Why 13% of Shipments Miss the MABD — and Why It Keeps Happening
The data to identify at-risk shipments exists. Project44 and FourKites have ETA feeds. The MABD commitments live in SAP S/4HANA. Blue Yonder TMS knows the carrier and lane. The issue is that nobody is running a continuous, shipment-by-shipment comparison across all those sources and surfacing risk early enough to do something about it. Your execution team is managing a high volume of in-transit shipments through Slack threads and manual exception reports — catching the ones that are already late, rather than the ones that are about to be. By the time a chargeback lands, the opportunity to prevent it has passed.
Continuous MABD Monitoring With Automated Expedite Decision Packages
An AI Labor Company agent mines your supply chain execution team's Slack MABD monitoring threads and Project44 ETA data to extract the risk identification workflow your team uses today. The deployed agent reads Project44 in-transit ETAs daily, computes projected delivery dates against MABD commitments by customer DC, and flags shipments on a trajectory to miss. For each at-risk shipment, it generates an expedite decision package: the SKUs at risk, the projected MABD gap, and a cost comparison between expediting the load and absorbing the expected chargeback. Your director reviews and issues the expedite instruction to the carrier or Flexport. The agent eliminates the identification latency — it finds the problem while there's still time to act.
The Business Case: Chargeback Reduction and Retailer Relationship Protection
Moving MABD compliance from 87% to above 95% translates directly to chargeback reduction. On a $2.4M annual exposure, recovering 8 percentage points of compliance can recapture well over $1.5M in deductions — without renegotiating a single contract. Beyond the direct P&L impact, sustained MABD improvement strengthens your vendor scorecard with retail customers, which matters for shelf allocation and distribution decisions that compound over time. Teams in this position typically achieve 70–90% improvement in at-risk identification cycle time, and the agent is generally live in about 3 weeks.
Can the agent handle multiple retail customers with different MABD windows and chargeback rate structures?
Yes. MABD windows and chargeback rates vary by retailer and program — the agent is configured with the specific commitments and penalty structures from your SAP customer master and TMS data during setup. It flags risk and calculates expedite-vs.-chargeback trade-offs using the correct parameters for each customer DC.
How far in advance does the agent start flagging shipments as at-risk?
The alert horizon is configurable, but most teams set it at 5–7 days before the MABD — far enough out that expedite options are still viable and cost-effective. The agent also recalculates risk daily as ETA updates come in from Project44, so a shipment that looked on-track on Monday gets flagged if it picks up a delay on Wednesday.