Set up your first forecast

The shortest path from “fresh install” to “useful reorder suggestions.” About 30 minutes once your initial data sync has completed.

Before you start

• Onboarding wizard completed.
• Initial data sync finished (Settings → Data Import shows all six steps as Loaded).
• At least one variant has historical sales (most do — Logistified picks them up from your Shopify order history).

Steps

1. Open the Forecast page.
2. Verify your variants appear in the table.
3. Open the Forecast settings panel. Switch the Model to Average and the History period to Manual / Last 90 days. This is the beginner setup — no hidden parameters, fully predictable math.
4. From the Columns popover, add Actual Reorder Quantity, Reorder Date, and Days of Stock to the visible columns.
5. Sort by Reorder Date ascending.
6. Save as a view named “Beginner — Average 90 d.”
7. Look at the top rows. Do the suggested quantities and reorder dates roughly match your gut?
8. If yes — you trust the inputs. Switch the model back to Auto and let the system pick a better model per variant.
9. If no — drill into a variant detail page (click the variant title). The History tab usually shows why.

Worked example

Say you have 100 units of widget X on the shelf. Logistified’s Average model on a 90-day window says you sell 2 per day. Your supplier’s lead time is 30 days, with safety stock at the auto setting (~10 units for this variant).

• Lead-time demand: 2 × 30 = 60 units.
• Reorder point: 60 + 10 = 70 units.
• Days until you hit it: (100 − 70) ÷ 2 = 15 days.

So your Reorder Date column shows “15 days from now.” Logistified suggests you place the order in 15 days, not today — and Actual Reorder Quantity will be set to the supplier’s MOQ (or higher, depending on EOQ).

Common failure modes

Symptom	Likely cause	Fix
Empty Reorder Date for many variants	Those variants have no recent sales history.	Wait until sales accumulate; or pick variants you know have history.
Reorder Date says “today” for everything	Inventory is below the reorder point for everything.	Verify thresholds; this can happen with very thin stock and a long lead time.
Suggestions don’t match your instinct	The model picked is wrong for the demand shape, or supplier values are wrong.	Try Persistence (cold start), Linear regression (trending), or Auto. Verify the supplier link.

See also

• Forecast → Overview
• Forecast → Forecast view table
• Forecast → Reorder suggestions

Last updated: 19 May 2026