Real-time OTIF (On-Time-In-Full) SLA monitoring: SQL window functions, PostgreSQL RLS/materialized views, and Power BI + Power Automate event-driven alerting.
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Jul 6, 2026 - Python
Real-time OTIF (On-Time-In-Full) SLA monitoring: SQL window functions, PostgreSQL RLS/materialized views, and Power BI + Power Automate event-driven alerting.
Python portfolio applied to Supply Chain & Operations: OTIF KPI, Inventory ABC/ROP, and report automation (Excel).
Operations analytics that audits its own numbers: OTIF, forecast accuracy, ABC-XYZ and Pareto with a mandatory honesty block. JSON-only, built for AI agents and pipelines.
Creation a logistics and supply chain dashboard for OTIF Analysis
This dashboard was created at the request of the Trading House Director to provide a comprehensive view of business performance.
AI-powered supply chain platform: OTIF Compliance Copilot + Exception Brain. Built with Claude API, Next.js 16, Supabase. UAE/GCC market.
Interactive Excel logistics dashboard tracking OTIF, SLA compliance, delay trends and return rates across 200 shipments — revealing a 42.5% SLA breach rate and 235% increase in delays from January to July.
How honest is your on-time KPI? A five-rung OTIF metric ladder, driver-decomposition charts and a Streamlit explorer for delivery-performance data.
This project contains two PostgreSQL queries used to build widgets for an **OTIF (On-Time In-Full) dashboard**, which helps monitor supplier performance and delivery accuracy across clients and distribution centers.
[1] What if delays are not random - but predictable?
Análise de dados logísticos com o dataset DataCo Smart Supply Chain — OTIF, lead time e taxa de atraso por região, modal e categoria.
Power BI dashboard analyzing OTIF, OT, IF, LIFR and VOFR metrics to improve supply chain service levels and operational performance.
Dashboard Power BI para métricas OTIF (On-Time In-Full). Relatórios executivos e modelo semântico.
End-to-end supply-chain analytics control tower: SKU-level demand forecasting, safety stock & reorder optimization (OR-Tools), OTIF and vendor scorecards. Built with Airflow, dbt, DuckDB, and Streamlit.
Interactive analysis tool that quantifies the full cost of short-shipping orders for a specialty food brand. Eight cost dimensions, adjustable parameters, buffer simulation, and exportable PDF. React + Python.
OTIF blind spot diagnostic — reconciles internal fulfillment metrics against retailer scorecards and quantifies the gap. Python + Dash.
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