Job Evaluation Methods: Point, Factor, and Regression
This paper examines three prominent job evaluation methods — Lott's Point Method, Benge's Factor Comparison, and Multiple Regression — used by employers to establish justified pay structures. It defines job evaluation as a systematic process for developing pay variations among jobs within a single organization, then compares the compensable factors, procedural stages, and statistical approaches associated with each method. The paper identifies key similarities, such as the shared use of statistical processes and overlapping compensable factors, as well as important differences in how each method assigns value to jobs, concluding with practical examples of how each approach operates in an organizational compensation context.
- Introduction to Job Evaluation: Defines job evaluation and its organizational purpose
- Overview of the Three Methods: Describes Lott, Benge, and Multiple Regression methods
- Similarities Among Job Evaluation Methods: Shared statistical processes and compensable factors
- Key Differences Between the Methods: Contrasting procedures for assigning job value
- Practical Application and Examples: Real-world compensation examples for each method
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What makes this paper effective
- The paper provides clear, concise definitions of each method before moving into comparison, ensuring the reader has the necessary context to follow the analysis.
- It systematically addresses both similarities and differences between the three methods, giving the comparison analytical balance rather than simply describing each approach in isolation.
- Concrete numerical examples (e.g., the 300% point spread) ground abstract concepts in practical organizational scenarios, making the content more accessible.
Key academic technique demonstrated
The paper demonstrates comparative analysis as an academic technique. Rather than treating each job evaluation method as a standalone topic, the author explicitly identifies shared features — such as the use of statistical processes and overlapping compensable factors — before distinguishing the procedural differences that make each method unique. This structure mirrors standard academic frameworks for compare-and-contrast argumentation.
Structure breakdown
The paper opens with a definitional introduction to job evaluation and its purpose, then introduces all three methods in a single overview section. It proceeds to a similarities section, followed by a differences section that gives proportionally more detail to Benge's multi-stage procedure and the Multiple Regression approach. The paper closes with applied examples drawn from organizational compensation practice. This classic problem-definition → comparison → application structure suits an undergraduate business or HR course.
Introduction to Job Evaluation
As evident in the works of many professionals and scholars, job evaluation is described as a method that helps establish a justified rank order of jobs. This process is considered the starting point for developing the relative variations of wage rates. In some cases, job evaluation is defined as a systematic process geared toward developing pay variations among jobs within a single employer. In the past few years, several methods of job evaluation have been developed to make this process easier to understand and carry out. In addition to being used as a formal method for setting wage rates and pay scales, job evaluation methods are used for assessing the value relationships between jobs. Some of the most common methods of job evaluation include Lott's Point Method, Benge's Factor Comparison, and the Multiple Regression method.
Overview of the Three Methods
Benge's method of job evaluation is based on five compensable factors: responsibility, mental requirements, working conditions, skill requirements, and physical requirements (Henderson, 2006, p. 181). The method is built around these factors because they are most commonly used for creating base wage differences. Notably, compensable factors are described as particular job content features or requirements that are common to nearly every job.
Lott's Point Method, by contrast, proposed the use of fifteen compensable factors to determine various aspects of a job, such as pay rates and content features. These factors are used to determine the value of jobs by assigning each factor a numeric or point value. Some of the fifteen compensable factors used in Lott's Point Method include skill, responsibility, effort, and working conditions.
Multiple Regression is a job evaluation method based on scientific investigation and empirical application rather than hypothesis and theory. As a result, this method relies on objective and statistically scientific processes to determine and evaluate compensable factors that generate fair, reliable variable data — such as pay rates or probable increases in payment for a given job.
Similarities Among Job Evaluation Methods
These job evaluation methods share several major similarities with regard to their use in determining pay differences between various jobs and their application in a bias-free environment. One of the primary similarities among the three methods is that they all use statistical processes to determine and examine compensable factors related to pay or probable increases in pay. Secondly, both Lott's Point Method and Benge's Factor Comparison use some of the same compensable factors — such as responsibilities, skill, effort, and working conditions — to determine the value of jobs.
References
Henderson, R. I. (2006). Compensation management in a knowledge-based world (10th ed.). Upper Saddle River, NJ: Prentice Hall.
"Position Evaluation is the Foundation of Pay Program Design." (2007). Exempt Pay Program Design. Retrieved from Evergreen State College website:
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