Backlog calculation showing existing backlog, order intake, sales and current state for the sake of forecasting

Description

In product manufacturing settings, supply chain planning greatly hinges on accurate backlog computation, which can directly influence forecasting accuracy. It helps to understanding the demand-supply dynamics and planning production and delivery schedules more efficiently. Without a full picture as described here, a forecast can never be fully accurate.

Example Use Case

Scenario: A product manufacturing company uses CPM software to forecast supply needs. This involves tracking the existing backlog in terms of the orders received but not yet fulfilled. It also includes monitoring new business transactions from the sales team CRM and from the website order portal.

Solution: The CPM software is configured to calculate the backlog precisely using order data from the ERP, showing the existing orders, new order intake, sales and the current state of all orders. This live connection enables accurate backlog calculation and assists with planning production scheduling. This enhanced forecasting capability assists with inventory management and can help in preventing stockouts and overproduction.

Considerations

Most backlog data is stored in an ERP or other supply chain management tool. Sometimes we see this stored in Excel, or in custom developed products. Either way, getting that backlog information into a planning environment is critical to producing an accurate plan that considers capacity constraints and assisting in identifying those constraints. For example, is that constraint unique to a supply issue? Or is it a workforce issue? Planning tools can assist in identifying those gaps.

Questions to Ask a Vendor

• Backlog Computation: How well does your system compute backlog including existing orders, new order intake, and sales data? Does it require it to be pre-computed and loaded in?
• Backlog Forecast: Does the system blend backlog, new business, and the associated constraints together in a forecast?
• Scenarios: Does the product have any intelligence to help us identify where we can modify the forecast to have an affect on backlog?