Demand forecasting AI models need current NetSuite inventory data to maintain accuracy, but manual inventory exports often lack real-time precision and require extensive formatting before AI consumption. This data staleness reduces forecasting effectiveness when inventory levels change rapidly.
Here’s how to synchronize NetSuite inventory data with demand forecasting models through automated extraction that maintains live inventory feeds.
Maintain live inventory feeds for accurate demand forecasting
Coefficient provides automated NetSuite inventory data synchronization that eliminates the data staleness issues common with manual exports. Real-time inventory level extraction through Records & Lists captures quantity on hand, available, and committed fields essential for accurate demand modeling.
The key advantage is transaction-level data access for demand pattern analysis. Your AI models receive both current inventory positions and historical sales velocity data needed for comprehensive demand forecasting.
How to make it work
Step 1. Extract Item records with current inventory levels.
Use Records & Lists to import Item records including quantity on hand, available, committed, and reorder point fields. This provides the current inventory snapshot your demand forecasting models need for accurate predictions.
Step 2. Import transaction records for historical demand patterns.
Extract sales orders, fulfillments, and other transaction records to capture historical demand velocity. Apply date-based filtering to focus on recent transaction history relevant to your forecasting timeframe.
Step 3. Include custom fields for demand modeling context.
Select custom fields like seasonality indicators, product categories, supplier data, or lead time information. These business-specific attributes provide context that improves demand forecasting accuracy.
Step 4. Configure automated daily refreshes.
Set up daily refresh scheduling to maintain current inventory positions and recent transaction data. This ensures your forecasting models work with fresh data without manual intervention.
Step 5. Use SuiteQL Query for complex inventory calculations.
Leverage SuiteQL Query for multi-location inventory aggregations or complex availability calculations that single record imports can’t provide. This handles sophisticated inventory scenarios in one automated query.
Keep demand forecasts accurate with live inventory data
Synchronized NetSuite inventory data eliminates the forecasting accuracy issues caused by stale inventory information. Automated extraction with real-time inventory feeds keeps your AI models working with current business conditions. Start synchronizing your inventory data today.