Logistified 2.2 - Forecasting Reinvented

Forecasting isn't just about predicting sales; it's about confidence. Confidence that you won't stock out during peak season, and confidence that you aren't tying up capital in dead stock. With Logistified 2.2, we are introducing the biggest leap forward in our forecasting technology yet.

The Problem with Manual Forecasting

Historically, merchants had to choose between simple "average sales" models or complex statistical tools that required a data science degree to configure. You had to manually decide if a product was "Seasonal" or "Linear". You had to filter out Black Friday spikes manually. It was tedious, prone to human error, and unscalable for catalogs with thousands of SKUs.

Auto-Mode: Intelligence on Autopilot

Logistified 2.2 introduces Auto-Mode, our new default forecasting engine. It doesn't just guess; it competes. For every single variant in your store, the engine runs a tournament of multiple algorithms (Linear Regression, Holt-Winters, Moving Averages, and Machine Learning models) against your historical data.

It automatically:

• Backtests Models: Checks which model would have most accurately predicted the last 3 months of sales.
• Detects Seasonality: Identifies recurring patterns (e.g., higher sales in Q4 or summer months) without you flagging them.
• Cleans Data: Automatically detects out-of-stock periods and removes those "zero sales" days from the average calculation, ensuring your velocity isn't artificially lowered by supply chain issues.

Unprecedented Parameter Control

While automation is powerful, control is essential. We have expanded the forecasting parameters to give you granular control over how your recommendations are generated.

1. Supplier Reliability & Safety Stock

Not all suppliers are created equal. You can now rate your suppliers or set specific Safety Stock buffers per supplier. If Supplier A is frequently late, Logistified will automatically recommend ordering earlier or holding more stock for their products to mitigate risk.

2. Cost-Based Optimization (EOQ)

We've introduced fields for Holding Costs (storage fees, capital interest) and Order Costs (freight, administrative time). The system can now calculate the Economic Order Quantity (EOQ), finding the mathematical sweet spot between ordering too frequently (high shipping costs) and ordering too much (high storage costs).

3. Lead Time Granularity

Lead times are no longer just global settings. You can override lead times at the Supplier, Brand, or even Variant level. This allows for highly accurate "Reorder Deadlines" for products that might be air-freighted versus sea-freighted.

The New "Views" Architecture

To support this depth of data, we rebuilt the forecasting interface from scratch. The new Views Page allows you to build custom reports similar to a spreadsheet but powered by live data.

• Real-time Filtering: Use complex AND/OR logic (e.g., "Tag is 'Summer' AND Stock is < 50").
• Instant Feedback: Change a forecast parameter and see the "Suggested Order Qty" update instantly without a page reload.
• High Performance: We optimized the rendering engine to handle tables with 10,000+ rows with zero lag.
• Exports: Export your exact current view to CSV or Excel with one click for offline analysis or sharing with stakeholders.