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4 Tips for Taking Your Money Back Through Software Optimization

Tim Flower

When Marc Andreessen famously wrote in 2011, "software is eating the world" his prediction was that software companies would disrupt traditional ones, which they did; Amazon, Uber, Netflix, Airbnb are all great examples. But what comes next? As software adoption rises and continues to disrupt traditional businesses, software licenses start to "eat away" at enterprise budgets.

Why and how is this the case?


Source: Nexthink

The complexity of enterprise IT environments is often vast due to a combination of legacy systems, upgrades from digital transformation projects, and disparate departments creating complex application portfolios and duplicate contracts.

As an example, just looking at project management platforms. This problem could result in half a dozen or more different project management tools across the same or more departments and hundreds of employees — and that's just an estimate of the duplicates and complexity. As employees change jobs and roles, deployed software can also go unused, leaving that project management app in place but dormant. And swap out "project management tool" for any other type of function: application development; collaboration; photo and video editing, and the list goes on and on.

And if your company hasn't adopted standardization as a practice, or has disparate IT shops, the problem can be even worse. Looking across 6 million devices in a study conducted by Nexthink, we found unused software licenses that account for $44,743,651 lost per month, or $84 per device per year. That may not sound like a lot on its own, but it is equal to $840k per year for every 10,000 devices. And considering only 5% of IT leaders claim "complete visibility" into the total number of software licenses being used by their employees, it's safe to say many organizations are in dire need of a better strategy.

Thankfully, there is a way to provide the right software licenses where needed without impacting employee productivity or wasting much needed budget.

Simply put, Software License Optimization is a strategy focused on making a single procured software license, or group of licenses, as cost-efficient and effective as possible through the management of software license counts, usage and cost. The focus of the strategy should be centered around software standards and usage to avoid losing money on unused or redundant software.

So how can it be done?

1. Start with a Software Usage Audit

Data is always key. Having the right data when entering into software negotiations gives IT leaders the upper hand. Often times, organizations end up buying more licenses than necessary (a "buffer") at the suggestion of the software vendor. In fact, a recent study uncovered that IT decision makers are roughly aware employees use between 11-50 applications every day but were unsure how many of those were actively used and how many seats (licenses) were available.

By knowing exactly what employees are using and how many licenses you need, you avoid overspending. So, before you look into buying licenses, start with an audit to get insight into how many licenses are installed but not being used; which licenses aren't being used often; and which are staples in your employees' day-to-day jobs.

2. Create Digital Personas Based on IT Usage Traits

The balance between efficiency, cost-effectiveness, and a strategy that fits everyone's needs is tough. A one-size-fits all approach is easy to implement but it likely won't meet everyone's needs and therefore isn't an efficient way of creating a positive digital experience. It would be great to be able to give every employee a personalized experience, but that wouldn't be very cost-effective.

So, what's the answer? Smart persona building can help create the balance between a personalized experience within a reasonable budget and use of resources. To accomplish this, you'll want to start by organizing employees using binary and variable IT traits.

Binary IT traits are the most clear-cut and require yes/no or this/that qualifications. For example, the question might be whether an employee's application mix and performance will require the four core or eight core CPU device. Those who need four would get one persona and those who need eight would get another. Same questions for RAM, drive space, graphics, etc.

Variable IT traits require numerical calculations that measure an individual construct such as "how much time is an employee accessing Microsoft Teams throughout the day." It is more focused on how much an employee is exhibiting a behavior as opposed to the simple binary choice. Creating a persona should combine both binary and variable traits.

3. Monitor Costs of Employee Software Usage

While a software usage audit is important to start your optimization journey, a one-time audit won't be sufficient in providing an accurate picture of changing software costs. Since employee software usage evolves over time, continuous monitoring is vital to identify potential cost reduction opportunities. One way IT teams can do this is through dashboards which allow teams to visualize what software is being used and what software is not. From there they can make an informed decision around software licenses.

4. Focus on Data-Driven Decisions

It is important to remember that even if software is being used on an occasional basis, it doesn't mean it isn't extremely important to certain employees. By combining usage data with employee sentiment data, you can corroborate employee feedback with employee software habits. This way IT leaders can make changes that reduce cost without it adversely effecting employee productivity.

These four steps will kickstart your software optimization strategy, but to be successful it should be an ongoing process with each step performed on a regular basis. Software usage audits should be a recurring initiative to ensure the software being offered is still the most–cost-effective and used solution. Employee turnover and company re-organization means employee personas should be re-examined on a regular basis and updated as needed. By paying closer attention to when, who and why employees are using software, IT teams can make the best decisions on value vs cost for the business — ensuring your budget isn't being "eaten up" by unnecessary or unused software licenses.

