Why Your Best Technician Probably Isn't Who You Think

Why Your Best Technician Probably Isn't Who You Think

Ask most MSP owners who their best technician is, and you'll get an answer in about two seconds. It's usually the person who closes the most tickets. Their name is at the top of the leaderboard, they always look busy, and the numbers seem to back it up.

But raw ticket count is one of the most misleading numbers in your entire service desk. The technician at the top of that list might genuinely be your best. Or they might just be the one who has learned how to game a metric. The uncomfortable truth is that most MSPs have no reliable way of telling the difference.

The problem with counting tickets

Ticket count measures activity, not value. Those are not the same thing.

Consider two technicians. The first closes 40 tickets a week, almost all of them password resets, printer issues, and "have you tried restarting it" jobs that take four minutes each. The second closes 18 tickets a week, but several of them are gnarly, multi-hour problems - a failing migration, an intermittent network fault, a security incident that could have become a breach.

On a ticket-count leaderboard, the first technician looks like a superstar and the second looks like they're coasting. In reality, the second technician is carrying the work that actually protects your clients and your reputation. If you reward the leaderboard, you are quietly training your best people to stop taking on hard problems.

That's the hidden danger. Metrics don't just measure behaviour - they shape it. When technicians know they're judged on volume, the rational move is to cherry-pick the quick wins and leave the difficult tickets to age in the queue.

What ticket count hides

Once you start looking past the raw number, a lot of important detail comes into view that a single figure can never capture.

Complexity is the obvious one. A ticket is not a unit of equal work. Ten simple requests and one complex project can show up as eleven closed tickets, as if they were interchangeable. Reopen rate is another. A technician who closes tickets fast but sees a chunk of them bounce straight back isn't being efficient - they're deferring the work and adding churn. First-time resolution tells a similar story from the other direction: the person who quietly fixes the underlying cause so the issue never returns is doing the most valuable work of all, and it's invisible on a volume chart.

Then there's the human side. Effort spread across clients, time-of-day patterns, and after-hours load all shape whether a technician is sustainably productive or heading for burnout. None of it survives being flattened into "tickets closed."

A better way to think about technician performance

Instead of asking "who closed the most tickets?", the more useful question is "who is delivering the most reliable outcomes for clients, efficiently, without creating hidden problems downstream?"

That question can't be answered with one metric. It needs a small basket of them, looked at together:

• First response and resolution time, so you can see who is genuinely fast versus who just looks busy.
• Reopen rate and first-time fix rate, so you can tell whether a "closed" ticket actually stayed closed.
• Complexity or effort weighting, so a hard problem counts for more than a password reset.
• Workload distribution, so you can see who is overloaded and who has room - and who might be quietly heading toward burnout.
• Customer satisfaction tied to the technician, so the client's experience is part of the score, not an afterthought.

Look at those together and the leaderboard almost always reshuffles. The volume champion often slides down. The steady, high-first-time-fix technician who never complains often turns out to be the person actually holding your service desk together.

Why this is hard to do in Autotask alone

Here's the catch. Every piece of data you need for this already exists inside Autotask. The timestamps, the reopens, the resolution times, the CSAT responses, the assignments - it's all being captured, ticket by ticket, every single day.

The problem is that Autotask is a system of record, not a system of insight. It's very good at telling you what happened. It's not designed to weigh those signals against each other and tell you what it means. Building a fair, multi-metric technician scorecard by hand means exporting data, wrestling with spreadsheets, normalising for complexity, and repeating the whole exercise every month. Most owners start, discover how fiddly it is, and quietly go back to counting tickets.

Turning the data you already have into a real score

This is exactly the gap Canopy is built to close. Autotask tells you what happened; Canopy tells you what to do next.

Canopy reads the data already sitting in your Autotask instance and automatically scores every technician across multiple performance metrics - not just volume, but resolution quality, reopen rates, workload balance, and customer satisfaction - so the person at the top of your leaderboard is there because they've earned it, not because they picked the easy tickets. You stop guessing who your best people are, you spot the ones heading for burnout before they hand in their notice, and you can have performance conversations grounded in a fair picture rather than a single misleading number.

The technician you've been calling your best might well be exactly that. But wouldn't you rather know for certain - and finally give real credit to the quiet ones who deserve it?