Salary surveys collect information about employee salaries and benefits across different industries, regions and jobs. These surveys serve as benchmarking tools to enable companies to make informed business decisions about compensation.
Credible salary surveys are valuable in any economic environment. They provide statistical insights into the markets in which you compete for employee skills. A thorough analysis of your skills market will allow you to maximize the return on investment (ROI) of your compensation programs. Such market intelligence can protect your startup from paying either too little or too much for skills, which is key in any industry.
Startups can use salary surveys to help understand their strengths and potential exposures with respect to compensation—competitive salary and benefits. By reviewing all their employees’ salaries against the benchmark data, startups can identify low salaries and makes plans to correct this.
Without reviewing your jobs against the market, attracting and retaining talent can become an issue. If your salary is not competitive you will not be able to find the right talent. As well, if employees feel their salary is too low, it can diminish motivation and commitment. This, in turn, can lead to employees leaving the company or reducing productivity.
Referring to compensation survey data can help you justify and communicate difficult business decisions and create a sense of fairness. This can help motivate your employees, as they will be able to see the diligence undertaken with compensation decisions and may be more likely to actively support your startup.
As your business grows, surveys can help an organization benchmark themselves against their desired compensation position within their relevant skills market, ensuring their ability to attract and retain key staff. Regular market analysis will help bolster employees’ confidence in the organization’s compensation decisions.
While there is market data free of charge available on the web and through other media sources, the most credible data is produced by reputable consulting firms. When using a compensation survey, it is critical to understand how the statistics were established to ensure the data is valid, meaningful and defensible.
The following chart outlines some of the differences between free online compensation sources and those from reputable consulting firms:
Web surveys | Traditional surveys | ||
Data source | Ad hoc anonymous web submissions | Complete sample submitted by organizations | |
Geography | Varies | Global | Regional/local |
Typical participants | Unknown | Defined list of global multinationals | Defined list of regional companies |
Benchmarking accuracy | Titles entered by participants; no job descriptions | Each job family and job level are clearly defined | Each job family and job level are clearly defined |
Price | Free or individual reports: $220+ -Subscriptions: $2,000 to $3,000 |
Subscriptions: $5,000+ | -Individual reports: $100+ -Subscriptions: $1,200 to $3,600 |
Number of countries represented by participants | Varies | 15+ | 1 |
Typical company size | Unknown | 500+ | 20+ |
Submissions per year | Unknown—depends on how many times an employee enters their salary data | 1 | 1 |
Integrity/ quality assurance |
-No follow-up with individual -High-level statistical review |
-Job matches reviewed -Thorough statistical review conducted |
-Job matches reviewed -Thorough statistical review conducted |
Note: Traditional surveys collect full distributions of data directly from organizations.
Where resources permit, two sources of data are recommended in order to make accurate assessments.
To further assess industry compensation surveys and choose an appropriate source to inform your pay decisions, consider:
Taking the time to think through the above elements will help you conduct a qualitative cost/value analysis to determine which surveys best fit your needs.
Bear in mind that a salary survey investment is negligible in comparison with the loss of one senior professional, which can cost thousands of dollars of costs in recruitment expenses and lost productivity.