Analyse ABC et Pareto des stocks basée sur Google Sheets
Avancé
Ceci est unMiscellaneous, Multimodal AIworkflow d'automatisation du domainecontenant 17 nœuds.Utilise principalement des nœuds comme If, Code, Filter, GoogleSheets, ManualTrigger. Analyse ABC et Pareto des stocks basée sur Google Sheets pour l'optimisation de la chaîne d'approvisionnement
Prérequis
- •Informations d'identification Google Sheets API
Nœuds utilisés (17)
Catégorie
Aperçu du workflow
Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement
Exporter le workflow
Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow
{
"meta": {
"instanceId": "",
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "dd09796e-b4c4-43df-8401-bba895d330b3",
"name": "Lors du clic sur 'Exécuter le workflow'",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-1056,
-400
],
"parameters": {},
"typeVersion": 1
},
{
"id": "5f502423-b87c-4322-aac6-10d07e685087",
"name": "Obtenir la/les ligne(s) dans la feuille",
"type": "n8n-nodes-base.googleSheets",
"position": [
-832,
-400
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "",
"cachedResultName": "Input Data"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultUrl": "",
"cachedResultName": "Data Analytics"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "",
"name": ""
}
},
"notesInFlow": true,
"typeVersion": 4.7
},
{
"id": "15e8b11a-83d9-41cb-84e4-dbfe0ddf970f",
"name": "Filtrer les ventes nulles",
"type": "n8n-nodes-base.filter",
"position": [
-608,
-400
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "39ce1523-ed7e-404a-82db-099200bcb82c",
"operator": {
"type": "number",
"operation": "notEquals"
},
"leftValue": "={{ $json.QTY }}",
"rightValue": "={{ 0 }}"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "2cd9b9a0-dc4f-4d99-b4c4-43f6d165cad8",
"name": "Transposer",
"type": "n8n-nodes-base.code",
"position": [
-160,
-592
],
"parameters": {
"jsCode": "const input = $input.all().map(i => i.json);\n\n// Collect store IDs\nconst stores = input.map(row => row.STORE);\n// Collect items (from keys)\nconst items = Object.keys(input[0]).filter(k => k !== \"STORE\");\n\n// Transpose\nconst result = items.map(ITEM => {\n let row = { ITEM };\n for (const store of stores) {\n const storeRow = input.find(r => r.STORE === store);\n row[store] = storeRow[ITEM];\n }\n return { json: row };\n});\n\nreturn result;\n"
},
"typeVersion": 2
},
{
"id": "7bedeb08-f47e-4809-9936-7cdc8a9236d1",
"name": "Ventes quotidiennes par magasin",
"type": "n8n-nodes-base.code",
"position": [
-384,
-304
],
"parameters": {
"jsCode": "const agg = {};\nfor (const {json} of items) {\n const k = `${json.STORE}|${json.DAY}`;\n if (!agg[k]) agg[k] = { STORE: json.STORE, DAY: json.DAY, QTY: 0, TO: 0 };\n agg[k].QTY += Number(json.QTY||0);\n agg[k].TO += Number(json.TO||0);\n}\nreturn Object.values(agg).map(r => ({ json: r }));"
},
"typeVersion": 2
},
{
"id": "b0134581-ef21-4485-bd75-8a5d7f865ad4",
"name": "Si",
"type": "n8n-nodes-base.if",
"position": [
-160,
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],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "59bb6e5b-0765-4812-a842-19a3bc7a0357",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.STORE }}",
"rightValue": "STORE-1"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "95a2efc7-9c7b-4263-aab4-c00bbe902714",
"name": "Ventes Magasin 1",
"type": "n8n-nodes-base.googleSheets",
"position": [
64,
-400
],
"parameters": {
"columns": {
"value": {
"TO": "={{ $json.TO }}",
"DAY": "={{ $json.DAY }}",
"QTY": "={{ $json.QTY }}"
},
"schema": [
{
"id": "DAY",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "DAY",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "QTY",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "QTY",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "TO",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "TO",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 421687347,
"cachedResultUrl": "",
"cachedResultName": "Daily Sales Store 1"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultUrl": "",
"cachedResultName": "Data Analytics"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "",
