The hidden cost of complacency and Jay Roland’s mission against corporate America’s technical debt crisis


Corporate America is hemorrhaging money through inefficient IT business processes, and Jay Roland, founder of Varex Solutions, believes that the industry is complacent about it. Technical debt, which is the accumulated cost of deferred IT fixes, misconfigurations, and other operational inefficiencies, is projected to cost US enterprises $2.41 trillion a year, costing $1.52 trillion to fix. With numbers this staggering, Roland argues that awareness, however, remains precariously low.

The numbers projected only tell part of the story,” he says. “The struggles companies are going through are far greater than any figure on a slide. I’ve walked into organizations spending $251 million a year on IT and found $51 million of it being wasted, year over year, on problems they didn’t even know existed.

Jay Roland

Jay Roland

To address the bottlenecks he witnessed, Roland launched Varex Solutions. The company functions within a specific pressure point, in the gap where enterprises believe their IT is costing them, and what it is actually costing them. Headquartered in Nashville, Tennessee, Varex offers a suite of consulting services spanning ITSM (IT Service Management) platform implementations, maturity assessments, health optimization, and SLA practice guidance.

According to Roland, the company’s key commitment is to uncover bottlenecks, technical debt, misconfigurations, and workflow inefficiencies and then turn those findings into actionable improvements that help increase ROI. This is achieved by Varex’s proprietary technical debt calculator. The tool, he explains, requires just three inputs from a company: industry, employee headcount, and annual revenue.

From those three data points, Roland’s algorithm, which he notes is built on years of archetypal industrial modelling, is designed to autofill an entire financial landscape. The output is intended to encompass a cohesive analysis of expenditure, wasted resources, action steps, and return on investment.

Roland explains, “There’s no AI involved in this entire process. This is all algorithmically structured technical debt assessments. There’s no point in telling someone they’re wasting money unless you can show them how to stop. Otherwise, it’s just noise. When I give you a number, I can show you exactly how I arrived at it, and your own IT team can verify it.

While most paths follow a direct pipeline shaped by education, Roland’s entry into the industry came through a side door, literally. In November 1999, he tagged along with a friend to a local internet service provider in Pontiac, Michigan, intending to play video games on the T3 line. Someone placed a broken computer on his desk and walked away. He started fixing it. “Ten minutes later, a manager walked by, glanced at the screen, and told me they’d put me on the payroll,” he recalls. “That was my entry into IT.

He carried that resourcefulness through a career that moved in and out of the industry, through the dot-com crash, through a tech support subscription startup he co-founded, and through a chapter advancing a popular role-playing game that handed him the exact spreadsheet modeling skillset he would later need to build Varex. Roland identifies this as his defining professional trait.

No matter what I do, I bring everything with me,” he says. “What started as projective analysis on character leveling in a Dungeons and Dragons-style game converted into using a spreadsheet software to optimize a quoting process, and eventually into the algorithms behind Varex Solutions. You never know when you’re going to need it.

Roland recalls growing up with modest means, without the cushion of inherited privilege, and he frames that experience as the source of his refusal to accept inefficiency as simply the cost of doing business, which now shapes his work. “The same water that boils the egg softens the potato,” he says. “Different people react differently to the same circumstances. It was sheer will and determination that got me here, to make something, to give my children something.

He rejects the common notion of walking into a boardroom with abstract consulting promises. Instead, Roland believes in handing executives a specific, verified number. He explains, “I show them: this is what you’re wasting, this is the proof, and this is how to fix it.” The calculator, he says, was built to close the distance between vague projections and hard accountability.

The resistance he often encounters tells its own story. “I once asked a CIO if I could help uncover $25 to $40 million a year in unnecessary IT spend,” he recalls. “But the response I received was one of indifference.” Roland believes this dynamic exists because uncovering decades of avoidable waste is a conversation most executives would prefer never to have. “Would you want to tell your CFO that you have been wasting tens of millions of dollars annually for all these years?” he asks.

The question Roland keeps returning to is a direct one: how bad does a problem have to get before the people responsible for it decide it’s actually a problem? How many misconfigurations have to stack up before the cumulative damage becomes unsustainable? That is the conversation Varex Solutions exists to propel forward, and on Roland’s timeline, it is already overdue.



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ZDNET’s key takeaways

  • Staff who use AI can end up with more to do, not less.
  • Think carefully about the tools you’re using and why.
  • Adopt a set of standards and refine your outputs.

The promise of productivity boosts from AI can come with an unwelcome side order of stress. Harvard Business Review found that AI doesn’t reduce work; it intensifies it, leading to cognitive fatigue and unsustainable hours.

While the common perception is that AI can help reduce workloads, allowing employees to focus more on higher-value and more engaging tasks, HBR’s research found that staff using AI worked more quickly and often ended up with more to do, not less.

Also: Forget productivity: Here are 5 strategic shifts that drive real AI value

While we’ve written about how some professionals are finding ways to turn AI’s time-saving magic into a productivity superpower, we’ve also recognized that some employees have started to become tired with the low quality of AI outputs.

Ankur Anand, group CIO at tech recruiter Harvey Nash, said professionals who want to avoid cognitive fatigue must understand how to use AI effectively and its potential risks.

