Kyle Pudenz, SVP, Enterprise Analytics at Cencora, speaks with David Zhao, Managing Director of Coda Strategy, in a video interview about the organizational data and analytic priorities, challenges the company is addressing, promoting data literacy, taking a probabilistic approach and its impact on business strategy, and the need for collaboration and understanding problems for developing solutions.

Cencora’s evolving data strategy

Introducing Cencora, Pudenz states that it is a major Fortune 10 organization primarily operating as a pharmaceutical wholesaler. He adds that many of the everyday medications people rely on for good health pass through its extensive distribution network. Apart from wholesale distribution, the organization also offers a range of life sciences and healthcare services as part of larger operations.

Pudenz leads Cencora’s enterprise analytics team, which includes data governance specialists, data scientists, and other experts. The team’s collective focus is on developing fundamental data products that enable the organization to access data and help execute the company’s supply chain strategy.

When asked about the top organizational data and analytic priorities, Pudenz shares that Cencora has been doubling down on its overall data strategy. For instance, ensuring the right architecture is in place to unlock core business capabilities.

Adding to that, Pudenz states that there has been a review of the data architecture and the team has settled on an analytics platform. With that in place, the company is focused on modernizing architecture, migrating data to the new platform, and establishing a solid foundation to develop analytics.

Speaking of priorities, Pudenz says, “It all starts with having that core data set that you can trust is reliable and consistent.” He notes that after having that, one can start building products that enable hardcore capabilities.

Addressing key challenges in data and analytics

Diving deep into the specific challenges that Cencora is working on, Pudenz states that a major shift in recent years has been the blending of operational data and analytics. In a supply-chain-driven organization like Cencora, integrating the two areas is critical to performing analytics, understanding customer needs, tracking products, and identifying issues.

At a time when up-to-the-minute information is critical to customers and patients, a key issue being addressed in the modernization effort is the increasing frequency of data set updates. Then, it boils down to ensuring the speed and capacity to perform analytics to provide the information to customers, enabling them to run businesses efficiently and have the products they need.

Another key aspect of this transformation, according to Pudenz, is establishing a consistent and reusable foundational dataset that can be used for various purposes. He shares that this composable dataset ties the solutions together, and this integration allows seamless translation of insights from one area to another without the questions around inconsistencies.

Advancing data literacy through a product mindset

Speaking of promoting data literacy, Pudenz states that understanding the data literacy level of user groups has been a persistent challenge for many companies. Cencora has approached it well by focusing on the critical business problems first. Next comes the education piece where the company is trying to pivot from descriptive or diagnostic reporting to predictive and prescriptive.

“It changes the way people engage with data. Instead of it being very deterministic where someone knows that this is the right answer, we’re moving into more of a probabilistic area,” says Pudenz.

He further suggests that users need to recognize that it is a long-term approach — applying the product mindset in the development with co-creation. Pudenz says that this will ensure users understand what the data team is trying to do, are involved, and aid in getting buy-in.

“We are still at the beginning of that process, but we are finding that engaging team members as part of the creation process works much better,” says Pudenz. He explains that this enables users to have a true buy-in and helps them grasp how to apply and use the solution. The collaboration builds partnerships and brings business insights with advanced analytics to drive better solutions.

Impact of a probabilistic approach on business strategy

Shedding light on whether the probabilistic approach impacts business strategy, Pudenz notes that it starts with the broader business strategy and understanding the real problems that require solutions.

The strategy helps define the specific challenge, and then analytics is applied to support the needs, says Pudenz. It does not start with analytics and searching for a problem, but the other way around.

The communication language is critical, as it must be tailored for the audience to understand. A huge part of the approach, according to Pudenz, is first, understanding the problem enough to create a viable solution, and then educating the user well to understand what is to be accomplished.

Delving further, Pudenz states that while presenting a business problem, it is necessary to break it down and engage in specific conversations on the problem. This approach helps translate a qualitative challenge into a quantitative approach.

Having specific definitions is critical, as it helps business leaders analyze challenges more effectively. The important part of the process is understanding the actual problem. Moreover, when applying analytics, it must be ensured that the problem is quantitatively addressed the right way and is not substituted with something easy to solve.

Moving forward, Pudenz states that understanding the cause of the disagreement is crucial, as it challenges one to assess whether they are thinking about the problem in the right way. Also, it may lead to a greater conviction of how one should approach the issue.

“That back-and-forth conversation with your team ultimately leads you to the right solution,” says Pudenz. Concluding, he states that processes are not eternal, and as business changes and understanding evolves, one must be pliable enough. The product mindset comes into play when one assesses how to continuously evolve the solution so that it remains relevant for users.

CDO Magazine appreciates Kyle Prudenz for sharing his insights with our global community.