Using Real-Time AI Methods to Automatically Process Customer Order Flow

Things used to be simple. You made a limited range of products, which you made to stock. Then you fulfilled customer orders from your warehouse as they arrived by Fax or directly from your sales people. Production was planned months in advance, using an MRP or ERP system, based on sales forecasts.

Now, customer orders can come from a wide variety of sources, including Amazon and your own E-Commerce website. They can also come from your distributors and resellers, who may require you to drop ship products, as well as other more traditional sales channels.

These orders flow in continuously, often for semi-custom products with a wide-variety of options. Customers expect their orders delivered in a few days and not a few weeks or months, as a result of the "Amazon Effect".

Also, money is now expensive. As a result, many manufacturers and distributors are forced to make-to-order, on a just-in-time basis, with Lean inventory management.

 Having people handle this customer order flow is becoming increasingly problematic due to the amount of time required to plan and schedule the needed purchasing, manufacturing, and warehouse operations, as well as the importance of preventing mistakes and of adapting plans and schedules when problems arise.

In this white paper, the authors describe how a real-time intelligent agent architecture can be used to automatically process the incoming customer order-flow thereby saving a lot of time and aggravation, as well as preventing mistakes.

To download a PDF of the white paper, please click on:

"Using Real-Time AI Methods to Automatically Process Customer Order Flow" .