In this article our focus will be on the use of Paterson Job Grading in the context of personal injury, and will cover the following topics:
1. The application of Paterson Job Grading in the context of personal injury.
2. Data smoothing within Corporate Surveys.
2. The use of Total Package versus Basic Guaranteed Package earnings.
1. JOB GRADING IN THE PERSONAL INJURY CONTEXT
We have been in various discussions with Mater and Chartered Rewards Specialists, registered with the professional body known as the South African Rewards Association, to gain greater insight into the application of Paterson Job Grading within the personal injury context. We have assumed that all Industrial Psychologists have exposure to the Paterson Job Grading systems, however since many readers may be novices, we will provide a brief overview of Paterson Job Grading.
1.1 Overview of Paterson Job Grading
The Paterson job grading approach is a job classification method. The classification consists of six bands of decision-making ranging from Band A (defined decision-making) to Band F (undefined decision-making/policy-making decisions), using four factors namely; variety of tasks, complexity of tasks, precision, and lastly pressure of work or physical effort. Bands would also consist of various sub-grades providing a greater range of decision-making classification. When this job grading system is applied, jobs are first classified under the specific band (A to F) with the definition that agrees most closely with the job requirements. Jobs would then be sorted into the lower and upper grades in terms of the coordinating principles i.e. jobs that include coordination of other jobs in the same band will be placed on a higher grade. Further sub-grading would then be applied following the same approach.
1.2 Job Grading by Industrial Psychologists
In a recent newsletter by Dr. R.J. Koch, it has come to our attention that Industrial Psychologists ascertain job grades by equating the claimant’s earnings to a job grade. This is an incorrect approach to follow. Upon my research and discussions with remuneration consultants and salary survey companies, the only approach to accurately grade a job is as follows:
a) Review the job description and specifications of the job.
b) Evaluate the job at the place of work.
c) Assess the reporting structure in the organisation.
In some cases, salary survey companies will be provided with payslips (or reported salaries) for specific occupational levels to include in their database. Sometimes the occupation would not be graded and the organisation may not be willing to pay to have the jobs graded by external consultants. In such cases, remuneration consultants would not necessarily evaluate the job within the workplace but would rely on the job description, specification, reporting structure and the modal grades (this requires remuneration expertise and judgement) for similar occupations.
We would therefore advocate that Industrial Psychologist use the same approach in plotting claimants on a Paterson grade or level before referencing the earnings level.
1.3 Disadvantages in the application of the Paterson System
The Paterson Job Evaluation method is commonly used around the globe and has the benefit of simplicity. Considering the array of occupations dealt with in the personal injury sector, Industrial Psychologists should take note of the possible disadvantages of the application of the Paterson job grading system:
- Even though the system is simple and easy to understand, it requires a job grading expert to derive the correct job grade.
- There is a lack of uniformity of the application by non-expert graders who use the system without following the correct process, and who may also apply their own subjectivity and interpretation.
- Problems can be experienced when grading complex executive positions – since the job is influenced by company size and complexity. Using an executive grading system achieves more granular results.
2. DATA SMOOTHING OF CORPORATE SALARY SURVEYS
We have been informed that a prominent corporate salary survey, used frequently by Industrial Psychologists, uses a technique referred to as data smoothing when reporting salary benchmarks. Data smoothing is a technique used to limit the influence of outliers and illustrate trends within the data set. This approach has the major disadvantage of reducing the representative nature of the data captured. This is a nonsensical approach for salary benchmarking since they report percentiles (and not trends or projections) of a specific job or decision-making universe. It would be better to use a benchmarking approach to get a more granular and accurate result.
Considering the above, Industrial Psychologists should be vigilant to refer to corporate salary surveys as representative of the entire working population. Multiple sources and experts would confirm that the profile of companies that firstly, grade jobs, and secondly, partake in salary surveys, are generally only representative of the formal job sector in South Africa. Alternative data sources need to be used for the informal job sector in South Africa.
It is therefore imperative that Industrial Psychologists assess the claimant in isolation and determine which salary research and data is most applicable on a case by case basis. Analytico uses both formal sector data through the 21st Century salary survey as well as multiple public sources of data for the informal sector.
3. TOTAL PACKAGE VERSUS BASIC GUARANTEED PACKAGE
Should Industrial Psychologists need to project a claimant’s earnings without confirmation that the claimant receives medical aid or pension fund contributions, it is recommended that the Basic Guaranteed Package is used for earnings postulations. An analysis conducted on the Quarterly Labour Force Survey could guide Industrial Psychologists on the use of Total Package versus Basic Guaranteed Package by adding the contributions to the Basic Guaranteed Package as per the table below:
It is important to also note the overall prevalence of these contributions. 46% of the sample from the QLFS received pension fund contributions with a significant decrease in employer contributions towards medical aid of only 28.1%.
The above tables shows that the higher the level of education the more likely one is to obtain employment in the formal sector where the employer is willing to contribute to pension/retirement fund and medical aid contribution.
We are looking forward to contributing towards further research and development in the legal sphere. We believe that even the most basic use of data and statistics can guide the court and experts to form informed decisions.
Senior Analytics Advisor