Overview
This spreadsheet model was built to support ecommerce teams in forecasting demand for new product launches without historical sales data. The tool allows for more confident inventory planning and alignment across teams by offering multiple forecasting methods in one easy-to-use workbook.
It includes five forecast models commonly used in ecommerce and product planning:
- Analogous Forecast: Based on sales trends from similar SKUs or categories
- Ratio Forecast: Anchored to existing product performance with a defined relationship
- S-Curve Forecast: Captures typical adoption and ramp-up patterns
- Sales Input Forecast: Combines projections from sales, marketing, and product for a consensus view
- Composite Forecast: Averages or weights inputs across the models for a final, blended estimate
Each method includes clear inputs, logic breakdowns, and visual summaries to help non-technical stakeholders interpret and align around projections.
Challenges
Forecasting new products is inherently difficult due to lack of baseline performance data. This model was designed to overcome several common issues:
No sales history to build a reliable forecast
Misalignment between sales, marketing, and product expectations
Overreliance on best guesses rather than structured methods
Difficulty comparing forecasting approaches side by side in a single tool
The spreadsheet needed to be flexible, transparent, and lightweight enough for small teams to use without expensive planning software.
Results
The result is a flexible and transparent forecasting tool that enables better decision-making during product launch planning:
Multiple forecast types built into a single, unified model
Designed for alignment between teams before inventory commitments
Lightweight enough to integrate with existing planning templates or tools
This project reflects my ability to build practical forecasting models, align stakeholders, and improve planning accuracy even in data-scarce situations.