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Episode 15: Cameron Davies (Yum! Brands) + Key Takeaways

Cameron Davies has only been at Yum! Brands for just under a year, but seems to be building (and acquiring) world-class analytics capabilities the way he has at other companies, in a way that is unique to Yum! Brands. If you don’t recognize the Yum! Brands name, you’ll surely recognize KFC, Pizza Hut and Taco Bell which are all part of the Yum! Brands family of companies. In this far-reaching conversation, Cameron shares a unique list of attributes that make for a strong analytics leader, and he even references World War II history for inspiration when describing analytics projects. You’ll also want to pay attention to how Cameron is applying lessons from his past to current challenges at Yum! Without question, an inspiring episode.

Key Takeaways

Describe your title and role.

My title is Chief Data Officer at Yum! Brands. Our functional mission is to bring data to life for the Yum! brands, whether that’s through data infrastructure, data products, or data services.

Where does the analytics function sit within the organization and who does it report into?

We’ve organized the analytics function so that we report up through the Chief Digital and Technology Officer, so within the central technology function here at Yum!.

Is that the right place for the analytics function to report?

Absolutely, yes. I've been in roles where analytics reported directly to the CEO, up through finance, or sometimes through marketing. At Yum!, given how we’re structured and what we’re trying to accomplish, IT is the absolute right place for it. What this has allowed us to do is integrate the data and analytics into the broader set of technology tools we’re trying to roll out across the organization. It also helps that we have strong leadership ties to both finance, and David Gibbs, our CEO, and his vision for analytics; this prevents the analytics function from being simply a technology role.

Describe the organizing model you have adopted for analytics.

We use a hybrid model. We have a center of excellence (COE) that is centrally funded with payments from the brands. We’re either working on helping each of the brands set up their own analytics functions so we can work directly with them, or, where they already exist, pulling their functions in. Yum! Brands itself is highly decentralized in the sense that we have 5,000 locations around the world across four brands that act very much like independent brands, with markets globally that act very much like independent markets and franchisees that act like independent businesses.

The COE consists of about 60 people worldwide. We currently have plans over the next 12–24 months to double that number based on our current product roadmaps and demand across the space. The brands are starting to pull their folks together within that hybrid model. My best guess is there’s another 40 to 50 people across the world who perform similar analytics functions, who we’re trying to organize in a more cohesive manner.

I'm seven months into this role. When I got to Yum!, one thing that became obvious fast was that we needed to put a three-prong strategy in place around data infrastructure, data products, and data services. On the services side, we saw that we spent a lot of money on marketing, but we didn’t have a lot of mathematical discipline around how we used analytics to help inform those decisions. To expand our analytics capabilities in this area, we recently acquired Kvantum. From a speed-to-market perspective, in that quintessential build-versus-buy decision, bringing in this little company and integrating them into our broader strategy will accelerate our speed to market for marketing decisions.

What are four or five important qualities and behaviors of leaders of analytics?

I’d like to spin this question a little bit. The key is leadership maturity—understanding what you’re great at and what you’re not as great at, and then how you hire around that based on your organizational needs. It’s about asking yourself questions.

  1. What's the maturity of the analytics organization? Because that will determine whether you need somebody who is a builder/influencer or an expert leader in a specific space.
  2. What’s the maturity of your data within the organization? Because that might imply you need somebody who understands data stacks on the engineering side as opposed to the analytic science solution side.
  3. What’s the maturity of the broader organization? Do you need somebody who’s more of an influencer or a mature maintainer? Both are important skill sets depending on what you’re trying to accomplish.

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

ROI, first and foremost. What kind of value are we driving to the organization, not in a squishy way, but in a very “finance bought-in” way? Everything we do has a measurement off of ROI. As an example, we released a new system called our Predictive Analytics Platform that will be rolling into 3,400 KFC stores this year. That was all about getting smarter about inventory management. And out of the gate, we’ve started producing KPIs around the reductions in inventory transfers from store to store and the value of the reductions.

I’m a firm believer that as analytics folks, we should be the best of all people when it comes to built-in self-measurement strategies that can show ROI. I like to use Disney as the gold standard for this. Years ago, when I worked at Disney, we put in something called Consumer Centric Revenue Management to optimize Disney World and Disneyland reservation offers that came through our call center and websites. We randomized every tenth offer—took out the analytics—so that we had an on-going, built-in measurement of the value that the algorithms were driving.

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