The finance director reports fee-earner utilisation at 61%. The operations director says it is 78%. They are looking at the same month, the same timesheet system and the same fee-earners in the same professional services firm. Both figures are correct.
That is the problem. An agency, architecture practice or consultancy can use several legitimate definitions of utilisation, and each answers a slightly different commercial question. A managing partner may want to understand whether paid capacity is generating fees. An operations director may want to know whether the hours genuinely available for client work were used. A finance director may want a measure that reconciles to recognised revenue.
If those definitions are not agreed before a Power BI report is built, the dashboard does not settle the argument. It gives the argument a polished new surface.
Four valid definitions of fee-earner utilisation
The right utilisation rate depends on the decision the organisation is trying to make. These are the four definitions I see most often.
1. Billable hours divided by total hours
Formula: billable hours / all recorded hours.
This is the broadest time-based definition. The denominator includes every hour entered on the timesheet: client work, internal meetings, business development, training, leave and administration. Finance teams often prefer it because it is simple, stable and easy to reconcile to the complete time record.
Its weakness is that it can make operational performance look worse during a month with annual leave, public holidays or planned training. Those hours were never realistically available for chargeable work, yet they still reduce the percentage. The measure is useful for understanding the relationship between the whole paid time base and billable hours, but it should not be mistaken for a pure scheduling metric.
2. Billable hours divided by available hours
Formula: billable hours / hours available for client work after approved exclusions.
Operations leaders often favour this version. Leave, public holidays and sometimes formal training are removed from the denominator before the utilisation calculation is made. The result asks a practical resourcing question: of the capacity that could reasonably have been assigned to clients, how much became chargeable hours?
This definition is usually the highest of the time-based measures, but it depends on a carefully governed list of exclusions. If one team excludes business development and another does not, the metric becomes inconsistent. The report therefore needs to show which non-chargeable codes reduce available hours and who owns that policy.
3. Billable hours divided by contracted hours
Formula: billable hours / contracted working hours for the period.
Managing partners and finance directors often use contracted hours when they want a consistent view of the capacity the firm is paying for. The denominator comes from each person’s employment pattern rather than the hours they happened to record. Part-time arrangements, starters and leavers must be prorated correctly, but the measure does not move merely because someone entered more or fewer total hours on a timesheet.
That consistency is valuable for workforce planning. It also exposes missing timesheets: if contracted capacity exists but recorded hours are incomplete, the utilisation rate falls rather than quietly shrinking the denominator. The trade-off is that annual leave remains inside contracted capacity unless the organisation explicitly decides otherwise.
4. Recognised fees divided by charge-out capacity
Formula: recognised fees / theoretical fees at the relevant charge-out rate.
The revenue-based variant asks whether available commercial capacity became recognised fee income. It is attractive to finance because it connects utilisation to the income statement and reflects write-offs, discounts, fixed-fee delivery and rate realisation that a pure hours measure cannot see.
It is not a direct substitute for an hours-based utilisation rate. Revenue recognition timing can differ from when the work was performed, and a single standard charge-out rate can oversimplify blended teams or negotiated client rates. This definition is strongest when it sits beside hours measures and is labelled as commercial or revenue utilisation.
An illustrative worked example
Consider one fee-earner in one month. This example is illustrative, not a client result. The fee-earner records 160 total hours, including 16 hours of leave and training, so 144 hours are treated as available. Their prorated contracted hours are 152 and their billable hours are 112. Recognised fees are £14,560 against theoretical charge-out capacity of £22,800.
| Utilisation definition | Illustrative calculation | Result |
|---|---|---|
| Billable / total hours | 112 / 160 | 70.0% |
| Billable / available hours | 112 / 144 | 77.8% |
| Billable / contracted hours | 112 / 152 | 73.7% |
| Recognised fees / charge-out capacity | £14,560 / £22,800 | 63.9% |
Nothing in the table is mathematically contradictory. The four percentages differ because the denominators and business questions differ. Reporting only one number without its definition makes a precise calculation look like an unexplained discrepancy.
Why utilisation definitions break BI projects
A Power BI project often starts with a request to reproduce an existing monthly utilisation report. The apparently simple requirement hides decisions about leave, missing timesheets, overtime, part-time contracts, internal projects, write-offs, revenue timing and rate cards. If the model hardcodes one stakeholder’s interpretation, every other stakeholder sees a number they believe is wrong.
Trust then fails at report level rather than measure level. The ops director does not merely reject the utilisation rate; they start to doubt the resourcing, pipeline and margin pages too. A technically correct dashboard can therefore lose its audience because the business definition was treated as a calculation detail.
This is why definition work belongs at the start of a Power BI solution, alongside the wider decisions described in the consultancy services. It is part of report design, governance and ownership, not an afterthought for the developer.
Choose a primary measure, but keep the alternatives visible
I recommend agreeing one primary definition for executive reporting. It should have a named owner, a written formula, an approved list of exclusions and clear treatment for starters, leavers, part-time staff and missing time. That gives the board pack and monthly management meeting one consistent headline.
The other definitions do not need to disappear. A report can expose them through a clearly labelled toggle or selector rather than burying one formula in DAX. The selected definition should be printed on the report page itself, close to the percentage, with a short tooltip or definition panel. Users should not have to find a separate methodology document to understand the number in front of them.
This approach also makes reconciliation easier. When finance and operations compare 63.9% with 77.8%, they can see that the first is revenue-based and the second is net-available-hours utilisation. The conversation moves from “whose dashboard is wrong?” to “which commercial question is the report answering?”
Where the utilisation data lives
For many agencies and professional services firms, CMap holds timesheets, capacity, project assignments and non-chargeable codes. Those records can support the total-hours, available-hours and contracted-hours definitions, provided employment patterns and exclusion mappings are complete and consistently maintained.
The revenue-based variant usually needs finance data as well. Xero may hold invoices, credit notes and recognised fees, while CMap holds the delivery hours and charge-out assumptions. The reporting model must align people, projects, clients, periods and legal entities across both systems before it can compare fees with capacity reliably.
Multi-entity groups add another layer. Different companies may use different currencies, calendars, rate cards, project codes or revenue-recognition practices. Consolidating those entities without a shared definition can create a group utilisation rate that is arithmetically correct but commercially meaningless. The consolidation rules need to be agreed with the metric, not after the first group dashboard is published.
One hour on definitions can save a month of rework
Fee-earner utilisation is not one universal number. It is a family of measures, each with a valid purpose and a different denominator. A professional services firm gets a more useful Power BI report when it chooses the primary purpose first, keeps alternative views transparent and labels the definition where people actually use it.
An hour spent agreeing those definitions can save a month of dashboard rework and stakeholder debate. I offer focused definitions workshops for agencies, consultancies and professional practices that want to settle the measures before they build. Get in touch to discuss a workshop.
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