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Lack of Visibility into IT Software Can Be Costly

Tim Flower

IT leaders have a tremendous influence on how their organization functions, setting the tone for how their teams respond to digital transformation and approach strategic challenges. Though economists are warning of a multi-year recession, Gartner predicts that IT spending will increase in 2023. As a result, IT decision makers are feeling the pressure to invest wisely when it comes to software applications, while also finding savings to offset some of the rising costs. However, research shows IT leaders don't understand how their employees are using company-issued tools.

The result? Expenses are higher than necessary, there is poor employee technology adoption — and the related risk of either under or over provisioning — and there is a lack of productivity associated with inconsistent configurations.


What Aren't IT Pros Seeing and What Is it Costing Them?

A recent study revealed only an alarming 5% of IT decision makers who report having complete visibility into employee adoption and usage of company-issued applications, demonstrating they are often unknowingly careless when it comes to software investments that can ultimately be costly in terms of time and resources.

On average, employees use between 11 and 50 software applications per day, with IT leaders unclear how many are actively in use, for how long, or how frequently, or how many seats (licenses) are available/used for each application.

Software licenses can easily eat large portions of an IT budget unnecessarily by teams unknowingly subscribing to overlapping or unnecessary applications, in addition to employees retaining licenses from a prior role, or using applications they are not licenced to have, all which multiply spending. The fix, in theory, is simple: Organizations can avoid overspending by creating visibility into application usage, consolidating like-for-like software, and prioritizing applications that already share similar data and don't require hard labor to create integrations. In actuality, IT leaders are in the dark about the specific applications being used and how, meaning efficient consolidation is difficult or impossible.

Think of it this way: if an organizations' subscription licenses add up to $500 in total per device across 20,000 employees, reducing unneeded license counts by a conservative 5% and consolidating like-for-like titles for an additional 5% improvement could provide $1M in cost reductions that could be booked as savings or reallocated to other more strategic initiatives.

The True Cost of Poor Visibility: Employee Productivity

For technology adoption to be successful IT needs the full support of management and the individual department heads where it is being deployed. If organizations had full visibility into how employees are using the technology at their disposal, they might uncover that their teams don't have a full grasp on how to even use the tools properly which costs time and resources to address and resolve resulting issues.

Over 70% of IT pros reported it takes their teams between 6 to 24 hours to fully resolve a single employee issue, whether it's a desktop or web application problem

For example, over 70% of IT pros reported it takes their teams between 6 to 24 hours to fully resolve a single employee issue, whether it's a desktop or web application problem. That time spent is a combination of technical issues coupled with usability and employee education and it keeps employees from doing their work and IT teams from focusing on larger issues.

More often than not, one application error is part of a larger network or device problem that exhibits itself across the application's user base that inhibits productivity long-term over a large number of people. Approaching these problems as widespread technology issues rather than individual incidents that impact one employee at a time, and looking at it from the perspective of the employees (all of them) can help IT team's see a bigger picture and get to the root of issues faster and for more people all at once.

So, What Now?

IT pros are in a difficult position amid a looming recession which calls for efficient IT investment from the C-suite, yet data shows many aren't even clear on what tools they already have in place and what capabilities they are missing. With top level executives paying closer attention to overall digital transformation that is necessary for long-term success, it's crucial that IT leaders know how their organizations use their software and applications, and how that usage can be better managed for improved financial management in the future.

There are several ways to achieve this: implementing employee surveys, technical education for employees on their tools, and monitoring services to better see the full utilization picture. The onus, then, is on IT leaders to understand how to use this information for full organizational efficiency and cost savings.

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Lack of Visibility into IT Software Can Be Costly

Tim Flower

IT leaders have a tremendous influence on how their organization functions, setting the tone for how their teams respond to digital transformation and approach strategic challenges. Though economists are warning of a multi-year recession, Gartner predicts that IT spending will increase in 2023. As a result, IT decision makers are feeling the pressure to invest wisely when it comes to software applications, while also finding savings to offset some of the rising costs. However, research shows IT leaders don't understand how their employees are using company-issued tools.

The result? Expenses are higher than necessary, there is poor employee technology adoption — and the related risk of either under or over provisioning — and there is a lack of productivity associated with inconsistent configurations.


What Aren't IT Pros Seeing and What Is it Costing Them?

A recent study revealed only an alarming 5% of IT decision makers who report having complete visibility into employee adoption and usage of company-issued applications, demonstrating they are often unknowingly careless when it comes to software investments that can ultimately be costly in terms of time and resources.

On average, employees use between 11 and 50 software applications per day, with IT leaders unclear how many are actively in use, for how long, or how frequently, or how many seats (licenses) are available/used for each application.

Software licenses can easily eat large portions of an IT budget unnecessarily by teams unknowingly subscribing to overlapping or unnecessary applications, in addition to employees retaining licenses from a prior role, or using applications they are not licenced to have, all which multiply spending. The fix, in theory, is simple: Organizations can avoid overspending by creating visibility into application usage, consolidating like-for-like software, and prioritizing applications that already share similar data and don't require hard labor to create integrations. In actuality, IT leaders are in the dark about the specific applications being used and how, meaning efficient consolidation is difficult or impossible.

Think of it this way: if an organizations' subscription licenses add up to $500 in total per device across 20,000 employees, reducing unneeded license counts by a conservative 5% and consolidating like-for-like titles for an additional 5% improvement could provide $1M in cost reductions that could be booked as savings or reallocated to other more strategic initiatives.

The True Cost of Poor Visibility: Employee Productivity

For technology adoption to be successful IT needs the full support of management and the individual department heads where it is being deployed. If organizations had full visibility into how employees are using the technology at their disposal, they might uncover that their teams don't have a full grasp on how to even use the tools properly which costs time and resources to address and resolve resulting issues.

Over 70% of IT pros reported it takes their teams between 6 to 24 hours to fully resolve a single employee issue, whether it's a desktop or web application problem

For example, over 70% of IT pros reported it takes their teams between 6 to 24 hours to fully resolve a single employee issue, whether it's a desktop or web application problem. That time spent is a combination of technical issues coupled with usability and employee education and it keeps employees from doing their work and IT teams from focusing on larger issues.

More often than not, one application error is part of a larger network or device problem that exhibits itself across the application's user base that inhibits productivity long-term over a large number of people. Approaching these problems as widespread technology issues rather than individual incidents that impact one employee at a time, and looking at it from the perspective of the employees (all of them) can help IT team's see a bigger picture and get to the root of issues faster and for more people all at once.

So, What Now?

IT pros are in a difficult position amid a looming recession which calls for efficient IT investment from the C-suite, yet data shows many aren't even clear on what tools they already have in place and what capabilities they are missing. With top level executives paying closer attention to overall digital transformation that is necessary for long-term success, it's crucial that IT leaders know how their organizations use their software and applications, and how that usage can be better managed for improved financial management in the future.

There are several ways to achieve this: implementing employee surveys, technical education for employees on their tools, and monitoring services to better see the full utilization picture. The onus, then, is on IT leaders to understand how to use this information for full organizational efficiency and cost savings.

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 ...