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HDI Service & Support World
April 25-29, 2027
Caesars PalaceLas Vegas, NV
How Power Design Inc. Became a World-Class Service Desk

When Josh Nelson, Ph.D., joined Power Design Inc.’s service desk in 2019 as the director of technology experience, he called it the “worst service desk he’d ever seen.” Ouch. But his co-workers, sitting right next to him at the panel discussion at HDI Service & Support World, agreed with him.

He was joined by Thomas Gartner, senior manager of technology experience; Ray Brown, technology asset manager; and Daves Vargas, senior manager of global service. The four told the story of how they turned the service desk into something the C-suite was seriously considering outsourcing to a five-star, world-class SDI-certified operation.

Matt Beran, IT industry analyst at InvGate, moderated the discussion, and set up the backstory of how the service desk operated in 2019. At the time, the company had 2,500 employees and seven people on the IT team doing everything (technical support, new hire setup, shipping, receiving).

The service desk manager had a background in logistics, not tech. There were no processes, no knowledge base, no SLAs that meant anything in practice. Tickets would get escalated and disappear. Three separate email addresses existed for different types of IT help, and most users had no idea which one to use or whether anyone would respond.

Nelson took the audience on a step-by-step process of how he worked with the team to turn everything around.


Look at the data

When Nelson joined the company, the service desk team morale was low. He also had a sense that the metrics didn’t match how the team was performing. He dug into the backend and discovered the dashboard hadn’t refreshed in 60 days. It was showing frozen data with only slight variations as older records dropped off the date range.

Next, he pulled ticket volumes, calculated what each technician could handle given the team’s turnaround time expectations and SLA commitments, and built a staffing case. The number he landed on: 289 tickets per technician per year as a benchmark. Multiplied against total volume — 30,000 to 35,000 tickets annually — the math showed the team was running at roughly half the headcount it needed. BTW: Now, the team is at 10,000 tickets annually because the majority of the tickets are getting resolved proactively.


Improve morale with a rebrand

Hiring more people helped, but the team needed a reason to see themselves as something worth believing in. Nelson rebranded the department as ATLAS (All Things Logistics and Support).

“We are the backbone of this company,” Nelson says. “We’re not always looked at as something that should be celebrated, but we are absolutely essential to the whole situation.”

Nelson also launched a program called “My Impact,” where every team member made a weekly commitment to do something above and beyond their regular job description.

“At first, they were doing the low-hanging fruit, pretty easy stuff,” Nelson says. “But as time went on, you saw people really trying to push themselves to make the entire team better and make the organization better.”


Understand that perception is reality

Nelson came back to one phrase over and over throughout the session: “perception is reality.”

“It doesn’t matter how fast you solved something,” Nelson says. “You can provide the best service in the world, but if the person you’re giving it to doesn’t feel that way, then you didn’t. No matter what metric you measure against, no matter how you feel about it yourself, if the person you served isn’t satisfied, you haven’t delivered a great experience.”

To close that gap, Nelson’s team runs regular pulse surveys — one question, five-point scale: How satisfied are you with your IT experience? Then, he takes the results and sits down individually with every department head to compare notes.

Most recently, the team built an experience dashboard that pulls from endpoint analytics, Microsoft adoption scores and CSAT data. Everything is compiled into a single score per department, displayed with color-coded smiley faces.


Make metrics engaging for staff

When an audience member asked how to make metrics engaging for frontline staff, Nelson says to make it personal, without it being pointed. They display team dashboards on screens throughout their work area, updated continuously, so the numbers are always visible. Nelson reviews team metrics in group settings, but makes individual performance visible alongside them without calling anyone out directly.

“Nobody wants to be the low man,” Nelson says. “We’re talking about the team’s win, the team’s success or failure, but while I’m talking about that, the individual is looking at their score compared to everyone they work with. It keeps the engagement because you’re making it personal.”

Related news

Bridging the Gap: 5 Tips for Cross-Functional Collaboration That Enables AI Transformation

Ask ten executives who owns AI at their company, and you’ll get ten different answers. IT says it’s not their call. Legal gets blamed for slowing everything down. HR figures it’s someone else’s department. Meanwhile, teams are buying tools nobody signed off on, duplicating work and hoping it all sorts itself out. Sound familiar?

Lisa Duerre spent the last year studying why that happens. As part of an applied research project for her leadership consulting collective, RLD Group, she studied where AI adoption breaks down inside organizations, and where it works. The findings from RLD Group’s research helped inform a collaboration on the CONVERSATIONS WORTH HAVING®: The Human Accelerator for Artificial Intelligence Quick Start Guide, which is available as a digital download.

Duerre views organizations through what she calls an I–WE–US leadership framework, defined like this:

  • I: individual judgment and accountability

  • WE: workflows and cross-functional coordination

  • US: governance, decision rights and organizational measures

“All three levels are contributing to the breakdown or the alignment, whether people realize it or not,” Duerre says. “AI is amplifying whatever’s already true in your system. The teams that were disconnected before AI showed up are more disconnected now. The ones that talked to each other are moving faster, together.”

