Olivia Kew is Chief Data Officer at Vanderbilt University, bringing a distinctive, strategy-led perspective to data leadership in higher education. She began her career in international development, working with Ukraine and other countries alongside international agencies, before moving into higher education in the early 2000s. Her early university roles focused on international programs and strategic institutional initiatives, spanning both the United States and the United Kingdom, and gave her deep insight into the complexity of how universities operate.
Throughout her career, Olivia consistently used data to evaluate strategic impact and inform decision-making. In the early 2010s, she began formally leading a data team, coinciding with the growing recognition of data as a strategic asset. Her remit expanded to include data governance, quality, and privacy, alongside data-informed strategy, performance measurement, and effective communication through data.
Olivia’s background is unusual for a technology leader. While she has long held an interest in technology, her expertise developed later in her career, shaped by strategic and operational roles rather than traditional technical pathways. As a strategist first and technologist second, she excels at translating complex data concepts for non-technical audiences and bridging the gap between institutional priorities and technical capabilities. This skill was first honed through her intercultural work and remains central to her leadership approach today.
At Vanderbilt, Olivia focuses on positioning data as an enabler of institutional strategy, impact, and trust, helping the university use data thoughtfully, responsibly, and effectively in service of its academic mission.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“I have found the most critical skill for a data and AI leader is to be able to engage with leaders in the business and understand their challenges and needs. Active listening and curiosity, coupled with a firm understanding of the context and industry, gain you credibility and enable you to deliver value through data.
“Another critical skill is the ability to learn because the data and AI landscape is changing so rapidly. This includes the ability to experiment and try things and learn from how things turn out.
“And finally, you need to have the ability to think at both the micro and the macro, often at the same time. With data you need to have an eye for detail, because the devil in data is often in the details: what is the denominator here and do those numbers really add up? But you also need to understand the system in which the data operates, where it came from, and what strategic question it is being applied to.”
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“Your most powerful skill is your ability to ask questions. You should have begun to hone that in college, and you should never stop working on it. Your questions don’t have to be complicated. I have found that a simple, even naïve, question can sometimes uncover a profound insight or a major issue.
“My biggest blunders have occurred because I held back from asking questions, usually out of fear of looking stupid. Having said that, don’t ask questions if you aren’t really listening either to what was said before or to the answer. Questions should not be asked as a power play, but with a genuine sense of curiosity.”