Risk Analysis of Investments In-Milk Collection Centers

Milk marketing in rural area of Dhofar Region face a lot of difficulties and constrains by individual small scale farmers due to the lack of facilities and access to market. Therefore, farmers reduce their cow and camel milk production and group their animal into three or four groups to be milked in alternative days. Government Authorities decided to establish Milk Collection Centers to facilitate milk marketing and provide raw milk to Dairy industries. A risk analysis for the investment in milk collection centers on rural area of Dhofar Region was conducted in this study. The results showed that all MCC investments had a positive NPV except Shahbi Aseab Center. The study indicates there is a direct relationship between total milk collected, milk price, distant between MCC and Dairy plan and investment profitability. The study revealed an inverse relation between animal population at MCC zone and risk. The probability of achieving returns lower than the opportunity cost was highest for MCC located far from dairy plant which process and market dairy products. Risk premium for four MCC has been calculated relative to Salalah MCC (preferred location) and (Garoun Hirity MCC) was found as preferred MCC location and risk efficiency. In order to make the investment in MCC more attractive, the Government incentives need to be offered to farmers to increase milk production and improve raw milk quality. However, this approach might make investments in bulk milk collection centers feasible. Thus, a recommendable strategy for a successful modernization of the Oman dairy sectors inbound logistics would be to promote an increase in the volume of the milk produced per farm and improve marketing facilities through MCC.


Introduction
Dairy products are currently one of the main sources of income for a significant share of the Omani farmers at Dhofar Region.In 2014, Oman dairy market is estimated of 167 Million liters per year with annual growth of 6% and only 30% of the demand produced by local dairy plant based at Dhofar Region.Due to lack of facilities and access to market, farmers reduce their cow and camel milk production and group their animal into three or four groups to be milked in alternative days.Government Authorities decided to establish Milk Collection Centers to facilitate milk marketing and provide raw milk to Dairy industries.
Changes in the country's economic environment over the last decade such as market openings and economic stability etc. have made it crucial that the dairy business sector need to be modernized and become more competitive.Operating costs need to be reduced and raw material quality needs to be improved to achieve these goals.The milk collection systems needs to be implemented and being put into operation.Using these MCC systems, milk has to be collected and cooled to 6 ° at each MCC.The raw milk then collected daily by temperature controlled tank trucks to dairy plant for processing and marketing.
One of the probable consequences of the bulk milk collecting system is that it excludes remote areas and scattered small dairy farmers from the dairy business, since their output is considered insufficient to justify investment in MCC.As a contribution to the analysis of this issue, the present work assesses the risks involved in the installation and operation of five MCC at recommended location with appropriate animal population and density.The financial analysis of these investments was performed by (HVA International, 2010).However, this study did not consider risk analysis for this investment.
Volume of raw milk produced and collected is risk-dependent item since output depends on several factors, such as animal population at each location zone, climate & rainy season, costs, and capital investments.Milk production in Dhofar Region is increases during the summer (rainy season) and decreases during the winter (dry season).This seasonal change is due to change in available pasture and fodder crop as more pasture in the summer, less in the winter.Farm investments to expand the herd, improve breeding stock, control diseases, and install milk cooling systems are economic factors that can contribute to increase milk production and assure raw milk quality.
Monte Carlo Simulation models were used in this study to quantify risk and uncertainty in milk collection project at Dhofar Region.The quantitative risk analysis will provide decision and policy makers a means of NPV estimating the probability that the project NPV will fall below zero.The model will also help in improving dairy sector management policy and achieve project objectives simultaneously: sustaining dairy business for food security and preserving the associated natural environment.Danielle D. et al. (2000), use Monte Carlo simulations to estimate profitability of different size of milk cooling tank under risky environment.In this study government subsidy and incentives at five locations were compared by performing dynamic location model.
Using Monte Carlo Simulation dynamic model for project appraisal was addressed by Savvakis C. Savvides in (1994).He argued that this integrated analysis provided a range of outcomes that can reduce the risk of uncertainty and give more reliable results for investor.
To sum up, the analysis revealed that, although technologically and financially feasible, cooling tank investments are subject to uncertainties the effects of which can jeopardize efforts to modernize of milk collection system in rural area at Dhofar Region.These issues are discussed in depth in the following analysis.

Materials and Methods
Data collection and identification of the equipment needed for MCC were performed through direct contact with suppliers and producers who had already begun their milk collection systems modernization.The choice of tank sizes considered in this study was based on results of a comprehensive diagnostic and survey of the dairy milk production at farm level and dairy industry raw milk requirement.
In order to carry out a financial analysis, cash flows were built for the investment cost and expense and operation cost for each MCC.The main MCC investments were for cooling tanks purchase and the construction of milk receiving area and laboratories and connection of water and electricity.
The operation cost components were consumption of electric energy, consumption of detergents for tank sanitation, maintenance costs, labour cost, and milk transportation cost and investment depreciation.The price offered by dairies industry to farmers for cow and camel is 0.200 RO per Lit plus Government incentives: an additional 0.100 RO per Lit added to the price paid for warm milk for supplying cooled milk.MCC will pay raw milk from farmers by (0.200) and sell it to dairy plant of (0.295).The cost of MCC operation is differing according to distant to dairy plant, milk volume and a reduction of 50% in the typical charge for using the traditional milk collection and transportation system for using the much less costly bulk transport system.
Based on the results from financial analysis, a sensitivity analysis of the investment was carried out, in which some parameters considered in the cash-flow estimation were varied.For each variation, a new net present value (NPV) was calculated for each MCC location.This produced a set of graphs known as Cumulated Distribution Function, which allow the assessment of the degree of uncertainty associated to each MCC investments.Gouse, M. et al. (2009).Assess GM Maize technology amongst smallholders in South Africa.The Cumulative distribution functions (CDFs) are used to compared yield and net returns.The CDFs analysis in this study used to identify the total milk collected revenue and expense items that had the most significant impacts on the financial indicators.The potential risks associated to these items are evaluated in detail in this study.

