Kyle Pudenz, SVP of Enterprise Analytics at Cencora, joins David Zhao, Managing Director at Coda Strategy, in a video interview to discuss building data architecture to tackle integration challenges in the supply chain, insights on the business value of data and its commercialization aspect, enhancing efficiency with generative AI (GenAI), and balancing long-term planning with innovation.

At the outset, Pudenz highlights the approach to designing a data architecture to tackle integration challenges. From an analytics standpoint, what matters most is having access to the right data needed to address specific business challenges, he says.

Achieving that relies on having a solid architecture, one that takes into account critical factors like data privacy and the organization’s need to maintain control and security over the information it shares. He mentions bringing in the right architectural partners and internal experts in the conversation.

About Cencora, Pudenz says this can bridge the legal team, cyber risk team, enterprise architects, and product development teams to align architecture with data usage rights. “As you go through that process, it is pretty critical to make sure that what you deliver is truly usable and also create something that, while it creates value, doesn’t unnecessarily put a patient’s or company’s information at risk,” Pudenz adds.

Speaking of data in business terms and organizational strategy, Pudenz states that in the broader pharmaceutical supply chain, Cencora goes beyond distribution into life sciences services and consulting. He adds that the organization sits at a strategic vantage point, rich with data and insights.

This position raises ongoing questions about how much transparency is appropriate, particularly from a public health perspective. Often, the insights derived from Cencora’s data can inform government agencies, contributing to policy development or highlighting systemic challenges that could improve efficiency across healthcare markets.

Delivering these data-driven solutions has a cost, says Pudenz. For a company of Cencora’s scale, implementing capabilities like product-level tracking across global distribution centers requires significant investment, he notes.

To justify that effort, the organization looks for opportunities to create value-added offerings for partners, whether customers or upstream manufacturers, that enable better business outcomes, remarks Pudenz.

Many times, the focus is on commercialization. However, he argues, “There’s a lot more in terms of value realization that may extend into operational savings, more efficiency, and better decision-making that can impact both your top and bottom line.”

Delving further, Pudenz states that in the supply chain sector, operating costs are significant and margins tend to be lower than in many other industries. It is critical to consider commercial opportunities where partners can gain significant value from the insights generated through data synthesis. On the other hand, there are substantial cost savings opportunities for both Cencora and the broader supply chain.

When asked how Cencora can maintain a competitive advantage through data analytics and AI, Pudenz states GenAI can significantly enhance efficiency. Particularly, by streamlining processes and automating tasks that do not leverage human expertise.

Organizations can free up their teams to focus on higher-impact work by bringing their supply chain knowledge to the broader healthcare industry, says Pudenz. Beyond GenAI, there’s growing excitement around emerging capabilities like knowledge graphs and graph analytics, he shares.

These tools represent a major evolution from traditional SQL-based approaches by bringing context into play. “Most challenges are going to be alleviated by understanding the broader context,” says Pudenz.

The ability to understand how different elements relate, interconnect, and depend on one another is critical. By providing that context both at scale and in near real-time capabilities,   organizations can unlock powerful applications that drive performance and help realize the value of underlying data and the industry.

When it comes to integrating emerging technologies into a complex environment like pharmaceutical supply chain distribution, Pudenz advocates taking the middle road. He mentions building a roadmap based on current business problems and applying capabilities to solve the problems. He maintains that it is fundamental to have a 5-year plan that aligns with current business challenges and technology, to enable making the right investments in architecture. The roadmap also helps prioritize the right data sets and set frameworks around data usage, all of which take time to establish and implement.

At the same time, it is equally vital to leave room for experimentation and innovation. Cencora has skilled data scientists, says Pudenz, who understand both the technology and the industry.

According to him, nurturing this aspect provides an innovative space that can lead to meaningful breakthroughs and novel applications with relatively low investment. “Just allowing for some time for that to be nurtured and developed could potentially really pay back in the future,” Pudenz concludes.

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

Making Everything Real-time Can Lead to Too Much Noise — Cencora SVP Enterprise Analytics