Forecasting ingredient demand based on trends

Purpose

1.1. Automate forecasting of ingredient demand for Anhui cuisine restaurants by analyzing sales trends, seasonal changes, event calendars, and external signals to optimize inventory procurement, reduce waste, and prevent supply shortages.
1.2. Integrate multiple data sources — POS, reservations, past purchasing, and market data — to create near real-time demand prediction for perishable and non-perishable inventory items.
1.3. Support data-driven decision-making for efficient restocking, supplier negotiation, and cost control.

Trigger Conditions

2.1. New sales data entry or POS transaction processed.
2.2. A scheduled interval (e.g., daily, weekly, monthly forecasting).
2.3. Receipt of market price changes for key ingredients.
2.4. Significant event updates (holidays, festivals, or local happenings).
2.5. Adjustment in menu offerings or planned promotions.

Platform Variants (with function/API)

3.1. Microsoft Power BI
 • API: Dataflow refresh; analyze sales/stock, output forecast model results
3.2. Google Sheets
 • Feature: IMPORTDATA, GOOGLEFINANCE for price feeds, custom script for forecast
3.3. AWS Lambda
 • API: Trigger ML model (Amazon SageMaker), automate forecast result writing
3.4. Zapier
 • Trigger: New row in sheets; Action: webhook to forecasting engine
3.5. Salesforce
 • Feature: Einstein Analytics; setting for predictive inventory dashboard
3.6. Tableau
 • API: Tableau Prep Flow, schedule refresh and visual notification
3.7. SAP Integrated Business Planning (IBP)
 • API: Forecasting API, Inventory Optimization
3.8. Oracle Netsuite
 • Feature: Saved Search + SuiteScript for auto-forecast
3.9. IBM Watson Studio
 • API: AutoAI pipeline scheduling, ingredient prediction project
3.10. QuickBooks Online
 • API: report snapshot to trigger forecasts via external service
3.11. Snowflake
 • Feature: Stream on table, run SQL-based predictive analytics
3.12. Airtable
 • Feature: Automation triggers on update, Scripting block for demand calculation
3.13. Shopify
 • API: Inventory Level Webhook, past order analysis
3.14. Google BigQuery
 • Feature: Scheduled Query for trend extraction
3.15. Smartsheet
 • Feature: Cell-link updates, cell-change workflow triggers
3.16. Monday.com
 • Feature: Board automation on purchase logs, integration recipes
3.17. Microsoft Dynamics 365
 • Feature: Demand Forecasting module, auto-generate purchase suggestions
3.18. Jotform
 • Feature: Webhook on supplier forms, update forecast leads
3.19. Slack
 • API: Incoming webhook to post forecast alerts, channel notifications
3.20. Trello
 • Feature: Automation rule on list updates, trigger checklist for procurement
3.21. Square
 • API: POS Item Sales Webhook, supply trend prediction
3.22. Facebook Prophet (open-source)
 • API: Run forecast model via Python/R script trigger
3.23. Freshservice
 • Feature: Workflow on new ticket (supplier inquiry), forecast update
3.24. Azure Machine Learning
 • API: Batch endpoint, send updated features, receive demand output

Benefits

4.1. Supports proactive ordering, preventing shortages or excessive stock.
4.2. Minimizes food waste by matching supply with actual demand patterns.
4.3. Improves financial accuracy through better budget forecasting.
4.4. Reduces manual workload and human risk in procurement cycles.
4.5. Enhances vendor relationships by providing clear, timely order signals.
4.6. Enables competitive menu pricing by tracking ingredient cost trends.
4.7. Facilitates multi-branch coordination for chain restaurants.
4.8. Empowers chefs and managers with data-driven restocking insights.