Demand Forecasting

Forecasts feed anticipated future demand into the MRP engine so planning looks beyond firm orders. A forecast behaves like demand of type Forecast in the netting calculation, letting SDI warn you about shortages for demand that hasn't been booked yet.

Where to Access

• Forecasts — /mfi/forecasts (also from the SDI Dashboard → Demand Sources → Forecasts).

The page has three tabs: Forecasts, Batches, and Accuracy.

Forecasts tab

A list of individual forecast records — Item, Location, Qty Required, UOM, Date Required, Status, Created. Filter by Item, Location, or Status. You can edit or delete a record, or select rows for bulk delete.

Creating forecasts

Click Create Forecast and pick a method:

From Historical Sales

Generate forecasts by projecting a source period of past sales onto a target period. Options:

• Period type — Daily, Weekly, or Monthly buckets.
• Multiplier — scale the projection up or down (e.g., 1.1 for expected 10% growth).
• Use seasonality — shape the forecast using historical seasonal patterns.
• Use trend — extend an observed growth/decline trend.
• Items / Location — limit to specific items and a location.

Quick-pick helpers set common source→target pairs (last month, last year's same month, last year's matching quarter) targeting next month or next quarter. You can preview the generated quantities before committing.

Period Forecast

Enter a known total demand for a period and distribute it across buckets using a distribution:

• Even — spread equally.
• Front Loaded (60/40) — heavier early.
• Back Loaded (40/60) — heavier late.
• Seasonal — follow historical seasonal patterns.

Manual Entry

Create a single forecast record: item, location (optional), quantity, date required, and notes.

Bulk Import

Add many forecast rows at once in a table — item, location, quantity, and date per row — and create them together.

Batches tab

Every generation run is recorded as a batch so it can be reviewed or undone as a unit. Each batch shows Name, Type (Historical / Period), Target Period, Period Type, forecast count, Total Qty, and Created date. You can:

• Delete batch only — keep the generated forecasts, remove the batch record.
• Delete batch and forecasts — remove both together.

Accuracy tab

Once actual demand has materialized, click Calculate Accuracy to score forecast quality.

Summary metrics

• Overall MAPE (Mean Absolute Percentage Error), graded:
  • ≤ 10% — Excellent
  • ≤ 20% — Good
  • ≤ 30% — Fair
  • > 30% — Poor
• Forecast Bias — positive means you tend to over-forecast, negative means you under-forecast.
• Items Measured — how many items have accuracy data.

Per-item table

For each item: MAPE, Bias, periods measured, trend direction (Growing / Declining / Stable), and an accuracy grade.

Typical workflow

1. Generate a baseline with From Historical Sales for the upcoming quarter, enabling seasonality and trend.
2. Adjust with Period Forecasts or Manual Entry where you have specific knowledge (a promotion, a known large order).
3. Let MRP net the forecasts so the SDI Dashboard plans ahead of firm orders.
4. After the period closes, run Calculate Accuracy and review MAPE/bias to tune the next round.

Tips

• Lean on seasonality and trend for items with clear patterns; use flat multipliers for steady movers.
• Keep batches tidy — delete superseded generation runs so the forecast set stays clean.
• Treat a persistent bias as a signal to adjust your multiplier (consistently over-forecasting? lower it).

Related Features

• Demand & Supply
• SDI Dashboard
• Planning View
• Supply-Demand Intelligence (Overview)