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The GRA Framework — Gap · Risk · Accountability

A decision-support framework that moves research analytics from static reporting toward judgment, readiness, and action — using AI as the analytical engine.

Presented as "Beyond Reporting: How AI-Enabled Research Analytics Reveals Gaps, Risk, and Accountability in Research Administration" at the Research Analytics Summit (REACH) 2026, Newport, RI.

Author: Ayomide Ajibola, MBA — Morgan State University


🔗 Links

The Framework

Most research analytics systems were built for compliance and record-keeping — they tell you what happened, not whether you're ready. The GRA framework reorients analytics around three questions:

Pillar The question it answers
Gap What data is missing or unverified? (system disagreements, incomplete records, untested assumptions)
Risk Where are we exposed without knowing it? (declining pipelines, slow expenditure, awards nearing end of performance)
Accountability Can we explain and defend our analytics? (who owns what, who gets alerted, whether decisions are evidence-based)

AI-enabled analytics is the engine that powers each pillar — surfacing gaps, flagging risk, and strengthening accountability in real time, while keeping every decision human-led.

The Interactive Demo

The live demo is a working mock GRA Analytics dashboard — an award portfolio monitor with a GAP detector, risk flags, a period-of-performance monitor, PI and cross-office views, and a live analysis engine where thresholds trigger GRA rules. It shows how the framework works in practice using accessible tools (Airtable, Power BI), not a data-science team. All data is illustrative.

Implementation Pathway

The framework is tool-agnostic and designed to start at any capacity level — from a Starter tier (Excel + structured reporting) through Intermediate (Airtable / Power BI + AI assist) to Advanced (integrated ERP + AI analytics layer).

Files

File Description
index.html Interactive GRA Analytics dashboard demo (runs in-browser)
Beyond_Reporting_GRA_REACH_2026.pdf Full presentation slide deck (13 slides)

Citation

Ajibola, A. (2026). Beyond Reporting: How AI-Enabled Research Analytics Reveals Gaps, Risk, and Accountability in Research Administration. Research Analytics Summit (REACH) 2026, Newport, RI. https://cassyni.com/events/KxSZkjNLHZsAgyk6UJm6qT

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The Gap-Risk-Accountability (GRA) framework for AI-enabled research analytics. Presented at the Research Analytics Summit (REACH) 2026

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