Updated September 2026.
The instinct when incidents keep slipping through and outages keep costing more than expected is to buy visibility: an AIOps platform, a new monitoring stack, an automation layer that promises to detect and remediate before anyone gets paged. Most of that instinct is correct. The mistake is buying it before finding out where the actual visibility gap sits, because automation built on top of an unmapped, unreliable view of the environment tends to automate the wrong response with more confidence, not less.
What operational blind spots actually cost
New Relic’s 2025 observability research puts a number on what is otherwise treated as an abstract risk. High-impact outages carry an annual median cost of $76 million, and cost businesses up to $2 million per hour once they start, roughly $33,333 for every minute systems stay down. Those figures alone justify almost any reasonable investment in visibility. The more useful finding is what separates organizations that avoid this from ones that don’t.
Organizations without full-stack observability experience high-impact outages at least weekly 40% of the time. Organizations with full-stack observability report that rate at 23%, roughly half. The same research found that engineers at under-instrumented organizations spend 33% of their time fighting fires or addressing disruptions instead of planned work, and 41% of IT leaders said they still learn about service interruptions through manual means rather than automated detection, meaning the alert that should have fired quietly still routes through a phone call or a support ticket first.
None of that is a tooling gap in the sense of “we don’t own an AIOps platform.” Most enterprises already own monitoring tools, often several of them; New Relic’s research found a median of four monitoring tools per organization even after consolidation. The gap is coverage, correlation, and trust in the underlying data those tools are watching, which is exactly what an ITOM maturity assessment is built to measure before an automation budget gets committed.
Why automation inherits whatever gap it’s built on
AIOps and automated remediation depend on two things being reliable at the same time: an accurate map of what exists and how it connects, and enough historical incident data to correlate a symptom with its actual cause. When either one is weak, automation does not fail loudly. It fails quietly, by acting on a plausible but wrong signal.
Automation layered on an unreliable CMDB
Configuration data is the map that correlation and automated remediation both depend on. An organization that has never assessed how much of its CMDB reflects reality, rather than how much was entered once and never reconciled, is handing an automation platform a map with holes in it and asking it to route around problems the map does not show. We cover how to assess and rebuild trust in that specific layer in our look at configuration management database maturity.
Automated response for incidents nobody has root-caused
Runbook automation is only as good as the diagnosis it is built from. Automating a restart or a failover for an incident type that has never had a proper root cause analysis just means the same underlying fault recurs faster and with less human attention on it, until it eventually surfaces somewhere the automation cannot reach.
Monitoring tool sprawl mistaken for coverage
Adding another monitoring tool to close a visibility gap frequently makes the gap harder to see, not easier, because more tools mean more dashboards, more alert channels, and more correlation work for a human to do manually. An assessment measures actual coverage and signal quality, not tool count, which is why organizations in New Relic’s research trended toward fewer, better-integrated tools rather than more of them.
What an ITOM maturity assessment actually diagnoses
Instead of starting from a shortlist of AIOps vendors, an ITOM maturity assessment scores monitoring and observability coverage against the real estate, not the estate as it was documented last year; the accuracy and currency of configuration and dependency data feeding correlation; the maturity of incident detection and escalation, including how much still depends on someone noticing manually; and how ready the operating model actually is for automated remediation, meaning whether the organization has the process discipline to trust and maintain automation once it exists.
That produces a specific, ranked answer to “what should we fix first,” instead of a platform recommendation that assumes the underlying data is already trustworthy.
Sequencing automation investment after the assessment
A focused ITOM maturity assessment typically takes a few weeks. Set against $76 million in median annual outage cost for high-impact incidents, or $2 million an hour while one is happening, that is a small, fast investment that determines whether the next automation dollar goes toward closing a real gap or toward making a bad signal move faster.
What the assessment produces beyond a maturity score
The practical output is a prioritized list of gaps rather than a single grade. Some findings are fast to close, such as extending monitoring coverage to a specific class of endpoint that was added to the estate after the original instrumentation plan was set. Others are structural, such as establishing a formal process for keeping configuration data current instead of relying on whoever last touched a system to update it correctly. Separating the two matters because an organization under outage pressure can act on the fast fixes immediately while the larger data quality or process work is scoped properly, rather than trying to solve both at once with a single automation purchase.
The assessment also gives incident response teams something they rarely have otherwise: an honest picture of which parts of the environment are well instrumented and which are effectively dark, so escalation and staffing decisions can account for that risk directly instead of assuming coverage is uniform across the estate.
Where DesQcon fits
DesQcon runs ITOM maturity assessments across monitoring coverage, configuration and dependency data quality, incident detection maturity, and automation readiness, and we are not paid by any monitoring or AIOps vendor to recommend a platform. The roadmap that comes out of the assessment reflects what your environment’s own data shows is actually broken, not a generic best-practice checklist.
See our ITSM Maturity Assessment Methodology for how we score people, process, tools, automation, AI, and governance, the same framework we apply when assessing operations maturity, and read ITSM Maturity Assessment: Why It Should Come Before Your Transformation Budget for why this baseline should come before any new spend.
Frequently asked questions
How is an ITOM maturity assessment different from a monitoring tool audit?
A tool audit checks what you own and whether licenses are current. A maturity assessment checks whether what you own is actually configured against a reliable map of your environment, whether the resulting alerts are trusted and acted on consistently, and whether the organization is genuinely ready to automate a response, three questions a tool inventory does not answer.
Do we need this if we’re not planning to buy an AIOps platform yet?
Yes, arguably more so. The assessment is what tells you whether AIOps is even the right next investment, or whether the larger gap is configuration data quality or incident process maturity that a correlation engine cannot fix by itself.
Does this overlap with a CMDB maturity assessment?
It overlaps by design. Configuration and dependency data is one of the dimensions scored in an ITOM assessment, because it underpins monitoring correlation and automation. Organizations with a known CMDB maturity gap often start there specifically; see our configuration management database page for that narrower assessment.
Check your own ITSM and ITOM maturity
If this raised questions about where your own organization stands, DesQcon’s ITSM & ITOM Maturity Assessment gives you a structured, evidence-based read on that. Start with a free trial across one process area, or request the full deep-dive assessment across people, process, tools, automation, AI, and governance.
