data-analysis-kpi-reporting

Convert established metrics into evidence-backed KPI readouts with status, pacing, drivers, and decisions.

Updated Jan 28, 2026
One-click install
npx skills add https://github.com/scanady/nexus-skills --skill data-analysis-kpi-reporting-scanady
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analysis-kpi-reporting
Source: https://github.com/scanady/nexus-skills/tree/main/skills/data-analysis-kpi-reporting
Command: npx skills add https://github.com/scanady/nexus-skills --skill data-analysis-kpi-reporting-scanady

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Recurring performance reporting often suffers from inconsistent definitions, misleading period comparisons, and causal claims unsupported by evidence. This Skill turns an established metric set into a disciplined operating readout that leaders can act on, with verified actuals, comparability checks, and clearly bounded driver explanations. ## Core Features & Use Cases - Comparability-gated variance analysis: Every variance passes a definition, population, calendar, and unit compatibility check before interpretation, with restated, qualified, or broken comparisons labeled explicitly. - Evidence-ranked driver attribution: Explanations are separated into quantified contributions, supported associations, operating context, and hypotheses so timing correlations are never promoted to causes. - Cadence-specific readout patterns: Reference templates for inline updates, KPI scorecards, weekly operating reviews, monthly business reviews, and quarterly business reviews. - Use Case: A data analyst preparing a monthly business review uses the Skill to reconcile actuals against plan, assess pacing against targets, decompose movement into verified drivers, and publish a scorecard with actions, owners, and due dates. ## Quick Start Prepare a monthly KPI readout for our executive team comparing October actuals to plan, with status, drivers, and next actions.

Frequently Asked Questions about data-analysis-kpi-reporting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prepare a KPI report for a weekly or monthly business review?▼

Define the audience, decision, period, cutoff, and comparison basis first, then freeze metric definitions and reconcile actuals against authoritative sources. The Skill produces a scorecard with actuals, variances, pacing, status, drivers, and actions in WBR or MBR format.

How to compare KPI actuals against targets and prior periods correctly?▼

Run each comparison through a comparability gate checking metric definition, population, calendar length, units, and data maturity. Comparisons are classified as comparable, restated, qualified, or broken, and broken comparisons are never reported as variances.

What is the difference between KPI reporting and KPI design?▼

KPI reporting packages existing governed metrics into recurring decision readouts, while KPI design chooses which metrics to track and writes metric contracts. Use a KPI designer skill when the measurement system itself does not exist yet.

Can this skill identify root causes of metric movement?▼

It bounds driver explanations by evidence level: quantified contributions, supported associations, operating context, and hypotheses. It does not perform open-ended root-cause analysis or build financial models; unresolved movement is labeled as residual or hypothesis.

What happens when metric definitions or data sources conflict?▼

The Skill surfaces the conflict, shows material disagreement between sources, and pauses precise interpretation until an owner or authoritative artifact resolves it. It never publishes a precise status when definitions, cutoffs, or pacing bases are unresolved.