--- title: Beyond OTIF: Measuring the Hidden Complexity of... description: FIOR (Fator de Impacto Operacional no Recebimento) is a Multi-Criteria Decision Analysis framework that quantifies the operational burden warehouse receiving... canonical: https://daily.dev/posts/beyond-otif-measuring-the-hidden-complexity-of-warehouse-receiving-with-mcda-and-python-vckrttuey twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Beyond OTIF: Measuring the Hidden Complexity of Warehouse Receiving with MCDA and Python | daily.dev og:description: FIOR (Fator de Impacto Operacional no Recebimento) is a Multi-Criteria Decision Analysis framework that quantifies the operational burden warehouse receiving... og:url: https://daily.dev/posts/beyond-otif-measuring-the-hidden-complexity-of-warehouse-receiving-with-mcda-and-python-vckrttuey og:image: https://api.daily.dev/og/posts/vckRttuey.png og:image:alt: Beyond OTIF: Measuring the Hidden Complexity of Warehouse Receiving with MCDA and Python og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Beyond OTIF: Measuring the Hidden Complexity of Warehouse Receiving with MCDA and Python **[Medium](https://daily.dev/sources/medium_js)** · 17 min read · 0 upvotes · 0 comments ## Summary FIOR (Fator de Impacto Operacional no Recebimento) is a Multi-Criteria Decision Analysis framework that quantifies the operational burden warehouse receiving teams absorb beyond standard procedure. Unlike traditional KPIs such as OTIF or Dock-to-Stock that measure outcomes, FIOR scores each receipt across four factors — Urgency (40%), Divergence (30%), Quality (20%), and Environment (10%) — producing a bounded 1.0–5.0 score that classifies receipts into Green, Yellow, or Red complexity zones. Applied to 1,000 real receiving records, the average score was 1.75 (Green), with 814 routine, 183 moderately impacted, and 3 crisis-level receipts. The framework is implemented as a Python package (`fior-analytics` on PyPI) using pandas for batch processing. FIOR is positioned as an explanatory layer over existing KPIs, not a replacement, with future directions including predictive modeling and WMS/ERP integration. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Why DORA Metrics Look Different When AI Is Part of Your Development Workflow](https://daily.dev/posts/why-dora-metrics-look-different-when-ai-is-part-of-your-development-workflow-rmx6rejzb) · DevOps.com · 0 upvotes · 0 comments - [DORA metrics are lying to you and AI is making it worse](https://daily.dev/posts/dora-metrics-are-lying-to-you-and-ai-is-making-it-worse-p5ki14fbt) · LeadDev · 0 upvotes · 0 comments - [DORA’s 2025 research on the impact of AI](https://daily.dev/posts/dora-s-2025-research-on-the-impact-of-ai-rxssp8auu) · Software Engineering Research · 0 upvotes · 0 comments - [Blog: Shipping Code Is Not the Job](https://daily.dev/posts/blog-shipping-code-is-not-the-job-glt1yhy9e) · Wawandco · 2 upvotes · 1 comments --- Tags: [#python](https://daily.dev/tags/python), [#data-analysis](https://daily.dev/tags/data-analysis), [#supply-chain](https://daily.dev/tags/supply-chain), [#pandas](https://daily.dev/tags/pandas) [View this post on daily.dev](https://daily.dev/posts/beyond-otif-measuring-the-hidden-complexity-of-warehouse-receiving-with-mcda-and-python-vckrttuey) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Beyond OTIF: Measuring the Hidden Complexity of Warehouse Receiving with MCDA and Python","url":"https://daily.dev/posts/beyond-otif-measuring-the-hidden-complexity-of-warehouse-receiving-with-mcda-and-python-vckrttuey","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/beyond-otif-measuring-the-hidden-complexity-of-warehouse-receiving-with-mcda-and-python-vckrttuey"},"datePublished":"2026-07-18T00:11:23.324Z","dateModified":"2026-07-18T00:12:21.905Z","description":"FIOR (Fator de Impacto Operacional no Recebimento) is a Multi-Criteria Decision Analysis framework that quantifies the operational burden warehouse receiving...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/576a3f1fe35c4060ffefc10724462fea?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/576a3f1fe35c4060ffefc10724462fea?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Medium","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Medium","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/medium","url":"https://daily.dev/sources/medium_js"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/beyond-otif-measuring-the-hidden-complexity-of-warehouse-receiving-with-mcda-and-python-vckrttuey","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"python,data-analysis,supply-chain,pandas","timeRequired":"PT17M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Medium","item":"https://daily.dev/sources/medium_js"},{"@type":"ListItem","position":3,"name":"Beyond OTIF: Measuring the Hidden Complexity of Warehouse Receiving with MCDA and Python"}]} ```