Salary Data Showdown: Which Source Is Best

Finding the right salary data to make smart decisions can be tricky, with so many sources out there claiming to have the most accurate data. This post breaks down the perks and pitfalls of the top salary data options. It aims to help companies figure out which one suits their needs best.

Strap in for a showdown between government data, salary surveys, job sites, and more. We will provide all the details on accuracy, customization, and availability so companies can pay people fairly based on reliable insights. Whether it is national stats or niche job figures, this inside scoop will help companies become compensation professionals.

Government Data: Using BLS Wage Data

The Bureau of Labor Statistics (BLS) collects compensation data for nearly every occupation in the U.S. While extensive, the data is not always timely. The BLS updates wage estimates annually, so the numbers may lag the latest trends.

Broad Coverage

The BLS surveys cover hundreds of jobs across the country. This breadth of data allows for comparing salaries in various roles, experience levels, locations, and industries. The survey data also includes estimates of total compensation.

Standardized Methodology

The BLS uses a uniform approach and definitions across all their surveys. This setting allows for comparing salaries accurately. However, the strict methodology and definitions also mean the data may not capture some types of compensation.

Free and Publicly Available

The BLS data is free to access on their website. Anyone can download spreadsheets with salary estimates for nearly any job. While a valuable public resource, this open data can sometimes lead to salary compression if companies directly benchmark against BLS numbers.

In short, the BLS provides broad and standardized data that serves as a useful reference point. But the timeliness and approach of the data have some limitations. For salary benchmarking, companies must combine the BLS numbers with other data sources to get the full picture.

Private Surveys

Useful

Private salary surveys can provide employers with a clear estimate of what they may expect to pay for a specific position. However, these estimates are based on self-reported data from a limited sample of individuals. As a result, the numbers may not always accurately reflect the broader job market in each city or industry.

Anonymous and Voluntary

Since input in private surveys is voluntary and anonymous, the data can be unreliable. Employees who feel they are underpaid may be more motivated to report their salaries. Those earning higher may choose not to disclose that data. This can lead the surveys to understate average pay for some roles.

Use With Other Data

Private salary surveys can be useful as a starting point. But they must not be the sole deciding factor when setting pay ranges. Employers will get the most accurate picture by also examining data from public sources. They can also conduct their own local salary surveys. With multiple data points, companies can make the best choice for their needs.

Compensation Software

Crowdsourced Data

These platforms enable employees to voluntarily and anonymously submit their salary and job details. The collected data provides companies with insights specific to their industry, location, and job functions.

Built-In Engagement

Employees often appreciate the opportunity to contribute to the company’s understanding of compensation. Their involvement can increase job satisfaction and boost their connection to the company.

Personalized Suggestions

Some compensation software can analyze a company’s existing salary data, job descriptions, and locations. It can also examine other factors to provide customized pay range suggestions for each role. These AI-driven insights help ensure pay fairness and market competitiveness.

While compensation software has valuable benefits, companies must exercise caution. Employee participation must be voluntary, and the data must remain anonymous. For the best results, compensation software must be one of quite a few tools to set fair and equitable pay within a company.

HRIS or Internal Data

Many companies prefer using data from their human resources information system (HRIS) or internal surveys to set salary ranges.

Cost Effective

Drawing from an existing HRIS is extremely cost-effective since it collects and inputs data into the system. Companies do not have to pay for an outside source or spend time distributing and collecting additional surveys. The data is at their fingertips, ready to be analyzed.

Suits Company Needs

Internal data reflects the company’s unique workforce, roles, and pay philosophy. It accounts for specific job titles, experience levels, performance, and other factors that outside data may miss. Compensation experts can see exactly what their own employees in each position are earning.

Potential for Bias

Internal data also has its downsides. It may reflect biases or inequities that exist within the company. The data is also limited to that single company, so it does not account for industry trends or how other businesses are paying for similar roles. This can put the company at risk of overpaying or underpaying compared to competitors.

Using a mix of internal data and external salary survey sources is the best approach for most companies. Internal data provides a key internal reference point. External data offers a wider industry outlook to balance it out. Together, they give employers a full, fair view of the compensation landscape.

Conclusion

When it comes to salary data, there are pros and cons to the various sources out there. Government data provides consistent numbers but may lag real-time shifts. Private surveys offer more current data but have smaller sample sizes. Rather than picking one "best" source, the ideal approach is likely to combine multiple inputs to get a well-rounded view.

Just remember to keep a critical eye on potential biases and limitations. By thoughtfully blending data from credible sources, companies can make fully informed decisions as we move deeper into the future.