Fulfill: keeping the promise

What it is. Order makes the commitment; Fulfill keeps it. The process covers executing customer orders and services — scheduling the delivery, picking, packing, and shipping, installation and commissioning where the offer includes them, and invoicing. Together the two processes replace classic SCOR’s Deliver, and the split earns its place because execution has its own physics: warehouses with labor curves, carriers with acceptance behavior, lanes with capacity that evaporates in a tight market, appointment windows that don’t move because your schedule slipped. An order can be promised perfectly and still fail here — which is exactly the diagnostic information the old combined process obscured.

The questions it answers. Are promises being kept — in full, on time, documented, undamaged — and when they aren’t, did the failure happen in commitment or in execution? How long does fulfillment actually take, stage by stage, and which stage is the queue? Is transportation capacity available at contracted rates, or is the network quietly sliding onto the spot market one declined tender at a time? Which lanes, carriers, and consolidation patterns keep the promise at the lowest reliable cost?

The metrics that matter.

Measure	SCOR DS	What it tells you
Perfect Customer Order Fulfillment	RL.1.1	The whole promise — every component must pass for the order to count
Customer Order Fulfillment Cycle Time	RS.1.1	End-to-end speed as the customer experiences it, not as stages report it
Fulfill Supply Chain Agility	AG.2.4	How much sustained volume change the fulfillment network absorbs
Tender acceptance rate	practice measure	Early warning that contracted capacity is evaporating — it falls weeks before service does
Freight cost per unit	practice measure	What keeping the promise costs, normalized so mix changes don’t hide drift

The decisions that live here. Carriers start declining tenders. The operational default — chase spot capacity — keeps the promise at whatever the market asks, and hides the structural problem inside the freight bill. The alternative is restructuring: re-mixing carriers, consolidating LTL into FTL, re-timing pickups to windows carriers accept. The tender-rejection caselet prices both paths at the same service level. Re-promising is the other recurring call: when execution can’t recover an order, the new date should be read from where recovery supply actually sits in the TMS, then written back so the order desk and the customer see the same truth.

SCOR is ASCM’s framework; coded metrics reference the SCOR DS quick reference. Uncoded measures are common practice measures.