Specifically, my work focuses on the unexplained gender pay gap, which is the difference between what a female worker can expect to make compared to a male in the same position after accounting for job roles, performance, education, and any other factors that may influence wages. The reason why this is referred to as the unexplained wage gap is because the difference in pay cannot be explained by anything except gender. The causes of the unexplained wage gap are up for debate, but unconscious biases are a part of it.
As part of my series about “the five things we need to do to close the gender wage gap” I had the pleasure of interviewing Dr. Margrét Vilborg Bjarnadóttir, an Assistant Professor of Management Science and Statistics at the University of Maryland Robert H. Smith School of Business. Dr. Bjarnadóttir graduated from MIT’s Operations Research Center in 2008, defending her thesis titled “Data Driven Approach to Health Care, Application Using Claims Data.” Since then, her work has focused on challenging, complex problems of significant social impact, mainly focused on two application areas, health care and pay equity.
Thank you so much for joining us! Can you tell us the “backstory” that brought you to this career path?
As an undergrad I did not really know what I wanted to do — I originally signed up for computer science, I checked out some math classes, and I finally selected engineering so I could “keep my options open.” After working my way through 50 pages on the chemistry of cement, a requirement of the civil engineering track, I switched to industrial engineering — and that’s where I found operation research. I remember thinking the mathematics behind optimization were just the coolest thing ever. I eventually went on to get my doctorate in operation research and have been fortunate enough to spend my career in academia.
Can you share the most interesting story that happened to you since you began this career?
I got to visit Lebanon as a faculty advisor, which was very memorable — it was such a range of experiences, from meeting the prime minister and the head of the central bank to seeing the marks of war on the buildings and how current events shape the society.
Can you share a story about the funniest or most interesting mistake you made when you were first starting? Can you tell us what lesson you learned from that?
When I was starting out as faculty, I obviously did not have the same great consulting stories as the more seasoned faculty. So instead I broke up my lectures with useless trivia from Iceland — and it was a hit. The biggest lesson I think one can take away from that is that you should not try to be something you are not.
Ok let’s jump to the main focus of our interview. Even in 2019, women still earn about 80 cents for every dollar a man makes. Can you explain three of the main factors that are causing the wage gap?
The reasons behind the 80 cents on the dollar figure are complex, and many are societal in nature — including how we as a society value different job roles. What my research focuses on is the notion of equal compensation for equal work. Specifically, my work focuses on the unexplained gender pay gap, which is the difference between what a female worker can expect to make compared to a male in the same position after accounting for job roles, performance, education, and any other factors that may influence wages. The reason why this is referred to as the unexplained wage gap is because the difference in pay cannot be explained by anything except gender. The causes of the unexplained wage gap are up for debate, but unconscious biases are a part of it.
Can you share with our readers what your work is doing to help close the gender wage gap?
Absolutely! I was drawn to work in this area when I was approached by an HR manager tasked with addressing their company’s gender pay gap. They could find no quantitative tools available to them, and because the previous literature provided no clarity on how best to close a gender pay gap — or any demographic gap for that matter — they did not know how to proceed after measuring their gap.
My work addresses this need. We have developed fairness-driven algorithms that determine how best to close the gap, focusing on fairness, costs and implementability. This was especially interesting as a research project, as each employee’s impact on the gender pay gap is complex. For example, one somewhat counterintuitive finding is that it is common to find men within an organization whose characteristics (in terms of their data) are such that giving them a raise may reduce the measured pay gap! We are now also broadening our research to address additional challenges, e.g., how to simultaneously consider and address multiple demographic pay gaps. These algorithmic approaches have then been translated into decision support tools that help those tasked with addressing demographic pay gaps to close them.
Can you recommend 5 things that need to be done on a broader societal level to close the gender wage gap. Please share a story or example for each.
I think one of the hindrances to moving towards equal pay for equal work is companies’ fear that public knowledge of the gap could be used against them in a lawsuit. It will therefore be very interesting to follow the developments in Massachusetts, as the state legislature recently passed a law protecting firms that measure a pay gap from such legal action as long as they are taking concrete steps to address the gap. The hope is that this will enable companies and organizations to start addressing the issue in-house and move the needle in the right direction.
Another interesting development to follow is the impact of a two-year-old law in Britain. This law requires all companies above a certain size to publicly publish their median pay broken down by gender (along with, for example, the percentage of employees who receive bonuses). Since the country just completed its second year of reporting, we have not seen a big measurable impact, but a recent study focusing on similar legislation in Denmark showed that the legislation has helped, and the salary increases for women in Denmark have been outpacing the salary increases for men. Perhaps this “name them and shame them” approach is something we should consider in the US!
However, while rules and regulations may be helpful to accelerate change, organizations need to take action. Here are a few thoughts about what may help an organization to take steps in the right direction. First, measure the gap using real-time data. Organizations evolve, new personnel are hired, and others leave or get promoted. Know your current gap — not the gap you had a year ago. Second, a pay gap does not resolve itself, even with good intentions. Develop a plan and budget for it. During the annual review cycle, set aside a proportion of the budget to invest in correcting the gap. Third, if you are using performance data to justify raises, make sure that your data is not biased. And lastly, broaden out the definition of equity — it is not only about equal pay, but equal opportunity. Identify barriers and remove them.
Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?
I am not a big quote person — I am, however, a big believer in using data to improve decision making. A story that I often share with my MBA students is when we needed to upgrade our MacBook. Instead of just taking our chances on eBay, we collected data on MacBook auctions (duration of the auction, starting price, ending time, the MacBook features, quality of the pictures, etc.). We then ran some models to understand what kind of auctions are the most successful and applied those observations to sell our MacBook, and we also did the reverse (modeling which auctions are likely to have the lowest bids) to buy a new one. And as a result, we upgraded for free (well, ignoring the time it took to collect data and model it!).
We are very blessed that some of the biggest names in Business, VC funding, Sports, and Entertainment read this column. Is there a person in the world, or in the US whom you would love to have a private breakfast or lunch with, and why? He or she might see this, especially if we tag them. 🙂
We are at a unique point in history when it is (finally!) no longer socially or politically acceptable to discriminate in pay based on one’s gender, skin color, sexual orientation or other demographic characteristics. I am a big believer in data driven decision support, and I believe that with data and scientific approaches we can accelerate change. I would be happy to share a coffee with anyone thinking about how to close the gap within their organizations.
This was really meaningful! Thank you so much for your time.