4. Diana Schildhouse, Chief Analytics and Insights Officer, Colgate Palmolive
Describe your career to date
I have led analytics and insights organizations for over 20 years across several consumer-facing companies prior to joining Colgate-Palmolive. I have worn multiple hats across those companies, including strategy, mergers and acquisitions, and corporate finance, working in close partnership with marketing and commercial organizations across the world; as a result, I come from a business-first lens (versus tech first) when leading data and analytics transformations.
I am currently Chief Analytics and Insights Officer at Colgate-Palmolive, where I lead Colgate’s data and analytics transformation, bringing together advanced data and analytics capabilities with deep people insights to drive growth and innovation in how Colgate designs, markets, and sells products and how we engage with consumers.
Prior to Colgate, I was Senior Vice President of Global Strategy, Insights, and Analytics at
Mattel, leading an organization focused on integrating the voice of the consumer
with actionable advanced analytics. I built Mattel’s first team of data scientists, advanced
Mattel’s data strategy, and pioneered large scale advanced analytics capabilities focused on marketing, media, new product development, customer and retail. With my team, I also led the development of enterprise-wide strategic planning for Mattel, with a focus on driving transformation, innovation and growth, across all brands, categories, and geographies.
Previously, I was Senior Director of Strategy and Market Research for Westfield, a global
shopping center developer, where my team analyzed opportunities for acquisition, investment and merchandising. I began my career at The Walt Disney Company in corporate finance.
Data literacy is a key enabler of the value and impact from data. How are you approaching this within your organization?
I have created a bespoke Data Literacy and Analytics Academy to upskill all 16,000 salaried employees at Colgate, from the CEO to entry level folks around the world. This has been externally recognized by the Brandon Hall Group with a Gold Award and received the highest engagement scores and completion scores of any learning program at Colgate.
Participants first took a confidential assessment written by my team, then received tailored recommendations for data, analytics, and artificial intelligence (AI) courses based on their skill level and function within the organization. They also earned Credly badges for different levels of completion, which were shared publicly on LinkedIn by the CEO and senior leadership team, resulting in a movement and significant progress in the company towards getting on a common language and understanding of how data and analytics is a part of everyone’s job, not just the data team.
What role do you play in building and delivering conventional AI solutions, including machine learning models? Are you involved in your organization’s adoptions of generative AI?
My team conceptualizes, builds, deploys, and embeds traditional AI solutions and applications, including machine learning models and predictive and prescriptive analytics, across a variety of use cases across Colgate-Palmolive globally, notably revenue growth management analytics, marketing and media effectiveness analytics, and innovation analytics.
I sit on the executive Steering Committee for generative AI (genAI), and my team has led education and upskilling across the organization, as well as the assessment and prioritization of priority genAI use cases, some of which my team and I are leading and are in pilot stage.
How are you preparing your organization for AI adoption and change management?
To enable transformational change and truly capture value from data, analytics, and AI, it must be embedded into the rhythm of how the business operates on a day-to-day basis. It must start with business questions to ensure that data and analytics are linked to measurable business outcomes and are not just tech for tech’s sake.
We tackle change management by including the business in all aspects: from clearly formulating the initial question or strategy; UX and UI research on how they make decisions and use tools to ensure an easy to use, intuitive interface in anything we build; leading deployment squads who work closely with teams on the ground to train and onboard and showcase the power of analytics, and work with them on key insights and takeaways; and finally embedding the discipline of following through on which actions were taken (or not) as a result, and what the business value of those actions was.
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