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HDI Service & Support World
April 25-29, 2027
Caesars PalaceLas Vegas, NV
Why Nobody is Reading Your Reports

"When was the last time you sent a report that directly led to a decision? Not acknowledged; not read. When did it actually change something?"

This was the question that Micah Armstrong, IT manager at UT Dallas, posed to a standing room only audience at HDI Service & Support World during his session, “From Data to Decisions: Creating Impactful Reports for Service Management.” Nobody raised their hand.

“You don’t want to be data rich and insight poor,” Armstrong says. “You have the data, but you’ve got to find the insight.”

This can be tricky because our industry has built an entire culture around data in IT service management. We track contacts, reopen rates, first contact resolution, customer satisfaction, handle time, blah, blah, blah. But most of the time, no matter how good the report looks, nobody does anything differently because of it.

Armstrong thinks this is because too many reports are bloated with data and are visually confusing. When he’s putting together a report, he decides which data point gets in by asking himself this question: If this number goes up or down, what will someone do differently? If he can’t answer that question, he doesn’t include the data point.

“A report to be useful needs to influence a decision, a conversation or direction,” Armstrong says. “You also have to accept that you can’t serve everyone in your organization with one report. Nobody knows what to look at.”

He talked about what each stakeholder group wants to know:

  • Executives want a few KPIs. Are we meeting our commitments? Is there something I need to be concerned about? “They’re looking for assurance because they’re making big decisions and don’t want to dive into individual ticket details,” Armstrong says.
  • Managers want friction. Where’s something taking a long time? How are my agents performing? Are customers happy? “This lets me know what needs to be prioritized next,” Armstrong says.
  • Frontline staff want the real-time data. What’s the priority? What’s coming next? “They want to know what’s happening right now,” Armstrong says.

When putting together the report, it’s important to understand the difference between activity metrics and insight metrics. A quick review:

  • An activity metric tells you what happened. Tickets opened, calls answered, calls missed.
  • An insight metric tells you what it means. First contact resolution rate, reopen rate, aging tickets. These are the numbers that prompt a question or demand an action.

Both types matter, but the mistake most people make is leading with activity, when they should be leading with insight.

“If your handle time drops, your first instinct is to celebrate,” Armstrong says. “But then, you pair that with an insight metric to get more understanding. Even if your handle time went down, maybe your open rate tripled. Maybe you’re doing things faster, but that might not necessarily be a good thing.”


Pick the right visual

A “pretty” report is not a clear report, Armstrong says.

“We often think: ‘I need to make this report look really good. It needs to impress someone,’” Armstrong says. “But if you include too much — too many numbers, too many extras — it gets harder to read.”

He shared a few design tips:

  • Trends over time go in a line chart. “Our brains are good at spotting movement over time,” Armstrong says. “Comparisons go in a bar or pie chart, but keep the pie to five or six categories maximum or it becomes impossible to read.”
  • Make single KPIs as big as possible. “Don't hide it in a corner,” Armstrong says. “Don’t put it in a pie chart. The number is what’s important.”
  • Use color deliberately. Red for bad, green for good, gray for neutral. Keep it simple.
  • Clean it up. “Don’t try to prove how much data you have,” Armstrong says.
    “The goal is to make the answer clear.”

Justin Powell, a deskside support technician at Oklahoma State University, said that Armstrong’s presentation resonated with him because they’re both in higher education and use similar tools.

“He’s been using the ITSM for about five years and even though my college has had it for a few months, I enjoyed seeing the possibilities of what can be put into a report,” Powell says. “Because of this presentation, I’m going to use visual charts to help convey information better.”


Be a storyteller

You can’t guarantee that everyone reading your report will think through it the way you did. In fact, you can probably guarantee the opposite, Armstrong says. The best way to solve this problem is to write down what the report means.

“When I send my boss monthly reports, I include a couple of bullet points or a few sentences to summarize what’s going on,” Armstrong says. “This reduces a lot of the friction, misinterpretation and reactive follow-ups you get when someone starts looking at it.”

Borrow this structure: context first (here’s what we’re looking at and why it matters), insight in the middle (here’s what the trend is showing and what the gap is), direction at the end (here’s what we’re doing or not doing about it).

“The best report doesn’t just look pretty,” Armstrong says. “It makes someone say: ‘I know exactly what I need to do next.’”



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.