Wholesale roaming agreements typically include traffic commitments — minimum volumes that each party agrees to deliver to the other, often structured as minimum revenue guarantees or minimum volume thresholds. The commercial logic is sound: predictable traffic volumes allow better capacity planning and justify infrastructure investment. In practice, commitment tracking is often poor, and the commercial leverage that commitment data provides in renegotiations is consistently underused.
What commitment tracking reveals
An operator that has accurately tracked outbound traffic delivered to each bilateral partner against the commitment schedules in those agreements has a precise picture of which relationships are in compliance with commitments, which are over-delivering, and which are under-delivering. Each of these states has different commercial implications in renegotiation.
Over-delivery — routing more outbound traffic to a partner than the commitment requires — is leverage: the operator is providing value beyond the contracted minimum and has grounds to request reciprocal consideration in the next IOT negotiation. Under-delivery is a risk: the operator may be exposed to shortfall payments, but also has an opportunity to propose modified commitment structures that better reflect actual traffic patterns.
Reciprocal commitment symmetry
Most bilateral agreements set commitments in symmetric terms — each party commits to similar minimum volumes. The traffic data almost never shows symmetric delivery. One party typically over-delivers while the other under-delivers, and over time the asymmetry grows as traffic patterns evolve with subscriber base changes, device penetration differences, and destination preference shifts.
Identifying the parties to each bilateral relationship where delivery is most asymmetric allows the commercial team to enter renegotiations with a specific and data-supported proposal: adjust commitment levels and corresponding IOTs to reflect actual delivery patterns. This is a more productive conversation than a generic request for better rates.
Building the commitment data asset
The commitment data asset is built from two sources: the agreement schedules (which define the commitments) and the outbound NRTRDE and TAP data (which record what was actually delivered). Joining these requires that agreement terms are held in a structured format that can be compared programmatically to settlement data, rather than in PDF contracts that must be interpreted manually.
Operators that have structured their agreement database to be queryable against settlement data are finding significant commercial value in the resulting analytics. The initial effort to digitalise existing agreements is non-trivial but is a one-time exercise; ongoing tracking is then automated against the existing data pipeline.
