# Kpi Dashboard Design

> Diseña dashboards de KPI efectivos: selección de métricas, buenas prácticas de visualización y patrones de monitoreo en tiempo real.

Fuente: https://skillsagentes.com/skills/wshobson/agents/kpi-dashboard-design
Markdown: https://skillsagentes.com/skills/wshobson/agents/kpi-dashboard-design.md

Repositorio: https://github.com/wshobson/agents
Autor: wshobson
Licencia: MIT
Actualizado: hace 4 meses
Coste de contexto: 119 tok instalada, 1.4k tok al activarse, 5.1k tok con todos los archivos del bundle
Bundle: 2 archivos, 20 KB
Permisos que pide: ninguno declarado

## Instalación

Un skill son archivos markdown: los mismos archivos valen para cualquier agente y lo único que cambia es el directorio de destino, es decir la bandera `--agent`. Añade `-g` para instalarlo en todos los proyectos de la máquina.

```bash
# Claude Code
npx -y skills add wshobson/agents --skill kpi-dashboard-design --agent claude-code
# Cursor
npx -y skills add wshobson/agents --skill kpi-dashboard-design --agent cursor
# Codex
npx -y skills add wshobson/agents --skill kpi-dashboard-design --agent codex
# Gemini CLI
npx -y skills add wshobson/agents --skill kpi-dashboard-design --agent gemini
# Windsurf
npx -y skills add wshobson/agents --skill kpi-dashboard-design --agent windsurf
# Cline
npx -y skills add wshobson/agents --skill kpi-dashboard-design --agent cline
```

## Qué hace

- Provee frameworks para elegir KPIs, estructurar jerarquías de dashboard y aplicar buenas prácticas de visualización
- Da patrones SQL/Python para normalizar métricas, cohortes mensuales, agregados pre-calculados y umbrales dinámicos de alerta
- Ofrece diagnóstico para dashboards con métricas contradictorias o inconsistentes entre equipos

## Cuándo usarla

- Diseñar dashboards ejecutivos
- Seleccionar KPIs significativos
- Construir displays de monitoreo en tiempo real
- Crear vistas de métricas específicas por departamento o mejorar dashboards existentes

## Qué la activa

- "Diseña un dashboard ejecutivo de SaaS con MRR, churn y LTV/CAC"
- "Nuestro MRR no coincide con el número de finanzas, ayúdame a diagnosticarlo"
- "Crea una vista de análisis de retención por cohortes"
- "El dashboard en tiempo real está saturando la base de datos"

## Archivos

- SKILL.md — 5 KB
- references/details.md — 15 KB

## SKILL.md

Reproducido tal cual desde wshobson/agents bajo MIT. Esta sección es el documento original y está en inglés.

# KPI Dashboard Design

Comprehensive patterns for designing effective Key Performance Indicator (KPI) dashboards that drive business decisions.

## When to Use This Skill

- Designing executive dashboards
- Selecting meaningful KPIs
- Building real-time monitoring displays
- Creating department-specific metrics views
- Improving existing dashboard layouts
- Establishing metric governance

## Core Concepts

### 1. KPI Framework

| Level           | Focus            | Update Frequency  | Audience   |
| --------------- | ---------------- | ----------------- | ---------- |
| **Strategic**   | Long-term goals  | Monthly/Quarterly | Executives |
| **Tactical**    | Department goals | Weekly/Monthly    | Managers   |
| **Operational** | Day-to-day       | Real-time/Daily   | Teams      |

### 2. SMART KPIs

```
Specific: Clear definition
Measurable: Quantifiable
Achievable: Realistic targets
Relevant: Aligned to goals
Time-bound: Defined period
```

### 3. Dashboard Hierarchy

```
├── Executive Summary (1 page)
│   ├── 4-6 headline KPIs
│   ├── Trend indicators
│   └── Key alerts
├── Department Views
│   ├── Sales Dashboard
│   ├── Marketing Dashboard
│   ├── Operations Dashboard
│   └── Finance Dashboard
└── Detailed Drilldowns
    ├── Individual metrics
    └── Root cause analysis
```

## Detailed worked examples and patterns

Detailed sections (starting with `## Common KPIs by Department`) live in `references/details.md`. Read that file when the navigation summary above is insufficient.

