Skip to main content

Meet the Newest Profit Center to Join the Enterprise: The IT Department

No Longer Just a Cost Center, IT Must Think Long-Term and Leave a New Legacy of ROI
Tim Flower

For decades IT departments have been regarded as "cost centers" — departments and entire divisions made up of necessary expenses which don't produce any measurable profit but instead help companies avoid losses by ensuring uptime, addressing end-user concerns and implementing C-suite approved technologies. As noted by the Harvard Business Review (HBR), however, this attitude is changing: Companies now recognize the potential of IT departments to drive total ROI and boost the bottom line.

To live up to this new role, however, IT must lose the short-term mindset, which, to be fair, has often been necessitated by one-off and sudden-impact issues. IT managers must adopt a long-term strategy in order to create new revenue, improve profitability, future-proof the corporate technology landscape and leave an ROI legacy.

Changing Conversation

According to a recent Forrester report, companies are coming around to a new way of thinking about IT, especially as applied to end-user experience management. Businesses now recognize the need to obtain ground-floor data about how end-users interact with IT systems "in the wild" instead of relying on pre-designed stress tests or waiting for front-line staff to submit IT tickets. The former method puts tech pros in a reactive rather than proactive position and encourages end-users to seek out their own answers, bypassing IT.

The Forrester data tells the tale: While 28 percent of companies put improved end-user productivity among their top-five goals, cutting the cost of end-user support was similarly prioritized. Leading their priorities was cutting the total cost of end-user operations using active monitoring tools. While not a revenue generator in isolation, this priority speaks to the emerging long view of IT departments: If real-time monitoring tools can reduce the costs of end-user operations by quickly addressing issues and determining root causes, this money can be re-invested into more "profitable" areas of IT such as deep-data analytics or social media tools.

Getting SaaSy

Another key driver of the emerging long-term view is the huge Software-as-a-Service market. As noted by WhaTech, the SaaS market is headed for a $170 billion-dollar value by 2025 as companies leverage the power of off-premise software. But it's not the only game in town — according to Forrester, companies must now bridge cloud-native, SaaS and packaged applications, all of which run on different platforms and may not play nicely together. The result? Thirty-six percent of companies surveyed by Forrester have adopted multiple clouds to ensure their SaaS stable can coexist with cloud-native offerings and in-house applications.

While this might seem short-sighted on the surface, it's a testament to the necessary future of IT: As cloud becomes ubiquitous, it only makes sense for companies to adopt the ideal combination of on-site, public and private clouds to cover all the bases. In effect, this doesn't limit IT potential but rather expands it, giving departments the room and resources they need to develop profitable initiatives rather than remaining locked in by limited network compatibility and outdated views of IT as a cost-center.

The role of IT is making a transition from a cost center that is simply chasing problems, to a profit center that is thinking long-term to implement strategic initiatives that leave a legacy of ROI. In doing so, IT needs to implement innovative tools and technologies, and work in collaboration enterprise-wide to better understand the needs and challenges of end-users to ensure a better business outcome.

Hot Topics

The Latest

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 ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

Meet the Newest Profit Center to Join the Enterprise: The IT Department

No Longer Just a Cost Center, IT Must Think Long-Term and Leave a New Legacy of ROI
Tim Flower

For decades IT departments have been regarded as "cost centers" — departments and entire divisions made up of necessary expenses which don't produce any measurable profit but instead help companies avoid losses by ensuring uptime, addressing end-user concerns and implementing C-suite approved technologies. As noted by the Harvard Business Review (HBR), however, this attitude is changing: Companies now recognize the potential of IT departments to drive total ROI and boost the bottom line.

To live up to this new role, however, IT must lose the short-term mindset, which, to be fair, has often been necessitated by one-off and sudden-impact issues. IT managers must adopt a long-term strategy in order to create new revenue, improve profitability, future-proof the corporate technology landscape and leave an ROI legacy.

Changing Conversation

According to a recent Forrester report, companies are coming around to a new way of thinking about IT, especially as applied to end-user experience management. Businesses now recognize the need to obtain ground-floor data about how end-users interact with IT systems "in the wild" instead of relying on pre-designed stress tests or waiting for front-line staff to submit IT tickets. The former method puts tech pros in a reactive rather than proactive position and encourages end-users to seek out their own answers, bypassing IT.

The Forrester data tells the tale: While 28 percent of companies put improved end-user productivity among their top-five goals, cutting the cost of end-user support was similarly prioritized. Leading their priorities was cutting the total cost of end-user operations using active monitoring tools. While not a revenue generator in isolation, this priority speaks to the emerging long view of IT departments: If real-time monitoring tools can reduce the costs of end-user operations by quickly addressing issues and determining root causes, this money can be re-invested into more "profitable" areas of IT such as deep-data analytics or social media tools.

Getting SaaSy

Another key driver of the emerging long-term view is the huge Software-as-a-Service market. As noted by WhaTech, the SaaS market is headed for a $170 billion-dollar value by 2025 as companies leverage the power of off-premise software. But it's not the only game in town — according to Forrester, companies must now bridge cloud-native, SaaS and packaged applications, all of which run on different platforms and may not play nicely together. The result? Thirty-six percent of companies surveyed by Forrester have adopted multiple clouds to ensure their SaaS stable can coexist with cloud-native offerings and in-house applications.

While this might seem short-sighted on the surface, it's a testament to the necessary future of IT: As cloud becomes ubiquitous, it only makes sense for companies to adopt the ideal combination of on-site, public and private clouds to cover all the bases. In effect, this doesn't limit IT potential but rather expands it, giving departments the room and resources they need to develop profitable initiatives rather than remaining locked in by limited network compatibility and outdated views of IT as a cost-center.

The role of IT is making a transition from a cost center that is simply chasing problems, to a profit center that is thinking long-term to implement strategic initiatives that leave a legacy of ROI. In doing so, IT needs to implement innovative tools and technologies, and work in collaboration enterprise-wide to better understand the needs and challenges of end-users to ensure a better business outcome.

Hot Topics

The Latest

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 ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...