Skip to main content

3 Steps for IT Teams to Turn Their Attention Towards Driving Revenue

James Field
LogicMonitor

As IT practitioners, we often find ourselves fighting fires rather than proactively getting ahead. Almost three-quarters (74%) of IT managers spend more than a full business day each week reacting to incidents, making it extremely difficult to work on what leaders want their teams do — like providing business value and looking for ways to improve customer experience. Many spend countless hours managing several tools that give them different, fractured views of their own work — which isn't an effective use of time.

Balancing daily technical tasks with long-term company goals requires a three-step approach. I'll share these steps and tips for others to do the same.

1. Identify what your impact on the bottom line should be

Depending on your role, your day-to-day output will look different, and your impact on the organization's greater goals should vary accordingly. While it may not be immediately obvious how each team's impact is perceived, it's crucial to recognize that developers and IT teams play a critical role in business success.

Starting simply: focus on the quality of your work. Is it error-free? Saving others time? Requiring input from other teams to be final? Check all these boxes consistently before shooting for the moon.

This big-picture thinking is often the more enjoyable and impactful work, like innovating for the business — that you can already do today. Keep current with releases and make sure you're on top of the best practices for your industry and role. You'll be surprised by the value you can provide and the heights you can reach using the tools already at your fingertips.

Or, it could be helping others do the same — I refer to this as resilience. Be the one to document and explain processes you've set up and succeeded with so others can follow your lead or help enhance your processes.

2. Don't overthink it!

There are many schools of thought when it comes to prioritization in the workplace, but I believe in the old adage KISS — "Keep it simple, stupid!" You could spend the better years of your career tinkering with the best tools available, over-indexing on the minute ways you can maximize productivity, or … you can just do it.

I begin by blocking off time on my calendar (see, simple!) to devote myself to thinking about how I'm "moving the needle." Then, I hone in on a problem that has been plaguing me, my team or our customers lately, and think about how to solve it. For example, it could be increasing the uptime or availability of a critical piece of infrastructure. Ask yourself:

What improvements could I make?

What is currently the best practice for solving this problem?

How could I simplify, automate or anticipate to make this better and even more resilient?

3. Work smarter, not harder

Keeping it simple, in my world, still involves taking advantage of the tools that can make our lives easier. If your role involves regular and repetitive tasks, scripting is your new best friend. Batch and script what you can to cut down the time you spend on tasks that AI can easily pick up (with your oversight, always). And for those tedious administrative tasks, lean on an AI co-pilot so you can focus on the work you want to be doing.

Another way to work smarter, not harder is to provide product feedback directly to its developer and product team. If I'm struggling with something, or sinking a lot of time into making something work, others likely are too. Speaking from my own experience, product teams truly value feedback straight from users, and you're likely to influence the development of tools in a direction that benefits you and your work. Win-win.

At the end of the day, it's important to start by viewing your work as essential to the business, then prioritizing tasks and dedicating time accordingly. When done effectively, your managers, teams and maybe even customers will notice.

James Field is Sr. Director of Product Strategy and Operations at LogicMonitor

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

3 Steps for IT Teams to Turn Their Attention Towards Driving Revenue

James Field
LogicMonitor

As IT practitioners, we often find ourselves fighting fires rather than proactively getting ahead. Almost three-quarters (74%) of IT managers spend more than a full business day each week reacting to incidents, making it extremely difficult to work on what leaders want their teams do — like providing business value and looking for ways to improve customer experience. Many spend countless hours managing several tools that give them different, fractured views of their own work — which isn't an effective use of time.

Balancing daily technical tasks with long-term company goals requires a three-step approach. I'll share these steps and tips for others to do the same.

1. Identify what your impact on the bottom line should be

Depending on your role, your day-to-day output will look different, and your impact on the organization's greater goals should vary accordingly. While it may not be immediately obvious how each team's impact is perceived, it's crucial to recognize that developers and IT teams play a critical role in business success.

Starting simply: focus on the quality of your work. Is it error-free? Saving others time? Requiring input from other teams to be final? Check all these boxes consistently before shooting for the moon.

This big-picture thinking is often the more enjoyable and impactful work, like innovating for the business — that you can already do today. Keep current with releases and make sure you're on top of the best practices for your industry and role. You'll be surprised by the value you can provide and the heights you can reach using the tools already at your fingertips.

Or, it could be helping others do the same — I refer to this as resilience. Be the one to document and explain processes you've set up and succeeded with so others can follow your lead or help enhance your processes.

2. Don't overthink it!

There are many schools of thought when it comes to prioritization in the workplace, but I believe in the old adage KISS — "Keep it simple, stupid!" You could spend the better years of your career tinkering with the best tools available, over-indexing on the minute ways you can maximize productivity, or … you can just do it.

I begin by blocking off time on my calendar (see, simple!) to devote myself to thinking about how I'm "moving the needle." Then, I hone in on a problem that has been plaguing me, my team or our customers lately, and think about how to solve it. For example, it could be increasing the uptime or availability of a critical piece of infrastructure. Ask yourself:

What improvements could I make?

What is currently the best practice for solving this problem?

How could I simplify, automate or anticipate to make this better and even more resilient?

3. Work smarter, not harder

Keeping it simple, in my world, still involves taking advantage of the tools that can make our lives easier. If your role involves regular and repetitive tasks, scripting is your new best friend. Batch and script what you can to cut down the time you spend on tasks that AI can easily pick up (with your oversight, always). And for those tedious administrative tasks, lean on an AI co-pilot so you can focus on the work you want to be doing.

Another way to work smarter, not harder is to provide product feedback directly to its developer and product team. If I'm struggling with something, or sinking a lot of time into making something work, others likely are too. Speaking from my own experience, product teams truly value feedback straight from users, and you're likely to influence the development of tools in a direction that benefits you and your work. Win-win.

At the end of the day, it's important to start by viewing your work as essential to the business, then prioritizing tasks and dedicating time accordingly. When done effectively, your managers, teams and maybe even customers will notice.

James Field is Sr. Director of Product Strategy and Operations at LogicMonitor

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...