Interpreting Salary Survey Data

A salary survey is the process by which internal job descriptions are matched to external jobs with similar responsibilities to identify the market rate for each position. Failure to remunerate employees comparably results in failure to attract key talent as well as an exodus of your employees to your competitors. Therefore, it is imperative that your organisation ensures that its salaries are comparable or better than what competitors are paying.

There are two kinds of salary surveys, generic surveys and customised surveys. Generic surveys can be described as off-the-shelf surveys presented in generic job titles and job grades which apply across the board. Customised salary surveys, as the name suggests, are conducted by a remuneration expert with specific terms of reference written by the client. There are pros and cons to each of the survey types. Generic surveys are readily available. This means that for a quick board meeting, you can easily request for one and get the salary information you require. However, generic surveys may include companies which may not be comparable to yours. As such, the reliability and relevance of the results may be questioned. Customised salary surveys on the other hand are very specific to your organisation. The survey targets companies you want included in the sample, job titles you want the survey to cover and the benefits you are interested in. Furthermore, you can quantify the risk of losing your employees and how much it will cost your organisation if you are to match the salaries which your competitors are paying without extra work. However, customised salary surveys take time and you do not have any guarantee that your chosen comparator organisations will participate in the survey.

You need to interpret salary survey results carefully. Some jobs are restricted to one industry while others, especially those in support functions such as Marketing, Human Resources, Administration etc. are found across the board. For positions specific to one industry, you should benchmark salaries within your industry but for those that are found across the board, it is prudent that you benchmark against a sample that includes several industries. For each job title, make sure that it has been benchmarked against at least five other similar positions. The sample size of five here is given as a rule of thumb. For positions where there are a lot of incumbents e.g. miners, a relatively larger sample size is required.

If the sample is constituted with good comparator organisations and if it is of the right size, the next step is interpreting the salary survey results. Any statistician will tell you that the average is sensitive to outliers. This means that a single organisation that pays extremely high or extremely low salaries will distort the results of the survey and mislead your decisions. This is where percentiles come in. They take care of outliers as well as provide you with a pay policy line. Many organisations choose as their pay policy lines, the market 25^th percentile (lower quartile), market 50^th percentile (median) and the market 75^th percentile (upper quartile). For example, an organisation paying salaries that are at the market 75^th percentile pays its salaries that are better than 75% of what other organisations are paying. It is important that you compare your salaries against market salaries taking into consideration your organisation’s pay policy line.

For organisations not on the Total Cost to Company Model (TCCM) where all employee benefits are lumped up into one cash amount for each employee, one needs to know how much they should give their employees as allowance. The questions to ask are as follows: How many organisations provide this allowance? Does the amount given as the allowance increase as you move from non-managers to managers? Is this allowance given as a necessity for work? If the allowance includes dependents or beneficiaries, how many are included and to what extent are they included? If the allowance or benefit is a non-cash allowance (e.g. company vehicle), what is the value attached to that benefit?

If a company misinterpret salary survey data and end up awarding salary adjustments without fully understanding the data or the consequences it can lead to the organisation not being able to sustain the salaries awarded.

This article was written by Tapiwa Chipoyera and reviewed by Memory Nguwi. Tapiwa is the Manager – Workforce Analytics and Research at Industrial Psychology Consultants. His contact details are as follows: https://www.linkedin.com/in/tapiwa-chipoyera-7557b0a9/ ; Phone +263 242 481946-48/481950; Cell number +263 774 852 759; email: tapiwa@ipcconsultants.com

Memory Nguwi an Occupational Psychologist, Data Scientist, Speaker, & Managing Consultant- Industrial Psychology Consultants (Pvt) Ltd a management and human resources consulting firm. His contact details are as follows: https://www.linkedin.com/in/memorynguwi/ ; Phone +263 4 481946-48/481950/or cell number +263 77 2356 361; Email- mnguwi@ipcconsultants.com

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