BPO and MSP operations are measured on SLA compliance. But SLA-compliant delivery can still hemorrhage margin through hidden repeat demand, transfer inflation, and escalation loops that never surface in client reporting. And as AI handles more of the queue, we independently verify whether it actually lowered the true cost-to-resolve for your client — the number your renewal depends on.
Hitting response time targets while resolution quality degrades. Tickets close within SLA but reopen within 7 days at 2-3x the original cost.
Tickets escalated to the client’s internal team and bounced back. Each bounce adds $20-40 in handling cost that neither party tracks.
Multi-queue routing creates phantom handle time. A 7-minute call that touches 3 queues costs 21 minutes of agent capacity but reports as 7.
Three of 16 fault lines the verdict grades. See the full method →
Did the AI work?
Would not hold
A ticket like this would close inside SLA — then reopen 8 days later at 2-3x the cost.
True cost to resolve
~$58
reported: $19
Fault attribution
Data
✓
Model
✗
Operator
✓
Handoff
✗
On a failure like this, fault would land on the model determination and the cross-queue handoff — clean inputs, correct operator routing, wrong call that bounced. Not your agents.
Figures are illustrative and conditional. On your engagement they’re produced from your de-identified data and labeled accordingly.
Standard CSV exports. No API integration is required for the initial read; security review can be scoped as needed. Most BPO operations can start with existing exports.
Go first in BPO & MSP
A scoped pilot on one use case, with concrete give/get terms — you help define the first independent verdict in your vertical, and get the read before anyone else has it.
Bring your volume, FCR, and cost — no PHI — and get your own true-CPR exposure. A founder-led Findings Call walks you through it.
Book a Findings Call