Restaurant Food Waste Prediction System
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Automate your restaurant's food waste reduction with an intelligent prediction system. This workflow leverages AI to forecast sales and optimize ingredient procurement, minimizing spoilage and maximizing profitability.
About This Workflow
This n8n workflow provides a powerful solution for restaurants looking to combat food waste and enhance operational efficiency. By automatically fetching historical sales data from Google Sheets, it feeds this information into an advanced AI model. The AI analyzes trends, predicts future sales for dishes, and forecasts optimal raw material usage with a buffer to prevent overstocking. It then calculates the amount of food waste that is being actively reduced. Finally, the system logs these actionable insights back into a dedicated Google Sheet, empowering your team with data-driven decisions to reduce waste, cut costs, and improve sustainability.
Key Features
- Automated Daily Predictions: Runs automatically every night to provide timely forecasts.
- AI-Powered Demand Forecasting: Utilizes AI to predict dish sales and raw material needs.
- Waste Reduction Optimization: Actively calculates and aims to minimize predicted food waste.
- Seamless Data Integration: Connects with Google Sheets for both data input and output.
- Actionable Insights: Delivers clear, structured data for informed decision-making.
How To Use
- Set up a Schedule Trigger: Configure the 'Daily Trigger' node to run at a specific time each day (e.g., 10 PM) to initiate the workflow.
- Connect to Your Sales Data: In the 'Fetch Historical Sales Data' node, link your Google Account and select the specific Google Sheet and sheet tab containing your historical sales and ingredient usage data.
- Format Data for AI: The 'Format Data for AI Forecasting' node automatically prepares your fetched data into the correct structure for the AI model.
- Configure the AI Forecast Generator: In the 'AI Forecast Generator' node, ensure the 'text' parameter is correctly linked to the output of the previous node. Review and customize the
systemMessageto fine-tune the AI's behavior and output format according to your specific restaurant needs. Adjust the AI's analysis period (e.g., 'past 5 days') and buffer percentages if necessary. - Clean and Structure AI Output: The 'Clean & Structure AI Output' node is pre-configured to parse the AI's JSON response. No immediate changes are usually needed here unless the AI output format unexpectedly shifts.
- Log Predictions to Google Sheets: In the 'Log Forecast to Google Sheets' node, connect your Google Account and select the target Google Sheet and the specific sheet tab where you want the predictions and waste reduction figures to be logged. Ensure the column mapping aligns with the AI's output structure.
Apps Used
Workflow JSON
{
"id": "c5087a4a-7960-4acb-b23c-c910fec92d6d",
"name": "Restaurant Food Waste Prediction System",
"nodes": 16,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: c5087a4a-7960...
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