When I took golf lessons and learned to putt properly, the instructor told me to aim for a spot beyond the hole to better the chances of the ball falling into the hole. It’s a common rule of thumb for putting. Employers need to learn this lesson. In all the efforts to close the gender pay gap, most employers are not only not aiming beyond the hole or target, they are aiming for a spot before the hole. Whether a disconnect or flawed logic, the gender pay gap will never close if it continues.
The gender pay gap is defined as the difference in median pay earned by men (MM) and the median pay of women (MW) who work full time. The goal is to get the difference to zero. As a mathematical equation it would be:
MM – MW = 0
According to a 2015 story in the Society of Human Resource Management (SHRM) 85% of companies target median pay of all people (MA) working in the job when determining compensation offers. The problem with that target is the median for all people is not equal to the median pay earned by men. For the vast majority of jobs, the median pay of all people doing a job is lower than the median pay of men doing the job.
MA < MM
That’s because the statistically lower pay of women drags down the number. The Bureau of Labor Statistics (BLS) annual report on median income by gender and job illustrates the problem of using median pay for all. There are 550 jobs in this report. Just 12 show women earning the same or more than men. Looking at all but those 12 jobs, the median income of women (MW) working in a job is less than the median income of all (MA) which is less than the median income of men (MM).
MW < MA < MM
Resulting in
(MA – MW) < (MM – MW)
It is virtually impossible to catch up to the income of men if we are using a target number lower than what men earn.
Sample Jobs from BLS Median Income Report by Gender
|
Job |
Median for Women (MW) |
Median for All (MA) |
Median for Men (MM) |
|
Marketing and Sales Managers |
$69,079 |
$82,357 |
$100,137 |
|
Human Resource Managers |
$70,342 |
$72,008 |
$77,463 |
|
Insurance Underwriters |
$56,465 |
$61,197 |
$73,389 |
|
Chemical Engineers |
$84,137 |
$100,425 |
$101,626 |
|
Psychologists |
$69,134 |
$72,789 |
$90,586 |
|
Librarians |
$50,671 |
$51,429 |
$57,961 |
|
Dental Assistants |
$31,161 |
$31,226 |
$32,231 |
|
Transportation Security Screeners |
$40,534 |
$41,793 |
$43,027 |
|
Elementary and Middle School Teachers |
$50,021 |
$50,659 |
$53,096 |
|
Janitors and Building Cleaners |
$22,962 |
$27,742 |
$30,654 |
You may have noticed that the amount of the difference in the chart above varies from job to job. The breakdown of men and women working in the job and the gender pay gap for that particular job impact the difference between the two. Yet, even with a small difference between the median income for all and the median income for men, there is a difference as shown in the $5 difference for dental assistants. Very few of us would complain about missing those $5. We would have a heated conversation for the almost $18,000 difference sales and marketing managers experience.
Yet, that is what is happening at 85% of employers. They are using a barometer for a fair and equitable offer that is not fair and is not equitable. To their defense, the tools available to determine fair and equitable offers typically report on the income of all people. Back in the day, compensation reports based on gender were very common and existed for the purpose of paying women less. Today, we need those reports again. Actually, we just need the compensation report for men doing a job to enable paying women the same. Employers start asking your vendors for such reports. Until they deliver, you can determine the median wages of men doing the job at your company or target higher than median wages for your offers. Oh, and candidates you can help out by never again accepting an offer which is the median pay of all.
Changing the data from everyone to the data of just men and preferably, just white men, will not automatically make pay equity a reality. It will remove an unrecognized barrier from achieving it. Similar to ending the time-honored best practice of using salary history in hiring and compensation decisions, the use of data from everyone is diminishing the progress so many have strived to achieve for too long. Some studies estimate it will take 200+ years to achieve pay equity. The date keeps moving further away instead of closer.
Like Sisyphus carrying his rock up a hill over and over again just to see it roll back down, pay equity efforts see progress that quickly comes back down. No progress will be sustainable without addressing the roadblocks that prevent it. Use of the wrong data, like salary history, is a roadblock. There are additional roadblocks that need to be addressed which will be covered in future articles. Stay tuned.