MA Budget Actual Variance

予算実績差異分析スキル。勘定科目タイプ（収益/費用）に応じた有利・不利差異の自動判定、 差異の分解（価格差異・数量差異）、重要度ランキング、根本原因の仮説提示を行う。 CSVデータのアップロードによる自動分析に対応。

Use when: 予算と実績の比較分析を行いたいとき。月次・四半期の予実管理レポート作成、 差異の原因分析、経営会議向けの予実サマリ作成に使用。

Triggers: “予実差異”, “予算実績”, “budget variance”, “budget vs actual”, “予算対比”, “差異分析”, “variance analysis”

No API Required

Download Skill Package (.skill) View Source on GitHub

Table of Contents

1. Overview

Analyzes the differences between budgeted and actual figures, identifying favorable and unfavorable variances with account-type awareness. Provides materiality ranking, root cause hypotheses, and actionable recommendations for management decision-making.

2. Prerequisites

Before running this skill, ensure the following data is available:

  • Budget Data: Approved budget figures by account (CSV or manual input)
  • Actual Data: Actual performance figures for the same period
  • Account Classification: Each account must be classified as revenue or cost/expense
  • Period Information: Target analysis period (month, quarter, or year)

Required CSV Format 

account_name,account_type,budget,actual
Sales Revenue,revenue,1000000,1200000
Material Cost,cost,400000,380000
Labor Cost,cost,300000,320000

Required Columns: | Column | Type | Description | |——–|——|————-| | account_name | string | Account or line item name | | account_type | string | revenue or cost (determines favorable/unfavorable logic) | | budget | numeric | Budgeted amount | | actual | numeric | Actual amount |

3. Quick Start

  1. Validate Input Format: Verify CSV structure and required columns are present
  2. Classify Accounts: Confirm account type assignments (revenue vs. cost/expense)
  3. Period Alignment: Ensure budget and actual figures correspond to the same period
  4. Data Cleansing: Handle missing values, zero budgets, and currency formatting

4. How It Works

  1. Validate Input Format: Verify CSV structure and required columns are present
  2. Classify Accounts: Confirm account type assignments (revenue vs. cost/expense)
  3. Period Alignment: Ensure budget and actual figures correspond to the same period
  4. Data Cleansing: Handle missing values, zero budgets, and currency formatting

5. Usage Examples

  • Monthly/Quarterly Budget Review - Compare actual results against budget to identify significant deviations
  • 「今月の予実差異を分析して」「月次の予算対比レポートを作成して」
  • Management Meeting Preparation - Create executive-level variance summaries with root cause analysis
  • 「経営会議向けに予実サマリを作って」「取締役会用の業績報告資料を準備して」
  • Cost Overrun Investigation - Identify which line items are over budget and why
  • 「コスト超過の原因を特定して」「予算オーバーしている勘定科目を洗い出して」

6. Understanding the Output

The analysis produces a structured variance report containing:

  1. Executive Summary: Total favorable/unfavorable variance, key highlights
  2. Variance Detail Table: Per-account breakdown with amounts, percentages, and direction
  3. Materiality Ranking: Top variances sorted by absolute impact
  4. Root Cause Analysis: Hypotheses and supporting evidence for major variances
  5. Recommended Actions: Prioritized list of corrective/follow-up actions

Output template: assets/variance_report_template_ja.md (Japanese) or assets/variance_report_template_en.md (English)

7. Tips & Best Practices

  • Begin with the smallest realistic sample input so you can validate the workflow before scaling up.
  • Keep skills/ma-budget-actual-variance/SKILL.md open while working; it remains the authoritative source for the full procedure.
  • Review the most relevant reference files first instead of scanning every guide: 第05回_その予算って根拠あるの_20250507.md, 第08回_予算実績差異分析_20250820.md.
  • Preserve intermediate outputs so you can explain assumptions, diffs, and follow-up actions clearly.

8. Combining with Other Skills

  • Combine this skill with adjacent skills in the same category when the work spans planning, implementation, and review.
  • Browse the broader category for neighboring workflows: category index.
  • Use the English skill catalog when you need to chain this workflow into a larger end-to-end process.

9. Troubleshooting

  • Re-check prerequisites first: missing runtime dependencies and unsupported file formats are the most common failures.
  • If a helper script is involved, run it with a minimal sample input before applying it to a full dataset or repository.
  • Compare your input shape against the reference files to confirm expected fields, sections, or metadata are present.

10. Reference

References:

  • skills/ma-budget-actual-variance/references/第05回_その予算って根拠あるの_20250507.md
  • skills/ma-budget-actual-variance/references/第08回_予算実績差異分析_20250820.md