Generate a Top-Down Forecast

Learn how to create a top-down demand forecast by converting revenue goals into SKU-level unit projections for inventory and supply chain planning.

The Top-Down approach allows you to enter your sales revenue goals and automatically convert them into a detailed unit forecast at the channel and SKU level.


Steps to Generate a Top-Down Forecast

  1. On the scenario plan flow, select the Use AI Forecast Models button.

  2. This reveals options for both Top-Down and Bottom-Up approaches. Select the Top-Down approach.

  3. Within the flyout, enter your sales goals for your channels based on the given months you've entered.

  1. Click the Generate Forecast button to transform your gross sales into unit sales projections. The planning page table will automatically update to display the converted data.


Available Top-Down Models

Bombay
New York (Coming Soon)

Model Type

Probabilistic

One-Shot

Cost / Compute

$

$$$

Forecast Method

Top-down

Top-down

Outcomes

Sales goals defined for the business

First one-shot forecasting model

Business Type

Fast-growing

Enterprise

Bombay

Bombay is designed to convert projected revenue forecasts into unit sales forecasts, enabling more accurate planning. This model is particularly useful for businesses where forecasts are often made in revenue terms, but operational planning requires forecasts in physical units.

This model is optimized for:

  • Businesses that forecast in revenue but need unit-level planning

  • Inventory and supply chain teams requiring unit sales estimates

  • Product lines with stable or predictable price-per-unit relationships

  • Scenarios where price data is available to translate revenue into units

Example Use Case:

If a skincare company expects to make $50,000 in sales and each skincare kit sells for $50, the model predicts they will need to prepare for 10,000 kits. This helps the company know how many toners, cleansers, and moisturizers to buy in advance.


How It Works

Moselle's Top-Down forecasting uses several advanced techniques to accurately translate revenue targets into unit projections:

Average Selling Price (ASP)

We use Average Selling Price (ASP) rather than MSRP (Manufacturer's Suggested Retail Price) to convert revenue into units. ASP reflects what customers are actually paying after discounts, promotions, and markdowns—giving you a more accurate forecast based on real market conditions.

For example, if a product has an MSRP of $99.99 but typically sells for $79.99 after promotions, using ASP ensures your unit projections reflect actual sales patterns rather than theoretical pricing.

Real-Time Currency Conversion

When your revenue targets are set in one currency but your sales channels operate in another, Moselle uses real-time market FX rates to adjust projections automatically. This ensures accurate revenue-to-unit conversions across international channels without manual currency calculations.

Probabilistic SKU Distribution

Starting from a total revenue target, Moselle uses probabilistic modeling to determine how revenue should be distributed down to the channel and SKU level. This approach analyzes historical sales patterns, product relationships, and channel performance to create realistic unit projections across your entire catalog.

AI-Generated SKU Grading

To further enhance revenue distribution, Moselle applies AI-generated SKU grading to your product catalog. This grading system evaluates each SKU's historical performance, seasonality, and market positioning to intelligently allocate revenue across products—ensuring top performers receive appropriate forecast weight while accounting for tail products.


Adjust Your Top-Down Forecast

  1. Select the Gear Icon found in the top right corner, choose Modify Forecast.

  2. Click Adjust Revenue Targets.

  3. A flyout will appear, where you can adjust and edit your revenue forecast by clicking into each cell or pasting your values into each cell.

  4. Click Regenerate Forecast, found on the bottom right of the flyout.


Known Limitations

  • Directional forecasts: All forecasts generated in Moselle are directional and should be refined using Mo to incorporate business context.

  • Price and currency volatility: Significant price changes or currency fluctuations may reduce model accuracy. Regenerate forecasts after major pricing or FX adjustments.

  • Incomplete product data: Missing unit prices or limited sales history may prevent certain SKUs from being forecast. Ensure the product catalog is current and complete before generating a forecast.

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