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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.

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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 ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...