"name": ""
}
},
"notesInFlow": true,
"typeVersion": 4.7
},
{
"id": "fdffd98a-36ac-425b-861c-b3f738828fe2",
"name": "Ventes Magasin 2",
"type": "n8n-nodes-base.googleSheets",
"position": [
64,
-208
],
"parameters": {
"columns": {
"value": {
"TO": "={{ $json.TO }}",
"DAY": "={{ $json.DAY }}",
"QTY": "={{ $json.QTY }}"
},
"schema": [
{
"id": "DAY",
"type": "string",
"display": true,
"required": false,
"displayName": "DAY",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "QTY",
"type": "string",
"display": true,
"required": false,
"displayName": "QTY",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "TO",
"type": "string",
"display": true,
"required": false,
"displayName": "TO",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 749936247,
"cachedResultUrl": "",
"cachedResultName": "Daily Sales Store 2"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultUrl": "",
"cachedResultName": "Data Analytics"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "",
"name": ""
}
},
"notesInFlow": true,
"typeVersion": 4.7
},
{
"id": "8a3afe9e-d873-4a02-9fb1-45fc9c380601",
"name": "Analyse de Pareto",
"type": "n8n-nodes-base.code",
"position": [
-160,
-784
],
"parameters": {
"jsCode": "// Normalize + sort by turnover (TO) desc\nconst rows = items\n .map(i => ({\n ...i.json,\n TO: Number(i.json.TO || 0), // turnover = QTY x Unit Price\n QTY: Number(i.json.QTY || 0),\n }))\n .sort((a, b) => b.TO - a.TO);\n\nconst n = rows.length;\nconst totalTO = rows.reduce((s, r) => s + r.TO, 0) || 1;\n\nlet cumTO = 0;\nrows.forEach((r, idx) => {\n cumTO += r.TO;\n r.cum_turnover = cumTO; // absolute cumulative TO\n r.cum_share = +(cumTO / totalTO).toFixed(6); // 0..1\n r.sku_rank = idx + 1;\n r.cum_skus = +((idx + 1) / n).toFixed(6); // 0..1\n r.cum_skus_pct = +(r.cum_skus * 100).toFixed(2); // 0..100 for charts\n});\n\n// Return table\nreturn rows.map(r => ({ json: r }));\n\n"
},
"typeVersion": 2
},
{
"id": "e8e1409d-b571-43b8-ae9e-bb8da228cefd",
"name": "TO, QTY GroupBy ITEM",
"type": "n8n-nodes-base.code",
"position": [
-384,
-784
],
"parameters": {
"jsCode": "const agg = {};\nfor (const {json} of items) {\n const ITEM = String(json.ITEM);\n const TO = Number(json.TO);\n const QTY = Number(json.QTY);\n if (!agg[ITEM]) agg[ITEM] = { ITEM, TO: 0, QTY: 0 };\n agg[ITEM].TO += TO;\n agg[ITEM].QTY += QTY;\n}\nconst rows = Object.values(agg).sort((a,b)=> b.TO - a.TO);\nreturn rows.map(r => ({ json: r }));"
},
"typeVersion": 2
},
{
"id": "9e02d5cb-701d-4a40-b2bf-c2fae43af8ef",
"name": "TO GroupBy (STORE, ITEM)",
"type": "n8n-nodes-base.code",
"position": [
-384,
-592
],
"parameters": {
"jsCode": "// Build dictionaries of unique stores & skus\nconst stores = new Set();\nconst skus = new Set();\n// Append dictionnaries with values\nfor (const {json} of items) { stores.add(json.STORE); skus.add(json.ITEM); }\n// List of Unique SKU\nconst skuList = Array.from(skus).sort();\n\n// Accumulate sums\nconst mat = {}; // store_id -> sku -> sum\nfor (const {json} of items) {\n const s = json.STORE;\n const k = json.ITEM;\n const v = Number(json.TO) || 0;\n if (!mat[s]) mat[s] = {};\n mat[s][k] = (mat[s][k] || 0) + v;\n}\n\n// Output wide rows with 0 fill\nconst rows = [];\nfor (const s of Array.from(stores).sort()) {\n const row = { STORE: s };\n for (const k of skuList) row[k] = mat[s][k] || 0;\n rows.push(row);\n}\nreturn rows.map(r => ({ json: r }));\n"
},
"typeVersion": 2
},
{
"id": "efe6f052-ff5d-4755-ae07-4a7bc480ddbb",
"name": "Ventes multi-magasins",
"type": "n8n-nodes-base.googleSheets",
"position": [
64,
-592
],
"parameters": {
"columns": {
"value": {
"TO": "={{ $json.TO }}",
"DAY": "={{ $json.DAY }}",
"QTY": "={{ $json.QTY }}"
},
"schema": [
{
"id": "DAY",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "DAY",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "QTY",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "QTY",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "TO",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "TO",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 421687347,
