Conference Blog

One of the best parts of any conference is the people you meet, and my experience attending this year’s INFORMS Conference on Business Analytics was no exception. I sought out connections in health care, where I have not worked before, and learned a great deal from the experience of others. But sometimes the connections that make the biggest impression are those that are surprises.

Most of us live in our own worlds, which we come to know well, and remain unaware of the many other worlds orbiting out there in the universe. This limited awareness is natural, because time is finite  and our brains can only process so much information. But as one of my new peers reminded me before I left for this trip, sometimes you learn more from those outside your world.

As a member of the planning committee for the Executive Forum, on Sunday night I facilitated an informal conversation for a small group. The table where I sat chose to talk about fostering an analytics culture. There were many interesting people seated with me, but the one who stuck out for me was Jackie Henningsen, who was recently retired from a civilian role in the Air Force, which is one of those worlds whose orbit I have never entered. She said she had served as Director for Studies and Analyses, Assessments and Lessons Learned. I later learned from other Air Force attendees at the conference that as a civilian this role is equivalent to a three-star general! She apparently was the first civilian and first woman in this role. The others I spoke with held her in awe and said the Air Force had even named an award after her.

Not knowing these details, I was just impressed with her comments. She talked about leading a group of analysts and believing strongly that aligning everyone along one vision was critical to fostering an analytics culture. Someone else at the table asked about how to foster a culture of analytics where it doesn’t exist, and Jackie spoke of how she explained to the senior leaders she worked with that analytics could provide fireproofing to help their decisions, but that the reverse was also true – if there weren’t open to the analysis her team could provide she could NOT fireproof their decision. She still offers analytic fireproofing as a consultant, and that term is on her business card!

What made such an impression on me was that she has a rare combination of humility and confidence while being very approachable and delightful person with whom to speak. One person told me that when she first took on her role as Director she felt her group needed more visibility and managed to get them moved to report directly to the Chief of Staff of the Air Force, which was quite a feat. I learned that she taught high school math for many years before returning to graduate school for a second MS and then a Ph.D. in industrial and management systems engineering. We spoke again few times during the conference, and I asked her if she’d encountered bumps along the way as a woman and as a civilian. She said she had, but that she had always preferred to focus on the results and not call attention to herself for being a woman. Her idea of progress would be when gender is not noteworthy on its own.

Meta Brown recently wrote an article for Forbes on women in analytics, and her call to action at the end was to “post about an analytics professional who deserves more recognition.” The photo above is of a group from the Air Force accepting the INFORMS Prize “for their pioneering and enduring integration of operations research (O.R.) and analytics programs into their organizations.” Jackie is the one holding the red plaque. And while I’ve clearly discovered that she is very well known in Air Force and military OR circles, I expect many outside those orbits aren’t familiar with her accomplishments. I am glad to see her years of leadership in the Air Force recognized with this award, and I’m adding to that recognition with this post.

Did you know that today (April 4, 2017) is Equal Pay Day?  I didn’t either until I woke up to this stream of tweets:

It’s simple. Women deserve to be paid equally for equal work. #EqualPayDay

— Sen. Al Franken (@SenFranken) April 4, 2017

I have various degrees unrelated to my profession. I know women with CS degrees who were still paid less than me. 🙁 https://t.co/5KqmWy1tPe

— Eric Mann (@EricMann) April 4, 2017

"If you want equal pay, major in engineering and not women's studies!"

The only women's studies major I know is a senior software engineer.

— tuxedo masq (@alicegoldfuss) April 4, 2017

Every #EqualPayDay, we see the same tired arguments against it. Let's put them to bed. https://t.co/lxw65Xloo9

— NWLC (@nwlc) April 4, 2017

Men: you know how you can support women on #equalpayday? Tell your female colleagues doing the same work as you are what your pay is.

— objkshn (@objkshn) April 4, 2017

There’s been a lot of talk in the news and politics about equal pay laws: the idea being that women should get paid an equal amount as their male colleagues for the same work. There have been a host of studies (here’s one by Pew Research Center) that show a stubborn persistence in the gender pay gap over the last fifty years. For example, last year, a black women would only make $0.65 for every dollar that a white man would make performing that same task! The response to this in a number of states has been legislation mandating equal pay for equal work.

What does all this have to do with the INFORMS Analytics Conference, you ask? Well, it just so happens that yesterday Margrét Bjarnadóttir from the University of Maryland, College Park and PayAnalytics gave a talk entitled Closing the Gender Pay Gap With Analytics. In this talk, she described an analytical model designed to help companies close the gender pay gap between their male and female employees, while attempting to minimize costs to the company and maintain some sense of fairness.

It seems like the solution to this problem is pretty simple: give raises to women until your pay gap is gone! However, what Dr. Bjarnadóttir highlighted in her talk (and accompanying paper, found here is that there is a complicated feedback loop that gets formed when trying to associate pay and work output. In particular, paying a particular individual X more will have a simultaneous effect on the pay gap as well as on the traits that are used to determine what “equal work” means. This means, to quote her paper, that “men who strongly typify male employees in terms of [traits related to high pay] also tend to have large differential influence because paying them more increases the explanatory power of these traits.” Thus, in such models, paying men more is the cheapest way to close the gender pay gap.

This was a pretty eye-opening revelation to me. It turns out that there are all kinds of unintended consequences in so-called optimal methods of closing the pay gap. Here’s another: “A firm can reduce the explanatory power of gender and thus the gender pay gap by cunningly finding other ways to explain women’s low relative pay. One particularly relevant strategy is to create a job classification scheme to ‘ghettoize’ women apart from men in the firm’s organizational structure; the resulting job classification scheme – as encoded in a set of dummy variables in the log-wage regression – would absorb much of the explanatory power of gender, reducing the gender pay gap without raising the compensation of women at the firm.”

Dr. Bjarnadóttir continues in her paper to do a robust statistical analysis of these trends, perform simulations, and then offer advice for companies seeking to close their pay gap that is more in line with the spirit of “equal pay for equal work”. So, on this #EqualPayDay, it’s worth taking some time to think about not just the end goal, but the methods that we take to get there–and how analytics can be used both for good and for ill in the process.

I’ve met with a few students in the last couple of days, and I always appreciate this chance to see where the world is heading. I’m impressed with the drive, passion, and courage of these young people. To cite drive and passion may be obvious, but any student who is in a graduate program focused on analytics or OR shows a high degree of motivation, and those who found their way to this conference have to step it up a notch to find funding and navigate a professional world. And I add courage because all three of the students I’ve met came to the US to study from other countries. Graduate school takes a significant dose of confidence to succeed, but I didn’t do mine in a foreign country, where I had to learn different customs and traditions, and all the while do so in a foreign tongue. I cannot imagine INFORMS or the larger world of advanced analytics, machine learning, and operations research without the contributions of so many who were born outside the US. Chinese, various Indian languages, Turkish, and Farsi overheard in the hallways are evidence of this rich diversity. Students are already seeing evidence of concern about the future of the H1-B program by fewer opportunities available to them if they need sponsorship, especially at the MS level. I hope that wisdom prevails and the US continues to open its arms (and university and professional doors) to any student with the drive, passion, and courage to succeed here, regardless of the country of their birth.