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Most organizations believe their biggest data challenges are technical. They invest in new tools, rebuild pipelines, and create more dashboards, expecting better decisions to follow. They usually don't. The real problem is not access to data. It is misalignment in how data is interpreted and used across teams. In many organizations, marketing, commerce, and data functions each operate with their own metrics, definitions, and perspectives. Each view is valid in isolation, but incomplete as a whole. The result is multiple versions of the truth, conflicting narratives, and decisions that do not reinforce each other. This session focuses on what actually bridges that gap. Through real-world examples, this talk explores why good data still leads to poor decisions, how misaligned interpretation creates hidden risk, and what it takes to move from fragmented insights to a single, decision-ready narrative. Attendees will learn how to identify misalignment in their own organizations, how to reframe data conversations around decisions instead of metrics, and how to create clarity without adding more complexity.
Most organizations believe their biggest data challenges are technical. They invest in new tools, rebuild pipelines, and create more dashboards, expecting better decisions to follow. They usually don't. The real problem is not access to data. It is misalignment in how data is interpreted and used across teams. In many organizations, marketing, commerce, and data functions each operate with their own metrics, definitions, and perspectives. Each view is valid in isolation, but incomplete as a whole. The result is multiple versions of the truth, conflicting narratives, and decisions that do not reinforce each other. This session focuses on what actually bridges that gap. Through real-world examples, this talk explores why good data still leads to poor decisions, how misaligned interpretation creates hidden risk, and what it takes to move from fragmented insights to a single, decision-ready narrative. Attendees will learn how to identify misalignment in their own organizations, how to reframe data conversations around decisions instead of metrics, and how to create clarity without adding more complexity.
Stacie Christensen is a data executive with more than 22 years of experience leading enterprise technology, data strategy, digital commerce, and organizational transformation.She specializes in enterprise data strategy, Master Data Management (MDM), Product Information Management (PIM), and data governance, helping organizations build trusted data foundations that improve decision-making and enable successful technology initiatives.Throughout her career, Stacie has helped organizations bridge the gap between business strategy and technology execution, creating alignment across product, data, governance, and digital commerce to deliver measurable business outcomes.She is the author of The Data Alignment Framework, including Built on Data, Built on Simplicity, and Built on Alignment, a practical series exploring how organizations create usable, governed, and aligned data ecosystems. Her work focuses on reducing complexity, strengthening organizational alignment, and ensuring technology investments deliver lasting business value.A frequent speaker on enterprise data strategy, AI readiness, governance, organizational alignment, and executive leadership, Stacie combines executive experience with practical frameworks that help organizations solve business problems before technology attempts to solve them.She holds a Bachelor of Science in Computer Science and Mathematics, an MBA from Texas State University, and is currently pursuing her Doctor of Business Administration (DBA).
