Insight

Designing BI Dashboards Through Decision Theory: From Simon’s IDC Model to Organisational Action

Introduction

Most dashboards present data; few guide action.
This article outlines how applying Herbert Simon’s Intelligence–Design–Choice (IDC) model can turn dashboards into decision-support systems.
The aim is practical: to move from static reporting to actionable intelligence — with frameworks relevant to designers, analysts, and managers alike.

1. Intelligence — Defining the Real Problem

  • Distinguish between available data and the problem that needs solving.
  • Practical steps: structured question framing, data cleaning, and creation of composite indicators (e.g. Adjusted ROI).
  • Expected outcome: a set of operationalised variables that describe the issue in actionable terms.

2. Design — Selecting KPIs Beyond Aesthetics

  • The three KPI layers: descriptive, diagnostic, and predictive.
  • Each visual must serve one goal — not decoration but decision relevance.
  • Apply what-if simulations for budget reallocation or parameter change.
  • Tailor dashboard views to decision-maker level: executive, tactical, operational.

3. Choice — Turning Analysis into Actionable Insight

  • From analysis to choice: how to translate simulations into explicit recommendations.
  • Quantify uncertainty using confidence bands and scenario-based thresholds.
  • Example: reallocating 20% of budget from Platform A to B, guided by forecasted impact measures.

4. Measuring Insight Quality

  • Depth: How far does the analysis explore root causes?
  • Accuracy: Are data and calculations reliable?
  • Actionability: Can recommendations be implemented under current constraints?
  • Risk Transparency: Are assumptions and limitations disclosed?

5. Implementation Roadmap (Quick Checklist)

  • Define reference metrics and ETL structure.
  • Build parameter-driven simulation modules.
  • Set access levels and role-based dashboard views.
  • Introduce a Decision Log to record rationale, assumptions, and outcomes.

Conclusion

A dashboard that fails to influence decisions is merely an expensive report.
Designing around Intelligence, Design, and Choice ensures that each chart and metric contributes to a coherent decision narrative — from recognising the issue to executing a response.

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