The Experience Intelligence Platform

The channel most people use isn't always the one that serves them best. Compare channels side by side and see where people lose the most time.

Hitting SLA targets and giving people a good experience aren't the same thing. See how your outsourced desk performs from the employee's side, not just the contract's.

Shift-left, self-service, and ticketless IT are all about bringing down the cost per ticket. The higher cost is the time employees lose, and almost nobody measures that.

A ticket closed too early usually comes back as a new one. Employee feedback shows where that's happening, so you don't need another report to find it.

A fixed refresh cycle replaces laptops people are still happy with and keeps ones that are costing them hours. Ask employees, and you'll see which devices can safely run another year and which need replacing now, whatever their age.

Someone says their laptop is slow, so it goes on the refresh list. Often, the laptop is fine, and the real problem is the VPN, WiFi, an application, or something else. That's a fix in days, not a new device.

Giving everyone the same laptop gets it wrong twice. Some people carry more machine than they'll ever use, and others wait on machines that can't keep up with their work. Employee feedback shows which roles are which across your organization.

A trackpad instead of a mouse, no proper keyboard, a dock that drops the screen. Nobody files a ticket about it, but across a whole organization, it quietly adds up to a lot of lost time, and the fix costs a fraction of a new laptop.

Every model you support adds buying, testing, and support work. Employee feedback shows which ones people actually rate well, so a lineup of ten can often come down to three or four without anyone missing the rest.

License counts and token usage show who's using AI, not what it's worth. The people using it know. Ask whether it saves them time and improves their work, and keep asking, so you can see whether the value is growing or fading.

Piloting with enthusiasts flatters the business case. The real test is the people in the middle who haven't made up their minds: if a pilot moves them, a rollout will.

When an AI tool  isn't landing with a team, it's usually because people don't know what to use it for, not because the tool is bad. Ask them, and you'll see which teams are stuck and what they're stuck on."

Unclear rules make careful people stop using AI tools altogether. You'll hear about it in their comments long before you see it in the usage numbers.

Somewhere, a team has already found a great way to use your AI tools, and nobody else in the organization has heard about it. Find the people getting value, share what they're doing, build training around it, and watch it spread like wildfire.

If a manager treats AI as optional, the team hears it. Managers who use AI in their own work set the pace for everyone around them. See where that's happening, and where it isn't, unit by unit.