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Optimize Your Team's Time and Resources to Get the Most Out of Your Applications

Gary Mann

In order to be successful, companies need to ensure that all three parts of the age-old IT adage are optimized — people, processes, and technology. My last blog, 3 Tips for Reining in Your Application Portfolio, covered technology-oriented best practices that application management and IT help desks can use to optimize the performance of their applications and the IT teams that oversee them. Now I'll explore what IT professionals can do to optimize their team's time and resources — the people and processes — in pursuit of that same goal.

For professionals who oversee application management and IT help desks, no one day is the same. Most wear many hats — supervising everything from the applications on which the organization depends, to taking care of the innumerable support requests that arise each day. Technology acumen is important, of course, but it's merely one piece of the "technology, people, and processes" required to succeed in such a multi-faceted role. That's why no discussion of application management is complete without exploring what can be done to ensure that processes best serve the people involved, and that these individuals are engaged in a cohesive effort.

In the course of my work, I've been fortunate to engage in projects that show how some of the world's most successful companies tackle this reality. What I've learned working with those companies to eliminate IT inefficiencies and best manage their application portfolios is applicable to organizations of all sizes, in all industries.

Perhaps most importantly, these lessons will only increase in relevance in the months and years to come. Application portfolios will continue to grow in scope as automation simultaneously plays a greater role in workflows. As a result, the potential for staff and IT inefficiencies will continue to increase. It does not matter what industry you are in, it's imperative to have processes in place to address these realities.

How can you do this effectively? Following are several best practices to ensure that you keep IT and staff inefficiencies in check, ensure the success of your application management efforts, and optimize the performance of your application portfolio to better serve those who rely on it.

Don't get bogged down in the now

If you are having issues with your staff, application portfolio, support processes, or needy or demanding users — these are "now" issues, not long-term priorities that will determine your direction moving forward. They are of course important and must be dealt with, but all too often, IT teams can get bogged down by the myriad details that arise around these activities, and in the process miss opportunities to attend to the underlying, root causes of inefficiencies.

One example is often encountered at hospitals. Physicians rightfully expect immediate action by the IT team when any application issues impact patient care, but it's important to separate those issues from ones that can reasonably be dealt with in a more measured fashion. Users' egos must be recognized and dealt with.

Similarly, make sure your IT organization does not lose its strategic focus

Maintaining a strategic focus, and separating it from the innumerable demands you're facing now, ultimately enables you to do more and provide higher quality service. Make sure you don't lose focus on what your staff needs to manage and support your growing application portfolio, acquire new skill sets to support new technologies — such as artificial intelligence, automation, and more — and remain nimble in order to meet the business needs of your team and the end users they serve. This includes having the right balance of skill sets on your team to address both maintenance and support needs, as well as your strategic priorities. Your expensive and experienced staff should not be unable to take on your strategic priorities because they are overwhelmed by maintenance and support-related tasks.

Build a team based on a functional breakdown versus an application breakdown

This will enable you to combine functions across the overall skill set and create opportunities for application performance and process/workflow improvements, operational efficiencies, and ultimately, cost savings.

For example, if a client has three different financial systems and they have three different people doing the same thing — each in a different application, but supporting common functions — the skill set can be identified, applied at a functional level, and result in one person performing these common tasks across the three applications. This creates efficiencies and saves money and time.

Make sure your team, and overall efforts, are dedicated to delivering quality

A steadfast commitment to quality and a dedicated quality program will be the key to managing your application portfolio today and in the future. An effective quality program is essentially one that is focused on the alignment of the people and processes needed for success, and the technology they require. It can be an expensive undertaking in the beginning, but one that will pay off many times over in the end once everyone understands their role and acts on it in an efficient manner.

By keeping these best practices in mind and applying the right technology to your efforts, IT teams can work confidently knowing that they are getting the most out of their applications and teams that oversee them. Perhaps most importantly, they will know they are providing the singular support end users need to be most effective.

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 ...

