Machine selection scorecard
A commercial buyer can score each machine from 1-10 against weighted criteria:
| Criterion | Weight |
|---|---|
| Productivity | 20% |
| Reliability | 15% |
| Local service | 15% |
| Parts availability | 10% |
| Fuel efficiency | 10% |
| Attachment compatibility | 8% |
| Operator acceptance | 5% |
| Transportability | 5% |
| Resale | 5% |
| Technology/data | 4% |
| Purchase price | 3% |
This deliberately prevents purchase price from dominating the decision. For production forestry, a cheap machine with poor uptime is rarely cheap.
Note that reliability, local service and parts availability together carry 40% — double the weight of productivity. That reflects how forestry fleets actually lose money.
The commercial hierarchy for buying forestry machinery
Work the variables in this order — and notice what happens when a buyer works them in the other one.
Purchase price appears last in the correct hierarchy — not because it does not matter, but because it is the only variable that is fixed once, while every variable above it recurs for the life of the asset.
Final commercial machine-type matrix
| Machine | Best commercial user | Main KPI | Main buying risk |
|---|---|---|---|
| Feller buncher | plantation harvesting contractor | stems/tonnes per hour | underutilisation |
| Harvester | CTL contractor | $/m³ | complexity/downtime |
| Forwarder | CTL contractor | tonnes/turn | wrong payload size |
| Skidder | full-tree contractor | tonnes/turn | extraction mismatch |
| Processor | landing contractor | m³/hour | bottleneck |
| Log loader | harvesting/yard | tonnes/hour | idle time |
| Tree shear | clearing contractor | stems/hour | overstated cut capacity |
| Grapple saw | vegetation/arbor contractor | controlled cuts/day | lift capacity |
| Forestry grapple | logging/clearing | cycles/hour | wrong geometry |
| Mulcher | vegetation contractor | ha/hour | tooth/fuel cost |
| Stump grinder | arbor contractor | stumps/hour | tooth wear |
| Stump shear | clearing contractor | stumps/hour | ground disturbance |
| Tiller | plantation/site prep | ha/day | rock/root wear |
| Pruner | utility/vegetation | cuts/hour | reach/stability |
| Chipper | biomass/arbor | tonnes/hour | feed bottleneck |
| Grinder | recycling/biomass | tonnes/hour | wear cost |
| Winch-assist | steep-slope harvesting | productive slope hours | system complexity |
The core commercial principle
Industrial forestry machinery should ultimately be purchased according to cost per unit of saleable production — not purchase price, horsepower or maximum cutting diameter.
For harvesting:
Total annual machine cost
÷
Annual merchantable m³
=
Machine cost per m³
For biomass:
Total production cost
÷
Saleable tonnes
=
Cost per tonne
For mulching:
Total operating cost
÷
Completed hectares
=
Cost per hectare
For stump removal:
Total operating cost
÷
Completed stumps
=
Cost per stump
Every specification should eventually connect back to one of those numbers. If a specification cannot be traced to one of them, it is a preference — and preferences are fine, as long as they are recognised as such and priced accordingly.
The order the decisions should be made in
Most buying processes run backwards: a machine attracts attention, a specification comparison follows, and the commercial questions are answered afterwards as justification. The sequence below inverts that, and each step constrains the ones below it.
1. Establish the work, and the hours behind it. Contracted or highly probable annual productive hours, and the term they run for. This is the input every subsequent calculation turns on, and it is the one most often inflated. If the hours cannot be underwritten, the honest answers are usually hire, subcontract, or buy used at a capital level the business can absorb through an idle period.
2. Identify the constraint. Which stage currently limits your production? Capacity added anywhere else changes your costs and not your output. If you cannot name the bottleneck, a specification comparison is premature.
3. Let the work choose the system. Silviculture, product specification, terrain and access determine cut-to-length versus full-tree, dedicated machine versus carrier-plus-attachments, chipper versus grinder. These are not preferences and they are not decided by machine capability.
4. Size each element against the constraint. Not against the catalogue, and not against the best case. Extraction against the longest haul, not the average; carriers against the access your work actually has; processors against the feed you can sustain.
5. Check compatibility in four separate calculations. Power, cooling, plumbing and lift chart. Passing one does not answer the others, and on attachment-based fleets the lift chart is usually the binding one.
6. Convert to cost per unit. Total annual machine cost divided by annual saleable production, in the unit you are paid in. Then run it again at the pessimistic end of your utilisation and production assumptions.
7. Price support as a line item. Convert response commitments into expected downtime hours and multiply by your hourly contribution. In an interdependent fleet this frequently exceeds the price difference under negotiation.
Only then does specification comparison between competing machines become meaningful — because you now know which specification differences change your output and which merely change your invoice.
The questions that decide most purchases
If a process has to be compressed, these six carry most of the weight.
- Can the hours be underwritten? If not, the capital level is the decision, not the machine.
