Women’s Day Special: “More Programs for Women to Learn Technical and Soft Skills to Move to Executive Positions" Peggy Tsai, CDO, BigID

Women’s Day Special: “More Programs for Women to Learn Technical and Soft Skills to Move to Executive Positions" Peggy Tsai, CDO, BigID

CDO Magazine celebrates women in data science, machine learning and analytics with our special International Women’s Day Series. Featuring known women data leaders in the industry.

Q. Tell us about your personal journey in the world of data. 

My journey into the world of data was quite random. I did not intentionally seek it out mainly because I was not aware of opportunities in data. When I graduated college in 2001 with a degree in economics, the popular career options were computer programming or management consulting. I was not quite a good fit for either one, but I knew that I enjoyed collaborating across teams, working with technology, and analyzing data in spreadsheets.

One of my early jobs in my career happened to be a data operations role in a center of excellence department in a large financial services company. I was lucky to start out my career in a data-centric organization that supported capabilities in data stewardship, data quality, operations, and strategy. I am one of the few data practitioners that literally started out learning my skills in the field at several large financial services companies in NYC. I was able to work in large enterprise organizations where I was hands-on involved with building out data governance programs in different areas like business glossary, quality, and stewardship. 

I was also in an opportune time to work in data governance while regulations compliance in financial services helped to grow this function. I also expanded my experience at the precursor to GDPR and global data protection laws in 2016. This expanded the importance of data functions in all industries as they worked to remain in compliance. I also actively sought to speak publicly on the fundamentals of data governance in analytics and AI as part of my data career. 

Q. What advice would you give to women having to handle being the only woman in the room?

This is a great question because for most of my career, the data teams that I worked in reported to technology, which is a male-dominated field. Coupled with the fact that I was young and naturally introverted, I was often forgotten or ignored. However, my advice for women would be to use the fact that you're the only woman in the room to your advantage. Behave as if you belong and are an equal in the room because you certainly are! Take a seat at the table, speak up and share your thoughts during the meeting. I would not be afraid to challenge others and stand up for yourself — this is advice that I would give to any woman regardless of the ratio inside the room.

I think that one of women's secret superpowers is the ability to read the room and adjust accordingly. I would certainly leverage your time effectively outside of the meeting room to build relationships to help smooth any potential awkwardness in meetings.

Q. Why do you think more women should consider a career in data, analytics, and AI?

More women should pursue a career in data, analytics, and AI not only because this is a growth area for innovation and change, but this is a career where women can naturally excel in terms of communication, collaboration, and teamwork. There are also various roles that require leadership and change management skills that women can identify with. For example, 70% of being an effective data leader is communication and juggling multiple priorities at once. There used to be more of a misconception that this field is technical, which limited women in some respects. But it also involves problem-solving, and logical and creative thinking.

Also, it is more important than ever that women participate and take a strong stance in the field of AI. Without proper representation and an increased diversity in this field, women will be at a disadvantage when data models and algorithms are created. Women bring new perspectives to solving problems, and in order for ethical results in automation machine learning, women need to have a strong presence in this field. 

Q. What are some of the biggest strengths that women bring to this field?

Women are collaborative and empathetic while also strong communicators across the team. They are also gifted storytellers. These are important skills because data is about interpreting results and explaining the value to other stakeholders. 

Q. While the number of women in data is increasing along with the number of women in CDO roles, what else needs to happen to get more women to the C-suite? Is it more mentoring? More support? Skillset? 

From what I have seen, there are fewer women in the talent pipeline because they lack mentoring, sponsorship, and support to stay and grow in the field. They tend to drop out and change careers because it is so difficult for them to continue to maintain a work-life balance while competing for a promotion.

It becomes challenging for women when they do not have access to the same leadership development training as their peers. There needs to be more programs for women to learn the technical and soft skills to achieve executive levels. Most company-sponsored leadership programs are competitive, but there should be external groups that women can tap into for knowledge sharing. I am hopeful that the number of women at the CDO and C-suite level will improve in the next few years if we work to actively close the gap by promoting and supporting women. 

Q. The theme for this year’s International Women’s Day is #breakthebias. What’s your perspective on that?

This is a great theme for this year's International Women's Day. I love this theme because it puts an emphasis on the bias against women that still exists. There is still an inherent problem for women when it comes to hiring, retention and promotion, and this same bias is pervasive in the world of data, machine learning, and AI. Unless there is clear recognition of a need for gender equality in the data field and in the workplace, then no significant change can be made. That's why it is critical that the message of #breakthebias continues every day of the year, not just on March 8.

Q. Who have been your most influential mentors and guides throughout your career? What lessons did they teach you to help shape your leadership style today?

My most influential mentors were never formally my mentors. I reached out to peers to gain guidance and perspective that shaped my career. I learned from the leadership styles of every manager in my career, and I observed the skills of the data executives on my team. 

One lesson that changed how I treat others happened early on in my career. I was included in an email chain with the chief data officer and my manager. There was a discussion going back and forth on a subject that was in my area of expertise. It was a late-evening exchange, and I was typing into my Blackberry a quick, short response to the situation. I thought I was being efficient and clear. However, a few days later, my manager told me that the chief data officer was taken aback by my response and interpreted it as being rude. I was surprised by this feedback and vowed to do better in the future. This shaped my leadership style whereby I'm more aware of the words I use with my team and peers in all forms of communication.

Another lesson I learned from a peer involved observing how others treat each other. About 15 years ago, I had knee surgery that forced me to stay at home for several weeks and go through several months of physical therapy. I had a difficult time adjusting to the commute and balancing my work commitment. I received advice to take notice of the people that supported me during my transition as well as people that did not. I immensely appreciated the support. From this experience, I learned to demonstrate additional support to all my peers and increase my level of empathy. 

Lastly, there was another lesson I learned from all informal mentors that I met during my career. I appreciated the time they spent with me, whether talking on the phone or meeting me for dinner to give me career advice. I initially met Pamela Cytron as an entrepreneur while working at AIG, and she introduced me to Dessa Glasser, who I currently work with on the EDM Council Women Data Professionals Forum. Both opened their network to me and gave me invaluable advice over the years. I was also impacted by the small gesture of time extended to me by Heather Wilson my former chief data officer at AIG.

I am continually surprised when people from my prior jobs extend their time to me and show me support. I have also tried to do the same to support and mentor within my network.

Q. Finally, what advice do you have for female data professionals this International Women’s Day 2022?

I encourage all female data professionals to keep learning new skills, grow/develop an entrepreneurial and innovative mindset, and spend time in networking groups. Spend the time outside of your day job to learn new concepts. Volunteer your time in a different area. Spend time talking with peers outside your team and department to expand your knowledge. Find opportunities to establish your expertise through blogging, writing papers, speaking at industry conferences.

It takes intention to grow and expand one’s knowledge, and I challenge everyone to develop a plan for themselves to do so.

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