Total cost of ownership
Purchase price is only the first line. A commercial model should include:
Purchase price
- residual value
+ finance cost
+ insurance
+ fuel
+ operator
+ service
+ repairs
+ tyres/tracks
+ attachments
+ teeth/chains/knives
+ transport
+ telematics
+ downtime
+ administration
Downtime belongs in that list and is almost always omitted. It is a real cost with a real dollar value: lost contribution margin per productive day, multiplied by days lost.
Fixed cost per hour
Suppose an illustrative machine costs:
Purchase: $800,000
Expected resale after 5 years: $300,000
Depreciation:
($800,000 - $300,000) ÷ 5
= $100,000/year
If the machine performs 2,500 productive hours:
$100,000 ÷ 2,500
= $40/hour depreciation
At only 1,250 productive hours:
$100,000 ÷ 1,250
= $80/hour depreciation
Same machine. Same purchase price. Double the depreciation cost per productive hour.
Depreciation per productive hour against annual utilisation
A machine depreciating $100,000 a year. Same machine, same purchase price — the hours decide the cost.
That is why utilisation is central to forestry profitability, and why an honest annual-hours estimate is worth more than a hard-won discount on the purchase price.
Cost per cubic metre
Assume total machine operating cost of $280/hour.
At production of 25 m³/hour, machine cost is:
$280 ÷ 25 = $11.20/m³
If productivity falls to 18 m³/hour, cost becomes:
$280 ÷ 18 = $15.56/m³
That is a 39% increase in machine cost per cubic metre without changing the hourly cost at all.
Production matters enormously — which is why production data, not specification sheets, should drive the purchase.
Cost per hectare for mulching
Assume machine cost of $350/hour and production of 0.75 ha/hour:
$350 ÷ 0.75 = $466.67/ha
If difficult vegetation reduces production to 0.35 ha/hour:
$350 ÷ 0.35 = $1,000/ha
That is why contractors should avoid quoting forestry mulching purely from satellite imagery or total hectares. Vegetation density can completely change cost, and the rate was fixed before anyone walked the site.
Productive machine hour versus clock hour
Forestry businesses should distinguish:
Scheduled machine hour — the machine was scheduled to work.
Engine hour — engine running.
Productive machine hour — machine actually producing.
Delay hour — waiting because of truck, breakdown, fuel, operator, weather, road or a processing bottleneck.
Commercial costing should not assume every engine hour is productive. Machines routinely record 15-30% more engine hours than productive hours, and a cost model built on engine hours will understate cost per unit accordingly.
Machine availability
A useful metric:
Mechanical Availability
=
Available Scheduled Hours
÷
Total Scheduled Hours
× 100
Example:
Scheduled: 200 hours
Breakdown: 20 hours
Availability: 180 ÷ 200 × 100 = 90%
Increasing availability from 85% to 95% can be more valuable than increasing theoretical production by 5% — and it is usually cheaper to buy, because availability is purchased through dealer support, parts stock and maintenance discipline rather than through capital.
The costs that do not appear on an invoice
Three of the largest costs in forestry machine ownership never arrive as a bill, which is why cash-based costing is so consistently optimistic.
Depreciation is the largest single cost on most forestry machines and appears nowhere in the monthly accounts. The worked example above puts it at $100,000 a year before fuel, wages or maintenance. A contractor pricing from cash costs alone can run profitably for years and still be unable to fund a replacement machine — which is the point at which the business discovers what it has actually been earning.
Downtime costs contribution margin, not repair dollars. If a machine generates $1,200 a day in contribution after variable costs, a three-day breakdown costs $3,600 in lost margin on top of whatever the repair invoice says. In an interdependent chain the figure multiplies, because a stopped processor idles the feller buncher, the skidders and the loader with it.
Capital tied behind a constraint is the least visible of the three. A fleet with 20% more felling capacity than it can extract is paying depreciation, finance and insurance on capacity that produces nothing. It looks like a well-equipped operation and costs like an over-equipped one.
Where cost models usually go wrong
Most cost models in this industry are not wrong in structure. They are wrong in three specific inputs.
Engine hours substituted for productive hours. A model that divides fixed costs by engine hours rather than productive hours produces an hourly rate the machine cannot deliver production at, and that error flows directly into every quoted rate afterwards.
Residual value assumed rather than verified. Residual is the difference between depreciation being the largest cost and being merely a large one, and it is the input buyers are most inclined to flatter. The market for purpose-built forestry machines is thin, so condition, hours and service history move price more than age does, and an unusual specification narrows the buyer pool further. A phone call to a dealer about a recent comparable sale is worth more than any depreciation curve.
Production modelled from a good day. A rate quoted from peak production has no margin in it. Sustained average output across weeks — including weather, difficult ground, minor stoppages and the days nothing goes right — is what the machine will actually deliver, and it is usually well below the figure a demonstration suggests.
