Utilisation Rate: Are You Really Getting the Most From Your Team?

A team can be busy all day and still be underutilised.

That sounds like a contradiction, and it is not. It happens constantly in construction, field service, installation, maintenance and engineering — anywhere work is organised around projects rather than a production line.

People move between sites. They solve small problems. They travel. They help a colleague for an hour. They sit in meetings. They wait for material that has not arrived. They finish work nobody ever scheduled. Some of those hours are billable, some are productive but not billable, and some quietly disappear into administration.

At the end of the month, management usually knows two things: how many people were employed, and how many hours were recorded. Neither one answers the question that actually matters.

That is the question utilisation rate exists to answer — and, in most companies, the data needed to answer it is already being collected.

What is utilisation rate?

Utilisation rate measures how much of an employee’s available working capacity went into productive work. At its simplest:

Take a technician with 160 available working hours in a month. Over that period, the record shows:

If customer work and internal productive work both count as productive, that is 125 productive hours out of 160 — a utilisation rate of 78.1%.

The arithmetic is trivial. Everything difficult about utilisation lives in the data underneath it.

Busy does not always mean utilised

This is the single biggest misunderstanding about workforce performance. An employee can look extremely busy and still show low productive utilisation.

A technician might spend a full working day on:

• driving between locations
• waiting for another trade to finish
• searching for material that was not where it should have been
• answering internal questions
• correcting paperwork
• sitting in a meeting that did not need them
• doing work that was never attached to a project or a task

They worked eight hours. Perhaps five of them went into productive project work. Without the right data, both kinds of hour look identical on a timesheet.

So utilisation is not really about checking whether people are working. It is about understanding where organisational capacity is being consumed — and the honest answer is usually uncomfortable in a useful way.

There is more than one utilisation rate

A single percentage is rarely enough. Most companies need to look at utilisation from more than one angle, because the angles answer different questions.

Billable utilisation

Billable utilisation measures how much available capacity is directly chargeable to a customer: billable hours ÷ available hours × 100. It is the natural metric for service businesses, engineering firms and anyone working time-and-material contracts.

On its own it misleads. A technician working under a fixed-price maintenance agreement may be creating substantial customer value while almost none of their hours are invoiced directly.

Client utilisation

Client utilisation counts all customer-facing work, billable or not:

• project work
• maintenance
• warranty work
• customer support
• site inspections
• technical preparation

This gives a truer picture of how much team capacity the customer base consumes, regardless of what appears on an invoice.

Productive utilisation

Productive utilisation goes wider still, and may include internal projects, training, documentation, preparation and process improvement alongside customer work.

There is no universal formula here, and looking for one is a waste of time. What matters is agreeing what productive work means inside your company — and then applying that definition consistently enough that this month can be compared with last month.

Start with available capacity, not calendar hours

Before calculating anything, you need to know how many hours an employee was genuinely available. Using every calendar working hour as the denominator produces numbers that look precise and are wrong.

Consider an employee with a theoretical monthly capacity of 176 hours who took 16 hours of annual leave and 8 hours of sick leave. Their real available capacity was 152 hours. Against 120 productive hours:

More than ten percentage points separate a fair number from an unfair one, for an employee who did nothing differently. Without accurate availability data, utilisation stops being a KPI and becomes a source of arguments.

What data do you actually need?

Less than most people expect. At a minimum: who did the work, what their available capacity was, when it happened, how many hours were recorded, which project or task the hours belonged to, and how that activity should be classified.

The last one carries most of the value. Once recorded time can be grouped — billable customer work, non-billable customer work, internal productive work, administration, training, travel, unallocated time, leave and absence — utilisation stops being a number and starts being an explanation.

That is the difference that matters. Knowing utilisation is 68% tells you very little. Knowing that 14% of capacity went into travel and 9% into looking for material tells you what to do on Monday.

The percentage on its own is not the goal

Imagine two employees. One shows 92% utilisation, the other 75%. The first looks obviously more productive.

Now suppose the first spends most of their time on low-margin support callouts, while the second delivers specialist work at a much higher rate. The percentages have not changed and the conclusion has reversed.

Utilisation becomes genuinely useful when it is read next to employee cost, hourly rate, project revenue and project profitability. The question stops being “who has the highest utilisation?” and becomes “which teams turn their available capacity into the most value?” — which is a question worth having a management meeting about.

Utilisation exposes operational problems

The reporting is valuable mostly because it surfaces things that are otherwise hard to see. Consistently low utilisation can point to weak workforce planning, too many people for the current workload, a thin project pipeline, poor scheduling, excessive administration, too much travel, missing material, or simply work that is being done and not recorded.

Consistently high utilisation is not automatically good news either. A team running at 95–100% for months has:

• no capacity for the unexpected, and site work is largely unexpected
• no time for training
• no room for internal improvement
• rising overtime
• a real burnout risk
• no honest way to say yes to a new project

The objective is not to push utilisation towards 100%. It is to understand capacity well enough to make better decisions about it.

From historical reporting to capacity planning

Utilisation gets considerably more powerful when it is pointed forwards. Historical utilisation tells you what happened; planned utilisation tells you what is about to.

Say an electrical team has five technicians, and over the next six weeks four of them are already committed almost fully across existing projects. A new job arrives needing roughly 300 technician hours. Utilisation stops being a report and becomes a planning tool: take the work now, move the start date, reallocate people, hire, subcontract, or reprioritise.

Those decisions get made either way. The only question is whether they are made on instinct or on capacity data.

RelayPlan already records most of this

This is the part that interests us directly, because a company running RelayPlan day to day is already generating most of the inputs: employees, projects and cost centres, tasks, assignments, schedules, recorded working hours, employee and project costs, materials, and the invoicing side.

The underlying operational data largely exists. The next step is not asking anyone to enter a second, parallel set of information — it is turning what normal operations already produce into something management can act on.

Where we are taking this next

Deeper workforce and resource intelligence is one of the areas we are building towards, and utilisation is a natural part of it. The goal is to connect information that already exists so that these questions have answers without anyone building another spreadsheet:

• What is our current team utilisation?
• Which people have unused capacity, and which are overloaded?
• How much time goes into customer work against internal activity?
• How much capacity will we have next month?
• Which projects consume the most employee capacity?
• Are we making money on the hours our teams spend?
• Could we take on another project with the people we already have?

From workforce tracking to workforce intelligence

Most companies already hold everything needed to understand their workforce properly. The problem is that it is scattered: hours in one system, schedules in another, project data somewhere else, costs in accounting, tasks in spreadsheets and email threads. Management then reconstructs the picture at month end, and the result is another spreadsheet.

Utilisation rate is a simple metric standing in for something much larger — the shift from recording work to understanding how people, projects and money actually interact. For project-driven companies, that visibility changes how the workforce gets planned.

Because the important question was never whether people are busy.

That is the question we want RelayPlan to help answer next. If you are already recording hours against projects and cost centres, you are closer to answering it than you probably think.