## Best Practices

### Do's

- **Limit to 5-7 KPIs** - Focus on what matters
- **Show context** - Comparisons, trends, targets
- **Use consistent colors** - Red=bad, green=good
- **Enable drilldown** - From summary to detail
- **Update appropriately** - Match metric frequency

### Don'ts

- **Don't show vanity metrics** - Focus on actionable data
- **Don't overcrowd** - White space aids comprehension
- **Don't use 3D charts** - They distort perception
- **Don't hide methodology** - Document calculations
- **Don't ignore mobile** - Ensure responsive design

## Troubleshooting

### MRR shown on dashboard contradicts finance's number

The most common cause is inconsistent treatment of annual plans. Finance may prorate to a daily rate while the dashboard normalizes to monthly. Align on a single formula and document it directly on the dashboard card:

```sql
-- Explicit formula shown in tooltip / data dictionary
-- Annual plans: divide total contract value by 12
-- Quarterly plans: divide by 3
-- Monthly plans: use as-is
CASE subscription_interval
    WHEN 'monthly'   THEN amount
    WHEN 'quarterly' THEN amount / 3.0
    WHEN 'yearly'    THEN amount / 12.0
END AS normalized_mrr
```

### Dashboard shows green but product team reports users complaining

The dashboard likely tracks system uptime (a lagging indicator) but not user-facing quality metrics. Add customer-perceived metrics alongside infrastructure metrics:

| Infrastructure (green) | User-perceived (add these) |
|---|---|
| API uptime 99.9% | P95 page load time |
| Error rate 0.1% | Task completion rate |
| Queue depth normal | Support ticket volume |

### Retention cohort looks flat — no variation between cohorts

Check whether the cohort query is partitioning by signup month correctly. A common bug is using `created_at::date` instead of `DATE_TRUNC('month', created_at)`, which groups by day and produces cohorts too small to show trends:

```sql
-- Wrong: too granular, cohorts are too small
DATE_TRUNC('day', created_at) AS cohort_date

-- Correct: monthly cohorts
DATE_TRUNC('month', created_at) AS cohort_month
```

### Real-time dashboard hammers the database

A live dashboard refreshing every 10 seconds with complex cohort SQL will degrade production query performance. Separate OLAP workloads from OLTP by writing pre-aggregated metrics to a summary table via a scheduled job, and have the dashboard read from that:

```python
# Scheduled every 5 minutes via cron/Celery
def refresh_mrr_summary():
    conn.execute("""
        INSERT INTO kpi_snapshot (metric, value, snapshot_at)
        SELECT 'mrr', SUM(...), NOW()
        FROM subscriptions WHERE status = 'active'
        ON CONFLICT (metric) DO UPDATE SET value = EXCLUDED.value
    """)
```

### Alert thresholds fire constantly, team ignores them

Static thresholds set once and never reviewed cause alert fatigue. Use dynamic thresholds based on rolling averages so alerts fire only when the metric deviates significantly from its own baseline:

```python
# Alert if current value is > 2 standard deviations from 30-day rolling mean
def is_anomalous(current: float, history: list[float]) -> bool:
    mean = statistics.mean(history)
    stdev = statistics.stdev(history)
    return abs(current - mean) > 2 * stdev
```

## Related Skills

- `data-storytelling` - Turn dashboard findings into narratives that drive executive decisions

## Dónde encaja

- Categoría: [Datos y analítica](https://skillsagentes.com/categorias/datos-analitica.md) — Consulta, limpia y visualiza datos sin salir del agente.
- Creador: [wshobson](https://skillsagentes.com/creators/wshobson.md) — 183 skills en el directorio
- [Todas las skills](https://skillsagentes.com/skills.md)
- [Ranking de instalaciones](https://skillsagentes.com/ranking.md)

## Otras skills del mismo repositorio

- [Hermes Tweet](https://skillsagentes.com/skills/wshobson/agents/hermes-tweet.md): Instala y opera Hermes Tweet, un plugin de Hermes Agent para investigar X/Twitter, leer timelines, analizar tweets y ejecutar operaciones privadas o de cambio de estado con aprobación previa.
- [Superself](https://skillsagentes.com/skills/wshobson/agents/superself.md): Úsalo cuando un proyecto guarda su estado en Superself: lee `self context` al iniciar sesión, vincula el trabajo a una work unit, reporta con evidencia y registra decisiones confirmadas.
- [Grounded Vault](https://skillsagentes.com/skills/wshobson/agents/grounded-vault.md): Úsalo para mantener un almacén Markdown de conocimiento donde cada afirmación compilada se rastrea hasta una fuente inmutable y el drift se detecta con git diff sin gastar tokens.
- [Postgresql Table Design](https://skillsagentes.com/skills/wshobson/agents/postgresql-table-design.md): Úsalo al diseñar o revisar un esquema específico de PostgreSQL: buenas prácticas, tipos de datos, indexación, restricciones, patrones de rendimiento y funciones avanzadas.
- [Prompt Engineering Patterns](https://skillsagentes.com/skills/wshobson/agents/prompt-engineering-patterns.md): Úsalo cuando pidan optimizar un prompt, mejorar su rendimiento, diseñar una plantilla, aplicar chain-of-thought, few-shot prompting o técnicas avanzadas de prompt engineering para producción.

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