From demand signal toreviewed purchase order

A reorder recommendation should be more than a number. It should show you what demand is doing, what you already have, what is on the way, and what your team should review next.

This is a Spark demo workspace using example data. We will follow one item from sales history through the planning decision, then show the approval step with a second captured recommendation.

Start with the item itself. Spark brings the current stock, incoming supply, days of cover, planning rate, stock health, recent sales, and the current recommendation into the same view.

The demand view separates what happened from what Spark expects next. Completed months remain visible as actuals. The forecast continues forward with a range, so the team can see both the expected level and the uncertainty around it.

Seasonality matters too. This item has a clear annual shape, with demand rising into the middle of the year and falling afterward. Demand ESP reads that pattern for the item instead of forcing every product into the same monthly average.

Now check the operational context. The warehouse view shows current stock, the reorder point, incoming supply, and the planning rate. Timing still matters, even when another order is already on the way.

The purchasing tab adds the vendor, minimum order quantity, cost, lead time, and incoming delivery date. That keeps the recommendation grounded in how the item can actually be replenished, instead of treating the forecast as an isolated chart.

Spark brings those signals together into a recommendation your team can inspect. The goal is to make the demand, stock, supply, and constraints visible before anyone commits cash to another order.

The existing purchase order stays part of the decision. The inbound quantity, expected delivery, supplier, line items, and total are all available for review. That context helps prevent a duplicate order made from an incomplete stock count.

To show the approval step, here is a second captured demo recommendation. Sparki found an item needing replenishment, prepared a purchase order proposal, and showed the vendor, destination, quantity, unit cost, and estimated total before creating anything.

After review, the user selected Create PO. Spark created a draft purchase order with the item and supplier details already filled in. The draft remained under team control. It was not issued or emailed to the vendor.

The same workflow can begin in Sparki or through Spark's MCP connector. Ask what needs attention, inspect the evidence, and prepare a draft for review. Forecasting is available free, while purchase order workflows are part of Spark's operating plans. See the full walkthrough at sparkinventory.com.