza, D. P., Badger, J. M., Fraser, R. L., Severt, J. B., & Gade, P. A. (2012). Generational differences in work-related attitudes: A meta-analysis. Journal of Business and Psychology, 27(4), 375-394. https://doi.org/10.1007/s10869-012-9259-4

Kooij, D. T. A. M., De Lange, A. H., Jansen, P. G. W., Kanfer, R., & Dikkers, J. S. E. (2011). Age and work-related motives: Results of a meta-analysis. Journal of Organizational Behavior, 32(2), 197-225. https://doi.org/10.1002/job.665

National Academies of Sciences, Engineering, and Medicine. (2020). Are generational categories meaningful distinctions for workforce management? The National Academies Press. https://doi.org/10.17226/25796