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abc-xyz-segmentation

Price unconfirmed★ 20 GitHub starsRegistry updated · Oct 13, 2026agent-skill

Overview

Segment a SKU portfolio on value (ABC) and demand variability (XYZ), produce the 9-box with a planning policy per cell, and reallocate planner attention accordingly. Use when the user mentions ABC analysis, inventory segmentation, SKU rationalization, stok segmentasyonu, envanter sınıflandırma, or asks which items deserve forecasting effort. Differentiator - ABC alone is treated as half an answer; policy lives in the value x variability combination.

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ABC-XYZ Segmentation

Value tells you where the money is. Variability tells you whether forecasting, buffering or restructuring can work. Never output a classification without the policy consequences.

Required data

Per-SKU demand history (sku, period, qty) covering 12+ periods, plus unit value (unit_price or cost). Without unit value, ABC degrades to a volume ranking - say so and ask for prices before presenting conclusions about money.

Workflow

ABC on annual value. Rank by annual consumption value; cumulative 80% = A, next 15% = B, rest = C. Report the actual concentration found (e.g. "15 SKUs = 80%"), not the folklore 20/80.
XYZ on variability. CV = std/mean of period demand per SKU. Defaults: X < 0.5, Y 0.5-1.0, Z >= 1.0. These are conventions - check the CV histogram for natural breaks and state the thresholds used. SKUs with structural zero periods (intermittent) belong in Z regardless of CV arithmetic; mean-based CV understates their risk.
Build the 9-box with SKU counts AND value share per cell. Value share is what makes managers act.
Attach the policy per cell (adapt wording to context):
- A-X: tight forecasting pays; low buffer, frequent review, automate replenishment
- A-Y: forecast + healthy buffer; investigate variability drivers
- A-Z: do not chase forecasts - strategic buffer, lead-time negotiation, or make-to-order
- B-X / C-X: min-max autopilot; withdraw planner attention
- B-Z: buffer or longer promise dates; check if variability is self-inflicted (promotions, batching)
- C-Z: rationalization shortlist - kill, consolidate, or on-demand sourcing
Name the reallocation. The deliverable is planner-hours and buffer money moving between cells - state explicitly which cells gain and lose attention.
Validate. Sum of cell value shares must equal 100%; spot-check two SKUs' classifications against their raw series before presenting.

Pitfalls to check explicitly

ABC computed on quantity while unit values vary 10x+ ranks the wrong items.
Self-inflicted variability (order batching, month-end pushes, promotions) shows up as Z; flag it as a process fix, not a demand fact.
Classifications rot - recommend re-running quarterly and tracking cell migrations.
A dominant "C-Z is 60% of SKUs" finding usually signals assortment bloat, not a planning problem.

Output format

The 9-box (counts + value share per cell)
Policy table per occupied cell
Attention-reallocation paragraph (from where, to where)
Rationalization shortlist (top C-Z items by holding cost or shelf age, if data allows)

Worked example including a safety-stock stress test: https://github.com/gulmezeren2-byte/abc-xyz-inventory

Source: industrial-engineering-ai-skills by Eren Gulmez (MIT). The full method pack - entry skill, role agents, data-hygiene rules and artifact templates - lives there.

View source ↗

File metadata

name: abc-xyz-segmentation
description: Segment a SKU portfolio on value (ABC) and demand variability (XYZ), produce the 9-box with a planning policy per cell, and reallocate planner attention accordingly. Use when the user mentions ABC analysis, inventory segmentation, SKU rationalization, stok segmentasyonu, envanter sınıflandırma, or asks which items deserve forecasting effort. Differentiator - ABC alone is treated as half an answer; policy lives in the value x variability combination.

View original text

---
name: abc-xyz-segmentation
description: Segment a SKU portfolio on value (ABC) and demand variability (XYZ), produce the 9-box with a planning policy per cell, and reallocate planner attention accordingly. Use when the user mentions ABC analysis, inventory segmentation, SKU rationalization, stok segmentasyonu, envanter sınıflandırma, or asks which items deserve forecasting effort. Differentiator - ABC alone is treated as half an answer; policy lives in the value x variability combination.
---

# ABC-XYZ Segmentation

Value tells you where the money is. Variability tells you whether forecasting, buffering or restructuring can work. Never output a classification without the policy consequences.

## Required data

Per-SKU demand history (`sku`, `period`, `qty`) covering 12+ periods, plus unit value (`unit_price` or cost). Without unit value, ABC degrades to a volume ranking - say so and ask for prices before presenting conclusions about money.

