By Autumn Walden, Editor, AACRAO Connect, Content Strategy Manager, AACRAO
Enterprise systems are getting better at surfacing signals for business needs such as risk alerts, staffing trends, spending anomalies, and performance indicators, but insight alone does not guarantee action. In his article “Closing the ERP Intelligence-to-Action Gap,” published in ERP Today, AACRAO Technology Advisory Council member Tirumala Rao Chimpiri of Stony Brook University describes the CAIP-HE reference framework he developed and argues that one of the biggest challenges in modern ERP environments is not a shortage of data, analytics, or even AI. It is the structural disconnect between where intelligence appears and where authority, accountability, and decision-making actually sit. As he notes, organizations may invest heavily in smarter ERP capabilities, yet still struggle to respond quickly when information is trapped across functions, approvals, and governance layers. The article cites a recent Gartner projection: more than 70% of ERP initiatives may fail to fully meet their original business goals by 2027.
That framing makes this conversation especially timely. Rather than treating ERP as a purely technical system, Chimpiri pushes readers to think about the human, organizational, and governance conditions required to turn intelligence into coordinated action. “Over the past year, I have developed a platform-agnostic ERP + AI reference framework called CAIP-HE,” shared Chimpiri. When asked about his framework, which includes: Cognitive automation, Advanced analytics, Integration and interoperability, and Personalization, “CAIP-HE looks at how organizations can reason about analytics, automation, integration, and personalization as a system—specifically, how insight moves from detection to decision to coordinated action across complex ERP environments,” said Chimpiri.
“I think this perspective could be useful for AACRAO members and member institutions, especially given how many are navigating modernization across student, finance, HR, and CRM systems at the same time, and trying to make AI and analytics actually influence decisions rather than just produce more dashboards,” offered Chimpiri. In this Q&A, we asked him about his ties to AACRAO, what leaders with limited resources can do to design more responsive, accountable enterprise systems, and recommendations for governance.
How did you learn about AACRAO, and do you recommend any resources to other members?
I’ve followed AACRAO’s work for years because it lives right at the intersection of policy, operations, data, and student outcomes, which is where some of the hardest day-to-day institutional decisions actually get made. As my own work has increasingly focused on how organizations move from insight to decision to execution across enterprise systems, I’ve found AACRAO’s guidance and community especially helpful for seeing how those decisions play out in practice. The challenges registrars and enrollment leaders deal with every day, things like governance, cross-unit coordination, data quality, and accountability, are exactly the kinds of situations where having clear decision structures and execution paths really matters.
With limited resources, what should enrollment leaders prioritize?
When resources are tight, I think the biggest leverage point isn’t another tool or dashboard. It’s being clear about how decisions actually get made and carried through, how insights turn into decisions, and how those decisions turn into action across teams and systems. Most institutions already have plenty of data. The real bottleneck is usually governance, accountability, and follow-through. I’d focus leaders on a small set of mission-critical decisions, make it clear who owns them, what evidence they rely on, and how they get executed across ERP, CRM, and academic systems. When that backbone is in place, technology investments start to reinforce each other instead of pulling in different directions.
Are there checkpoints or governance structures you recommend for decisions that affect student access and success?
Yes, governance becomes even more important as institutions rely more on analytics, automation, and AI-informed processes. The real shift is treating governance not as a compliance afterthought, but as part of how decisions are actually designed and carried out.
For high-impact areas like student success, I think it helps to have a few clear checkpoints around three things. First, decision authority, who owns the decision and when it can be automated versus when it needs to be escalated. Second, transparency and traceability, how a recommendation or action was arrived at and what data went into it. And third, human override and accountability, when and how staff can step in, especially when there are academic, financial, or equity implications.
In practice, the question isn’t just “Can the system make this recommendation?” It’s “Is the way we’ve designed the decision process clear about who’s responsible, how oversight works, and what happens after the decision is made?” When those checkpoints are built into the process, institutions can move faster without losing trust or control.
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