Diana Schildhouse secures her place in the 2025 DataIQ 100 North America as a defining voice in the analytics and AI leadership space, both within her organization and across the wider data community. A top ten mainstay for the past three years and ranked number one in 2023, she brings a rare blend of business acumen and technical fluency that cuts through the noise. At Colgate-Palmolive, Diana has embedded data and AI not as a parallel initiative but as a core business function, directly shaping how products are developed, marketed, and experienced by consumers around the world. A regular panelist at DataIQ events, her consistent contributions reflect not just expertise but generosity, offering first-hand insights into what AI-driven transformation really takes.
I lead Colgate-Palmolive’s global analytics and insights function, where our goal is simple but ambitious: to embed data, analytics, and AI into the way the business thinks, operates, and grows. That means moving beyond isolated use cases to building a culture and capability that drives innovation in how we design, market, and sell products—and in how we connect with consumers around the world.
My approach is shaped by a 25-year career spanning strategy, finance, and consumer insights, always grounded in close partnership with marketing and commercial teams. From leading analytics at Mattel, where I built the company’s first data science team and enterprise-wide planning capability, to shaping strategy at Westfield and Disney, I have seen first-hand how transformation sticks when it is tied to business priorities. That experience reinforces my belief in a business-first approach to data: one that aligns technical capability with outcomes that matter – growth, efficiency, and customer impact.
The key is integration. Data must be part of the day-to-day rhythm of the business, not an add-on, but a catalyst. That starts with asking the right questions, co-creating solutions with the teams who will use them, and delivering tools that are intuitive, relevant, and actionable. Success isn’t about what we build but the business impact it delivers and the sponsorship it earns.
We make that impact visible by tracking outcomes the organization cares about – revenue, profit, ROI – and by celebrating wins that build momentum and trust. It is this cycle of clarity, delivery, and engagement that accelerates adoption and brings data to life at all levels of the business.
Looking ahead, I believe the most effective data leaders will be those who can make complexity clear. As AI scales and expectations grow, our role is to demystify, translate, and champion value in ways that resonate across functions, not just within the data team.