This repository contains a lightweight Excel-based demand forecasting model designed to compare multiple forecasting methods and explicitly track forecast error.
The purpose of this model is to make common forecasting logic transparent and inspectable, rather than hidden behind software interfaces or black-box tools.
It is not intended to replace an ERP or advanced forecasting system, but to clarify how such systems estimate demand and evaluate forecast performance under the hood.
The model is intended to support understanding and discussion of forecasting behavior by illustrating how different approaches perform under real-world demand variability.
It emphasizes transparency, interpretability, and traceability of calculations over algorithmic sophistication.
The workbook provides:
- Multiple demand forecasting methods
- Explicit forecast error calculation and comparison
- Clear separation between:
- Input data
- Forecast outputs
- Error metrics
- A reference sheet explaining assumptions, formulas, and methodology
This model is intended for:
- Educational purposes
- Scenario analysis
- Comparing forecasting approaches
- Explaining forecasting and error-measurement logic
- Supporting planning and process discussions
It is not intended to replace an ERP system, forecasting platform, or automated planning tool. Most production systems perform these calculations internally; this model exists to make those calculations visible and understandable.
- The model is not automated or optimized for large-scale production use.
- Results depend on the quality and representativeness of historical demand data.
- External drivers such as promotions, policy changes, or supply disruptions are not explicitly modeled.
- The model assumes stable demand-generating processes over the historical window.
This project complements an inventory planning model that translates demand uncertainty into inventory policy decisions.