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It's Not Downtime We Should be Worried About - It's Uptime

Ivar Sagemo

Here's an eight-letter word, twice as bad as any four-letter word, that no business leader wants to hear: downtime. Today's businesses are far more dependent on IT services than ever, and that's true whether you're talking about internal IT services (like ERP) used to drive strategic operations, or external IT services used to satisfy client and customer demand.

Among the more daunting long-term potential consequences of downtime to the organization are these:

• Lost revenues because business couldn't be transacted. A recent Ponemon study tells us the average cost of downtime for US-based organizations is a stunning $5600/minute.

• Diminished brand strength, because the company is seen as unreliable. The same study suggests the average length of downtime was 90 minutes, leading to roughly $500K of costs per incident.

• Evaporating market share, because unhappy customers go to competitors.

Quite a mess in short. And it's a mess that's rapidly getting bigger. Aberdeen Group found that between 2010 and 2012, the cost per hour of downtime climbed an average of 65%!

Now, all of this is obvious in my own area of application performance monitoring (APM), and while downtime is a problem, there is a bigger issue, more subtle lurking just beneath the surface. When we believe everything is running smoothly but don't know something is wrong, that’s when the most damage happens.

For instance, suppose a BizTalk-based service is up and running in a holistic sense, but operating in a subtly inconsistent manner — difficult to detect — that leads to lost transactions from time to time. By this I mean occasionally lost e-mails, lost database entries, lost purchase orders, etc. Time spent by customers resending email and clients waiting or employees spending time looking for an invoice that has not come through – all of these cause more loss in productivity and reputation over a longer period of time.

According to Pricewaterhouse Coopers, the average organization, spends $120 searching for a lost document and wastes 25 hours recreating each lost document.* But what we don't know is how much productivity is lost through not knowing when a problem exists, searching for a file that is not lost at all. Waiting on document resends, searching for "missing" invoices or customer relationships that need to be repaired due to an apparent miscommunication because information is not flowing smoothly in a system all impact company efficiency and costs.

Application performance, and service uptime, can be affected by myriad factors — some as subtle as a gradual shortage of key computational resources. That's why it's important to find a way to granularly monitor your system. To have control and visibility over the problems that are happening so you can decide which ones to tackle is key.

Over time, I think we're going to see that kind of granular insight play a larger and larger role in APM as a field. But in the meantime, it's important to have a clear view of the information that flows throughout your organization so you can see any problem lurking out of sight.

Ivar Sagemo is CEO of AIMS Innovation.

Related Links:

www.aimsinnovation.com

* DocuSense Blog: How Much are Lost Documents Costing You?

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It's Not Downtime We Should be Worried About - It's Uptime

Ivar Sagemo

Here's an eight-letter word, twice as bad as any four-letter word, that no business leader wants to hear: downtime. Today's businesses are far more dependent on IT services than ever, and that's true whether you're talking about internal IT services (like ERP) used to drive strategic operations, or external IT services used to satisfy client and customer demand.

Among the more daunting long-term potential consequences of downtime to the organization are these:

• Lost revenues because business couldn't be transacted. A recent Ponemon study tells us the average cost of downtime for US-based organizations is a stunning $5600/minute.

• Diminished brand strength, because the company is seen as unreliable. The same study suggests the average length of downtime was 90 minutes, leading to roughly $500K of costs per incident.

• Evaporating market share, because unhappy customers go to competitors.

Quite a mess in short. And it's a mess that's rapidly getting bigger. Aberdeen Group found that between 2010 and 2012, the cost per hour of downtime climbed an average of 65%!

Now, all of this is obvious in my own area of application performance monitoring (APM), and while downtime is a problem, there is a bigger issue, more subtle lurking just beneath the surface. When we believe everything is running smoothly but don't know something is wrong, that’s when the most damage happens.

For instance, suppose a BizTalk-based service is up and running in a holistic sense, but operating in a subtly inconsistent manner — difficult to detect — that leads to lost transactions from time to time. By this I mean occasionally lost e-mails, lost database entries, lost purchase orders, etc. Time spent by customers resending email and clients waiting or employees spending time looking for an invoice that has not come through – all of these cause more loss in productivity and reputation over a longer period of time.

According to Pricewaterhouse Coopers, the average organization, spends $120 searching for a lost document and wastes 25 hours recreating each lost document.* But what we don't know is how much productivity is lost through not knowing when a problem exists, searching for a file that is not lost at all. Waiting on document resends, searching for "missing" invoices or customer relationships that need to be repaired due to an apparent miscommunication because information is not flowing smoothly in a system all impact company efficiency and costs.

Application performance, and service uptime, can be affected by myriad factors — some as subtle as a gradual shortage of key computational resources. That's why it's important to find a way to granularly monitor your system. To have control and visibility over the problems that are happening so you can decide which ones to tackle is key.

Over time, I think we're going to see that kind of granular insight play a larger and larger role in APM as a field. But in the meantime, it's important to have a clear view of the information that flows throughout your organization so you can see any problem lurking out of sight.

Ivar Sagemo is CEO of AIMS Innovation.

Related Links:

www.aimsinnovation.com

* DocuSense Blog: How Much are Lost Documents Costing You?

Hot Topics

The Latest

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...