Consumables scale with production, not time
Fuel, chains, bars, teeth, knives, hammers and tyres are consumed per unit of output rather than per hour, which has a practical consequence: they should be tracked per cubic metre, per tonne or per hectare rather than per hour.
The reason is diagnostic as much as financial. Consumable cost per hour rises and falls with how hard the machine is working, which tells you very little. Consumable cost per cubic metre should be stable, so when it moves, something has changed — cutting technique, chain speed, soil contact, material type or a component approaching failure. Tracked per hour, that signal is invisible.
This matters most where the cost base differs from the one a model was built on. Abrasive Australian hardwood consumes chains, bars, knives and rollers faster than plantation softwood; rocky ground consumes mulching teeth and tiller tool-holders at rates that can exceed fuel cost. A model carried across from softwood or from benign soils will be optimistic in a way that only becomes visible after several months of operation.
Finance is a separate cost from depreciation
Depreciation is the loss of the asset's value. Finance interest is what the money costs. They are different things and both belong in the model — a calculation that captures only depreciation understates the machine's annual burden, and the gap is largest in the early years of a term when interest is highest.
The structure of the finance also matters commercially. A balloon payment lowers the monthly obligation and raises the exposure at the end of the term, at exactly the point when the machine's condition and the resale market determine whether the balloon can be cleared. A term longer than the contract supporting the machine does not remove that exposure; it defers it.
Putting the model to work
The useful output of a cost model is not a number but a comparison.
- Total the annual fixed costs — depreciation, finance, insurance, registration, storage, standing compliance.
- Divide by the productive hours you can genuinely contract, not the hours you hope for.
- Add the variable costs per hour — fuel, operator fully loaded, service, consumables.
- Divide by sustained production per productive hour to reach cost per cubic metre, tonne, hectare or stump.
- Compare that against your contract rate. If the gap does not cover overheads and margin, either the rate is wrong or the production assumption is.
Run these figures in the machine cost calculator, or see the cost guides by type of work for what drives the cost of mulching, harvesting, clearing and stump removal specifically.
A model end to end
Every component so far, assembled into one calculation. The figures are illustrative — substitute your own — but the structure is the one to use.
A machine bought for $800,000, expected to be worth $300,000 after five years, financed over that term, working 2,000 productive hours a year and producing 22 m³ per productive hour.
Step 1 — annual fixed costs
Depreciation ($800,000 - $300,000) ÷ 5 = $100,000
Finance interest (illustrative) = $28,000
Insurance, registration, storage = $12,000
---------
Annual fixed cost = $140,000
Step 2 — fixed cost per productive hour
$140,000 ÷ 2,000 = $70.00/hour
Step 3 — variable cost per productive hour
Fuel 28 L/h × $2.00/L = $56.00
Operator (fully loaded) = $65.00
Service and repairs = $22.00
Consumables (chains, bars, etc.) = $18.00
-------
Variable cost per hour = $161.00
Step 4 — total cost per productive hour
$70.00 + $161.00 = $231.00/hour
Step 5 — cost per unit sold
$231.00 ÷ 22 m³ = $10.50/m³
That last number is the one to compare against your contract rate. If the rate is $16/m³, the machine contributes $5.50/m³ toward overheads and margin — about $121,000 a year at these hours and production.
Now run it again, pessimistically
The point of building the model is not the number. It is the sensitivity.
Take the same machine and move only the two inputs buyers most often get wrong — utilisation and production — to the pessimistic end:
| Scenario | Hours | m³/h | Fixed $/h | Total $/h | Cost per m³ |
|---|---|---|---|---|---|
| Planned | 2,000 | 22 | $70.00 | $231.00 | $10.50 |
| Production short | 2,000 | 18 | $70.00 | $231.00 | $12.83 |
| Hours short | 1,400 | 22 | $100.00 | $261.00 | $11.86 |
| Both short | 1,400 | 18 | $100.00 | $261.00 | $14.50 |
Nothing about the machine changed in any row. Against a $16/m³ rate, contribution falls from $5.50/m³ to $1.50/m³ — a drop of roughly 73% — and the annual contribution at those hours collapses from about $121,000 to about $38,000.
Overheads, margin and the number you actually quote
The model above produces machine cost, not a rate. Between the two sit two things it does not contain:
Business overheads — management, administration, insurance not attached to a specific machine, compliance, vehicles, yard, systems. These are recovered across all machines and all jobs, and a business recovering them from only its busiest machine is mispricing everything else.
Margin — the return for carrying the risk. A rate that covers machine cost and overheads exactly is a rate that works only if nothing goes wrong, which is not a plan.
The practical approach is to establish machine cost per unit first, because it is the part that can be calculated rather than judged. Then add an overhead recovery per unit derived from total overheads divided by total expected production across the fleet, and then a margin. Quoting a rate without knowing which of the three is being squeezed is how contractors discover, late, that they have been subsidising a client with their own depreciation.