Dec 2022
Monetizing Machinery Decisions
Dec 2022
Monetizing Machinery Decisions

Written by:

Andrew Jones | Farm Business Consultant | 0456 688 171

  • Machinery investment decisions have always been an important part of the farming industry and will remain a complex decision.
  • The complexity of the decision is highly dependent on the ‘service’ the machine is expected to provide and needs to be considered as a future requirement, not the historical one.
  • Individual business appetite for risk and tolerance of disruption will dictate the acceptable threshold for replacement.
  • The cost of replacement is not a simple cost of finance calculation.

These concepts are well-proven in other fields of high mechanization. Two leading examples are the mining industry and aviation industry. Earth moving equipment is re-engined and re-manufactured multiple times, until such time as a new machine is more cost effective to operate. Commercial aircraft have complex component redundancy scheduled into the flight service maintenance. A Boeing 747 has an airframe lifespan limit of 35,000 pressurization cycles. The engines are serviced daily, and routine maintenance carried out at periodic checks, and the ‘time between overhauls (TBO) or complex part rebuilds is 5,000 hours. The aircraft with consume many engine cycles in the life of the airframe.

When you are next faced with a major machinery investment, how will you access the justification for the cost?

A quick history lesson

In an earlier landline article, we challenged readers to think about the cost of machinery replacement. The previous article explored some of the machinery decision financial indicator tools and placed them in the present economic environment. This follow-up article will explore the principles of the machinery decision-making process and monetize some aspects of past and future decisions. A little history helps to understand
the principles of the development of this age-old dilemma.

Farmers initially swung a wooden hoe-shaped stick in the field, tilling the soil to cultivate foods that enhanced the hunting and gathering diets intrinsic to their ancestors. With the development of established permanent village communities, there was a need for greater production to provide more certainty of sustainable village life. As these villages grew to be cities, so too did the need for greater capacity. Work Animals and Beast of Burden were engaged to pull heavier wooden equipment with greater capacity than Man himself, and so was the advent of farm and transport machinery. Longevity and reliability became inbuilt in the late iron age with crude cast metals, and this improved again as cast iron gave way to forge techniques.

Fast forward to the industrial revolution and history records a rapid rise of scaled farm mechanization with the advent of powered machinery. Production had moved on from catering for survival.

Machinery investment decisions for greater capacity have been part of the farming industry since the production of surplus (beyond the needs of the village) and the advent of regular commercial trading and commodity exchange markets. Today, machine decisions are driven by the need to retain production efficiencies and business viability under declining terms of trade for agricultural production.
Despite the shift in economic drivers, the principles of machinery decisions remain unchanged.

  • What is the service (task) the machine is providing?
  • What is the required capacity of the machine?
  • What is the replacement threshold?
  • What is the cost of the machine vs machine?

There are also technological step changes to contemplate. To revisit the history above, the adoption of new techniques and technology has made quantum leaps in production possible. The advent of powered rotating shafts and reciprocation has led to many step changes. E.g., powered handpieces replacing hand shears for sheep shearing, machines powered by internal combustion engines replacing teams of horses and bullocks, and more recently the adoption of conservation tillage techniques transformed the yield potential for crop production. There are literally hundreds of innovations that have improved productivity.

For each iteration of development through the ages, increased productivity* (*definition: the effectiveness of productive effort as measured in terms of rate of output per unit of input) has resulted in continuous improvement in the capacity of individual units to complete greater scopes of service. Current variants of machinery may challenge previous machine variants in more than one aspect of productivity. E.g., a 400hp tractor is still a 400hp tractor, but a current machine may provide greater transmission efficiency, or better transfer of power to the ground, or better fuel efficiency per hp produced – or
potentially all 3 improvements in productivity.

Having consideration for productivity gains is one aspect of the decision tree. The adoption of technology to further enhance major developments provides a further economic advantage. There is little debate today about the benefits of auto-steer in tractors and section control in broadacre spray units, a widespread practice today – a pipe dream 30 years ago.

As with any financial decision in your farming business, the purpose of investment needs to be monetized. To do this effectively – the first step is within the statement – define the purpose of the investment.

What service does the machine provide.
Whilst replacing a machine beyond its ‘used by date’ is a simple idea, there is some merit in revisiting the purpose of the machine and looking at all potential utilization tasks. As agricultural systems change, the adoption of current ideas and technology may make a previous methodology and service requirement redundant.

This ‘blank canvas’ approach can open options for both utilization and potential machinery options not previously considered. This is less pertinent for specific task equipment (Combine harvester), however with the escalation of both cost and machine complexity/capacity this is a little less clear with options for a primary traction power unit (tractor).

The ‘Hughes S curve’ shows the principle of the overlap of technology/s as new idea adoption replaces a previous technology.

Where is your machine service task on this line? Is your current technology ‘out of date’? Don’t reinvest in declining technology.