"cachedResultUrl": "",
"cachedResultName": "Daily Sales Store 1"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultUrl": "",
"cachedResultName": "Data Analytics"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "",
"name": ""
}
},
"notesInFlow": true,
"typeVersion": 4.7
},
{
"id": "5bd88834-9c20-4d9e-bd31-146dc31e2c18",
"name": "Variabilité de la demande x % des ventes",
"type": "n8n-nodes-base.code",
"position": [
-384,
-16
],
"parameters": {
"jsCode": "// INPUT items: rows with fields ITEM, DAY, QTY (others optional)\n\nfunction mean(a){ return a.reduce((s,x)=>s + x, 0) / (a.length || 1); }\nfunction stdev_samp(a){\n if (a.length <= 1) return 0;\n const m = mean(a);\n const v = a.reduce((s,x)=> s + (x - m) ** 2, 0) / (a.length - 1);\n return Math.sqrt(v);\n}\n\n// 1) build daily series per ITEM (sum across stores)\nconst series = {}; // ITEM -> { day -> qty_sum }\nlet totalQty = 0;\n\nfor (const { json } of items) {\n const item = String(json.ITEM);\n const day = String(json.DAY);\n const qty = Number(json.QTY || 0);\n\n if (!series[item]) series[item] = {};\n series[item][day] = (series[item][day] || 0) + qty;\n totalQty += qty;\n}\n\n// 2) compute metrics per ITEM\nconst out = [];\nfor (const [item, dayMap] of Object.entries(series)) {\n const daily = Object.values(dayMap); // array of daily qty\n const qty_total = daily.reduce((s,x)=>s+x, 0);\n const m = mean(daily);\n const sd = stdev_samp(daily);\n const cv = m ? sd / m : null;\n const share_qty_pct = totalQty ? (qty_total / totalQty) * 100 : 0;\n\n out.push({\n ITEM: item,\n qty_total,\n share_qty_pct: Number(share_qty_pct.toFixed(2)),\n mean_qty: Number(m.toFixed(3)),\n std_qty: Number(sd.toFixed(3)),\n cv_qty: cv == null ? null : Number(cv.toFixed(3)),\n });\n}\n\n// Optional: sort by share desc\nout.sort((a,b) => b.share_qty_pct - a.share_qty_pct);\n\n// Return as n8n items\nreturn out.map(r => ({ json: r }));\n"
},
"typeVersion": 2
},
{
"id": "805e6a80-bb24-446e-ab9c-a0e0c68f555a",
"name": "Analyse ABC XYZ",
"type": "n8n-nodes-base.googleSheets",
"position": [
64,
-16
],
"parameters": {
"columns": {
"value": {
"ABC": "={{ $json.ABC }}",
"ITEM": "={{ $json.ITEM }}",
"cv_qty": "={{ $json.cv_qty }}",
"std_qty": "={{ $json.std_qty }}",
"mean_qty": "={{ $json.mean_qty }}",
"cum_share": "={{ $json.cum_share }}",
"qty_total": "={{ $json.qty_total }}",
"share_qty_pct": "={{ $json.share_qty_pct }}"
},
"schema": [
{
"id": "ITEM",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "ITEM",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "qty_total",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "qty_total",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "share_qty_pct",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "share_qty_pct",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "cv_qty",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "cv_qty",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "ABC",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "ABC",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "mean_qty",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "mean_qty",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "std_qty",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "std_qty",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "cum_share",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "cum_share",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "limit_cov",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "limit_cov",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {
"useAppend": false
},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 1281688243,
"cachedResultUrl": "",
"cachedResultName": "ABC XYZ"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultUrl": "",
"cachedResultName": "Data Analytics"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "",
"name": ""
}
},
"notesInFlow": true,
"typeVersion": 4.7
},
{
"id": "fb1b23cb-cad9-4a75-bb41-5d87209b51c5",
"name": "Mettre à jour la feuille Pareto",
"type": "n8n-nodes-base.googleSheets",
"position": [
64,
-784
],
"parameters": {
"columns": {