“That focus will help to reduce the noise around the workload that AI creates,” he told ZDNET, suggesting that many people have unrealistic expectations about the productivity boost that AI will provide.

Also: Why I ditched Copilot for Claude in Word, Excel, and PowerPoint – and how you can, too

“Many organizations are telling their people, ‘We want to understand how you’re making an impact with AI,'” he said. “But these professionals are not empowered, which means that using AI adds a lot of pressure, because they need to prove themselves on their own terms.”

If you’re going to make the most of AI at work, then you’re going to have to find an effective balance between completing tasks quickly and producing high-quality work. 

Here’s how the experts believe professionals can ensure they reap the benefits, not the problems, of AI — and they suggest that you’ll need to focus on three core areas: tools, guidelines, and outputs.

Limit your toolset

Alex Read, senior enterprise product manager for data at energy provider EDF UK, told ZDNET that the best way for professionals to reap the benefits, not the challenges, of AI is to be uber-focused on tools that help you produce value in your roles.

While there are thousands of potential AI-enabled services on the market, Read said sensible professionals limit their horizons.

Also: How this travel company’s AI rollout drove a 73% satisfaction boost: A 5-step playbook for your business

In his own role, for example, Read focuses on how AI can help him build a data platform and update information accurately, efficiently, and productively: “Anything outside of that scope is noise for me.”

That sentiment resonated with Nick Pearson, CIO at technology specialist Ricoh Europe, who told ZDNET it’s important to take a step back and think carefully about how an AI tool can help you produce value in your role.

“If you think about the phrase ‘gen AI,’ the tech is very good, by definition, at generating outputs,” he said. “I could go to bed in the evening, set the model to work, and we could have four new IT strategies produced overnight.”

Also: Worried AI agents will replace you? 5 ways you can turn anxiety into action at work

However, quantity doesn’t necessarily mean quality. Pearson suggested it’s important to focus on AI’s blind spots, particularly as most models are trained on preexisting content.

“AI can’t inspire people, per se; it can’t naturally create something new, because it’s actually quite recursive,” he said.

“And the judgment you have to put in sometimes, on top of everything else, whether it be an ethical or a capability judgment, is not there automatically in the technology.”

It’s in this gap, said Pearson, that human experts play a critical role: “We’re toying with that concern as an organization and saying, ‘Where does AI really play an important role, versus where are we upskilling people in areas that AI probably won’t play for a long time?'”

Work to the guidelines

HBR’s research found that an initial productivity surge when AI is adopted can lead to lower-quality work, turnover, and other problems as people work harder rather than smarter.

To correct this issue, HBR said companies need to adopt an “AI practice,” or a set of norms and standards around AI use that help professionals ensure they use AI in a constrained but productive manner.

Also: 90% of AI projects fail – here are 3 ways to ensure yours doesn’t

At EDF UK, Read is part of an internal AI Center of Excellence in enterprise IT, which enables policy for the effective use of AI across the wider organization. 

In addition to Read, who contributes input from a data-use perspective, the group includes other tech representatives, such as the firm’s senior manager of AI, principal software engineer, and principal solution architect.

“The remit of this center is to make sure that, when the federated business units are looking to build, develop, and deploy AI services, they have platforms, guidance, best practices, architectural assets, and materials to guide them on how to safely and efficiently adopt AI and operationalize it at scale,” he said.

Some of the key themes the center considers when assessing AI tools are scalability and reusability, ensuring a proposed service doesn’t replicate one already in use.

Also: 5 ways to use AI when your budget is tight

“All new tools and services related to AI will go through that hopper and funnel to understand scope and ensure the security, regulatory, and ethical side of things are understood,” he said, suggesting that all professionals should use their organization’s pre-existing guidelines to foster an appropriate exploitation of emerging tech.

“The benefit that guided approach brings is that it allows us to be clear in our messaging around what AI services can be used, how they’re used from a use-case perspective, and ultimately, what personas are allowed to use them.”

Refine your outputs

Even when tools are assessed and considered acceptable, there can still be an overreliance on AI outputs. Worse, some professionals can drown in the insights they receive, leading to higher stress and fewer benefits.

Louise Newbury-Smith, head of UK&I at technology specialist Zoom, told ZDNET that one way to ensure your outputs are constrained is to focus on prompting.

“Use simple amendments to be specific, such as ‘Give me the top three things with the biggest impact.’ That approach should guide your prompt, rather than saying, ‘Give me everything you know about this topic.'”

Also: 5 ways to fortify your network against the new speed of AI attacks

Newbury-Smith said the successful use of AI is all about being smart about how it’s exploited, and that effectiveness comes down to enablement and engagement. If a prompt yields too much information, refine it until you get what you need. She said this should still be faster than trying to get answers without AI.

The basic message for professionals is that effective applications of AI are all about you staying in the loop, said Bernhard Seiser, vice president of digital, data, and IT at AOP Health.

Think before you use AI, and think again before you push your outputs around the organization.

“It doesn’t help the business if you get AI-generated emails that are many pages long, and then you need ChatGPT to summarize the text,” he told ZDNET.

Seiser said that while there are certain tasks generative AI is good at and worth using for, in the end, “you need to use your brain.”





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