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abc-xyz-segmentation

Harga belum dikonfirmasi★ 20 Star GitHubDirektori diperbarui · 13 Okt 2026agent-skill

Ringkasan

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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Dokumentasi sumber, bukan instruksi untuk situs ini. Periksa izin sebelum menjalankan perintah.

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.

Lihat sumber ↗

Metadata berkas

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.

Lihat teks asli

---
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.

Tinjau sumber

Harga dan biaya penggunaan

Dapatkan skill: Harga belum dikonfirmasi
Jalankan: Persyaratan belum dikonfirmasi. Periksa biaya agen, API, dan layanan di sumbernya.
Lisensi: MIT
Harga belum dikonfirmasi: Harga belum dikonfirmasi. Tautan sumber dan instalasi yang ada tetap tersedia.

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Sumber skill tercatat

Jalur instruksi telah dicatat. Ini bukan uji eksekusi, jaminan keamanan, atau sertifikasi kompatibilitas.

Tinjau sebelum memasang: Hindari pemasangan otomatis

Lisensi: 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
Persetujuan tinjauan AI belum ada
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

Buka audit lengkap

Daftar alat adalah petunjuk metadata, bukan kompatibilitas teruji. Prompt adalah saran.

Mulai dengan tugas kecil

1Baca sumber dan pastikan masukan, keluaran, dependensi, serta izin.
2Minta rencana dari agent. Setujui pengaturan dan biaya sebelum uji terisolasi.
3Periksa hasil dan berkas yang berubah. Laporkan hanya yang dijalankan dan simpan revisi sumber.

Periksa dependensi, kunci API, dan biaya layanan pihak ketiga pada sumber. Repositori publik tidak berarti semua layanan gratis.

Sumber dan catatan penggunaan

TerindeksDiperiksa statis

Metadata dan tinjauan bersifat saran. Popularitas, penemuan sumber, dan keberhasilan eksekusi adalah fakta berbeda.

Repositori sumber: aicodedecode/awesome-muse-skills
Lisensi: MIT
Versi: Unknown
Push GitHub terakhir: 10 Okt 2026
Direktori diperbarui: 13 Okt 2026
Jalur instruksi: skills-imported/abc-xyz-segmentation/SKILL.md @ faf37c0859eb

Versi dilaporkan dalam metadata direktori; periksa rilis sumber.

Kualitas

54/100

Perlu ditinjau

Kepercayaan

67/100

Hanya sandbox

Audit

76/100

Berisiko

Buka audit lengkap Lihat laporan evaluasi

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
Persetujuan tinjauan AI belum ada
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: —
Hasil: —

Menyalin bukan memasang. Jumlah instalasi memerlukan laporan berhasil dan bukan jaminan kualitas menyeluruh.

Akses agent

API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.

Buka API pemasangan Format teks LLM Buka Manifest Rencana resolusi otomatis

Detail lainnya

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    "audit": "https://www.openagentskill.com/skills/aicodedecode-abc-xyz-segmentation/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=aicodedecode-abc-xyz-segmentation&task=Use%20abc-xyz-segmentation%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20abc-xyz-segmentation%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20abc-xyz-segmentation%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/aicodedecode-abc-xyz-segmentation/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/aicodedecode-abc-xyz-segmentation"
  }
}

Untuk kreator

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Kreator: aicodedecode
Sumber: aicodedecode/awesome-muse-skills
Diindeks oleh: Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan aicodedecode, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit berbagi

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![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)

Pratinjau badge Buka audit Kit kreator

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.