Salesforce, SVP of Global Data Governance and CDO of Trust: Today's Female Leadership Must Lift the Next Generation, Not Wait for It to Happen Magically

Salesforce, SVP of Global Data Governance and CDO of Trust: Today's Female Leadership Must Lift the Next Generation, Not Wait for It to Happen Magically

(US and Canada) Wendy Batchelder, SVP of global data governance and CDO of Trust, Salesforce talks with Peggy Tsai, CDO, Big ID, about the need to get more women to the C-suite.

Batchelder shares that mentoring, support, sponsorship, and skillset are required to pull more women to the C-Suite. She thinks it's interesting that there are more women in data now than before. However, she shares that she is unsure if that's a sheer count or maybe we are shining a light on it.

If one looks at some of the statistics from the world economic forum, it's 237 years before we will see true gender equality in the workplace, and it's unacceptable to her. So she thinks women need to do a lot more. She further shares some of the narratives that she often hears daily at the time of promotion, not necessarily in one particular company or another, but by talking to folks across industries and companies. She shares that the remarks are like, "Well, we didn't have any women in our promotion cycle because none were ready, and we hope they'll be ready next year."

Batchelder shares that these statements and remarks make her cringe. If we don't have enough qualified women for a promotion, she thinks that's our fault. What are we doing to qualify them to be promotable and not just waiting for women to be ready suddenly? It's the job of a manager to develop the people. As a manager, why are they not taking accountability? Accountability that they were unable to do it this year or the year before? And so now you have this pipeline of talent that is mainly underrepresented women. She shares that she has seen in data teams across industries that the lower levels have perfect gender equality. Maybe the same has to reflect in the leadership team. Look at your middle management data; everyone she shares she has talked to agrees that it's not great. As an organization or a manager, she thinks women are not promoted fast early enough in their careers.

We keep looking at the criteria, and she thinks the criteria sometimes may be biased. She shares that there is a need to be mentoring up and down and reverse mentoring. 

She believes that it's essential to have a mentor that is far more junior than you so that one can listen to the perception and feelings on the ground floor? She advocates," If you don't have a reverse mentor, get one." Make sure that you are sponsoring other women because it's our job to make sure that they're ready when it comes time for promotion. If there are skillset gaps, then help them to connect those. If there are common skills or core skills or soft skills, communications, strategic thinking, leadership, give them that, give those opportunities and be intentional about it, but don't just do it theoretically; build an actual plan.

She believes that all women leaders' jobs are to make sure that we lift the next generation of female talent and not just wait for that to happen magically. Organically, because that's not working, or it wouldn't be another 237 years before we see gender equality. So we have to do more. 

She shares her ideology behind how better data governance can help reduce the bias for training data used in algorithms today. She hopes to acknowledge that bias and data exist now; if you're using historical data and historically there's been bias, your data is biased. She thinks we all have probably heard about hiring algorithms to predict the right candidate and consistently predict the white man because historically, those were the ones hired in that role. She thinks it's essential to look at the underlying data set and ensure that we are not teaching bad behaviors; just because we're automating something doesn't mean it will always be correct. Because it's primarily for unmonitored AI algorithms where we're setting it and forgetting it, maybe coming back to check on it in a year. What's the risk there and assessing that. So looking at the data, making sure that it is a complete representation, she thinks doing something like robust AV testing, ensuring that you're getting the results you expect to get, and just making sure that you're not letting it run rogue is equally essential. She believes that just having a data governance professional look at the quality of the data set isn't a fair representation of the population. Is there anything that we need to change to ensure that that data set is pro for use is essential?

Wendy shares further about the three people who helped her shape her career and what she is today. Laura Pat is one of the primary mentors and the main reason she is in data today. Pat was a stakeholder in her early career who asked her to take on a data role, and at that time, she felt she was unqualified for it. However, Pat helped Wendy understand that some of her skills were not necessarily like understanding the nuances of metadata or understanding data governance. These were not necessarily reasons she thought of her for a data leadership role. It was more around understanding her aptitude to learn and explore things and look at things objectively and be able to take complex situations and translate them into more simplistic terms that were understanding for others.

All this gave her a lot of confidence in herself. Because she thinks until that point, she always felt like she needed to be the expert, understand things from top to bottom in detail, and be very technical. Pat gave her the empowerment to know that sometimes you can ask excellent questions. And that's good leadership. You don't need to have all the technical knowledge across. 

As one moves up in the career, they will not know everything technically. But it was a pivot point for her, and it built a lot of self-confidence for Wendy. Along the way, Stephan Harris and Charles Thomas are two others mentors and actual sponsors. They breathed a lot of confidence into her and helped her understand her strengths when she was mainly the youngest person in the room and aware that she was often the only female in the room. They helped her feel like she belonged, and she could influence differently and uniquely. They helped her understand her leadership style was unique in those circumstances, and that's why she was there. She often faced situations with a degree of curiosity and just sought to understand and maintain a humble posture.

Her mentors, as per her, made sure she was always learning and never going to be the expert in everything, be curious, and be willing to ask straightforward questions, which sometimes people are afraid to ask, especially in leadership roles. So that's something crucial that her mentors taught her, and that is something that she can carry forward to and practice every day.

She shares that to break the bias beyond the campaign, one needs to do much more beyond telling our stories. Our stories are compelling. Please don't get me wrong, but we also need to push harder than we are for equality in this space.

She shares if you're a female in the data profession, you're in the minority. We all are. We know that. It is vital to think about some questions like: How do you bring others with you? Who are we bringing into rooms with us? Who's not represented? What opinions or opportunities are we missing out on? 

If they are not in the room with us. So get them. Like if you're in a meeting and you're the only female or in the minority, which is most meetings. Is there someone else you could bring along, and maybe their expertise is not perfectly applicable to the topic. So bring them as an observer, bring them into the conversation, and encourage them to speak up and question themselves.

Are you speaking up? Are you setting the example? Are you offering a suggestion? Are you asking a question but bringing others with us? So that is the best way to grow the pie to bring others along with us. And help them. So if you're not mentoring, you need to be; if you're not mentored, you need to be, if you're not helping others to learn, you need to be, and it's extra for us.

She thinks that the only way it's going to get better is by taking that on, and hence she encourages every woman to make sure that you are paving a path with those behind you. And that we're always keeping in mind that a rising tide lifts all the ships. There's not a scarcity here. There is a dramatic under-availability of data professionals.

So bringing one or 100 female leaders with you is just going to help our pie be more diverse and help break the bias that we experience in the data.  

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