Organizations are pouring billions into AI, analytics, and automation, yet the majority fail to realize meaningful business value. According to new research from Info-Tech Research Group, the root cause lies not in strategy or technology but in poorly defined or misaligned data operating models that leave ownership, governance, and collaboration unresolved.
Info-Tech Research Group’s latest blueprint, Establish the Target Operating Model Needed to Execute Your Data Strategy, highlights a critical gap: leaders frequently leap from high-level data strategy directly to execution without addressing foundational operating model decisions. This oversight leads to inconsistent data quality, siloed initiatives, stalled projects, and escalating costs.
The research stresses that technical solutions alone cannot resolve these issues. Long-term success hinges on deliberately balancing three core dynamics across the data ecosystem: proximity to business problems, clear decision rights over data meaning and access, and scalable, cost-effective capability delivery.
"Organizations often believe their data strategy is sound, but most fail at the operating model level, where ambiguity around ownership, decision rights, and partnership undermines progress," says Nysa Zaran, research director at Info-Tech Research Group. "Leaders cannot design operating models in isolation. They need structured conversations with business partners to negotiate accountabilities, surface risks, and define how capabilities will actually come together to deliver value."
Info-Tech identifies recurring challenges that data and IT leaders must confront:
Info-Tech’s blueprint provides a structured, step-by-step methodology to move organizations from fragmented operations to a unified, outcome-oriented target operating model:
Phase 1: Deconstruct and Assess Capabilities vs. Outcomes Leaders align on success principles, visualize the current operating model, map capabilities to desired outcomes, and identify gaps that inform the target state.
Phase 2: Build the Roadmap and Plan Engagement Strategy Teams define critical building blocks, clarify scope of control (“mine, ours, yours”), identify stakeholders, and quantify partnership risks and requirements.
Phase 3: Co-Design Operating Model Shifts Stakeholders engage in facilitated conversations to align on accountabilities, risks, and required changes across people, process, and technology, directly shaping the final design and roadmap.
Phase 4: Communicate and Secure Endorsement Leaders consolidate the operating model, roadmap, and risk register into executive-ready materials that articulate decisions, funding needs, and strategic impact.
"Data strategies only succeed when operating models enable proximity, clarity, and cost discipline," explains Zaran. "By deliberately balancing these success principles, leaders can build a model that earns funding, accelerates delivery, and remains resilient as AI and analytics needs evolve."
The blueprint includes comprehensive tools—capability assessments, negotiation guides, roadmapping templates, and executive presentations—enabling data and IT leaders to bridge the gap between strategy and measurable results.
About Info-Tech Research Group
Info-Tech Research Group is one of the world's leading and fastest-growing research and advisory firms, serving over 30,000 IT, HR, and marketing professionals around the globe. As a trusted product and service leader, the company delivers unbiased, highly relevant research and industry-leading advisory support to help leaders make strategic, timely, and well-informed decisions. For nearly 30 years, Info-Tech has partnered closely with teams to provide everything they need, from actionable tools to expert guidance, ensuring they deliver measurable results for their organizations. To learn more about Info-Tech's HR research and advisory services, visit McLean & Company, and for data-driven software buying insights and vendor evaluations, visit the firm's SoftwareReviews platform.
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