April 8, 2014

Jay Horton
Founder & Managing Director, Strategis Partners

Valuing the Farm

Becoming "Investment Ready"
The Global Food Forum held in Sydney in March 2014 highlighted the need for the farm sector to be “investment ready”. While there is a deep intuitive understanding across the farm sector of managing farm operations within an ever-changing context, few farm operators apply a rigorous framework for valuing the farm, or use a set of risk analytics to deal with uncertainty. Yet that is precisely what agri-investors need to see, in order to commit the hundreds of millions of dollars, ready to be deployed in Australian agriculture. Risk, complexity, and opportunity define agriculture in the decade ahead. Farm earnings are inherently uncertain and therefore, single-point estimates of farm values are generally misleading. Recall the explorer who drowned while crossing a river that was, on average, only one metre deep. This paper explains why farm operators need to move to an integrated approach to value and risk management.
 

What's Wrong with Conventional Valuation?
Under current valuation standards outlined by the Australian Property Institute, rural land values are determined by comparative analysis – essentially what farms down the road sold for. The earnings capacity of a property – the farm's ability to generate a stream of future cash flows – needs to be the new focus, not comparative property analysis. But there is a problem with conventional earnings valuation methods. It's the ‘flaw of averages’: Valuations based on the assumption that average conditions will occur are usually wrong. A farm valuation reflecting the outcome of future uncertain events is best represented, not by a single estimate of earnings value, but by a shape known as a probability distribution. Furthermore, the valuation should also take into account the agri-producer's real options to take actions – under the appropriate conditions – to increase cash in-flow and reduce cash out-flow.

Valuation must recognize the uncertainties in agriculture – and the value of flexibility
Any method of agri-investment valuation must explicitly recognize the prospect of 'droughts and flooding rains', volatile commodity prices, market competition, climate change uncertainty, and agri-tech innovation, but also the prospect of huge export opportunities in Asia. Valuation methods must also recognize the full array of producer flexibilities to deal with cash flow volatility. This reality of multiple uncertainties applies to the fast-growing agri-technology sector as well.

An integrated model of strategy, value and risk management
Agri-investments will succeed or fail depending on how well they are designed to cope with uncertainty. Value will be driven by product and process innovation, and the investor’s ability to respond to shifting markets, new technologies, and new regulatory imperatives. Scenario Planning and Risk Analytics tools – Monte Carlo and Real Option Valuation – have complementary advantages as tools to support investment decisions under uncertainty. Risk-analytical tools can improve our understanding of earnings value and risk. Monte Carlo and Real Options enable investors to lay out on the table the uncertainties and deal with them directly. Real options are designed to enlarge the flexibility of strategy implementation, thus reducing risk. Using probability to define risk, these tools can quantify the investor’s level of confidence about key investment assumptions, such as future crop yields, market prices, and production costs. The result is better investment decisions; more value with less risk.

Scenario Planning
Since the 1970s, Scenario Planning has been proven, time and again, as the essential uncertainty management tool. Scenarios are plausible, compelling yet surprising stories that describe how the future might pan out. They weave together changes in technologies, markets, politics, social values and drivers of change in the form of a “storyline.” Scenarios are not predictions, nor options from which a preferred choice should be made. Rather, they are examples distilled from many possible futures.They serve to challenge preconceptions about the future – since shifts to new environments are always disruptive. The natural inclination of managers is to work from what is known. Scenarios force us to look at what is not very well known, and what cannot be controlled.

Scenario Planning is used in three broad contexts:
1. Directional strategy – “given the future scenarios, what’s our best course of action?”
2. Contingency planning – “what risks and opportunities is the company not considering at present?”
3. Learning and team building – “what should be our company’s next big initiative?”
To find out more about Scenario Planning, click here.

What is Monte Carlo analysis?
Most spreadsheet valuation models predict results for an investment by changing each assumption one-by-one. In contrast, Monte Carlo analysis predicts results based on simultaneous changes in numerous input variables. Instead of using a single best guess for each input assumption, Monte Carlo simulates the impact of multiple risks on an asset’s value by running the valuation model thousands of times. The input variables are sampled from their respective probability distributions for each run of the model, while the resulting outputs are tracked.

The output is a probability distribution of the investment's net present value, as shown in Exhibit 1.

Monte Carlo analysis is well suited to modelling agri-investments, which have many value and risk drivers, each of which can be modelled as a probability distribution:

• Future market prices and sales volumes
• What level of product quality the market will demand
• Future production yields and operating costs
• Cost to expand capacity, now and in the future.

One limitation of Monte Carlo, however, is that it does not take into account the fact that decision-makers can change course in response to changing conditions. This is where Real Options is so powerful.

Real Option Valuation

The real option model defines an investment as a set of decisions, which can be taken both now and in the future, in the form of a decision tree as shown in Exhibit 2. Uncertainties or risks are modelled by discrete distributions also shown in Exhibit 2. Real Option Valuation recognises that a key element of value in agri-investments can be their inherent flexibility. Agri-producers can Maximize value and minimise risk through such actions as converting the land to alternative uses, switching to other crops, building storage capacity, and so on. To find out more about Real Option Valuation, click here.

In Conclusion
Integrated strategic, value and risk management works as:

• A different way of thinking: recognizing that multiple scenarios and pathways to the future are a better way to manage risks and opportunities than a single view of the future;
• New analytics for evaluating investments: These methods enable investors to lay out on the table the uncertainties and deal with them directly. They quantify the investor’s level of confidence about key investment assumptions;
• A dynamic decision making process that involves a strategic dialogue between the decision makers, experts and financial analysts – and integrates the tasks of formulating strategy and implementing strategy.

How companies respond to the big uncertainties and opportunities of our time – disruptive technologies, global economic shifts, volatile commodity prices, climate change – can benefit from an integrated model of strategy, value and risk management for agri-investments.

About Strategis Partners
Strategis Partners is a management consultancy and executive development firm operating in Australia and across South East Asia. The Firm works with clients in agriculture, food & beverage manufacturing, supply chain – logistics, retail distribution industries.

About the Author
Jay Horton, Founder and Managing Director of Strategis Partners, is a leading adviser to Companies and Governments in Asia and Australia on strategic management issues, including scenario planning, capital investment decision making and real options analysis, and corporate strategy. During his twenty five year management consulting career, he has worked with clients in Australia, Canada, China, Japan, Hong Kong, New Zealand and South East Asia. Jay has played a number of leadership roles, including as a Partner of PricewaterhouseCoopers, McKinsey & Company, and Managing Director of management consultancy ORG Pty Ltd. Jay is a regular guest lecturer at the Australian School of Management, the Sydney University School of Business & Economics, Australian School of Business at the University NSW, and the Macquarie Graduate School of Management. Jay’s qualifications include Master of Arts from Sydney University, Master of Economics from Australian National University, a Bachelor of Engineering – Electrical from James Cook University, and Fellow of the Australian Institute of Company Directors.

Contact Strategis Partners
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Sydney, NSW 2000
Phone: +61 2 9238 6886
info@strategispartners.com.au
www.strategispartners.com.au

To download a copy of this paper, click here.

The opinions expressed in this editorial are the author's own and do not reflect the view of Global AgInvesting.