Reactive or proactive: what your MTTx says about the return on your tools
The question · Three numbers · What reactive costs · Is it paying off? · What to ask for · Second opinion · Sources
You have paid for monitoring. The question for leadership is simple: does it find problems before your customers do? Three numbers answer it, and they show whether the investment is paying off.
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The question to ask
Are we in a reactive posture, or a proactive one?
Take the two-minute posture check →
Three numbers to ask for, every month
- Share of incidents found by our tools first, not by users or customers.
- Median and slowest-10% time to detect and to restore, for the services the business depends on.
- Repeat incidents: how many came back, and how many problems were permanently fixed.
Trends matter more than any single month.
What reactive costs
median annual cost of high-impact IT outages for the businesses surveyed, with a median hourly cost of $2 million.
average cost of a single hour of downtime for over 90% of mid-size and large enterprises.
of respondents said their most recent significant, serious or severe outage cost more than $100,000.
of IT leaders said outages or disruption have reduced customer trust.
of engineers’ time goes on fighting fires or addressing disruptions instead of building new features.
These are large-enterprise figures. Smaller organizations lose less per hour, but often have less slack to absorb it.
Is the tool investment paying off?
What the surveys report about returns. Each figure is labelled with who ran or paid for it.
of businesses report a positive return from their observability investments (vendor survey).
annual return reported by observability ‘leaders’, as defined by the vendor’s own scoring; only 11% of respondents qualified (vendor survey).
less downtime reported by respondents with full-stack observability (70 vs 338 hours a year). This is a correlation: organizations with it reported less downtime, not proof that it caused the difference (vendor survey).
ROI for a composite organization in a Total Economic Impact study commissioned by the vendor (vendor-commissioned study, not an industry benchmark).
The balancing view
Only 28% of AI use cases in infrastructure and operations fully succeed and meet ROI expectations; of leaders with a failure, 57% said they ‘expected too much, too fast’.
Only 21% of survey respondents reported high levels of success with infrastructure and operations automation (2022 survey of large enterprises).
Tools pay back when the operating model changes with them: owners for alerts, measured MTTx, and problems fixed at the root.
What to ask for
- A posture assessment of where each critical service sits today.
- The three numbers above, trended monthly.
- An alert ownership and noise review.
- A list of repeat incidents and who owns the permanent fix.
- A plan to move one step up the ladder this year, with the tools you already own.
Second opinion
Sources
Facts checked Oct 13, 2026.
Illustrative examples are invented to explain the ideas and are not measured data. Survey figures are as published by their sources; King Tech is independent and is not affiliated with any of them.