"value": {
"TO": "={{ $json.TO }}",
"QTY": "={{ $json.QTY }}",
"ITEM": "={{ $json.ITEM }}",
"cum_skus": "={{ $json.cum_skus }}",
"sku_rank": "={{ $json.sku_rank }}",
"cum_share": "={{ $json.cum_share }}",
"cum_skus_pct": "={{ $json.cum_skus_pct }}",
"cum_turnover": "={{ $json.cum_turnover }}"
},
"schema": [
{
"id": "ITEM",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "ITEM",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "TO",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "TO",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "QTY",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "QTY",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "cum_turnover",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "cum_turnover",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "cum_share",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "cum_share",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "sku_rank",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "sku_rank",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "cum_skus",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "cum_skus",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "cum_skus_pct",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "cum_skus_pct",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 1760689869,
"cachedResultUrl": "",
"cachedResultName": "Pareto"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultUrl": "",
"cachedResultName": "Data Analytics"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "",
"name": ""
}
},
"notesInFlow": true,
"typeVersion": 4.7
},
{
"id": "82773b29-a1dc-445c-a8ea-d9c393d36eb4",
"name": "Mappage de classe ABC",
"type": "n8n-nodes-base.code",
"position": [
-160,
-16
],
"parameters": {
"jsCode": "// 1) Extract and sort by sales contribution\nlet rows = items.map(i => i.json);\nrows.sort((a, b) => b.share_qty_pct - a.share_qty_pct);\n\n// 2) Compute cumulative contribution\nlet cum = 0;\nfor (let r of rows) {\n cum += r.share_qty_pct;\n\n // 3) Assign class based on cumulative %\n if (cum <= 5) {\n r.ABC = 'A'; // top 5%\n } else if (cum <= 20) {\n r.ABC = 'B'; // next 15%\n } else {\n r.ABC = 'C'; // rest\n }\n\n r.cum_share = Number(cum.toFixed(2));\n}\n\n// 4) Return enriched rows\nreturn rows.map(r => ({ json: r }));\n"
},
"typeVersion": 2
},
{
"id": "21867671-78aa-4580-b51f-53c34f6a1dfa",
"name": "Note adhésive2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1166,
-784
],
"parameters": {
"color": 7,
"width": 540,
"height": 544,
"content": "### Trigger the workflow\nThis starts by collecting the transactional sales from the spreadsheet `Input Data` from the Google Sheet.\n\n#### How to setup?\n\n- **Load records in the Google Sheet Node**:\n 1. Add your Google Sheet API credentials to access the Google Sheet file\n 2. Select the file using the list, an URL or an ID\n 3. Select the sheet `Input Data`\nination**, **distance**, **duration**, **n_steps**\n [Learn more about the Google Sheet Node](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.googlesheets)\n"
},
"typeVersion": 1
}
],
"pinData": {},
"connections": {
"b0134581-ef21-4485-bd75-8a5d7f865ad4": {
"main": [
[
{
"node": "95a2efc7-9c7b-4263-aab4-c00bbe902714",
"type": "main",
"index": 0
}
],
[
{
"node": "fdffd98a-36ac-425b-861c-b3f738828fe2",
"type": "main",
"index": 0
}
]
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}Foire aux questions
Comment utiliser ce workflow ?
Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.
Dans quelles scénarios ce workflow est-il adapté ?
Avancé - Divers, IA Multimodale
Est-ce payant ?
Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.
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Description de la difficulté
Auteur
Samir Saci
@samirsaciAutomation, AI and Analytics for Supply Chain & Business Optimization Helping businesses streamline operations using n8n, AI agents, and data science to enhance efficiency and sustainability. Linkedin: www.linkedin.com/in/samir-saci
Liens externes
Voir sur n8n.io →
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