## Workflow

1. **ABC on annual value.** Rank by annual consumption value; cumulative 80% = A, next 15% = B, rest = C. Report the actual concentration found (e.g. "15 SKUs = 80%"), not the folklore 20/80.
2. **XYZ on variability.** CV = std/mean of period demand per SKU. Defaults: X < 0.5, Y 0.5-1.0, Z >= 1.0. These are conventions - check the CV histogram for natural breaks and state the thresholds used. SKUs with structural zero periods (intermittent) belong in Z regardless of CV arithmetic; mean-based CV understates their risk.
3. **Build the 9-box** with SKU counts AND value share per cell. Value share is what makes managers act.
4. **Attach the policy per cell** (adapt wording to context):
- A-X: tight forecasting pays; low buffer, frequent review, automate replenishment
- A-Y: forecast + healthy buffer; investigate variability drivers
- A-Z: do not chase forecasts - strategic buffer, lead-time negotiation, or make-to-order
- B-X / C-X: min-max autopilot; withdraw planner attention
- B-Z: buffer or longer promise dates; check if variability is self-inflicted (promotions, batching)
- C-Z: rationalization shortlist - kill, consolidate, or on-demand sourcing
5. **Name the reallocation.** The deliverable is planner-hours and buffer money moving between cells - state explicitly which cells gain and lose attention.
6. **Validate.** Sum of cell value shares must equal 100%; spot-check two SKUs' classifications against their raw series before presenting.

## Pitfalls to check explicitly

- ABC computed on quantity while unit values vary 10x+ ranks the wrong items.
- Self-inflicted variability (order batching, month-end pushes, promotions) shows up as Z; flag it as a process fix, not a demand fact.
- Classifications rot - recommend re-running quarterly and tracking cell migrations.
- A dominant "C-Z is 60% of SKUs" finding usually signals assortment bloat, not a planning problem.

## Output format

1. The 9-box (counts + value share per cell)
2. Policy table per occupied cell
3. Attention-reallocation paragraph (from where, to where)
4. Rationalization shortlist (top C-Z items by holding cost or shelf age, if data allows)

Worked example including a safety-stock stress test: https://github.com/gulmezeren2-byte/abc-xyz-inventory

---

Source: [industrial-engineering-ai-skills](https://github.com/gulmezeren2-byte/industrial-engineering-ai-skills) by Eren Gulmez (MIT). The full method pack - entry skill, role agents, data-hygiene rules and artifact templates - lives there.

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Review before install: Avoid automatic install

License: MIT

Financial research output is not financial advice; require human review before any live investment decision
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
Low GitHub adoption signal
AI review approval is missing
Financial research output is not financial advice; require human review before any live investment decision.
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
GitHub adoption: 20 GitHub stars
Stars/forks activity: 20 stars, 4 forks; issue activity unavailable in current metadata
Review status: AI review approval is missing

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Source & usage notes

IndexedStatic Checked

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: aicodedecode/awesome-muse-skills
License: MIT
Version: Unknown
Last GitHub push: Oct 10, 2026
Registry updated: Oct 13, 2026
Instruction path: skills-imported/abc-xyz-segmentation/SKILL.md @ faf37c0859eb

Version reported in registry metadata; check source releases before relying on it.

Quality

54/100

Needs review

Trust

67/100

Sandbox only

Audit

76/100

Risky

Open full audit View eval report

Financial research output is not financial advice; require human review before any live investment decision
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
Low GitHub adoption signal
AI review approval is missing
Financial research output is not financial advice; require human review before any live investment decision.
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
GitHub adoption: 20 GitHub stars
Stars/forks activity: 20 stars, 4 forks; issue activity unavailable in current metadata
Review status: AI review approval is missing

Verified installs: —
Outcomes: —

Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.

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More details

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Creator: aicodedecode
Source: aicodedecode/awesome-muse-skills
Indexed by: OpenAgentSkill community index

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[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/aicodedecode-abc-xyz-segmentation?metric=listed&label=Listed)](https://www.openagentskill.com/skills/aicodedecode-abc-xyz-segmentation?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/aicodedecode-abc-xyz-segmentation?metric=trust&label=Trust)](https://www.openagentskill.com/skills/aicodedecode-abc-xyz-segmentation?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/aicodedecode-abc-xyz-segmentation?metric=audit&label=Audit)](https://www.openagentskill.com/skills/aicodedecode-abc-xyz-segmentation/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/aicodedecode-abc-xyz-segmentation?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/aicodedecode-abc-xyz-segmentation?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

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