If your company is ready to collaborate better with AI tools, Duerre shared the following tips. Take a look.

Form a cross-functional AI committee

Duerre’s background is in HR, and she says most HR leaders assume AI ownership belongs to IT. It doesn’t, at least not exclusively.

“Ownership needs to sit at the system level,” Duerre says. “Each function carries a piece of it, based on what they do, how well they understand that part of the business and how their work depends on everyone else’s. AI is flattening how we work. You can’t just keep it in your own business unit anymore. You have to look all around you.”

For starters, she suggests building a cross-functional AI committee instead of having one department make all the AI decisions. Legal, IT, cybersecurity and HR should be on the committee, Duerre says.

“If you have a C in front of your title, you should be on that committee,” Duerre says. “That’s how I look at it, because it’s a system-level solution.”

During these meetings, Duerre says you’ll find out that some departments are racing ahead with AI and others are holding back.

“Both sides need to name the trade-offs aloud,” Duerre says. “With teams moving too cautiously, you have to talk about the opportunity cost of falling behind. With teams sprinting ahead, you have to ask them what happens if they don’t bring everyone else along with them.”

Figure out how to use AI strategically

Most companies spent the past two years telling employees to use AI with anything, without much strategy behind it. Duerre says that’s starting to catch up with organizations as finance teams scrutinize the cost.

Her rule of thumb: if you can’t articulate the goal and how you’ll measure success, don’t roll it out yet.

“Teams that use AI well have a strategy behind it,” Duerre says. “They’ve kicked the tires on what they’re trying to solve it for. You need to ask yourself, ‘Which business outcome are we trying to improve, and what must be aligned for AI to create measurable value?’”

Here are a few examples of how to use AI strategically:

  • A company could select a workflow that regularly creates delays, redesign it with AI and test the new approach. Then, measure whether it improves time, cost, quality or capacity.

  • Use AI to support early sales outreach and qualification across markets and languages. AI can help a business reach and assess more potential opportunities, while people remain responsible for understanding the customer and building trust.

  • Flag patterns in customer complaints across multiple channels with AI, so leadership can see recurring problems before it shows up in satisfaction scores.

Check-in regularly during an AI rollout

Duerre recommends a minimum weekly check-in during any AI rollout, sometimes daily depending on complexity. But the format matters more than the frequency. Status updates don’t cut it.

“Ask, ‘What are we learning and what are we surprised by?’ That’s a question that helps you with your check-ins, versus, ‘It’s in three products now and we’ve tested six,’” Duerre says. “That doesn't help, because you’re having these meetings to figure out what’s working and why. If you ask more strategic questions, you can move even faster.”

Publish AI guardrails

Employees who don’t know what’s allowed with AI will either freeze or go around the system entirely, Duerre says. She recommends publishing clear, specific guardrails on what’s okay and what’s not. Come up with some real examples, and pair them with an intake process that doesn’t require writing a thesis to get an approval for using it.

"The approval path should be lightweight, not bureaucratic,” Duerre says. “Something like, ‘If you’re going to use AI, here’s the path. And if it needs approval, here’s three or four quick questions for you to answer.’”

Take employee anxiety about AI seriously

“AI is just a tool” is a phrase Duerre hears at nearly every conference she attends, but she doesn’t buy it.

“Saying it’s a tool is underselling what’s happening at companies right now,” Duerre says. “AI is changing how we work. It’s changing how we lead teams.”

Duerre wants leaders to remember that a lot of employees are fearful of AI. Pew Research Center found 52% of U.S. workers are worried about the future impact of AI in the workplace.

Employees who feel AI is being “done to them,” instead of built alongside them are especially anxious, she says.

“Leaders need to recognize that anxiety is contagious,” Duerre says. “As a leader, this is your opportunity to show up as the safe, steady person who is showing what you’re learning with AI. And don’t be afraid to show how you’ve failed using AI, too.”

Duerre asks every executive she works with: “Who am I with AI?” and encourages them to pass this mindset question along to their employees, too.

“AI is now your teammate,” Duerre says. “Phrasing it as, ‘who am I with AI?’ is different than, ‘what’s going to happen to me with AI?’ You really want your team to feel empowered with AI and show them how it can help accelerate their career.”

Put these ideas into action

Rewiring your organization for AI requires more than the right tools. It takes shared language, practical frameworks, and a willingness to keep learning. Here are a few resources to help you take the next step.

  • Enterprise AI Playbook: Practical frameworks and executive discussion questions to help IT, HR, and business leaders align around AI that delivers measurable value.

  • Work-First AI Use Case Assessment: Identify the workflows where AI can have the greatest impact before you invest in new tools.

  • The REWIRED Brief: Get weekly insights, real-world case studies, and practical advice on leading AI transformation.

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