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Productivity is one of those topics that quietly sits in the background of most field service businesses.
Everyone tracks it in some form. Everyone has a sense of whether it feels high or low. And yet, it’s rarely something people feel comfortable talking about openly.
That’s usually because productivity gets reduced to a number.
Jobs per engineer. Utilisation. Output per day.
Once it’s framed that way, it quickly turns into pressure rather than insight. A measure of effort rather than a signal of how well the operation is actually working.
When productivity becomes a target
In many businesses, productivity data slowly shifts from observation to expectation.
Numbers get shared. Comparisons get made. Targets creep in.
And while that’s rarely the intention, the effect is fairly predictable.
Engineers feel the clock ticking. Preparation time gets squeezed. Decisions get made faster than they should. Follow-on work becomes more likely, even when intent and effort are high.
On paper, productivity can look like it’s improving. In reality, quality suffers, repeat visits increase and pressure quietly builds across the system.
That’s not because people don’t care. It’s because productivity is being treated as something to push, rather than something to understand.
Productivity is an outcome, not a lever
Here’s the part that often gets missed.
Productivity isn’t something you can simply turn up.
It’s something that falls out of how well everything else is working.
Planning. Information quality. Workflow design. Capacity protection.
When those foundations are weak, productivity struggles no matter how hard people work. When they’re strong, productivity improves without anyone needing to push harder.
That’s why chasing the number rarely delivers lasting improvement.
Why benchmarking often creates more noise than clarity
Benchmarking is supposed to help make sense of this. But it’s often misunderstood.
Industry averages get quoted. Targets get copied. Numbers get compared without context.
The problem is, benchmarks on their own don’t tell you what to fix.
What’s ‘good’ for one business can be completely wrong for another. Size, job mix, geography, contract types and maturity all play a role.
Without context, benchmarking doesn’t guide improvement. It creates noise and, in some cases, unnecessary pressure.
How well-run field service businesses use benchmarks differently
More mature operations tend to approach benchmarking in a calmer, more deliberate way.
They don’t use it to prove they’re doing well. They use it to decide where to focus.
Benchmarks become signals rather than scores.
They highlight imbalance. They surface exposure. They help leaders ask better questions.
Where are we starting to feel strain?
What doesn’t line up with the rest of our operation?
What’s likely to cause problems as we grow?
That shift, from judgement to guidance, makes all the difference.
Productivity changes as businesses grow
Another common mistake is assuming productivity should always move in one direction.
In reality, productivity changes as businesses scale.
Early on, output can be high but fragile, propped up by experience, heroics and informal workarounds. As volume increases and complexity grows, productivity often dips before systems catch up.
That dip isn’t failure. It’s a signal.
More experienced businesses expect this. They read productivity data differently depending on where they are in their growth journey.
They don’t panic when numbers shift. They use those changes to guide where structure and protection are needed next.
Using data to decide what to fix next
Seen through this lens, productivity and benchmarking stop being about comparison.
They become tools for decision-making.
They help teams understand where workflows aren’t holding, where capacity is being stretched and where attention should be focused.
Used well, data reduces guesswork. Used badly, it increases noise.
The difference isn’t the data itself. It’s how it’s interpreted.
A better way to think about productivity
Rather than asking how to push productivity higher, a more useful question is this.
What is our data actually telling us to fix next?
That question shifts the conversation away from effort and towards design. Towards how work flows, how plans are protected and how the operation is set up to cope as demand changes.
Final thought
Productivity isn’t a scoreboard.
It’s a signal.
When it’s read in context and paired with benchmarking that reflects reality, it becomes one of the most useful tools a business has.
Not to judge performance, but to guide better decisions, protect teams and support sustainable growth.
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