What is Compensation data in Canada and How to make it Work for Your Organization
Posted: Jun 23, 2017
Compensation data includes a variety of information about salaries and benefits that employees receive for their work; the data is usually collected through employer survey. Some compensation surveys give an overview of the industry, while others focus on certain positions or a particular type of organizations. Mainly policymakers and agencies use the information from compensation surveys as well as by employees and employers.
Why You Should Use Compensation Data as an Employer in Canada
Equipped with knowledge of the wider compensation information, companies can ensure that they compensate their workers in ways that are aligned with their organizations’ objectives and competitive. Compensation data helps organization compete for talent. Most non-profit organizations operate on little budgets thereby paying relatively small salaries. But there is much more to compensation than just salaries.
Compensation also includes factors like challenging work culture, flexible working arrangements, and professional development opportunities. Research shows that these non-financial forms of compensation are important to employees. The critical thing is thinking broad and with a creative sense of what kind of compensation system will help your organization and staff gets the best from each other. Survey data can illuminate a range of compensation practices and possibilities.
How to Use Compensation Data in Canada
Like all research information, compensation data must be drawn approached fundamentally. A few attributes to search for are Validity and Reliability, Usability, and Completeness of the data. Depending on your requirement, some data will be more useful to you than others. As a base search for surveys that get results from organizations that are similar to yours. To make the ultimate use of the data, it is vital that you consider what allowances you have to make for contrasts between your organization and data you are using.
A good sample size can likewise be significant when it comes to enabling correlation. Assume you want to understand how the compensation data of an administrative assistant measures up. Preferably, you would want a survey that plenty similar organizations had completed, and that covered organizations that are similar to yours in size, that employ administrative assistants and, whose administrative assistants’ job descriptions are similar to yours. You might not be able to find a perfect data set, but surveys with a broader scope can be more likely to provide valuable comparative data that meets your needs.
Look carefully at the reported data to ensure that you are interpreting the information accurately. If data uses shorthand (especially in a chart or caption), it wouldn't be less than difficult not to mistake one for the other. Being able to understand what you are reading will help you draw the needed conclusions for your organization.
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