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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

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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

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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 ...