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Built a Python and Streamlit analytics platform for EthioChicken to track chick mortality, vaccination compliance, agent performance, and regional distribution, helping identify operational risks and performance patterns.

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ETHIOCHICKEN ANALYTICS & SUPPLY CHAIN INTELLIGENCE PLATFORM

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DESCRIPTION

An end-to-end data platform, statistical modeling suite, and interactive Streamlit web application built to optimize poultry distribution logistics, monitor chick mortality risks, track vaccination compliance, and segment agent performance across regional supply chains.

THE PROBLEM

Poultry distribution networks face severe operational inefficiencies, notably elevated early-stage chick mortality rates averaging 6.65% across 4,196 analyzed cycles. Specifically, "New" tier agents experience critical mortality spikes reaching 12.26%, driven by onboarding gaps and inconsistent vaccination compliance (which averages 85.44% globally). Furthermore, regional credit risks manifested by high Days Sales Outstanding (DSO averaging 14.7 days) and manual tracking bottlenecks hinder proactive supply chain management and field intervention.

THE SOLUTION

This platform delivers a comprehensive data science and analytics solution that:

  • Automates data ingestion, cleaning, and metric calculation for over 1.16M distributed chicks.
  • Deploys L2-Regularized Logistic Regression and XGBoost models to predict high-mortality risk orders exceeding the 10% threshold.
  • Applies unsupervised K-Means clustering (k=4) to segment agents by behavioral and performance profiles.
  • Provides an interactive Streamlit operational dashboard for real-time risk monitoring, regional filtering, and agent tier evaluation.

TECH STACK

  • Core Language: Python 3.10+
  • Data Manipulation & Processing: Pandas, NumPy
  • Machine Learning & Statistics: Scikit-Learn (Logistic Regression, KMeans, StandardScaler), XGBoost, Statsmodels (OLS Regression), SciPy (ANOVA, Kruskal-Wallis)
  • Visualization & Dashboarding: Streamlit, Plotly, Seaborn, Matplotlib
  • Environment Management: Local venv with pip dependency control

RECOMMENDATIONS FOR IMPLEMENTATION

  1. Prioritize Onboarding Mentorship: Implement targeted brooding mentorship and field support for "New" tier agents to mitigate their elevated 12.26% mortality rate.
  2. Automate Compliance Enforcement: Leverage the confirmed inverse relationship between vaccination compliance and mortality outcomes by integrating automated compliance tracking alerts into agent workflows.
  3. Tighten Credit & Financial Controls: Address elevated Days Sales Outstanding (DSO) in high-risk regions by introducing stricter payment terms or integrated digital micro-finance workflows.

DEVELOPED BY

Aklilu Abera | Data Analyst

About

Built a Python and Streamlit analytics platform for EthioChicken to track chick mortality, vaccination compliance, agent performance, and regional distribution, helping identify operational risks and performance patterns.

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