Labor economics theory suggests greater earning profiles are associated with increased human capital, which is associated with greater productivity (Medoff & Abraham, 1980; Ehrenberg & Smith, 2006). Employees who have more experience have a greater accumulation of human capital and operate at a higher level of productivity than less-experienced and low-valued capital employees.
Correspondingly, more productive employees are paid an increased wage due to their increased human capital and added worth to the employer. However, “there exists no evidence that corresponding pieces of the experience-earnings and experience-productivity profiles have the same sign” (Medoff & Abraham, 1980, p. 704). However, Medoff and Abraham (1980) argue that it is “very difficult to measure an individual worker’s productivity in an advanced industrial society” (p. 704). Additionally, there is little evidence that more productive employees are necessarily operating at a higher level of performance than what is expected of them.
Regarding performance-based compensation, Turner (2006) claims if motivation is driven by expectancy theory, then incentive-based compensation should be a relatively large percentage of employee compensation.
Motivating employees by using performance-contingent rewards is a long- established management practice. Pay for performance is used to promote two ends. First it is expected that these systems will motivate employees to increase their effort and thereby their performance. Expectancy theory clearly posits that effort is increased when meaningful rewards are offered […]
Second, these compensation plans are often introduced to better align the efforts of employees with organizational goals and objectives set by
management. (Turner, 2006, p. 23)
Regardless of the difficulties associated with measuring productivity and individual performance, companies utilizing performance-based compensation are cognizant of the fact that they must reward their employees accordingly. In
receive a proportionately higher amount of compensation relative to the average or the below-average performers in that same grade. However, “evidence from
research on compensation plans indicates that explicit financial rewards in the form of transitory performance-based bonuses seldom account for an important part of a worker’s compensation” (Baker et al., 1988, p. 595). This evidence leads
researchers to question if employees are really receiving performance-based compensation.
Medoff and Abraham (1980) analyzed two large manufacturing firms, Company A and Company B, with their results shown in Table 16. Employee performance ratings are shown in column 1, the earnings premium relative to the lowest performance rating is represented in column 2, and the percent of employees in that level receiving the performance grade is depicted in column 3.
Table 16. Salary Premiums Associated with Performance Ratings, and Frequency Distribution of Performance Ratings,
for Managers in Two Large Manufacturing Firms
Their findings indicate that the within-grade salary differential of employees in professional and managerial positions was minimal. Medoff and Abraham (1980) concluded that even though experience was rewarded by higher salaries, employee experience did not result in a significantly higher level of performance. Both
Company A and Company B administered performance evaluations by employees’ immediate supervisors indicating “how well an individual in the year of evaluation, is carrying out the responsibilities of his or her job” (Medoff & Abraham, 1980, p. 708). Employees in Company A earning “not acceptable” or “acceptable” ratings were below-average performers; “good” was an average performance mark; and “outstanding” was awarded to the top performers. In Company B, employees earning “satisfactory” or “good” ratings were below-average performers; employees receiving “superior” were average performers; and marks of “excellent” indicated top performance. Though Company B had two lower levels of performance, no
employees received those marks. (Medoff & Abraham, 1980)
There is a 7.8-percent wage difference between the lowest and the highest ranking employees in Company A, while Company B shows only a 6.2-percent difference between the same employee performance classifications. Additionally, Medoff and Abraham’s (1980) findings show that while nearly 95 percent of
Company A’s employees received ratings of “good” or better, only 20.2 percent were above-average performers. Meanwhile, Company B evaluated over 98 percent of their employees as “good” or better, but only 3.8 percent were recognized as above average. Furthermore, their study showed only a 2.5-percent and a 2.6-percent earnings premium between employees who received an average performance rating and those that earned the top performance mark for Companies A and Company B respectively (Medoff & Abraham, 1980).
