Minimizing shipping cost

Minimizing shipping cost is one of the five fulfillment objectives of IBM Sterling Fulfillment Optimizer with Watson. When this objective is prioritized, fulfillment decisions are based primarily upon the most cost-effective way to ship orders while still meeting customer expectations.

Overview

Fulfillment Optimizer considers the following variables when optimizing orders to minimize shipping costs:

Delivery date
Node carrier applicability
Carrier schedule
Ship date
Dimensional weight
Carrier rates and zones
Node ship calendars

Fulfillment Optimizer then uses the following factors within shipping cost optimization:

Large-scale combinatorial optimization.
Transportation cost and SLA optimization at the time of source node selection.
Smart weight allocation.
Smart upgrade and downgrade to optimize cost and customer satisfaction.
Smart order splitting to reduce costs.
Order processing (labor) costs.

To calculate the shipping cost associated with each order, Fulfillment Optimizer uses the shipping transit days and shipping rate card data that was uploaded to the system.

Example

For example, your goal is to minimize shipping costs while also meeting customer SLAs, so you set the weight of the Minimizing shipping cost objective at 100%.

Note: When a weight is set for the Minimizing shipping cost or Minimizing processing cost objectives, also set the weight of the Balancing node capacity objective if you want to promote a balanced fulfillment network.

In this example, a customer purchases 5 products within a single order. The total weight of all of the products in the order is 8 pounds. A single shipment that contains all the items costs $22.56 to ship. However, Fulfillment Optimizer determines that it is cheaper to send the order in two separate packages: one package that weighs 4.8 pounds and costs $8.34 to ship, and a second package that weighs 3.2 pounds and costs $7.57 to ship. By sending the order in two shipments, you ultimately save $6.65 in shipping costs.