Fleet Utilisation & Cost Modelling

This use case explains how to model fleet utilisation and operating cost for logistics, transport and fleet based businesses in Model Reef.

You will:

• Represent vehicles and fleets in the branch structure.

• Define utilisation drivers such as kilometres, hours, drops or loads.

• Build cost models covering fuel, maintenance, tyres, tolls, drivers and overheads.

• Connect fleet utilisation and cost into P&L, Cashflow and Cash Waterfall.

Model Reef is not a telematics or route planning system. It sits above those tools as a planning and financial modelling layer.

When to use this pattern

Use this pattern when:

• You operate a fleet of trucks, vans, buses or specialist vehicles.

• Vehicle utilisation and operating cost are major drivers of profitability.

• You want to compare routes, contracts, depots or customer groups on a consistent economic basis.

• You need a full three statement view of fleet operations, not just unit metrics.

You will often combine this pattern with:

• Route or Region Profitability

• Fuel and Maintenance Forecasting

• Asset Replacement Planning

Architecture overview

Fleet utilisation and cost modelling uses four main layers:

• Fleet structure

  • Branches per region, depot or fleet segment.

  • Optional sub branches for vehicle types or contracts.

• Utilisation drivers

  • Kilometres, hours, loads or drops per vehicle or fleet group.

  • Load factors and empty running assumptions.

• Cost drivers

  • Fuel burn per kilometre or hour.

  • Maintenance, tyres and tolls.

  • Driver wages and oncosts.

  • Insurance and registration.

• Financial outputs

  • Cost per kilometre, per hour, per drop or per tonne.

  • Fleet cost and margin per route, depot, contract or customer.

  • Integration with P&L, Cashflow and valuation.

1

Set up branches for fleet and depots

Start by deciding how you want to view performance. Common approaches are:

• Branches per depot or operating centre.

• Branches per region (for example North, South, Metro, Regional).

• Branches per fleet type (linehaul, last mile, refrigerated, bulk).

For example:

• Group

  • Region - North

  • Region - South

  • Region - Metro

Within each region, you can add sub branches for depots or specific fleets if needed.

Keep branch structure aligned with how operations and finance think about accountability and reporting.

2

Define utilisation drivers

In the Data Library, create drivers that describe how your fleet is used, for example:

• Kilometres per Period - Linehaul Fleet - North.

• Kilometres per Period - Last Mile Fleet - Metro.

• Operating Hours per Period - Bus Fleet.

• Drops per Period - Last Mile Fleet.

• Tonne Kilometres per Period where relevant.

You may also define:

• Load factors (for example average trailer fill percentage).

• Empty running percentage (how many kilometres are unproductive).

These drivers can be created from:

• Historical telematics or odometer data.

• Forecast route volumes and network plans.

• Contract commitments.

Store them as time series so they can grow, shrink or respond to scenario changes.

3

Build fuel and variable operating cost per kilometre or hour

For each fleet group, define unit cost drivers such as:

• Fuel Burn per 100 km - Linehaul Fleet.

• Fuel Price per Litre.

• Maintenance Cost per km.

• Tyre Cost per km.

• Tolls per km where toll roads are used heavily.

Compute a composite variable cost per kilometre or hour, for example:

• Variable Cost per km - Linehaul Fleet = Fuel Burn per km × Fuel Price per Litre plus Maintenance Cost per km plus Tyre Cost per km plus Tolls per km.

Then create COGS or Opex variables such as:

• COGS - Variable Fleet Cost - Linehaul North = Kilometres per Period - Linehaul North × Variable Cost per km - Linehaul Fleet.

Typing these as COGS ensures they reduce gross margin correctly and flow through to the Cashflow Statement and Cash Waterfall when timing is applied.

4

Model fixed and semi fixed fleet costs

In addition to variable costs, fleets incur fixed or semi fixed costs, for example:

• Vehicle lease or finance payments.

• Depreciation if you own vehicles, modelled as Asset variables.

• Insurance and registration.

• Driver base salaries (often Staff variables).

• Depot rent and overheads (Opex).

For each region or depot, create variables such as:

• Staff - Drivers - North.

• Opex - Insurance and Registration - Fleet.

• Opex - Depot Rent - North.

• Asset - Vehicles - North for capitalised vehicles with depreciation.

Ensure timing rules reflect when cash actually leaves the bank (for example monthly lease payments, annual insurance or registration).

5

Compute fleet unit economics

With utilisation and cost variables in place, build unit economic metrics such as:

• Cost per km by fleet type and region.

• Cost per hour where relevant.

• Cost per drop for last mile operations.

• Cost per tonne kilometre for bulk freight.

You can implement these as:

• Custom chart formulas, or

• Variables that divide total cost by total utilisation drivers.

For example:

• Cost per km - North = Total Fleet Cost - North ÷ Total Kilometres - North.

Connect these to route or region level revenue where you have Route or Region Profitability configured, so you can view:

• Margin per km.

• Margin per trip or route.

• Margin per contract or lane.

6

Link fleet modelling to P&L, cashflow and valuation

Because all fleet costs are represented as variables with correct types and timing:

• P&L will show fleet cost lines in COGS, staff and Opex.

• Balance Sheet will capture vehicles as Assets and associated debt as Liabilities.

• Cashflow and Cash Waterfall will show fuel, maintenance, lease, debt and capex payments over time.

You can then:

• Test different utilisation and cost assumptions in scenarios.

• See how fleet decisions affect overall cash requirements and valuation.

• Compare the economics of owning versus leasing or outsourcing routes.

7

Use scenarios to test fleet strategies

Clone the model into scenario models to represent different fleet strategies, for example:

• Higher utilisation of existing fleet with minimal growth in fleet size.

• Fleet expansion to support new contracts or geographies.

• Increased outsourcing of certain routes to third party carriers.

• Electrification or alternative fuels with different capex and operating cost profiles.

In each scenario, adjust:

• Utilisation drivers (kilometres, hours, drops).

• Variable cost per kilometre or hour (fuel, maintenance, tyres).

• Fixed cost structures (leases, assets, staff).

• Revenue per route or region in the connected route profitability models.

Compare scenarios using:

• Fleet cost and margin per route, region or customer.

• Required capex and financing.

• Cashflow and funding needs.

• Valuation and risk metrics.

Check your work

• Fleet groupings in branches match how operations view the network.

• Kilometre, hour and drop drivers align with historical patterns when calibrated.

• Unit cost assumptions for fuel, maintenance and other running costs are realistic.

• P&L and cashflow outputs look plausible relative to recent financial results.

Troubleshooting

Cost per km looks too high or too low

Check that you have captured all relevant cost components and that you are dividing by the correct utilisation driver for that fleet.

Fleet looks over utilised in the model

Compare kilometres and hours per vehicle to realistic limits and adjust utilisation or fleet size assumptions.

Difficult to maintain at individual vehicle level

Aggregate vehicles into homogeneous fleets and only model individual units where they are unusually large or important.

Related guides

• Build a Staffing Cost Model

• Build a Central Assumption Library

• Differences vs Ticker Fundamentals Import

• Operational Driver Fields