Compensation Management: Pay, Benefits, and HR Strategy

Job Characteristics Theory and Intrinsic Compensation

Job characteristics theory was first introduced by Hackman and Oldham. Building on this theory, a job characteristics model—also known as the JCM—was later proposed. The theory focuses on five job attributes that help motivate employees and make them feel satisfied in their roles. The five job characteristics are as follows:

Task Identity refers to the task assigned at a job having a defined beginning and end. This enables a worker to have a complete understanding of the job procedure and the set criteria for job evaluation.

Autonomy is the level of freedom permitted to an employee in his or her job. It addresses whether an employee is allowed to make changes to the work schedule and methods, or whether he or she must seek permission from higher-level staff to do so.

Skills Variety refers to the range of talents and skills required at the job. It indicates whether an employee performs only repetitive tasks or is required to do a variety of different things.

Task Significance refers to whether an employee's job has meaningful worth within an organization. It asks whether the job makes a substantial impact on the organization or society, or whether it is routine in nature.

Job Feedback refers to the organizational practice of regularly informing employees about their job performance (Hackman & Oldham, 1976, pp. 250–279).

Together, these job characteristics enable an employee to experience meaningfulness of work, a sense of responsibility, and knowledge of outcomes. These motivational factors are collectively referred to as intrinsic compensation. Because money alone cannot fully satisfy employees, organizations must also compensate their employees intrinsically in order to foster genuine motivation at work (Faturochman, 1997, pp. 1–13).

Exempt vs. Nonexempt Classification of Shift Leaders

According to the U.S. Department of Labor, shift leaders who function as assistant managers are considered exempt from overtime rights. Because they supervise subordinates and participate in managerial decisions, overtime pay does not apply to them as administrative staff. Furthermore, since the tasks performed by employees such as Jane are not repetitive in nature, she cannot claim overtime payment under the exempt classification.

There is a practical benefit for Jones Department Store in classifying shift leaders as exempt, since a number of employees have already left due to excessive workload—representing a financial loss for the store. The classification is also consistent with applicable labor regulations.

No. In this case, shift leaders are not properly classified as exempt. Jane is neither being paid at a rate equal to that of assistant managers nor compensated for overtime. Although she performs the work of an assistant manager and participates in managerial decisions as part of the management team, she is being overburdened beyond what her official job description requires, without equivalent compensation.

The first factor Amy should consider is whether shift leaders are actually being paid at a rate equal to the standard rate for assistant managers. Second, she should assess whether shift leaders are performing the same set of tasks repeatedly or a varied range of duties. Third, she should determine whether shift leaders—who are officially classified as associates—are performing only the tasks their job requires or are being overburdened with additional responsibilities beyond their designated role.

Profit Sharing Plans: Advantages and Disadvantages

Profit sharing plans—also known as deferred profit sharing plans—are arrangements under which employees receive a share of the profits earned by the company. These profits may be distributed in the form of stocks, bonds, or cash. Employees may also elect to receive profits at retirement or invest them in other ventures. Generally, there are three forms of profit sharing plans: cash plans, deferred plans, and a combination of both (Coates, 1991, pp. 19–25).

Companies establish profit sharing plans to foster a sense of organizational ownership among employees and to improve loyalty. While there are numerous advantages to these plans, there are also notable disadvantages.

Advantages:

The motivational level of employees increases. Employees become more committed to the organization. Employees work harder to improve company profitability. The gap between employee and employer is minimized. The overall well-being of employees is improved.

Disadvantages:

Administrative costs increase. Administration must monitor the equitable distribution of profits. Employees may focus solely on profitability and neglect work quality. It becomes difficult for the company to manage individual profit distributions on a regular basis (Watson, 2000).

Survey Data Analysis and Statistical Summaries

There are two broad approaches to analyzing survey data: basic analysis and advanced analysis. Basic analysis software such as Zoomerang and Survey Monkey include built-in options for graphs and charts. Advanced survey analysis can be conducted using tools such as Microsoft Excel and SPSS, which allow for customizable visualizations including bar charts, pie charts, and histograms. Analytical techniques such as cohort analysis and cross-classification analysis can be used to more rigorously assess collected data (Chromy & Abeyasekera, 2005, pp. 1–27).

Survey statistics can be summarized using two major approaches: measures of central tendency and measures of dispersion. Central tendency identifies the midpoint of a distribution, while dispersion indicates the degree of variation within the data.

There are three measures of central tendency: arithmetic mean, median, and mode. The arithmetic mean is applied to interval- and ratio-scaled data and is calculated by dividing the sum of all observations by the number of observations. The median is used with ordinal data, and the mode is applied to nominal data.

Three measures assess the compactness of data: standard deviation, variance, and range. Smaller values for these measures indicate that data points are more tightly clustered. The standard deviation formula uses frequency (f), the mid-range cell value (m), the sample size (n), and the sample mean to calculate spread (Horgan, 2009, pp. 13–22).