Dear Manager of Talent: Another Employee Waits Outside Your Door With Pay Data for Their Job…

You know the drill. Employee strolls into HR or their manager’s office, printouts in hand, to present and discuss the salary information they have compiled from the Web, which clearly shows that they are underpaid. Perhaps significantly so.

How do you deal with that? I offer some thoughts.

First of all, take the meeting. This can and should be a constructive exchange. You can’t really blame
the employee (well, not most of them, anyway) for wanting to ensure they are being fairly treated – through whatever methods are available to them. You can, however, insist that all data considered for compensation decisions at your organization – whether it comes through employees or from your own corporate survey “library” – meet certain criteria. This ensures that your pay practices are based on sound, reliable, relevant and quality information. It also helps position you for a constructive session, where you sit down together to review the information against this established set of criteria.

As a stepping off point, here is a suggested set of pay survey data criteria to consider:

1. The survey gets its information from an independent and verifiable source. Is the data gathered through HR or Payroll departments, or is it self-reported? Data that relies on self-reporting of pay by the incumbents themselves is not considered reliable, for all of the obvious reasons.
2. The survey describes its data collection method and process. A quality survey typically details the process followed for collecting and analyzing data as well as for checking data quality and validity. Typically, contact information is provided so that you can ask questions and get further information about the survey method and approach.
3. The survey identifies its participants. Many surveys, particularly those published by the big consulting houses, list the participating organizations. Failing that, the survey should at least provide basic demographic information on participants, including number of participating companies and statistics on their size, industries and geography.
4. The survey collects data using titles and job descriptions, rather than titles alone. Given the wide variation in titling practices across organizations, matching jobs by title alone is fraught with peril.
5. The survey reveals when the data was collected and its effective date. It’s important to know how old the data is in order to judge its applicability. Data that is too old – regardless of whether an “aging factor” has been applied – may no longer reflect the reality of a particular job’s competitive market value.
6. The survey identifies sample sizes. I feel differently about data that comes from a sample of 200 employees versus data that comes from a sample of just 5 – and so should you. But without sample size indications, you are missing information you need to make this appraisal.

What if the employee’s pay data does not meet the criteria? They may not be thrilled to learn that their information can’t be considered – but hopefully you’ll have provided a teaching moment and prepared them to look at future web pay data with a more informed eye.

And what if (gasp) the employee’s pay data does meet the criteria? If it does, then it probably is information you should be considering, and you may need to thank the employee for bringing it to your attention. There may be additional discussion necessary regarding whether the employee has correctly matched their position, etc. – but those are bridges to cross only after you determine that the source meets your criteria.