Five Ways Data Analytics Can Help Close The Gender Gap

Beatriz Sanz Saiz

The more we learn and use data analytics ethically and responsibly, the greater our chances of living in a more equitable world.

In both my professional and personal life, people who know me know that I’m passionate about data analytics – for lots of reasons. From talent management, where businesses can use data from recruitment interviews to gain a strategic advantage in the competition for talent, to finance, where analytics can help intercept fraud, the benefits of data analytics are all around us. And, now, it can also play a powerful role in closing the gender gap.

According to the World Economic Forum’s latest Global Gender Gap Report, at the current rate, it’s going to take almost 217 years for the world to achieve gender parity. Could data analytics help to accelerate that process? The answer is a definite yes. I truly believe organizations can Press for Progress by collecting data and leveraging it to close the gender gap in these ways:

  • Monitoring. As the saying goes, “What gets measured gets done.” It’s imperative to start measuring factors that can help improve gender parity. To date, a lack of meaningful data interpretation has hindered attempts to close the gender gap. As more organizations introduce diversity metrics relating to recruitment, training, progression and pay, they will have more data to analyze – data that will yield valuable insights into patterns, trends and discrepancies between how female staff is treated compared with male counterparts.
  • Recruiting. Data analytics is key to recruiting a diverse workforce. Not only does it allow HR teams to check that hiring managers are attracting candidates from a broad talent pool, it can also help organizations to assess whether those candidates’ values match their own. Algorithms can use data taken from surveys of the candidate and the employer to assess the strength of the potential interpersonal relationship between the two. This is a great way to circumvent unconscious bias.
  • Predicting. Diversity initiatives often focus on recruiting diverse talent, but it is just as vital to retain that talent. Predictive analytics can help organizations to forecast whether certain groups of people are more likely to resign than others, giving HR teams the opportunity to develop initiatives that improve the workplace experience of those groups.
  • Eliminating bias. Today’s analytics programs can crunch reams of data relating to employee salaries, bonuses, positions and turnover rates, going back years. They allow HR teams to identify patterns of bias that existed in the past and to devise fair and robust compensation structures that are fit for the future.
  • Educating. This is probably is the most important opportunity for data analytics to drive positive change. Closing the gender gap fundamentally relies on women being educated in science, technology, engineering and mathematics (STEM). I know from personal experience that women who are skilled in data analytics will discover that they have multiple career choices. They can also become advocates and role models who can drive change. In fact, at EY, we want to enable all our talent with opportunities for education, and that’s one of the reasons why we launched EY’s Analytics & AI Academy, under our EY Badges program. This fresh, comprehensive learning initiative aims to inspire our people with the confidence and expertise to speak confidently about analytics and artificial intelligence with their clients, so they can help drive better outcomes and new business opportunities. Through the learning platform, our people have the opportunity to access almost 500 internal and external data and analytics courses – and gain the essential knowledge that they will need to develop high-value expertise in data analytics.

I feel confident that the more there are people who understand analytics, and who understand how to use it ethically and responsibly, the greater our chances of living in an equal world. We can get there sooner than we think. And, of course, we will have the data to prove it.

#PressforProgress

This article originally appeared on EY’s “Building a Better Working World.”


Beatriz Sanz Saiz

About Beatriz Sanz Saiz

Beatriz Sanz Saiz is leading the Global Advisory Analytics practice and is responsible for driving EY’s “Analytics Infusion” strategy, which focuses on the integration of our global analytics strategy across all domains, sectors and Regions to accelerate our growth. Beatriz has been a Partner in the firm for 10 years in various roles within EMEIA and Asia Pac. During her career, she has also held senior positions with leading companies where she was responsible for establishing analytics and innovation as core competencies. Beatriz combines her business acumen services with her quants and innovative skills to define and support the growth agenda of large multinationals.