R Shiny app for tracking sales, managing stock levels, and generating time series forecasts to support smarter ordering and planning.
Sales and inventory data for footwear were scattered across spreadsheets and files. The team needed one place to view current sales and stock levels, compare performance over time, and get simple forecasts to support ordering and planning.
Manual updates and ad hoc analysis were time-consuming and error-prone — the business needed a self-service tool that non-technical staff could use daily without relying on data analysts for every query.
I built an interactive web application in R Shiny that connects to the sales and inventory data (CSV, Excel, or database). The app includes dashboards for current and historical sales, stock levels by product or category, and key metrics such as units sold, revenue, and stock turnover.
I added time series forecasting using ARIMA and similar methods in R, so that users can see projected demand and use it for restocking decisions. The interface lets users filter by product, date range, and other dimensions — charts and tables update in real time.
The business now has a single, interactive dashboard for sales and inventory, with built-in forecasting to support planning and replenishment. Reporting and ad hoc analysis are faster and more consistent.