Tackling pay equity challenges, with Margrét Bjarnadóttir and PayAnalytics

We caught up  with Margrét Bjarnadóttir, cofounder of PayAnalytics to learn more about their data driven strategy to help improve pay equity.

What are you working on now and how could it be useful in general, and in Ireland, in particular?

We have been working on pay equity for almost a decade now, meaning successfully supporting companies in measuring their pay gaps, closing them, and integrating pay equity into decision processes. Now, we’re broadening the PayAnalytics platform to include broader workplace equity, using data informed approaches to support inclusive practices, and shedding light on attrition, promotions and hiring. By broadening the scope of the platform we are supporting companies in attracting and retaining talent, and companies around the globe have realized the benefits of pay equity.

Margrét Bjarnadóttir, PayAnalytics

For Irish companies in particular ,we support them in fulfilling their Irish reporting requirements with a couple of mouse clicks, and we’re preparing them for the E.U. Pay Transparency Directive. Companies can now easily run a readiness check to understand where they stand and what they need to do to become ready.

What are the benefits of pay transparency and pay equity. Where will they lead us?

When we think about the benefits of pay transparency, we need to think about what we mean by pay transparency.

The different pay transparency rules and regulations around the world can take many forms. Ireland will be affected by two key pay transparency tools.. First, the Irish reporting requirement mandates that companies publicly disclose their pay gaps in relation to gender, and that they create an action plan to reduce gender-based differences in compensation . For most employers, this will undoubtedly  put pressure on tem to improve year over year, and may therefore lead to a slow but steady  progression towards closing the absolute pay gap.

Second, the forthcoming EU Pay Transparency Directive will require organizations to  disclose salary ranges in job postings. To prepare, employers will have to be ready to post salary ranges, which includes preparing to explain salaries to current employees. They will have to answer the question: “Why is my salary what it is?” Pay equity advocates therefore have high hopes that this requirement will move the needle on fair pay. In fact, academic research has shown that salary disclosures reduce inequity.

Where do tech companies stand compared to other sectors? Are they any better or worse than the mean?

I think we cannot put all tech companies under the same hat. In fact, one of our first tech clients insisted that they did not have a pay equity issue prior to adopting our solution. That is rarely the case, so I was skeptical. But the CHRO was right, they did not have a pay gap, and it stemmed from their strategy of taking proactive action to retain and attract talent. And I would to this that most tech companies have realized that they need to be able to communicate to their employees that they take pay equity seriously, and that they monitor pay and take proactive actions. In this sense, many of our tech clients are leading the way in pay equity.

Of course, there are other companies that have not started their pay equity journey, that do not have inclusive culture, and lack representation of women in their workforce. So to sum up, technology companies are leading the way, while others have some catching up to do.

How will Large Language Models (LLMs) change the HR technology landscape – or will they?

HR tech is in many ways unique when it comes to the adoption of analytics. While we have been applying analytics across the organization (think supply chain, finance, accounting) for a long time, HR was left behind, but for a good reason. The decisions that we make in HR can be life altering for our employees. Who gets hired, who gets promoted, who receives a salary increase. Therefore, it is incredibly important that the algorithms that we apply are unbiased and fair. And this is going to shape the way we take advantage of recent breakthroughs in  LLMs in the HR space, but I am super excited about the possibilities.

Just one example: One of the largest hurdles for pay equity analysis is to group similarly situated employees together. LLMs can help us do that faster and more efficiently. Instead of starting from scratch, we can start with a suggestion to iterate.

People analytics tools that are informed by historical bias: What can cases like Amazon’s teach us?

I think at the core, what the Amazon case taught us was that even the best talent in the world can make mistakes and create biased algorithms. It is therefore central that we ask critical questions of HRtech providers, and monitor the impact of AI and algorithms.

As you point out, applying any analytical tools in HR is especially challenging because (a)  the past does not reflect the future workplaces we are trying to build, so building prediction models on past data will only get us so far, and (b) our past data reflects past decisions which may be biased, and there’s no wand that we can wave to make this bias magically disappear. We therefore need to carefully create decision support tools that highlight bias, not magnify it.

But I also want to highlight two additional challenges that we need to tackle:

(1) Very often, our data is imbalanced (e.g., 80% men, 19% women, 1% non-binary), and we therefore need to play machine learning modeling tricks in order to ensure the models we build work as well as possible for as many employees as possible.  And (2) lt is difficult to quantify humans.

It’s therefore critical that we define what elements fall outside of our data (e.g., leadership abilities, likability), and decide beforehand how these factors are going to be incorporated into the decision making. The Amazon case serves as a cautionary tale, and at the same time should inspire us to improve.

What are your sources of information and inspiration?

I have been inspired by many people. I grew up with Vigdis Finnbogadottir as the president of Iceland, the first democratically elected woman to serve as President in world history. As a young girl, therefore I planned to become a president! Having Vigdis as a role model, I think, inspired generations of women in Iceland to think big. Second, I’m inspired by Professor Dimitris Bertsimas, my advisor at MIT. His use of data and analytics to solve problems of critical importance to society is second to none.

Would you say that your own path from mathematician to solving a real world problem is something that will inspire others to tackle other important issues too?

The first step in tackling social and environmental problems is to understand and accept that there is a problem. Using mathematical methods can help us get to that point. Then the next step is to use data to make informed decisions that tackle the problem. At PayAnalytics, we  have built a solution that uses data-driven methods to tackle the societal problem of inequity that has persisted for hundreds of years. I certainly hope that that can be an inspiration for others to tackle important issues.

How can people learn more about you & your work?

You can learn more about us by visiting our website. Feel free to reach out to me, too, at margret@payanalytics.com.

About Margrét Bjarnadóttir

Margrét Vilborg Bjarnadóttir, founder of PayAnalytics, is an Associate Professor of Management Science and Statistics at the University of Maryland’s Robert H. Smith School of Business. Her research focuses on using data-driven decisionmaking to address complex problems with a significant social impact. As an educator, Margrét is adept at communicating complex concepts—including those that underpin the PayAnalytics software—to non-technical audiences.

Margrét represented PayAnalytics at the annual Nordic Fintech Week, where we received the Nordic Fintech Impact Award.

Her work on pay equity has appeared in  the Harvard Business Review, Forbes, BBC, Authority Magazine, Inside Big Data, and HR Magazine. In 2020, she was awarded the GWIIN Overall Inventor Innovator Platinum Award for her innovative approach to addressing pay equity. In 2019, she was named University Woman of the Year in Iceland for the impact of her work. She is not waiting 200 years to close the pay gap.

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