When we talk about women being underpaid, I think what we are discussing is that women are paid less to do a job that a man is paid more for. Since we don’t really have a good solid baseline for what a person is worth, it is just as likely that men are overpaid as it is that women are underpaid, on average. Salaries are established through a series of largely subjective decisions, which we’ve largely tried and failed to make objective. And let’s be clear, salary inequality doesn’t just exist between men and women. It exists between men and other men, and women and other women, as well. But it isn’t always easy to differentiate between a false perception and reality.
The influx of artificial intelligence and robotics may fix this, but I really doubt most of us are going to like that eventual process, particularly CEOs. And here I mean that what we eventually may be worth is something less than it will cost a robot to replace us. For CEOs, far better algorithms for determining executive salary are coming that are more closely tied to actual performance. Failure to use them will most certainly become a board liability (activist investors, hedge fund managers really, love their stats).
Let’s look at why inequality exists and why fixing it is problematic.
Causes of Inequity
I’m going to focus on technology because that is the area where I spend my time. For decades, talented men were pushed into STEM kinds of courses that lead to engineering classes and degrees, while women were discouraged from this same path. My own engineering classes were virtually all men. That clearly resulted in a huge imbalance in viable candidates, and whenever you have a massive majority in a field, that majority tends to become an illegal, but still used, standard for employee selection. This all drives what we now know is a false perception that men are better at these jobs than women genetically, when the more accurate answer is that the discrepancy is due to discrimination starting in childhood and initial hiring practices that pay men more.
Now we know from testing that if a manager believes a thing, they do things to validate that thing. And managers tend to be older, which means their perceptions also tend to lag reality, not lead it. So, part of the cause is a perception that women are worse at things like engineering, which may have been true, largely due to failures in the education system, but increasingly is not true. This behavior violates the rule that pay always should be based on actual performance, not gender-based stereotypes. But we’ve really done very little to change these deep-seated beliefs in managers and instead tried to fix this by policies and laws, which rarely are effective when they violate belief. I can write a policy that states no discrimination but if my managers naturally discriminate, and feel justified doing so, that policy will only make it look like I took action. No real change will result.
Another increasingly false belief and justification (which was stupid in the first place) is that men needed more money because they supported a family and women didn’t. The reason I think this is stupid isn’t because it wasn’t accurate, back then men were generally the bread winners, but because pay should be based on your value, what you produce, not on your need.
But even that screwy cause is gone because now it is far from uncommon to have two-earner households, single mothers, and stay at home fathers. While this cause has evaporated, I still see managers making salary decisions as if it were the 1950s.
Effect of Money on Productivity
A lot of work was done in the 50s and 60s analyzing the effect of money on productivity, but few today seem to know the results of those studies (I did a lot of my undergraduate and graduate work in this area). These studies found that giving someone more money had little effect on their productivity. Give someone a 10 percent raise, and they don’t work 10 percent harder. However, taking money away has a massive effect on productivity. Take 10 percent away and you can drop productivity by as much as 50 percent (and often the employee resigns).
This is a problem because employee salary, rolled up, goes against profit margins, and CEOs are measured on margins. Any adjustment to resolve inequality would have to reduce the expense of something to balance the increase of women’s salaries. The obvious source would be men’s salaries. So, let’s say men were paid 20 percent on average more than women. If you reduced men’s salaries by 10 percent and increased women’s salaries by 10 percent, you’d have equality. However, the men would be pissed, large numbers would likely resign, and productivity would drop sharply. Women wouldn’t work harder, because money doesn’t work that way, and would likely not be happy with the result, because they wanted a 20 percent raise. An additional problem is that some women would likely be blamed by the men for taking money the men thought they’d earned, creating additional tension in the workplace.
By the way, given the effect of salary reductions on productivity, it still amazes me how many CEOs implement broad salary reduction programs. They falsely appear to believe salary reductions are better than layoffs. Most find that they still must do the layoff due to a continued reduction in company performance.
What’s a Job Worth?
At the heart of this problem is that we still don’t have an objective baseline for what a specific job is worth, except for a few high-value jobs where the salary is based on high demand and low availability. We often don’t even have a great objective way to measure performance in a job. This allows some CEOs to think they can replace highly paid, experienced people with far less experienced people and lower salaries, and think that is a good decision. I once watched a CEO decide to get rid of a salesforce of high-powered hunters (those good at getting new business) with an equal group of farmers (those that assure customer care), and while he did save a ton on salaries, he also dropped revenue by a whopping two-thirds and got fired (the company never recovered).
Wrapping Up: Fixing the Problem
The answer here starts back in education by ensuring a good mix of men and women getting the degrees needed to get equivalent compensation. It moves to a hiring practice that matches skills with salary objectively, and then it finishes assuring that managers are trained to be as objective with raises and reviews as is humanly possible. However, overarching this is a system that the employees trust, that identifies those who are significantly overperforming or underperforming their salaries, and helps management address both problems. Only if we fix the education part will this work. Otherwise, men’s salaries in the firms that implement this will be lower than the firms that don’t and they’ll lose talent, unless there is a large pool of women that can pick up the slack.
I’ll leave you with one personal story. When I joined IBM, I did so from a family business where I was massively underpaid. As a result, because my salary was partially based on what I had been making, I was paid about 50 percent what a woman starting the same week I did with similar education and skills but no prior job, was paid. During the next decade, I nearly always got the highest percentage raise in my division, largely because the system was making up for the discrepancy, while my peers who were far higher in the range got very little or nothing. Since my cost of living was set by how much I made, I was generally happier than my peers were. The raises made a real difference in my life and did allow me to save more even though I made less. If I focused on the raises and not the salary discrepancy, I was happy and I generally was happy.
My lesson was that you can choose whether to let this kind of thing depress you or hurt your performance, or you can choose to focus on the positive things and kick butt. I did the latter and eventually I topped out what was a very lucrative salary range. Then I quit, because I really started missing those raises. Something to think about.
Rob Enderle is President and Principal Analyst of the Enderle Group, a forward-looking emerging technology advisory firm. With over 30 years’ experience in emerging technologies, he has provided regional and global companies with guidance in how to better target customer needs; create new business opportunities; anticipate technology changes; select vendors and products; and present their products in the best possible light. Rob covers the technology industry broadly. Before founding the Enderle Group, Rob was the Senior Research Fellow for Forrester Research and the Giga Information Group, and held senior positions at IBM and ROLM. Follow Rob on Twitter @enderle, on Facebook and on Google+