End-to-end café inventory project: clean transaction data, build daily item-level demand series, backtest strong baseline forecasters, generate next-30-day demand forecasts, convert forecasts into safety stock + reorder points, and validate policies with Monte Carlo stockout-risk simulations, wrapped in a Streamlit dashboard.

Analyze and propose the plan to monitor and estimate business aspects

Go library for practical inventory and supply-chain threshold calculations.

Local-first inventory reorder radar for small shops using CSV exports.

XGBoost-powered demand forecasting & reorder alert system for e-commerce — flags stockouts before they happen and surfaces cash trapped in overstock. Nightly auto-retraining via GitHub Actions.

Free Business Central extension: Reorder Point calculator = demand during lead time + safety stock, make-to-stock aware.

MIN, OPHQ, and MAX per item, faithful to a real spreadsheet formula and improved with variability-based safety stock, compared on realized service level.

A multidisciplinary Java-based application for calculating economic order quantity (EOQ) and reorder point.

This project provides an in-depth analysis of purchasing data from 2023 to 2024.

Comparing King's Formula vs Weighted average for safety stock | Supply Chain Analytics | Excel

Demand forecasting model and inventory policy simulation built in Excel — using FORECAST.ETS, safety stock calculation and scenario testing to minimize stockouts and reduce reorder frequency by 32%.

Retail demand forecasting and EOQ reorder point dashboard built with Python, Streamlit, Pandas, Plotly, and Scikit-learn.