The hidden cost of incidents that are impacting your business

What is the hidden cost of failing to detect incidents in time? It's a cost resulting from the combination of direct losses due to downtime (which can range from hundreds of thousands to several million dollars per hour) and indirect damage to productivity, reputation, and growth that is rarely measured but far outweighs the immediate impact of the technical failure. (Businesswire, “New Relic Study Reveals IT Outages Cost Businesses Up to $1.9 M Per Hour”, October 22, 2024).

Observability significantly reduces that cost because it allows for shorter detection and resolution times, limiting the window in which the business is "in the dark".

In this article, we answer key questions about how a smart observability strategy can improve your business by reducing the hidden costs associated with system incidents.

Let's get started!

What do we mean by "not detecting incidents in time"?

When we talk about "failing to detect incidents in time," we're not just referring to complete system outages, but to any significant degradation that the business doesn't see until it already has an impact: slow response times, intermittent payment errors, unresponsive APIs, or overloaded internal services. (IBM, What is SRE observability?, March 4, 2025)

In terms of system reliability (SRE) and observability, the key problem is an excessively high mean time to detect (MTTD): the longer it takes to realize something is wrong, the longer the mean time to repair (MTTR), downtime, and loss of value become. Modern observability aims precisely to shorten this time, providing near real-time visibility into the system's internal behavior. 

The direct cost: every minute counts

According to Article published by Erwood Group, the average cost of IT downtime is very high:

• For medium-sized companies, the average cost of downtime is around $9,000 per minute, or about $540,000 per hour.
• In large companies, various benchmarks cite ranges from hundreds of thousands to several million dollars per hour; for example, analyses by Siemens and other suppliers place the automotive industry at around $2.3 million per hour of downtime.
• New Relic Data and other observability providers point out that the cost of a major crash can exceed $2 million per hour, with cumulative annual losses of tens of millions.

The key point is that the cost does not scale linearly: the more critical the platform is to the business (ecommerce, logistics, financial services), the more expensive each minute becomes that users cannot operate or their experience is significantly degraded.

The hidden cost: beyond visible downtime

In addition to the cost clearly attributable to the outage, there are several "hidden" components that arise when incidents are detected late:

• Lost internal productivity: Studies indicate that IT teams can spend up to a third of their time managing outages and resolving incidents, instead of investing it in improvements and new features.
• Impact on future revenue: a Splunk report (June 2024) for large companies, it is estimated that downtime contributes to aggregate losses of hundreds of billions annually, largely due to customers not returning after bad experiences and business opportunities that are never closed.
• Opportunity cost in innovation: every hour the team spends putting out fires is an hour not spent launching new digital capabilities or optimizing processes.

These effects are usually left out of standard ROI calculations, but in the medium term they weigh as much or more than the direct figure of "X dollars per hour of decline".

How the lack of observability amplifies that cost

The data from the Observability Forecast report New Relic (2024) are consistent: organizations with advanced observability capabilities detect and resolve incidents much earlier, and that translates into less cost per interruption.

• Companies with full-stack observability can reduce the total fall detection time by more than 50% compared to those with limited capabilities.
• According to New Relic's Observability Forecast, organizations with full observability experience up to 79% less annual downtime and pay approximately half as much per incident hour ($1.1 million vs $2.1 million).
• The same reports show an average ROI of close to 4x: for every 1.95 million invested annually in observability, approximately 8.15 million in value is generated (mainly due to less downtime and less mitigation effort).

When there is no observability (or it is fragmented), the team usually finds out about problems through user tickets or business alerts (dropping sales, increased cart abandonment), which implies that the incident has already been causing damage for some time when it is detected.

Where does the hidden cost manifest itself in the business?

The hidden cost of not detecting incidents in time is spread across several layers of the business:

• Customer experience: long loading times or errors at key moments (payment, registration, login) erode user trust; indicators such as NPS, repeat purchase or conversion deteriorate cumulatively.
• Operations and support: calls to the contact center, support tickets and trade compensations increase, with an added operating cost that is often underestimated.
• Compliance and risk: In regulated sectors, a prolonged degradation can lead to SLA breaches, contractual penalties, or even regulatory sanctions, in addition to impacts on audits.

Overall, the "hidden cost" is the sum of lost revenue, lost customers, unproductive work hours, and risks that materialize precisely because the organization is late in addressing the issue. (Managed IT Solutions of NC, 2025)

Intelligent Data Analytics and Observability in Oriented

From our perspective at Orienteed, in ecommerce projects and digital platforms in production on AWS, we have observed that the adoption of observability practices (distributed tracing, business metrics and SLO-oriented alerts) reduces the average time to detect critical incidents by more than 50% after deployment.

In some cases, this has meant going from learning about a problem through a sudden drop in the conversion rate to detecting the anomaly in the application layer minutes before the user perceives a visible failure.

This space allows for the incorporation of internal (anonymized) metrics and specific use cases in e-commerce or B2B. For a global eyewear brand, after implementing our observability service with modern tools, the client was able to measure a 186% year-over-year growth in online orders, 97.7% SLA compliance for their main brand, as well as improvements in stability, visibility, and decision-making. (Orienteed, Case Study, Digital transformation of eCommerce support for a global eyewear brand, 2023).

Conclusion: the real cost is following blindly

To put it simply: the hidden cost of failing to detect incidents early is paying for the same problem multiple times over: first in lost revenue due to downtime, then in lost productivity, reputation, support, and a stifled innovation. Our experience and reports from New Relic and IBM show that companies with advanced observability dramatically reduce both detection time and downtime cost per hour, achieving a clear return on investment.

For organizations that rely on digital channels—such as e-commerce, B2B platforms, or online services—not investing in observability is not about saving on tools: it's about taking on a hidden liability that accumulates with each incident not detected in time.

A systematic approach to observability turns that liability into an opportunity for resilience, efficiency, and sustained trust with customers and partners.