Full monitoring coverage doesn’t equal value.

Most enterprises are drowning in data, creating millions of events (9.6 million, on average) annually. In addition, 27% occurred on weekends, which is bad news for those on call. Yet only 18% of incidents were actioned on average, underscoring the disconnect between the belief that comprehensive observability coverage of applications, services, and infrastructure equates to better ITOps, incident management, and customer outcomes.

Noise reduction is exceptionally high for BigPanda customers.

Most (82%) organizations achieved at least 97% noise reduction with BigPanda, and over half reduced noise by 99.5–99.9%, showing the power of deduplication, filtering, correlation, and suppression when properly implemented with a unified AIOps platform.

Full-stack observability is still an illusion.

Despite enterprises using a median of 20 inbound tool integrations, few monitoring and observability tools had high coverage and actionability rates. In addition, despite their popularity, open-source tools had a low impact at the enterprise level. This suggests that even widely used tools often generate noise instead of insight.

Alert enrichment boosts actionability.

Organizations enriched 60% of alerts with context data for all incidents, but enriched 77% of alerts linked to actioned incidents. This comparison indicates that enrichment from CMDB, cloud and virtualization management, service discovery, and APM tools significantly improves alert quality and operator confidence.

Healthy correlation is powerful.

Nearly half (49%) of organizations fell into the healthy alert-to-incident correlation range (40–75%), and those that did showed stronger filtering, a more manageable incident volume, and a higher operational signal fidelity.