Business Intelligence

Setup

On first use, read setup.md for integration behavior and memory initialization.

When to Use

Use this skill when the user needs to build or improve business intelligence systems: KPI definitions, metric architecture, dashboard planning, executive reporting, and decision review loops.

This skill is optimized for operators, founders, product leaders, finance leaders, and analysts who need clear answers to "what changed, why it changed, and what to do next".

Architecture

Working memory lives in ~/business-intelligence/. See memory-template.md for base structure and status behavior.

~/business-intelligence/
├── memory.md                # HOT: goals, KPI ownership, active decisions
├── metric-tree/             # WARM: objective -> driver -> metric maps
├── kpi-contracts/           # WARM: metric definitions and formula versions
├── dashboard-specs/         # WARM: visualization and drill-down specifications
├── insight-briefs/          # WARM: weekly and monthly decision briefs
├── operating-cadence/       # WARM: review rituals and escalation rules
└── archive/                 # COLD: retired KPIs and past planning cycles

Quick Reference

Load only the file needed for the current task to keep context focused.

Core Rules

1. Start from Decision Questions, Not Charts

Every BI request must begin with one decision question and one owner.

If there is no decision owner, the output is reporting noise and should be reframed before building metrics.

2. Build a Metric Tree Before Dashboard Design

Map each business objective to drivers, then drivers to measurable KPIs.

Do not build dashboards first. Dashboards without a metric tree create disconnected charts and contradictory narratives.

3. Enforce KPI Contracts

Each KPI needs a written contract: definition, formula, grain, source, refresh cadence, owner, and valid interpretation window.

Never compare KPI values across periods if formula version or source logic changed without annotation.

4. Separate Leading and Lagging Indicators

For every lagging KPI, define at least one leading indicator that signals future movement.

If the system only tracks lagging outcomes, intervention happens too late.

5. Brief Insights in Decision Format

Every insight output must include:

• What changed
• Why it changed
• Confidence level
• Recommended action
• Action owner and due date

A BI summary without an action owner is incomplete.

6. Standardize Dashboard Specs Across Teams

Use consistent metric naming, time windows, segment logic, color semantics, and drill-down paths.

Inconsistent dashboard specs make cross-team comparisons invalid.

7. Run a Fixed Operating Cadence

Define daily, weekly, monthly, and quarterly BI rituals with clear participants and escalation triggers.

Without a fixed cadence, KPI review becomes reactive and decision quality degrades.

Business Intelligence Traps

• Starting with visualization tooling before KPI contracts -> expensive dashboards with weak decisions.
• Tracking too many KPIs per objective -> teams lose focus on actual drivers.
• Blending forecast assumptions with actuals in one number -> executives make false confidence calls.
• Changing formulas without version notes -> historical trend comparisons become invalid.
• Reporting movement without attribution depth -> teams cannot identify correct interventions.
• Sending BI updates without action owners -> insights do not convert into execution.

External Endpoints

This skill makes NO external network requests.

No data is sent externally.

Security & Privacy

Data that leaves your machine:

• Nothing by default.

Data that stays local:

• BI context, KPI contracts, and reporting notes under ~/business-intelligence/.
• Decision cadence and retrospective notes stored locally when memory is enabled.

This skill does NOT:

• Access files outside ~/business-intelligence/ for memory storage.
• Transmit metrics or business data to third-party APIs by default.
• Create background automations without explicit user confirmation.
• Modify its own skill definition files.

Related Skills

Install with clawhub install <slug> if user confirms:

• analytics - analysis workflows for interpreting performance patterns.
• data-analysis - analysis workflows for modeling trends, segments, and causal signals.
• dashboard - dashboard implementation for KPI visualization layers.
• strategy - strategic planning frameworks tied to business outcomes.
• report - structured report generation for stakeholder communication.

Feedback

• If useful: clawhub star business-intelligence
• Stay updated: clawhub sync