SLA-based checkout

Sterling Intelligent Promising offers Service level agreement (SLA) based checkout calculations when a shopper prefers to receive the order on either the earliest date or in the minimum number of shipments. In these cases, the shopper selects either minimize shipments or earliest delivery fulfillment options on the Order Hub UI during the checkout process.

When the user selects one of these options, the Get Checkout Shipment Plan (Pre-Purchase)API provides the SLA-based checkout calculations by default. If a shopper selects Minimize shipments as a fulfillment preference, then Sterling Intelligent Promising optimizes the order fulfillment to deliver the order in the minimum number of packages.

If the shopper selects earliest delivery as their fulfillment preference, Sterling Intelligent Promising optimizes the order fulfillment to deliver the order as soon as possible. In this case, Sterling Intelligent Promising prioritizes the carrier services that can deliver on the earliest date, even if the shipping and processing costs are higher. For more information, see the Get Checkout Shipment Plan (Pre-Purchase) API.

The following Calculation APIs support inventory tag identifiers or the tag number:

The batchNo, lotNo, revisionNo inventory tag identifiers or the tagNumber is supported in SLA-based promising. When tag identifiers are provided, tag matching takes precedence over SLA optimization. The APIs source only from matching tagged inventory, even if untagged inventory could provide earlier delivery or fewer shipments. For more information, see Scenario: Tag-aware checkout assignment for specific inventory requirements.

Note: Other than SLA-based promising, Sterling Intelligent Promising can also apply delivery date and shipping dates as order optimization constraints. If date-based optimization is used, the checkout calculations consider delivery date and shipping date over the number of shipments. By default, the SLA is applied as an order optimization constraint for checkout calculations in prepurchase scenarios.