> For the complete documentation index, see [llms.txt](https://docs.claret.app/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.claret.app/sell/forecast-workbench/quick-start.md). # Quick Start: Forecast Workbench ## What You'll Learn The Forecast Workbench uses statistical models with historical sales data to forecast demand into the future. After this guide, you'll be able to select an Item @ Customer Group combination, review or configure a forecast, run the model, read the output, and apply overrides. ## Before You Begin Your admin should have already: * Set up Items, Customer Groups, and Item @ Customer Groups * Imported historical sales data * Configured Forecast Workbench settings in Application Settings If the page appears empty or models won't run, check with your admin that setup is complete. See [Setting Up Forecast Workbench](/using-claret/getting-started/setting-up-modules/setting-up-forecast-workbench.md) for what's required. {% hint style="info" %} The Forecast Workbench requires historical sales data to generate forecasts. The more history available, the better the model's predictions. {% endhint %} ## Step 1: Access Forecast Workbench Navigate to **Sell > Forecast Workbench** in the left navigation menu.

The Forecast Workbench landing page

## Step 2: Select an Item and Customer Group When you enter the Forecast Workbench, all Items and Customer Groups are listed on the left side of the page. 1. Click on the **Item** you want to forecast 2. Click on the **Customer Group** you want to forecast for 3. The banner at the top will update to show the selected Item @ Customer Group combination

Selecting an Item and Customer Group on the left side of the page

{% hint style="info" %} The Item and Customer Group must be linked as an [Item @ Customer Group](/master-data/item-customer-groups.md) for forecasting to work. {% endhint %} ## Step 3: Review the Forecast Configuration If a forecast has been run previously for this combination, you'll see the existing results. To view or adjust the configuration: 1. Click the **configuration button** (blue icon) in the top-right of the screen 2. Review the settings: * **Timing Interval** — weekly or monthly forecast buckets * **Forecast history start / end** — the date range of historical data used by the model * **Forecast horizon** — how many months into the future to forecast 3. Review the model configuration: * **Auto** — Claret selects the best regression model automatically * **Manual** — you choose the model, missing imputation method, and forecast constraints yourself

The Forecast Workbench configuration panel

## Step 4: Run the Model Once the configuration is set: 1. Click the **Play button** in the top-right corner to run the model 2. Wait for the model to complete — this may take a few seconds depending on the data volume {% hint style="info" %} You need to re-run the model whenever you change the configuration. The model does not re-run automatically. {% endhint %} ## Step 5: Interpret the Results The output has three sections: 1. **The chart** — shows historical data (red) and the forecast projection (blue) over time. Hover over a point to see exact values. 2. **Point detail** — below the chart, shows the precise history and forecast values for whichever point you hover over on the chart. 3. **The data table** — a scrollable table with all values by time period, including any overrides. The area between the "History start" and "History end" markers on the chart highlights the data used to generate the forecast. All available history is shown on the chart, but only the selected range feeds the model.

The Forecast Workbench output — chart, point detail, and data table

## Step 6: Make Overrides (Optional) To adjust the forecast for a specific period: * **By adjustment amount** — enter a value in the "Overrides" field to add to (or subtract from, using a negative number) the forecast * **By target total** — enter a value in the "Total" field and the override amount will be calculated automatically The chart updates to show the adjusted value, with a dotted line indicating the original forecast for comparison.

Entering an override adjusts the forecast value and updates the chart

## Understanding the Data | Column | What It Shows | | ----------------- | ---------------------------------------------------------------------------------- | | **Hist/Forecast** | The original modeled value — history for past periods, forecast for future periods | | **Overrides** | Any manual adjustments applied to the forecast | | **Total** | The final value (forecast + override) | ## Common Questions ### How much historical data do I need? More history generally produces better forecasts. At minimum, you need enough data to cover the patterns in your sales (e.g., at least 12 months to capture seasonal trends). Check with your admin about how much history has been imported. ### What if there are gaps in my sales history? The "Missing Imputation" setting in the model configuration tells Claret how to handle gaps. Options include interpolating missing values or treating them as zero. Check the configuration panel to see what method is being used. ### Can I override the forecast for multiple periods at once? Overrides are entered one period at a time in the data table. Enter your adjustment for each period you want to change. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.claret.app/sell/forecast-workbench/quick-start.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.