Cost-based promising

IBM® Sterling Intelligent Promising provides cost-based promising to make cost-efficient sourcing recommendations. The Get Optimized Checkout Plan (Pre-Purchase) API processes data by using configuration data, transactional data, and artificial intelligence (AI) and calculates the most cost-efficient sourcing solutions for prepurchase shipment assignments.

The promising factors like inventory availability, capacity, distribution groups, carrier services, transit rates, transit duration, lead time, and many more are considered to shortlist the potential sourcing nodes. The overall cost-to-serve that includes all cost factors is calculated for all nodes and one or more sourcing nodes with the lowest cost-to-serve are selected for fulfilling an order.

For cost-based promising, the Get Optimized Checkout Plan (Pre-Purchase) API calculates the promising dates for prepurchase shipment assignments that allow order fulfillment at the lowest cost. For more information, see the Get Optimized Checkout Plan (Pre-Purchase) API.

Tag-aware cost-based promising

The batchNo, lotNo, and revisionNo tag identifiers or the tagNumber enable cost-efficient sourcing while respecting tag-specific inventory requirements. The following Calculation APIs support inventory tag identifiers or the tag number:

Tag matching behavior in cost optimization

When tag identifiers or the tag number are provided in the request, the APIs apply strict tag matching before evaluating cost optimization:

The APIs source only from inventory that matches the specified tags.
Cost optimization is performed within the pool of matching tagged inventory.
The APIs will not fall back to untagged inventory even if it offers a lower cost-to-serve.
If no matching tagged inventory exists, the APIs return "No Availability" or "Backorder" status.

Cost implications of tag-specific requests

Tag-specific requests might result in higher cost-to-serve compared to untagged requests because:

The available inventory pool is restricted to matching tags only.
Optimal sourcing nodes might not have the required tagged inventory.
Shipping costs might increase if tagged inventory is located further from the destination.
Processing costs might increase if tagged inventory requires special handling.

However, tag-specific fulfillment ensures:

Contractual compliance with vendor-specific inventory restrictions.
Regulatory compliance for industries requiring batch tracking.
Margin protection by preventing unauthorized consumption of premium inventory.
Customer satisfaction by delivering the exact product specifications required.

Untagged requests and cost optimization

When tag identifiers are null or empty, the APIs request from the untagged inventory pool and perform cost optimization across the available inventory. The actual inventory pool depends on the tenant's untaggedMatchAllTag setting that is managed by the inventory layer.

For more information, see Scenario: Tag-aware checkout assignment for specific inventory requirements.

The cost-based objectives that are considered for calculating the lowest of cost-to-serve are as follows.

The Get Optimized Checkout Plan (Pre-Purchase) API accounts for penalty that is applied during prepurchase shipment assignments.

Delay penalty

Both the distance penalty and delay penalty contribute to shipping cost. Therefore, Get Optimized Checkout Plan (Pre-Purchase) API aims to avoid penalties for reducing overall cost-to-serve. The Get Optimized Checkout Plan (Pre-Purchase) considers the optimization constraints when the cost-to-serve is calculated. For more information, see Optimization constraints.

Example

For example, your objective is to fulfill an order with multiple order lines at the lowest cost-to-serve, so you call the Get Optimized Checkout Plan (Pre-Purchase) API to get cost-efficient sourcing recommendations.

In this scenario, a shopper has ordered two items, a pair of shoes and a T-shirt. The selected delivery type is Standard delivery, which allows you to ship and deliver the order today or tomorrow. The potential ship nodes are Colonie, NY and Woodbury, NY. The pair of shoes is available at both the ship nodes, but the t-shirt is only available at Woodbury, NY. The following transactional parameters are used for each ship node.

Ship node- Colonie, NY
- Operational days/Inventory capacity- Today and Tomorrow
- Carrier service- FedEx Ground
Ship node- Woodbury, NY
- Operational days or Inventory capacity- Tomorrow (Woodbury, NY ship node doesn't have inventory capacity for shipping today.)
- Carrier services- FedEx Ground and USPS Ground

Note: The transaction rate for FedEx Ground is 12 USD per shipment, whereas it is 11 USD per shipment for USPS Ground. Also, FedEx Ground offers early pickup everyday.

Considering all these transactional parameters at both the ship nodes, here are your promising possibilities for Standard delivery type.

Table 1. Promising possibilities
Delivery objectives	Sourcing solution	Cost-to-serve
Deliver earliest	Shoes Ship Node- Colonie, NY Carrier service- FedEx Ground Deliver today T-shirt Ship Node- Woodbury, NY Carrier service- FedEx Ground Deliver tomorrow	24 USD Note: This promising possibility requires two shipments by using FedEx Ground carrier service. Each shipment costs you 12 USD, which sums up to 24 USD as overall cost-to-serve.
Minimize the number of shipments Deliver early tomorrow	Shoes Ship Node- Woodbury, NY Carrier service- FedEx Ground Deliver tomorrow T-shirt Ship Node- Woodbury, NY Carrier service- FedEx Ground Deliver tomorrow	12 USD Note: This promising possibility requires only one shipment to deliver two order items by using FedEx Ground carrier service hence it costs only 12 USD as overall cost-to-serve.
Minimize shipping cost Deliver late tomorrow	Shoes Ship Node- Woodbury, NY Carrier service- USPS Ground Deliver tomorrow T-shirt Ship Node- Woodbury, NY Carrier service- USPS Ground Deliver tomorrow	11 USD Note: This promising possibility requires only one shipment to deliver two order items by using USPS Ground carrier service hence it costs only 11 USD as overall cost-to-serve.

After considering all promising possibilities that are mentioned in the table, Sterling Intelligent Promising recommends the third sourcing solution.

You can configure cost-based optimization to calculate prepurchase shipment assignments and minimize overall cost-to-serve. For more information, see Configuring cost-based optimization for promising.