GB546 Unit 9 Retention Plan Example

Moving the First Raise to Month Five: A Unit 9 Retention Plan for Night-Crew Operators

[Student Name]

Purdue University Global

GB546: Talent Acquisition and Retention

Unit 9 Retention Plan

[Instructor Name]

[Date]

The plant, its crews and every rate, count and cost are composite and illustrative; the sources cited are real.

1. Segment Table

Turnover was broken down by shift and tenure for the last two quarters, annualized.

Night-crew operators: 170 people, 58 percent annualized, about 99 departures a year.

Day-crew operators: 171 people, 29 percent annualized, about 50 departures a year.

Technicians and quality technicians, all shifts: 14 percent and 12 percent, close to their trailing rates.

The combined operator rate, about 44 percent annualized, is higher than the 36 percent trailing-year figure used in the Unit 2 forecast, which supports that forecast's test of a 45 percent rate. Night-crew operators stand out against every other group.

2. Departure Timing

Night-crew departures were grouped by tenure at exit.

Months one to three: about 25 departures, 25 percent.

Months four to eight: about 46 departures, 47 percent.

Months nine to twelve: about 14 departures, 14 percent.

After month twelve: about 14 departures, 14 percent.

The four-to-eight-month window holds nearly half of all night-crew departures. Exit interviews from that window most often mention pay, specifically that the first raise is too far away, and the difficulty of the night schedule. Departures in the first three months more often mention the job itself, which the Unit 6 and Unit 7 recommendations address.

Night operators are not leaving because night pay is too low but because the first raise arrives after many of them have already given up waiting for it.

3. The Intervention

Operators now receive a $1.00 hourly raise at month twelve. The plan moves that raise to month five for any operator who qualifies on a second tool family, a skill the plant needs anyway as the second floor adds tools. About 90 night-crew operators a year are expected to qualify by month five. Operators who do not qualify by month five still receive the raise at month twelve, as now.

Griffeth et al. (2000) found that pay satisfaction and perceived alternatives both predict turnover, and Hom et al. (2017) describe how departures cluster at points where employees reassess whether to stay. The month-four-to-eight window is such a point, and the intervention changes what an operator sees at it.

4. Cost Table

Accelerated pay: seven months earlier, at 42 hours a week, about 1,273 hours at $1.00 plus payroll taxes, $1,371 per qualifier, $123,431 for 90 operators.

Qualification training: twelve hours of trainer and trainee time per operator at a combined $31.20 an hour, $374 per qualifier, $33,696.

Total: $157,127, or $1,746 per qualifier.

5. Break-Even

At $9,400 per operator departure, the plan breaks even at about 17 avoided exits a year. That is a cut of about 36 percent in the 46 departures in the four-to-eight-month window. The target is ambitious, and the plan says so: it is not certain the intervention can achieve it, which is exactly why it begins as a pilot.

6. Alternative Considered

A night differential for everyone. Adding $1.00 an hour to all 170 night operators would cost about $371,280 a year in wages, about $400,000 with payroll taxes, more than twice the plan's cost. It would reach operators who were not leaving and does not address timing, which the data show matters more than the level of pay. It was set aside.

7. Pilot Design

Groups. Two of the plant's four night crews receive the intervention; the other two continue on the current schedule and serve as the comparison.

Duration. Operators hired over two quarters are followed through month twelve.

Measures. Departures in months four to eight for each group, qualification rates on the second tool family and departures after month twelve, in case the raise only delays exits.

Decision rule. If pilot crews show at least 30 percent fewer departures in the window than comparison crews, the plan expands to all night crews; if the difference is under 15 percent, it stops; between those, the pilot runs another two quarters.

Comparing crews over the same quarters isolates the effect from seasonal hiring patterns or changes at nearby employers, and running on two crews halves the cost of a trial that may not work. Allen et al. (2010) recommend testing retention measures against a comparison group before scaling them, for exactly these reasons.

8. Risks

Day operators may see it as unfair. The intervention is available on days too, but day turnover is lower, so the plan funds it there only after the pilot.

Qualification standards may slip. The tool family sign-off stays with the training department, not crew supervisors.

The raise may only delay departures. If operators who receive the raise at month five simply leave at month nine instead, the plan would have paid for little. The pilot measures departures after the window for exactly this reason, and a shift of departures rather than a reduction would count as failure under the decision rule.

Second-floor demand may change the picture. As the second floor adds tools, operators with two qualified tool families become more valuable to the plant, which strengthens the case for the intervention even if its retention effect is modest. The plan does not count that value in its break-even, so the figure is conservative.

References

Allen, D. G., Bryant, P. C., & Vardaman, J. M. (2010). Retaining talent: Replacing misconceptions with evidence-based strategies. Academy of Management Perspectives, 24(2), 48-64. https://doi.org/10.5465/amp.24.2.48

Griffeth, R. W., Hom, P. W., & Gaertner, S. (2000). A meta-analysis of antecedents and correlates of employee turnover: Update, moderator tests, and research implications for the next millennium. Journal of Management, 26(3), 463-488. https://doi.org/10.1177/014920630002600305

Hom, P. W., Lee, T. W., Shaw, J. D., & Hausknecht, J. P. (2017). One hundred years of employee turnover theory and research. Journal of Applied Psychology, 102(3), 530-545. https://doi.org/10.1037/apl0000103