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4 Tips for Taking Your Money Back Through Software Optimization

Tim Flower

When Marc Andreessen famously wrote in 2011, "software is eating the world" his prediction was that software companies would disrupt traditional ones, which they did; Amazon, Uber, Netflix, Airbnb are all great examples. But what comes next? As software adoption rises and continues to disrupt traditional businesses, software licenses start to "eat away" at enterprise budgets.

Why and how is this the case?


Source: Nexthink

The complexity of enterprise IT environments is often vast due to a combination of legacy systems, upgrades from digital transformation projects, and disparate departments creating complex application portfolios and duplicate contracts.

As an example, just looking at project management platforms. This problem could result in half a dozen or more different project management tools across the same or more departments and hundreds of employees — and that's just an estimate of the duplicates and complexity. As employees change jobs and roles, deployed software can also go unused, leaving that project management app in place but dormant. And swap out "project management tool" for any other type of function: application development; collaboration; photo and video editing, and the list goes on and on.

And if your company hasn't adopted standardization as a practice, or has disparate IT shops, the problem can be even worse. Looking across 6 million devices in a study conducted by Nexthink, we found unused software licenses that account for $44,743,651 lost per month, or $84 per device per year. That may not sound like a lot on its own, but it is equal to $840k per year for every 10,000 devices. And considering only 5% of IT leaders claim "complete visibility" into the total number of software licenses being used by their employees, it's safe to say many organizations are in dire need of a better strategy.

Thankfully, there is a way to provide the right software licenses where needed without impacting employee productivity or wasting much needed budget.

Simply put, Software License Optimization is a strategy focused on making a single procured software license, or group of licenses, as cost-efficient and effective as possible through the management of software license counts, usage and cost. The focus of the strategy should be centered around software standards and usage to avoid losing money on unused or redundant software.

So how can it be done?

1. Start with a Software Usage Audit

Data is always key. Having the right data when entering into software negotiations gives IT leaders the upper hand. Often times, organizations end up buying more licenses than necessary (a "buffer") at the suggestion of the software vendor. In fact, a recent study uncovered that IT decision makers are roughly aware employees use between 11-50 applications every day but were unsure how many of those were actively used and how many seats (licenses) were available.

By knowing exactly what employees are using and how many licenses you need, you avoid overspending. So, before you look into buying licenses, start with an audit to get insight into how many licenses are installed but not being used; which licenses aren't being used often; and which are staples in your employees' day-to-day jobs.

2. Create Digital Personas Based on IT Usage Traits

The balance between efficiency, cost-effectiveness, and a strategy that fits everyone's needs is tough. A one-size-fits all approach is easy to implement but it likely won't meet everyone's needs and therefore isn't an efficient way of creating a positive digital experience. It would be great to be able to give every employee a personalized experience, but that wouldn't be very cost-effective.

So, what's the answer? Smart persona building can help create the balance between a personalized experience within a reasonable budget and use of resources. To accomplish this, you'll want to start by organizing employees using binary and variable IT traits.

Binary IT traits are the most clear-cut and require yes/no or this/that qualifications. For example, the question might be whether an employee's application mix and performance will require the four core or eight core CPU device. Those who need four would get one persona and those who need eight would get another. Same questions for RAM, drive space, graphics, etc.

Variable IT traits require numerical calculations that measure an individual construct such as "how much time is an employee accessing Microsoft Teams throughout the day." It is more focused on how much an employee is exhibiting a behavior as opposed to the simple binary choice. Creating a persona should combine both binary and variable traits.

3. Monitor Costs of Employee Software Usage

While a software usage audit is important to start your optimization journey, a one-time audit won't be sufficient in providing an accurate picture of changing software costs. Since employee software usage evolves over time, continuous monitoring is vital to identify potential cost reduction opportunities. One way IT teams can do this is through dashboards which allow teams to visualize what software is being used and what software is not. From there they can make an informed decision around software licenses.

4. Focus on Data-Driven Decisions

It is important to remember that even if software is being used on an occasional basis, it doesn't mean it isn't extremely important to certain employees. By combining usage data with employee sentiment data, you can corroborate employee feedback with employee software habits. This way IT leaders can make changes that reduce cost without it adversely effecting employee productivity.

These four steps will kickstart your software optimization strategy, but to be successful it should be an ongoing process with each step performed on a regular basis. Software usage audits should be a recurring initiative to ensure the software being offered is still the most–cost-effective and used solution. Employee turnover and company re-organization means employee personas should be re-examined on a regular basis and updated as needed. By paying closer attention to when, who and why employees are using software, IT teams can make the best decisions on value vs cost for the business — ensuring your budget isn't being "eaten up" by unnecessary or unused software licenses.

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 ...