- Which stage is the bottleneck, and does this purchase move it? If not, the purchase adds cost without adding production.
- What does an hour of this machine cost, in the unit I sell? Not what it costs to buy.
- What does the lift chart allow at the reach the work actually uses? With attachment, rotator and coupler weight deducted.
- What is the residual, verified against a recent comparable sale? It moves the largest cost on the machine.
- What support is guaranteed in writing, and what does a day of downtime cost me? The product of those two is a number.
When the answer is not to buy
A decision framework that can only produce purchases is not a framework. Three outcomes are legitimate and frequently correct.
Hire. Where utilisation sits below the break-even, or where hours are uncertain enough that converting a fixed cost into a variable one is worth the higher hourly rate. Uncertainty is itself an argument for hire.
Subcontract. Where the capability is needed occasionally and the capital would be idle most of the year. This applies to specialist attachments as often as to machines.
Fix the constraint without capital. Landing layout, shift patterns, haul planning, truck scheduling, maintenance timing and operator training all move production at no capital cost, and they should be exhausted before a machine is bought. A bottleneck solved by rescheduling is a bottleneck solved cheaply.
A framework whose answer is sometimes "not yet, and here is the number that would change it" is doing its job.
Documenting the decision
The cheapest improvement available to a buying process is recording the assumptions the purchase rests on. Very few contractors do it.
Before signing, write down:
- Contracted and expected annual productive hours, and the term
- Sustained production per productive hour, and where that figure came from
- Expected residual, and the sale it was benchmarked against
- Support commitments, as given in writing
- The cost per unit the model produced, at both the expected and pessimistic cases
- The one assumption you are least confident in
Twelve months later that page is the most useful document the business has. Either the assumptions held — in which case the process works and can be trusted next time — or they did not, and you know precisely which input to distrust. Without it, the next purchase starts from the same guesses.
Work through the procurement checklist, run the cost model, and use the bottleneck analyser to establish which stage this purchase should be addressing.
The framework applied, start to finish
An illustrative case, worked through the sequence above, to show what each step actually rules in or out.
The situation. A land-clearing contractor runs one 25 tonne excavator with a grapple and hires a mulcher perhaps fifteen days a year. Mulching enquiries are increasing and the contractor is considering buying a mulching head.
Step 1 — the hours. Fifteen hire days last year. Two enquiries in hand, neither contracted. Honest expectation: 25-40 days next year. Nothing is underwritten.
Step 2 — the constraint. The business is not turning down mulching work for lack of a machine; it hires one. The constraint is demand, not capability. That alone should slow the purchase down.
Step 3 — the system. Attachment on the existing carrier, not a dedicated mulching machine — 40 days a year cannot carry a purpose-built carrier, and the excavator earns across several industries.
Step 4 — sizing. Against the vegetation that actually fills the work, and against what the existing carrier can sustain, rather than against the largest job enquired about.
Step 5 — compatibility. Four checks on the existing excavator: continuous auxiliary flow against the head's requirement, working pressure at that flow, cooling for sustained duty in summer, and the lift chart with the head fitted. Mulching is a continuous duty, so cooling is the check most likely to fail.
Step 6 — cost per unit. Head capital and expected consumables against 40 days of mulching, compared with the hire rate across the same 40 days. Then again at 25 days.
Step 7 — support. Teeth and tool holders are consumed continuously. What is held in Australia, and at what lead time?
The finding. At 40 days, ownership is likely marginally ahead of hire. At 25 days it is clearly behind, and nothing is contracted. The defensible decision is to keep hiring, quote the increased enquiry flow, and revisit once mulching days are contracted rather than anticipated — while using the hire period to measure tooth cost per hectare in the contractor's own soils, which is the figure most likely to differ from a supplier's estimate.
One page, if you take nothing else
Hours before machines. Constraint before specification. System before model. Cost per unit before price. Support in writing before a discount. And the pessimistic case run before the finance documents rather than after.
Every expensive mistake this guide describes is a version of doing one of those in the wrong order.
Who should be in the decision
Equipment decisions are usually made by whoever signs, and the people who know most about how the machine will behave are frequently not consulted until it arrives.
Three perspectives are worth collecting before the order, and none of them take long:
The operator who will run it. They will tell you about visibility, control layout, access for daily checks and the things that make a shift tiring — all of which affect production in the back half of a day and none of which appear in a specification. They will also tell you honestly whether the demonstration was representative.
Whoever maintains it. Service access, filter locations, what needs a technician versus what can be done in the yard, and which components on the shortlisted machines have a reputation. Maintenance staff hear about failures that never reach a sales conversation.
Whoever does the invoicing. They know what the business is actually paid per unit, how reliably, and how the rate has moved — which is the input the whole cost model turns on and the one most often supplied from memory.
None of this is a committee. It is three conversations, and each of them routinely surfaces something that would otherwise be discovered in the first month of ownership.