Querri for Demand Forecasting Cut Costs, Reduce Surprises, and Stay Ahead in Logistics
Predicting demand is crucial for logistics success, but traditional methods often miss the mark. Querri helps you forecast demand accurately by analyzing patterns in your data, so you can optimize inventory, reduce costs, and avoid stockouts or overstock situations.
Querri Demand Forecasting Demo
See how Querri transforms your logistics operations with AI-powered demand forecasting. Watch as we predict demand patterns, optimize inventory levels, and help you stay ahead of market changes.
What Makes Logistics Forecasting So Hard?
Demand forecasting in logistics is notoriously difficult. Seasonal patterns, market changes, supply chain disruptions, and customer behavior shifts all impact demand unpredictably. Traditional spreadsheet-based forecasting often relies on outdated data and simple trend analysis, leading to costly mistakes like overstocking slow-moving items or running out of high-demand products.
Without accurate forecasting, you face increased carrying costs, stockouts that disappoint customers, and missed opportunities to optimize your supply chain efficiency.
Forecasting with Querri Makes It Easier to Act Early
Querri transforms your historical sales data, inventory levels, and market indicators into actionable demand forecasts. Simply upload your data and ask questions like "What's my expected demand next month by SKU and region?"
Querri analyzes patterns across multiple variables—seasonality, trends, external factors—and provides forecasts with confidence intervals. You can drill down by product category, geographic region, or time period to make informed decisions about inventory planning and resource allocation.
The AI-powered insights help you identify demand spikes before they happen, optimize stock levels, and reduce both carrying costs and stockout risks.
Business Outcomes of Better Forecasting
Accurate Demand Predictions with Confidence Intervals
Reduced Inventory Carrying Costs by 25-40%
Minimized Stockouts and Lost Sales
Optimized Supply Chain Resource Allocation
Early Warning System for Demand Spikes
How-To in Five Simple Steps
Connect Your Data Sources
Upload sales history, inventory data, seasonal patterns, and any external factors that might influence demand
Define Your Forecasting Scope
Specify what you want to forecast—by product, region, time period, or customer segment
Ask Forecasting Questions
Use prompts like: "What's the expected demand for Product X next quarter?" "Which regions will see the highest growth in Q4?" "Should I increase inventory for the holiday season?" "What's the risk of stockout for our top 10 SKUs?"
Review Forecasts and Confidence Levels
Examine the predictions, confidence intervals, and underlying factors driving the forecast
Take Action and Monitor
Adjust inventory, production, or procurement based on forecasts and track accuracy over time
Best Practices
Include Multiple Data Sources
Combine sales data with external factors like seasonality, promotions, market trends, and economic indicators for more accurate forecasts.
Forecast at the Right Granularity
Start with high-level forecasts, then drill down to specific products or regions. Too much detail can introduce noise, while too little can miss important patterns.
Account for Lead Times
Factor in supplier lead times and production cycles when planning inventory adjustments based on demand forecasts.
Regularly Update and Refine
Review forecast accuracy monthly and adjust your models. Market conditions change, and your forecasting approach should evolve with them.
FAQs
How far into the future can Querri forecast demand?
What if I don't have much historical data?
Can Querri handle seasonal products or irregular demand patterns?
How does Querri handle new products with no sales history?
Can I get forecasts for specific customer segments or regions?
How accurate are Querri's demand forecasts?
