Skip to main content

ECM: Evolving, Critical and MANAGEABLE

Dave Gibson

My, how times have changed. Enterprise content management applications were once viewed as “backend” systems that were primarily focused on archival or records management processes. However, their role in organizations have grown and evolved. A recent survey executed by AIIM and Reveille shows that 80% agree their content systems are now just as critical to their business operations as transactional systems.

That’s no surprise given the fact that ECMs are often deployed for thousands of users, across a multitude of locations and have integrations with numerous customer-facing applications. But, all of this does shine a light on the need for constant uptime, in-depth platform visibility and trending of key performance indicators.

However, according to the same survey, the majority of respondents (57%) said they had nowhere near the same performance information about the content systems as they do for their transactional systems. Why the disconnect? What can be done to fix this?

Complex and Complicated

First, it is important to recognize that the growth in ECM systems’ criticality did not happen overnight. As organizations have grown, acquired other companies with competing applications, consolidated applications, added databases and servers – the entire ECM ecosystem has grown increasingly complex.

Many organizations have tried, often in vain, to manage these applications manually or at a thousand foot level with enterprise-standard monitoring solutions. Unfortunately, these approaches are also extremely complicated, costly, and time-consuming; and organizations still don’t get visibility into the specific processes that are unique to ECM. Regardless, both methods fail to deliver the necessary insight.

Often, the end result is an IT department that is stuck in a reactive mode, constantly responding to end-user calls rather than proactively preventing ECM issues in the first place. In fact, 72% of survey respondents described their current performance monitoring as “manual – triggered by incidents/support calls.”

Monitor, Measure and Manage

There has to be a better way. A better way to manage your business-critical content… A better way to spend your staff’s man-hours… A better way to ensure application performance.

As with so many technologies; they must be managed in a process-oriented way - from determining baselines that can be leveraged for threshold-based alerts, to defining service levels that can be agreed upon and measured, through trending key performance indicators to report on usage and enable better decision making. The only way to achieve this is an in-depth understanding of the ECM application platform and a management solution that stays current on the latest product releases.

So start monitoring and measuring the intricate details of your ECM with application-specific management solutions. Finally get the insight you need to provide key stakeholders with valuable reports and trending, ensure performance and service levels are optimized, and start focusing on more critical projects. And let’s all agree that yes, ECM has evolved. Yes, ECM is critical. And Yes, ECM applications are manageable.

Dave Gibson is COO of Reveille Software.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

ECM: Evolving, Critical and MANAGEABLE

Dave Gibson

My, how times have changed. Enterprise content management applications were once viewed as “backend” systems that were primarily focused on archival or records management processes. However, their role in organizations have grown and evolved. A recent survey executed by AIIM and Reveille shows that 80% agree their content systems are now just as critical to their business operations as transactional systems.

That’s no surprise given the fact that ECMs are often deployed for thousands of users, across a multitude of locations and have integrations with numerous customer-facing applications. But, all of this does shine a light on the need for constant uptime, in-depth platform visibility and trending of key performance indicators.

However, according to the same survey, the majority of respondents (57%) said they had nowhere near the same performance information about the content systems as they do for their transactional systems. Why the disconnect? What can be done to fix this?

Complex and Complicated

First, it is important to recognize that the growth in ECM systems’ criticality did not happen overnight. As organizations have grown, acquired other companies with competing applications, consolidated applications, added databases and servers – the entire ECM ecosystem has grown increasingly complex.

Many organizations have tried, often in vain, to manage these applications manually or at a thousand foot level with enterprise-standard monitoring solutions. Unfortunately, these approaches are also extremely complicated, costly, and time-consuming; and organizations still don’t get visibility into the specific processes that are unique to ECM. Regardless, both methods fail to deliver the necessary insight.

Often, the end result is an IT department that is stuck in a reactive mode, constantly responding to end-user calls rather than proactively preventing ECM issues in the first place. In fact, 72% of survey respondents described their current performance monitoring as “manual – triggered by incidents/support calls.”

Monitor, Measure and Manage

There has to be a better way. A better way to manage your business-critical content… A better way to spend your staff’s man-hours… A better way to ensure application performance.

As with so many technologies; they must be managed in a process-oriented way - from determining baselines that can be leveraged for threshold-based alerts, to defining service levels that can be agreed upon and measured, through trending key performance indicators to report on usage and enable better decision making. The only way to achieve this is an in-depth understanding of the ECM application platform and a management solution that stays current on the latest product releases.

So start monitoring and measuring the intricate details of your ECM with application-specific management solutions. Finally get the insight you need to provide key stakeholders with valuable reports and trending, ensure performance and service levels are optimized, and start focusing on more critical projects. And let’s all agree that yes, ECM has evolved. Yes, ECM is critical. And Yes, ECM applications are manageable.

Dave Gibson is COO of Reveille Software.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...