- "Turning IoT Roaming into a Profitable Business" (case study)
- Client is listed as "Under NDA," region Europe, solutions include IoT BCE / IDA.
- The case describes analysis of IoT roaming connections/traffic during a prior period and contrasts seasonal retail roaming patterns versus the typically stable patterns observed for IoT connections.
- Critical evaluation:
- The client is unnamed and results are presented narratively with limited hard metrics in the public excerpt, which makes independent validation of business impact difficult.
- The method references signaling analysis, a plausible approach for detecting device behavior; procurement teams should request concrete KPI deltas (for example, revenue uplift, leakage reduction, fraud reduction), baselines and measurement windows, and source data details when validating claims.
- QoS / analytics white paper
- TOMIA published a QoS-in-roaming white paper (recent framing) describing analytics that use machine learning models, predictive analytics, and anomaly detection; it includes a case study about IPN steering to improve QoS.
- Critical evaluation:
- The white paper is vendor-authored. Any analytics performance claims should be validated with before/after QoE metrics, false positive/negative rates for anomaly detection, and evidence of operational workflow impacts (for example, how many changes were automated versus how many required human approval).
- "Improved QoS Drives Roaming Data Consumption"
- TOMIA shared a LinkedIn post claiming its Adaptive Steering segments roamers and adapts steering decisions in real time to assign high-data users to higher-QoS networks.
- Critical evaluation:
- The LinkedIn post is a marketing artifact; procurement teams should obtain the underlying case study and verify statistical significance, QoS measurement methodology (RAN KPIs? throughput? latency? user complaints?), and whether increased consumption resulted from improved experience versus policy changes.