In a 1985 study by Guzzo, Jette, and Katzell, the effects of monetary
compensation on worker productivity were measured. The authors concluded there were no performance benefits from financial rewards. According to Turner (2006), the data from the study:
produced no significant effects for financial incentives. The non-significant result for financial incentives suggests that, on average, the motivational value of incentives across these studies was zero. The use of financial incentives did not produce performance improvement. (pp. 26-27) Additional arguments contend that “money actually lowers employee
motivation, by reducing the intrinsic rewards that an employee receives from the job” (Baker et al., 1988, p. 596). Some performance-based compensation critics claim that employee motivation is decreased due to improper evaluation and performance measurements. “[E]vidence indicates that pay is not very closely related to
performance in many organizations that claim to have merit increase salary systems […] suggest[ing] that many business organization do not do a very good job of tying pay to performance” (Baker et al., 1988, p. 595). Performance-based compensation may even affect quality as employees become more concerned with chasing a performance bonus. Others assert additional negative side-effects of performance- based pay: deteriorated organizational morale and reduced productivity. These spillover effects more likely occur in organizations in which the performance-based compensation is incongruent with the current organizational culture; such was the case with Hewlett-Packard.
Furthermore, union pressure and court cases, filed by the American Federation of Labor and Congress of Industrial Organizations (AFL-CIO) and the American Federation of Government Employees, have stalled the implementation of performance-based compensation programs on the grounds of collective bargaining rights issues. Court cases have blocked, delayed, and forced revision to DHS and NSPS performance-based compensation programs (“Judge blocks merit pay at Pentagon,” 2006). Union workforces in the private sector face similar challenges, as the AFL-CIO are involved from the planning stages to the implementation phases of performance-based compensation programs (DoD, 2005a). Unions are strongly involved in performance-based compensation transition processes, highlighted by 36 labor unions’ participation in the NSPS’ “meet-and-confer process” during the initial planning phase (DoD, 2005a, p. 66,122).
H. Chapter Summary
Arguments exist on both sides of the spectrum as to the organizational
benefits of instituting performance-based compensation. What works in one industry may not work in another. However, prior to rushing to judgment and implementing a performance-based compensation system, organizations must conduct a thorough top-to-bottom organizational analysis that includes cultural and strategic objectives. In order to establish an effective performance-based compensation system, an organization must first understand what it expects from such a system. Will it be a vehicle for increasing performance, improving retention, or organizational change? It is essential for Navy leadership and policy makers to respect both the intended consequences and the unintended spillover effects when considering performance- based components of the SWO retention bonuses—as newly minted weapons to combat the Surface Warfare Officer retention problem.
VI. Modeling the Retention Effect of Adding a
Performance-based Component to the SWO Critical
Skills Bonus
A. Overview
The SWO community has identified retention issues at critical ports of exit in the mid-grade and senior level officer ranks (Crayton et al., 2002; Commander Naval Surface Forces, 2008b). Current SWO incentive pays offered to junior Surface Warfare Officers, (i.e., SWOCP and Junior SWO CSRB) are designed primarily to capture and retain officers early in their careers. Combined, these incentive pays allocate up to $75,000 for those officers who commit to serving through their department head tours, or approximately 10.5 YCS (Chief of Naval Operations, 2005b; Navy Personnel Command, 2008a). These two retention bonuses address the requirement to retain 275 SWO department heads; however, they do not directly combat the inventory shortage in the mid-grade and senior officer ranks at later critical ports of exit (Monroe & Cymrot, 2004). As depicted in Figure 8 and Figure 9, it takes several years for increased retention at 9 YCS to spill over and influence later SWO inventory shortages. Therefore, a more immediate solution is required to directly address retention at the 13-year port of exit to affect the current SWO
inventory through 15 YCS and beyond. The following data analysis addresses retention at the 13-year critical retention point, utilizing the SWO Critical Skills Bonus to capture mid-grade officers. The existing SWO Critical Skills Bonus is void of a performance metric and does not discriminate officer quality or economic rents of retention decisions for the targeted SWO population. The following models examine the potential retention effects of adding a performance-based component to the SWO Critical Skills Bonus.
The first section describes the dataset and sample utilized in the multivariate econometric and optimization models. The second section provides a description of the dependent and independent variables. The third section details the methodology
employed in developing the 13-year retention, tier characteristics, pay elasticity, and optimization models. Section four explains the hypothesized effects of the
independent variables of interest. The fifth section discusses the descriptive statistics, and the sixth section presents the results of the econometric regression models and optimization models. The last section addresses model limitations.