When it comes time to determine the best source of data for your compensation needs, there are a few things to keep in mind to adequately evaluate sources:
- Breadth of data: How wide are you casting your talent net and defining your competitive set? Do the data cover your industry, jobs and locations?
- Precision: How specific do you need the data set to be? Does it need to cover specific skills that may be hot in the market? Or is a more general set of responsibilities enough?
- Age: How often do you need a pulse on the market for your jobs?* The frequency with which you obtain market data will depend on the competitiveness of your market for your industry, location, organizational size, jobs and even specific skills. Do you hire in cycles? Do you have in-demand jobs?
*According to PayScale’s 2017 Compensation Best Practices Report, 25 percent of organizations have completed a full market study in the past six months. Thirty-nine percent of enterprises check market data at least weekly for their critical jobs. Sixty-seven percent of tech companies have completed a full market study within the past year.
- Ease of use: Will the data be used by a diverse set of stakeholders or exclusively by compensation experts? Who will need to see, use or understand the data? If you will need to share the data and data source with executives, managers and/or employees in your organization, is the information easy to access? Easy to understand? Easy to share? How integrated is your compensation team with managers and team members? Consider your data source with socialization in mind.
Next, you want to be sure to understand the methodology of the data source well enough that you can teach it to other people within your organization. This is necessary to both ensure buy-in among managers and executives, as well as to explain the data to your front-line managers and employees. There is both an art and a science to compensation. Data is the science part of the formula, with a healthy dose of strategy applied. The art comes into play when you begin to tell the story of your data. Why does this data set solve your needs? How does this data-driven compensation strategy lead to business results?
Finally, consider that you may not be able to solve all data needs with a single data source. If that’s the case, what sources do you intend to use? Will you blend them or consider using one source for some jobs and another source for others?
Interested in more info on salary data sources? Keep your eyes peeled for our whitepaper “The Compensation Data Landscape: A Review of Data Sources, Plus How to Choose” — coming soon!
Tell Us What You Think
How does your organization choose salary data sources? We want to hear from you. Tell us your story in the comments.