The power of a healthy smile defines Colgate’s global mission. In this episode, you’ll hear about the central role that data, insights and analytics play in driving that mission forward. Diana Schildhouse joins the Leading Analytics Podcast for an episode filled with wisdom based on her experience leading analytics and insights efforts at Colgate. You’ll hear a clear and consistent description of how value is generated through the use of data and advanced analytics at Colgate, and some timely advice for what makes an analytics professional successful these days. And if you listen carefully, you’ll be the proud owner of a new book from the IIA library.

Describe your title and role. Where does your function report within the organization?

My title is Chief Analytics and Insights Officer. This is a newly created role that brings together both the insights and analytics teams at Colgate. I report to the group president of growth and strategy. In addition to analytics and insights, she oversees global marketing, strategy, M&A, supply chain, IT, digital technology, R&D, and innovation. Organizationally, my team and I are very close to the business, which is one of the reasons why we've had early success.

What are the most important application areas at Colgate? Which business partners do you work with most?

Great things are happening in areas like supply chain analytics and people analytics, but my team is focused on what we call commercial analytics. We work with teams like marketing, customer development, and sales. We think about the areas to prioritize as simply following the money. We're focused on revenue growth management analytics, or RGM—things like pricing and promotions in stores and online assortments. Another area is marketing and media effectiveness analytics. There's a lot of value to be had in analytical approaches that help the business think about how to allocate a bucket of spend across different media levers, brands, and markets. If I have the proverbial next dollar, where should I put that? Beyond those two areas, innovation analytics is a really exciting space. So, using analytics in a predictive capacity for new product development.

What is your talent strategy for data and analytics personnel?

We call it the war for talent because it's just getting harder. There are a few dimensions that we consider. Compensation, of course. People feeling like they're fairly compensated for the value that they bring. Beyond that, we focus on culture and community. It's important for us to promote a positive culture for our team, so that they're having fun, and they feel like what they're working on impacts the organization. Also, within analytics it's important to have both technical and managerial tracks so that people know they can continue growing and adding more value to the company. So, offering developmental opportunities, which can mean things like exposure—bringing people along to big meetings, giving them the chance to present themselves and showcase the work that they've done. We also provide ways for them to get involved in the broader analytics community beyond the day-to-day job.

How do you think of performance when it comes to data and analytics? How do you measure success?

Organizationally, success for commercial analytics is about driving value for the company. That can mean revenue growth, cost optimization, or some combination of both. We make it a point to quantify the value and focus on the analytics that were actually acted upon by the business. Business adoption is part of the formula. There's also promoting data-driven decision making. We look at things like, are we scaling out tools and solutions to the organization? We look at adoption metrics. How often are they used? Are they becoming part of decision making? Are they part of the rhythm of how the business operates? Are they being used for key events in the commercial process? For my own personal success, building a great team, and coaching and helping my people shine, is something that is important to me.

What advice would you give to aspiring analytics professionals?

1. Find a great boss and team. Having a great boss who supports you and will help shape your career can matter more than the specifics of the day-to-day in your actual role.
2. Be curious. That is, engage in continuous learning. Cultivate as many experiences and as much exposure as you can to learn about the business.
3. Build your skill set beyond the technical. Enhance your storytelling and communication skills. It's a lot harder to have impact if you can't articulate why the analytics work you've completed is important to the business.
4. Grow your emotional intelligence. I don't have P&L responsibility, but I have to influence decisions that are being made. This comes down to softer skills, such as reading the room, understanding where people are coming from, and putting yourself in their shoes, so that you know the best way to present something that you believe is the right direction for the company.

For more insights from Diana, listen to the full podcast.