What is the required capacity of the machine?
At a base level, this is a simple calculation that considers the greatest limiting factor when in use. Many farmers do these calculations frequently. For a machine that is restricted by ground speed and width, it is likely to be area required to cover/time allocated = worked required per time unit.

Example 1.
Minimum till. Seeding 2,000 ha/25 effective
days = 80 ha/day. 80Ha= 800,000 sqM.
If the ground speed is 8km/hr. = 8,000M/hr. x 12M (tillage width) = 96,000sqM/hr. = 8.33
hours/day.

However, that’s not the end of the equation. Machine efficiency is often overestimated.

A machine can only be considered to be working when it is providing its’ ‘service’ to a previously untreated area of operation. Whilst the field efficiency rates are influenced by many factors unique to each location. Listed below are some of the more common factors reducing efficiency. These are; paddock shape and angle of work, paddock obstacles, length of suitable runs for optimal speed of application, terrain undulations/surface conditions, implement failures/reliability, blockages, and environmental conditions.
The advent of telemetry data today suggests the following are good guides to current efficiency rates – which are dependent on
limiting factors:

From example 1 above. Apply average paddock efficiency – say 75%. 8.33 hrs./75% = 11.1 hrs. /day field time.

This establishes the capacity required of the machine investment to complete the service (task) requirement.

What is the replacement threshold?
A replacement threshold is a circumstance that acts as a catalyst to bring a decision point to action. Examples of circumstances that could be catalysts for action.

  • Insufficient capacity due to new (increased) service requirements.
  • Redundant technology that no longer provides the required ‘service’.
  • The desire to adopt technology unavailable with current equipment.
  • (Nb. b&c are the two opposing curves of the ‘innovation window’- see above)
  • Unacceptable operating costs with increased input prices (E.g., Fuel cost)
  • Unacceptable risk of time loss or production loss.

In all cases, and in keeping with the historical premise – each threshold can be monetized. It is essential to measure ‘all advantages’ resultant of a machinery decision. To use loss of production as an example, we further examine the example above.

The loss of production manifests in terms of reduced production value (downgraded) or sales value. In most cases, there is an element of prediction required and it is important the values applied are truly representative. We can all convince ourselves the numbers work if we want the desired outcome. Keep it real.

As an extension of example 1. take the loss of grain yield if the crop establishment falls outside the optimum planting window.

E.g. Reduced grain yield from the delayed planting date.

Rate of seeding example 1. = 80 ha/day
Yield at ideal planting time – 3.5T/ha
Reduced Yield if delayed by 30 days – 2.5 T/ha

Assuming a linear response to the yield loss, then the average loss of yield will be at 15 days and a mid-range loss, therefore the average reduced yield is 3.0T/ha x the area affected after the ideal date (not the whole
crop).

Lost production = 30 days x 80ha x 0.5 T/ha = 1,200T x grain price.
If the grain is worth $200/T net of all costs including harvest & handling = $240,000.

Graphic representation of yield loss per planting window delay.
A similar example could be worked for a downgrade from poor herbicide or fungicide application that results in a downgrade. Again, if the crop is only partially affected it is only justified to apply the discount to the
affected area.

What is the cost of the Machine (retained) vs Machine (replacement)?
Notwithstanding all the considerations about affordability within a cashflow, hire purchase vs lease vs outright purchase, relative interest rates, available depreciation rates, and the plethora of tax-related implications, there is a baseline cost of a machinery decision that needs to be calculated before any of these can be rightly contemplated.

Let’s assume you are considering a genuine replacement machine (like for like), no additional capacity, no advantages. In your eyes, an existing machine has reached a lifespan you consider to be ‘time to replace’.
Let’s also assume the capital cost of rebuilding the ‘complex components’ of the machine is also known and no further capital investment in the machine is acceptable.
Complex components are the components that need to be both removed from the machine and then further disassembled for re-manufacturing with specialized equipment and skills. E.g. Engine rebuilds, transmission remanufacturing, final drive re-race – you get the picture. These repairs extend the life of the machine past the ‘normal time to replace’ and give the machine a revised lifespan. Whilst these repairs can be treated as R&M costs, they can be considered as part of the capital cost of continuing to own and operate that machine – hence the expression – don’t overcapitalize a machine with excessive
repairs.

To demonstrate a method of determining the comparable costs of a machine investment decision, below is a table demonstrating the treatment of two different machines typical of a broadacre cropping operation.
Examples below are an SP sprayer and a 400Hp articulated tractor.

In each example, the cost of the replacement unit indicates an increase in the net capital cost for the same service, which brings into question the justification for replacing the machine at that point of lifespan. Can an
extended lifespan be considered?

It also shows that the replacement machine cost per measured unit can be reduced with the extension of the lifespan at a constant service rate annually (Ave ha/hr).

The final line in each example shows how overcapitalization of repairs can also increase the cost of the application of service per unit measured. Redundancy and unreliability
have superseded the machine.

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