Quick answer
To forecast inventory with Logiwa, use its real-time stock positions and outbound velocity to read demand by SKU and location, then time replenishment to inbound lead times and safety stock. Connecting Logiwa to a live financial model turns fulfillment data into a forward plan tied to cash.
What Logiwa brings to inventory forecasting
Logiwa is a cloud warehouse-management and fulfillment platform built for high-volume DTC operations. It maintains real-time inventory across warehouses and high-throughput order activity.
Logiwa's real-time, high-volume inventory and order data give a forecast an accurate, current view of fast-moving stock. Projecting that velocity forward by SKU and location, and tying it to cash, is where a financial model adds value.
| Logiwa data | What it drives in the forecast |
|---|---|
| Real-time inventory | Current coverage across nodes |
| High-volume order activity | Demand velocity |
| Multi-warehouse stock | Coverage by location |
| Inbound receiving | In-transit visibility |
How the forecast is built
With real-time inventory positions and outbound velocity flowing from the warehouse, forecasting comes down to reading how fast each SKU is moving across fulfillment nodes, projecting that demand forward, and timing replenishment to inbound lead times and a safety-stock buffer.
Formula: Weeks of supply = current on-hand units / average weekly demand. It flags stockout risk when it drops too low and trapped cash when it climbs too high. Reorder point = (average daily demand x lead time in days) + safety stock.
Multi-node fulfillment adds a wrinkle: stock can be healthy in aggregate but short in one region. Forecasting by SKU and location keeps you from stocking out in one node while overstocked in another.
Rule of thumb. Read velocity and coverage by SKU and location, not just in total. Logiwa can show healthy aggregate stock while one node is about to stock out.
From Logiwa data to a cash-aware forecast
A forecast is only as good as the data behind it and only useful if it connects to cash. Drivepoint pulls Logiwa data through its Logiwa integration into a live, Excel-native model, then turns on-hand and open-order data into forward weeks of supply, reorder timing, and the cash each purchase order will consume.
Because inventory is the largest use of cash for most consumer brands, every reorder is checked against runway, not just demand. That is the same connected approach that let Oats Overnight tie demand timing to a capacity decision worth $4M in EBITDA. For the underlying method, see our guide to SKU-level demand forecasting.