Job levelling is important for organisation for many reasons:
In this method, positions are directly assigned to predetermined grades or salary levels based on a quick comparison with benchmark positions. Job descriptions are compared to established role profiles and then placed in the most appropriate grade or level.
This method is faster and less resource-intensive than other job levelling methods, making it particularly useful for smaller organisations or when evaluating new positions. However, it can be less precise and more subjective than other levelling methods, potentially raising concerns about accuracy and fairness.
Job classification is a more structured approach which involves systematically categorising positions into grades based on predefined criteria. In contrast to job slotting, it uses a more detailed analysis of job characteristics against established grade definitions.
This approach can produce greater consistency across similar roles, a clearer organisational structure, and standardised pay ranges.
The drawbacks are that implementation can be time-consuming, while the potential rigidity in level definition can make it a challenge to accommodate unique roles. It’s also a system which requires regular reviews to maintain relevance.
Factor comparison is a quantitative job levelling method that evaluates jobs by comparing them against factors or criteria (such as skills, effort, responsibility, and working conditions). It involves evaluating jobs on a factor-by-factor basis.
This is a more analytical and detailed job levelling approach which better supports pay equity and pay transparency. It’s also more effective for unique jobs because each role is considered individually.
The potential downsides are that factor comparison can be complex, time-consuming, and requires significant expertise to implement. It can also be expensive to maintain, and HR teams may face resistance due to its complexity.
The point factor method is essentially an evolution of the factor comparison method. It builds on factor comparison by assigning numerical points to factors. Each factor (such as skill, effort, responsibility) is broken down into levels, with specific points allocated to each level.
A questionnaire is developed so that points can be assigned for each factor for a job role. The points are then added up to produce a score. This score is then matched against the levelling structure to determine the job level. Each level has a predefined total score range so the jobs are automatically sorted into levels via their total score.
This method allows organisations to adjust the relationship between points and pay more easily. The structured nature of this method provides greater objectivity and consistency in evaluations. It still requires significant time investment in developing and maintaining the point system and factor definitions.
This approach focuses on external data, using job descriptions to compare jobs to identical or similar positions in the external marketplace. Pay data is collected from published sources and the value of the position within the competitive market is determined.
This approach helps organisations to consider their positioning on compensation and is used by many companies to assess internal pay equity and the competitive value of individual positions.
Many job levelling frameworks have been developed – based on some of the methods outlined above - to help organisations with job levelling. Here are some of the key ones:
Radford (Aon) Job Levelling Framework
The Radford job levelling framework is a globally recognised system which categorises jobs into six levels: Entry (P1), Developing (P2), Career (P3), Advanced (P4), Expert (P5), and Principal (P6). These levels are applied across career tracks such as Professional, Support, Technical, and Managerial roles, allowing organisations to differentiate between individual contributors and managerial positions while maintaining internal equity and market alignment.
Radford evaluates and levels jobs using key factors including:
the level of people management, financial responsibility, knowledge and skills required, and the role's impact on business outcomes.
Willis Towers Watson (WTW) Global Grading System (GGS)
The Willis Towers Watson (WTW) Global Grading System (GGS) is a robust job levelling framework operates on a scale of up to 25 grades. The framework uses a two-step process: banding and grading. Banding places jobs within a hierarchical structure based on their contribution to the organisation, while grading evaluates roles against seven key factors:
Korn Ferry Hay Method
The Korn Ferry Hay Method of job levelling is another widely used framework for evaluating and comparing job roles across organisations. It employs a point-factor methodology to assess jobs based on three core elements:
Each of these elements is scored using detailed charts, and the total score determines the job's level within an organisation's grading or levelling structure. The method also incorporates checks to ensure logical relationships between roles in hierarchical structures, such as comparing knowledge depth and management breadth between a role and its supervisor.
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