Optimize Your Team's Time and Resources to Get the Most Out of Your Applications

Gary Mann

In order to be successful, companies need to ensure that all three parts of the age-old IT adage are optimized — people, processes, and technology. My last blog, 3 Tips for Reining in Your Application Portfolio, covered technology-oriented best practices that application management and IT help desks can use to optimize the performance of their applications and the IT teams that oversee them. Now I'll explore what IT professionals can do to optimize their team's time and resources — the people and processes — in pursuit of that same goal.

For professionals who oversee application management and IT help desks, no one day is the same. Most wear many hats — supervising everything from the applications on which the organization depends, to taking care of the innumerable support requests that arise each day. Technology acumen is important, of course, but it's merely one piece of the "technology, people, and processes" required to succeed in such a multi-faceted role. That's why no discussion of application management is complete without exploring what can be done to ensure that processes best serve the people involved, and that these individuals are engaged in a cohesive effort.

In the course of my work, I've been fortunate to engage in projects that show how some of the world's most successful companies tackle this reality. What I've learned working with those companies to eliminate IT inefficiencies and best manage their application portfolios is applicable to organizations of all sizes, in all industries.

Perhaps most importantly, these lessons will only increase in relevance in the months and years to come. Application portfolios will continue to grow in scope as automation simultaneously plays a greater role in workflows. As a result, the potential for staff and IT inefficiencies will continue to increase. It does not matter what industry you are in, it's imperative to have processes in place to address these realities.

How can you do this effectively? Following are several best practices to ensure that you keep IT and staff inefficiencies in check, ensure the success of your application management efforts, and optimize the performance of your application portfolio to better serve those who rely on it.

Don't get bogged down in the now

If you are having issues with your staff, application portfolio, support processes, or needy or demanding users — these are "now" issues, not long-term priorities that will determine your direction moving forward. They are of course important and must be dealt with, but all too often, IT teams can get bogged down by the myriad details that arise around these activities, and in the process miss opportunities to attend to the underlying, root causes of inefficiencies.

One example is often encountered at hospitals. Physicians rightfully expect immediate action by the IT team when any application issues impact patient care, but it's important to separate those issues from ones that can reasonably be dealt with in a more measured fashion. Users' egos must be recognized and dealt with.

Similarly, make sure your IT organization does not lose its strategic focus

Maintaining a strategic focus, and separating it from the innumerable demands you're facing now, ultimately enables you to do more and provide higher quality service. Make sure you don't lose focus on what your staff needs to manage and support your growing application portfolio, acquire new skill sets to support new technologies — such as artificial intelligence, automation, and more — and remain nimble in order to meet the business needs of your team and the end users they serve. This includes having the right balance of skill sets on your team to address both maintenance and support needs, as well as your strategic priorities. Your expensive and experienced staff should not be unable to take on your strategic priorities because they are overwhelmed by maintenance and support-related tasks.

Build a team based on a functional breakdown versus an application breakdown

This will enable you to combine functions across the overall skill set and create opportunities for application performance and process/workflow improvements, operational efficiencies, and ultimately, cost savings.

For example, if a client has three different financial systems and they have three different people doing the same thing — each in a different application, but supporting common functions — the skill set can be identified, applied at a functional level, and result in one person performing these common tasks across the three applications. This creates efficiencies and saves money and time.

Make sure your team, and overall efforts, are dedicated to delivering quality

A steadfast commitment to quality and a dedicated quality program will be the key to managing your application portfolio today and in the future. An effective quality program is essentially one that is focused on the alignment of the people and processes needed for success, and the technology they require. It can be an expensive undertaking in the beginning, but one that will pay off many times over in the end once everyone understands their role and acts on it in an efficient manner.

By keeping these best practices in mind and applying the right technology to your efforts, IT teams can work confidently knowing that they are getting the most out of their applications and teams that oversee them. Perhaps most importantly, they will know they are providing the singular support end users need to be most effective.

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 ...