As a female and a feminist who has worked in male-dominated fields for most of my career, what immediately caught my eye when reading the most recent TDWI Salary Survey report was the on-going pay disparity between women and men in BI. According to TDWI research, men continue to out-earn women in the BI field, with a gap of $12,581 in average salaries for 2014. You can see in this chart that for the past five years, women in BI have, on average, earned about 89 percent of what their male counterparts in BI earn.First, though, I think it makes sense to look at the bigger wage-gap picture.
It has been widely reported that women are paid only 78 percent of what men are paid. Yes, I’ve heard all of the arguments about the wage gap. Women earn less than men because they choose to work in industries that are less lucrative than men. Men are engineers; women are teachers and social workers. Women are poor negotiators; they don’t self-advocate for higher pay. Research has shown that women are less likely to negotiate their salary than men. (See reference #1 at end of this article.)
There is the argument that women earn less because they choose to work less to be with their children — or that they put in less face time at the office — or that there is discrimination in promoting women (really, imagine that!). I’ve read the op-ed pieces dissecting the numbers, arguing with the statistics, and pointing out faults in the logic of the analysis.
Some of the best research in the field has been done by those who try to control for variables such as education and experience and look at pay discrepancies within a particular field. For instance, Harvard economist, Claudia Goldin (see reference #2) has found that the pay gap is widest in some of the highest-paying fields such as in finance, law, and medicine. Goldin argues that the gender pay gap is due to firms that have “an incentive to disproportionately reward individuals who worked long hours and who worked particular hours.” This is about face time.
What’s happening in the specific field of BI? I decided to take a deeper dive into some of our 2014 salary data. I was particularly interested to understand women’s roles in BI and how big the salary gap is in those roles. I could not control for all variables; I needed to use the data I had. The survey was not designed to specifically look at gender pay discrepancies. I didn’t have the time to look at past surveys (although I might in the future). There were 300 responses from females and 757 from men. My preliminary analysis (U.S. and Canada only) yielded some interesting findings.
Roles: Women are less likely than men to be BI directors or lead architects. Women are more likely to be BI project managers or data analysts/modelers. In other words, men are more likely to be in leadership roles that pay more money.
Salary: I looked at the salary in areas where you’re more likely to find men proportionately (e.g., BI directors and lead architects) as well as where you are more likely to find women (such as in data analyst and project manager roles). In all instances, women earned less (see Table 1, below). In the BI director role, women were slightly older (47 vs. 45 years), although men had slightly more (1 year) experience. Men earned slightly higher median bonuses in this role (although only about two-thirds of all respondents earned bonuses). The median differential between women and men in this role was about $5K in 2014.
In other roles, such as data analyst/modeler where women are more likely to be positioned proportionately, women still earned less than their male counterparts, although they were about the same age and had the same experience. Women also earned slightly less in the project manager role. The result? Women appear to earn less in roles where men dominate as well as in roles where men are proportionately more numerous. Women even earn less in roles where there is no significant difference in their numbers (proportionately, such as in the program manager role shown below). Although I haven’t explored data from previous years, my hypothesis is that although the actual numbers will differ, the gap will still be present.
(2014 Median $)
(2014 Median $)
Table 1: Median salaries (2014) for men and women in different roles.
Education: The 2014 salary gap widened significantly due to education. Although men earned higher median incomes as their education level increased, women’s median income stayed essentially flat, despite their level of education, at about $97K. However, 2014 may have been an anomaly. A similar analysis of 2013 showed that although men with any degree were paid more than women with the same degree, at least women’s median salaries increased as their education level increased. This requires further investigation. I think it’s interesting that the AAUW (American Association of University Women) found that, in general, at any level of education, women’s median earnings are less than men’s median earnings, and in some cases the gender pay gap is larger at higher levels of education (see reference #4).
Fair pay: There was no difference between men and women when it came to job satisfaction or fair pay. In other words, the percent of women respondents who thought they were unfairly paid did not differ much from the men who thought they were not fairly paid.
As Goldin postulates, pay discrepancy might well be due to the face time factor. The data from this survey suggests that a top priority for women in looking for a position is work schedule or hours (significantly different compared to men). It may not matter that women are working hard, at home, both before and after office hours. Others might believe that if you can’t see it, it doesn’t count. Some men might have the option of schmoozing in the break room; some women may not have that luxury. That doesn’t mean that they aren’t putting in as much time as men, they may just do it differently. Because it’s also often not about what you know but who you know in terms of getting promoted, the face time issue might also hurt women’s chances of getting promoted (or even getting appropriate pay) because of the schmooze factor.
Perhaps if pay became more transparent, women (and some men) would get angry enough to negotiate for higher pay up front. Maybe we don’t negotiate as well as we should, especially for the non-executive positions. Maybe we would if we had more facts. Some technology companies are making salary information more transparent. Some, like eBay, don’t want to. The eBay Board has stated its belief that implementation of this proposal is not in the best interests of eBay and its stockholders (see reference #5). You have to ask, “Why?” unless there is something to hide.
My bet is that many companies don’t actually have any way to defend their salaries except to have a salary range. Maybe some people think that the gap is small enough that it doesn’t matter and that women don’t want to be in leadership positions, so the discrepancies perpetuate. This is a topic that I will continue to investigate.
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