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Summary of full report
Testing management strategies and financial feasibility of Angora goats for the production of mohair and meat
by Stephen Chaffey
June 2006
RIRDC Publication No 06/086 RIRDC Project No OSE1A
Who is the report targeted
at
The report (Chaffey &
McGregor 2004) proposed the Mohair industry take more control of the investment
decision-making process and this would lead to more people making more
informed decisions about the Angora goat enterprise. The report identified
a wide range of useful financial and management data existing in the mohair
industry however it had not been collected and packaged into a form that
enables people to make fast and informed commercial decisions about the
Angora goat enterprise. This project advances the work by Davies and Murray
(1997).
Background
The Australian mohair industry
is an emerging small industry in the Australian rural landscape exporting
mohair for processing into a range of luxury textiles. Low production volumes
and loss of breeding stock threaten the future viability and sustainability
of the industry. The mohair industry needs to expand and attract further
investment by current and existing commercial farmers.
Aims/Objectives
The aim of the project was
to create a financial analysis product, using computer software that was
easy to operate yet sufficient to test a range of management strategies
applicable to the Angora goat enterprise. The analysis includes revenue,
direct and indirect costs, taxation, capital costs, and depreciation over
a time frame of 12 years. The product is easily useable by industry and
allows for experimentation and learning about the different ways the enterprise
could be managed and the possible financial performance arising from different
management strategies and assumptions.
Method used
While benchmarking has become
a familiar phrase in Australian agriculture, Ronan and Cleary (2000) criticised
the whole business approach to benchmarking arguing the focus should be
on the processes involved in producing an output and that diagnostic power
comes from showing how all the performance numbers are linked to productivity,
costs, profit and return on investment. They argue ‘to act on benchmarking
results without then doing modelling, cost benefit analysis or partial
budgeting would miss a vital step’. This product is complementary to benchmarking
work carried out within the industry.
Given the case for business modelling and the complementary nature of benchmarking, the term Biz Mod has been used to describe the product. The commercially available software iThink® has been used as the platform to build the Biz Mod product. Hence through this document the product (software model) will be referred to as Biz Mod for Mohair (BMM).
The central feature of BMM is the herd population structure that allows population changes over time based on the parameters set by the user. Animals are weaned; they age, die, are bought and sold. As animals age the volume and quality of mohair produced changes. The model runs over a 12-year time frame with annual increments. This allows the user to think about how they might manage the enterprise over multiple years and what performance might be possible when adopting one management strategy versus another under a given set of assumptions.
Results/Key Findings
The results and findings
section takes a case study approach by using BMM to examine the establishment
of a self replacing angora enterprise with a desired breeding herd size
of 300 does. The initial strategies and assumptions are outlined and base
case performance illustrated. Details of each section of the model are
referred to in the appendices and the base case herd population, income
statement, cash flow, enterprise balance sheet and performance ratios are
also illustrated. A further eight tests are applied that examine different
actions and assumptions made by management and the resulting performance
compared to the original base case.
The management strategies and assumptions applied to the case study enterprise and the eight tests suggested an internal rate of return ranging from 9.3% to 21.2% over 12 years, a median gross margin per effective hectare ranging from $82 to $167, cash at bank in year 12 ranging from $8,700 to $56,800 and net enterprise assets ranging from $69,900 to $155,700.
Implications
A key benefit of BMM is
to allow new growers to explore potential management strategies and their
assumptions about a future enterprise before embarking upon it. Decisions
made early in the establishment of an enterprise can have significant effects
on the return on investment. They can also have significant effects on
delivery of mohair to Australian supply chains. For example, if the base
case strategy and assumptions were adopted to manage the case study enterprise
in test 1 the business would have returned an 11.5% internal rate of return
and 35,771 kilograms of mohair with a farm gate value of $331,196 over
twelve years of operation.
If ten new growers to the industry adopted the same strategies and assumptions based on test 1 then they would contribute 357,771 kilograms of mohair to the supply chain in the same time frame with a farm gate value of $3.3 million. However, if the ten new growers were able to make small improvements on key drivers of enterprise performance, the internal rate of return could move to 17.5%, a 52% increase (see test 5). They would also contribute an extra 24,770 kilograms of mohair to Australian supply chains over twelve years, an increase in total farm gate value of mohair of $305,110 over twelve years.
Recommendations
As a result of the project,
the following recommendations have been made: Introduce BMM
to the industry in partnership with the launch of the MLA ‘Going with Goats
– Profitable producer best practise guide’ to be carried out in 2006. Use
other industry functions during 2006 to promote the availability, benefits
and access arrangements for BMM.
Concurrently, identify private consultants, public officers or experienced growers who service the goat industry and select those who have the interest to use BMM in their consulting and advisory work. Offer this group a training program that enables them to competently present BMM to current and potential growers. The consulting group could have a BMM product that allows for data transfer to Microsoft Excel®.
Examine the opportunity to maintain an ongoing partnership with the MLA product ‘Going with Goats – Profitable producer best practise guide’ particularly if this program is workshop based.
Determine under what conditions BMM is transferred to growers. For example growers may need to participate in a short training program to become competent in using BMM and interpreting the output for their situation before gaining access to a version of BMM. Growers could access a product with or without links to Microsoft Excel®.
Monitor the use of BMM by consultants, service providers and growers to determine the extent of its use, the value it provides to its users and if any further developments would add additional value to the industry.
Monitor the use of BMM to determine if there is value in adapting the basic model to other industry sectors such as cashmere and meat goats to create Biz Mod for Cashmere and Biz Mod for Meat Goats in a way that further complements the MLA product ‘Going with Goats – Profitable producer best practise guide’.
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