Advantage Solutions sits at the intersection of brands, retailers, and consumers, serving as a critical execution partner for some of the world’s biggest CPG companies. With a business spanning sales, marketing, retail execution, digital commerce, and advanced analytics, the organization depends heavily on real-time, high-quality data to deliver value across thousands of retail environments and client engagements.

In this first installment of a three-part series, Jo O’Hazo, Chief Data Officer at Advantage Solutions, joins Nathan Turajski, Sr. Director of Product Marketing at Informatica, to discuss the foundational work required to scale data and AI initiatives, the human dynamics behind trust-building, and why micro-wins matter as much as major milestones in enterprise transformation.

A people-first CDO

O’Hazo begins by emphasizing that her role extends far beyond technology oversight. “I would best introduce myself as a people leader first. I co-create and lead through so many talented individuals at Advantage Solutions.”

Her team oversees the full spectrum of data strategy — from architecture and governance to the delivery of data products and analytics capabilities used across the organization. But she stresses that data and technology expertise alone cannot drive transformation.

“We are deep experts in business where data and technology intersect. And with so many facets of managing and driving value from data, it takes a diverse and well-curated group of talented individuals to create success in any CDO office.”

Winning through micro-successes

When asked about the challenges she faced when she stepped into the role, O’Hazo says the barriers were not large, single obstacles — but layers of smaller, systemic issues. “It’s been more about a series of challenges. Some of them seem very small, but they become the greatest obstacles you overcome.”

She describes the painstaking process of building an enterprise data foundation as a journey made up of micro wins:

• Uncovering data that was previously inaccessible
• Answering basic business questions that teams had stopped asking
• Eliminating manual workarounds
• Modernizing data flows step by step

Each small victory compounds into momentum. “Those series of micro wins around solving a particular challenge create that big flag on the moon for the team.”

However, none of it works without talent.

“It’s about recognizing and identifying talent, and many times showing individuals that they can achieve far beyond what they themselves may think,” O’Hazo says.

This combination — people and foundational data — unlocks everything downstream: AI, advanced analytics, and real-time insights.

Trust is the first data product

When asked how she builds trust in data and AI strategies, O’Hazo emphasizes that trust begins before the data. “Trust starts with the rapport with individuals. It starts with listening. It doesn’t start with building solutions.”

She highlights that facts alone don’t solve decision-making challenges. Business intuition still matters — but it must be balanced with truth derived from data.

“Sometimes the facts alone aren’t enough. There’s a balance between data and the business-led gut experience. All of it is important.”

Trust requires time, consistency, and transparency. And it evolves in stages:

• Person-to-person understanding
• Shared definition of the problem
• Aligned expectations
• Data-supported insights
• Repeatable outcomes

This sequence is essential because, as she notes, “It’s a long game. It’s not a one-and-done, one-hit-wonder situation.”

The power of cross-functional collaboration

O’Hazo frames AI not as a disruption, but as a spotlight. “AI is almost spotlighting the need for foundational data.”

The reason: modern organizations need to answer multidimensional questions, not isolated ones.

“It’s no longer a singular flat question. It’s ‘How is X related to Y, and what are the factors that drive growth?’ To answer that, you need data from so many different functions organized and architected the right way.”

This interconnection does more than support analytics; it transforms relationships across the business.

“When you start to interconnect the data, you naturally and organically have meaningful conversations across functions.”

Cross-functional literacy for both data and AI becomes a catalyst for breaking down silos, empowering business users, and accelerating adoption.

The enterprise source of truth: AI didn’t change the rules — it revealed them

Turajski raises the common phrase “source of truth,” asking whether AI has changed how organizations think about it. O’Hazo’s response is clear: AI doesn’t rewrite the rules; it reveals the gaps. “AI is spotlighting, sometimes unfavorably, where the pre-work on the data foundation hasn’t accelerated enough.”

This wake-up call has elevated data readiness to board-level priority. Organizations now see that:

• AI cannot compensate for weak data governance
• AI cannot fix inaccurate or incomplete data
• AI cannot operate without secure, compliant, well-modeled data
• AI cannot scale without semantic interoperability

“Governance, security, compliance, accuracy — those things don’t just organically happen by plugging an AI agent over a component of information,” O’Hazo states. She adds that applying the principles of data management to AI ensures not only quick wins but sustainable ones.

“It has to be curated. It has to be enterprise-sturdy. That accelerates not just the value of AI, but the consistency of the results,” she concludes.

CDO Magazine appreciates Jo O’Hazo for sharing her insights with our global community.