The "Best of the Force" has been an effort to highlight some of the most popular posts from our eight years of archives. This post (first published in October 2010) presents you with my advice to the internet-age problem of addressing the compensation data that employees generate via their own personal research and bring to you as proof of their being underpaid.
Short version: Don't miss a teachable moment (perhaps for you as well as the employee) and don't automatically assume their data isn't valid.
oday, any motivated employee can gain access to salary data which suggests, nay proves, that he or she is underpaid by many thousands of dollars. Yes, even in these tough economic times, and you know the practice will only increase as the economy recovers.
One of the most frequent questions I get from my own clients is how to deal with the line of employees out their door waiting, Internet pay survey printout in hand, to discuss their compensation.
I recommend meeting this challenge head on by focusing on pay data quality and establishing a policy that features specific quality criteria that all pay data must meet (whether brought to the table by Human Resources or an employee) before it will be considered relative to the organization's compensation practices. Armed with a formal policy on pay data quality, the HR pro is positioned to have a productive discussion about the specific data an employee brings in.
Let's face it. Data of questionable quality exists both on the Internet and in traditional hard-copy format from publishers who should know better. The good news, though, is that the same quality standards should apply regardless of the source of the pay information. Here are some of the standards I recommend for assessing pay survey quality, presented for your consideration in developing your own policy.
Survey details its methodology. The survey data provider should detail its process for contacting or soliciting participants, collecting and analyzing data, and checking data quality and validity. A lack of transparency around survey process and method only makes me wonder what they are trying to hide.
Survey data is collected from an independent, verifiable source. I would consider the Human Resources, Finance or Payroll departments of an employer to be independent, verifiable sources of pay data. Surveys based on data submitted by recruiting firms or self-reported by individual employees (both of which stand to gain by inflating pay rates) are not considered reliable by most compensation professionals.
Survey identifies participants. If not a list naming participating organizations, there should at least be a demographic profile which outlines information like their number, size, location, industry and other characteristics. If you don't know where and from whom the data is drawn, how can you determine whether it truly represents your organization's labor market?
Survey provides job descriptions adequate for matching. Proper job matching is the foundation for successful market pricing. Matching by job title alone is fraught with peril given the wide variances in titling practices that exist among different organizations and industries. Survey job descriptions should include education and experience specifications, as well as a listing of job purpose and typical responsibilities. (And it is sometimes necessary to remind the employee that the employer sets job price by the job responsibilities and requirements, not the years of experience they happen to possess.)
Survey reveals effective date of data. Its important to know how current the data is so that its validity can be ascertained. Given the turbulence in today's labor market, data that is too old -- regardless of whether or not an aging factor has been applied to bring it forward -- may no longer reflect the realities of a particular job's competitive value.
Survey notes sample sizes. How many organizations and employees are represented in a particular piece of data? Obviously, data based on 200 employees is more meaningful than data based on 5 employees; without this information it is impossible to determine whether a markedly high or low pay figure is valid, or simply the skewed result of a small sample size.
With formal pay data quality policy in hand, my advice to the HR pro who is approached by an employee with their own competitive information is as follows:
1. Thank them for their efforts in bringing the data forward. (Yes, I know, but really. If it turns out that the data is valid, they may be doing you a favor. Just keep your mind open to the possibility.)
2. Explain (and provide a hard copy of) the organization's policy on pay survey data and quality criteria.
3. Sit down with the employee and review their information together to ascertain whether it meets the organization's criteria.
To the extent that the employee's information meets the quality criteria (and it represents a valid match for his/her job), it ought to be taken seriously and considered in light of current pay practices for the position and the particular employee. To the extent that it does not, the occasion should provide a teaching moment for the employee (although the astute HR professional may wish to go afterwards and double check the data used historically to set pay practices for the position, just to ensure that the organization is standing on firm ground).
What's your practice and approach for responding to employee data and the quality questions it often raises? Got any tips to share with us here?
Image "Piggybanks Eating Money Showing Monetary Loses" courtesy of Stuart Miles at FreeDigitalPhotos.net