Overview

This presentation introduces a structured and repeatable methodology for Business Intelligence (BI) governance, designed to align data initiatives with strategic priorities while enabling fast, sustainable delivery. Fine-tuned across multiple organizations, the approach empowers business analysts to move from fragmented reporting efforts to coherent, high-impact BI systems—balancing rapid delivery with long-term value.

The methodology will be illustrated through a real-world project conducted in the telecommunications industry, focused on building a legal and regulatory BI solution. This example will demonstrate how the framework supports both compliance and strategic insight in a highly constrained environment

Innovation

The framework is composed of five foundational steps: 1. Aligning BI initiatives with organizational goals 2. Defining measurable key results (KPIs) 3. Mapping core business events using BPMN-like modeling 4. Clarifying shared business concepts via semantic modeling (e.g., ELM) 5. Grounding analytics in operational data sources

The methodology fosters cross-functional collaboration, breaks down organizational silos, and ensures traceability from strategy to data products. It supports scalable BI delivery while embedding a culture of shared ownership and data-driven decision-making.

Emerging Directions

Two active research directions are extending the methodology’s scope: • Emotions and Neuroscience: A sixth, exploratory step investigates how to integrate insights from neuroscience and emotional cognition into early project framing. By asking empathy-based questions, analysts can surface pain points and domain requirements before diving into solutions—making conversations more fluid and user-centered. • AI-Supported BI Framing (Early Stage): In parallel, a prototype AI agent is being explored to guide BI scoping activities. Still at an early stage, this assistant would help elicit strategic goals, KPIs, business events, and concepts, producing functional specifications based on the framework—without losing the nuances of human context.

Industrial Relevance

Proven across sectors, the methodology delivers: Stronger alignment between business and IT strategy, shared definitions, KPIs, and data sources to reduce conflict and rework, accelerated delivery and reduced time-to-insight, resilience through governance, documentation, and onboarding processes, a pragmatic, people-centered approach to building high-trust BI systems.

Expected Impact

For practitioners, this session will offer a practical, human-centered BI governance model grounded in Requirements Engineering principles and enhanced by successful real-world applications. It provides actionable techniques to structure BI conversations, align analytics with strategy, and boost adoption across diverse teams.

For academics, the presentation invites collaboration and critical input on the framework’s two exploratory extensions: the integration of neuroscience-informed elicitation practices and the design of AI agents capable of scoping BI initiatives. These lines of inquiry offer opportunities for advancing both theory and tools in requirements engineering, cognitive modeling, and socio-technical system design.

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