Risk Analysis
The financial analysis performed by (HVA International, 2010) considered that the project would be implemented with perfect control of its variables.However, due to uncertainties in the near future, this approach only approximates reality.In practice, project risks should be investigated, defined, and then controlled by policy makers and decision-makers.Risk is defined as the possibility of future loss in predicted return over a certain period of time (Palisade Corporation, 1995;Martins & Assaf NETO, 1992) Calculated by the Author.
Uncertain variables in simulation mode outlined and estimated in Table 2. Initial unit price, sale price, raw milk collection volume, percentage of good milk received at plant and capital cost of the MCC establishment were the main uncertain variables incorporated in the models.Table 3 shows a recommended MCC locations, animal population and distance from each MCC zone to Dairy plant at Salalah City.
The modeling process began by defining a series of inputs to describe the initial status and behavior of the project and farm system.The underlying behavior of the local milk marketing system was represented using current knowledge and recorded data from survey, MAF and literature.The purpose of qualitative risk analysis in this study is to provide a high level of understanding of risks of the MCC project.Such analysis may increase attention of project management and policy team members to the top risks they need to understand and manage effectively.The operation cost estimated according to total raw milk volume and distance between MCC and Dairy plant at Salalah City.

SERF and Risk efficiency
The analysis of investment decision of MCC needs entails understanding of how investors rank alternative MCC locations with uncertain outcomes, given the stochastic MCC milk yield for each center and the stochastic market price of milk.The economic evaluation of MCC is implemented considering the whole range of net present values (NPVs) and their associated probabilities, along with the relative preferences (utilities) of the decision makers.To assess and compare the economics and the risk efficiency of each MCC location, this study employs stochastic simulation as an unconventional method that incorporates risk in the analysis (Hardaker, J.B., 2004).Stochastic dominance and stochastic efficiency with respect to a function (SDRF and SERF) analyses have a major advantage in that they reduce the set of all possible risky choices to a small group of alternatives.
The SERF technique is a novel improved methodology for assessing and ranking risky alternatives but empirical studies using SERF are limited, Especially in agriculture, SDRF and SERF analyses have been used to compare risky alternatives regarding farm production, marketing and financial matters.In this study, SERF analysis has been used to rank MCC locations and to determine risk efficiency of MCC locations, and also to explore the economic viability of MCC investment.However, this analysis will help in identifying best MCC location to start with and Government milk purchase subsidy required for each MCC location.

Results and Discussion
The study carried out by (HVA International, 2010), based on estimated cash flows, and showed that investment in MCC Project is only visible under Government price subsidy, since the 8% internal rate of return from that investment would be below the adopted 12% minimum rate of investment attractiveness.The previous study (Danielle et al., 2000), has not evaluated MCC locations risk in their study.However, this study investigated profitability for each recommended MCC location and incorporates risk of price paid to producer and milk collection volume for each MCC location in the analysis.Table 4 shows the result of simulated model for each MCC location and statistics.
The analysis shows that Garoun Hairity Location is highly profitable with RO 1 723 345 NPV and no risk of getting negative NPV and low Coefficient of Variation 0.402%.Shahbi Asaeb location got a negative NPV under different discount rates i.e. (6%-8%-10%-12% and 14%) and high Coefficient of Variation 1.190%.The probability of getting positive NPV for this location is only 20% with 6% discount rate and reduced to 3% at 14% discount rate.Government capital subsidy for this location is highly required to mitigate risk and encourage investors and farmers to participate and benefit from MCC project.

Cumulated Distribution Function (CDFs) Analysis
The Cumulated Distribution Function (CDFs) analysis performed to illustrate the range and probabilities of NPV for different MCC locations.Figure 1 shows Garoun Hirity location is a superior location and has a high probability of getting positive NPV.However, CDF analysis shows that Al Haq City and Tawi Ahater MCC location are not first-degree or second-degree stochastically dominant as their CDFs lines crossed each other up to cumulative probability of 0.45% is reached and no clear ranking under different ARAC is possible.However, a more improved technics such as stochastic dominance and stochastic efficiency with respect to a function analyses can be used to rank alternative MCC location risk efficiently within specified range of ARAC values. www.ccsen

Table 1 .
. Current data is imperfect, future data Camel milk production and feed of survey sampleThe above table shows that farmers with big animal group more than 100 camels could not maintain enough cash to feed his animal due to marketing and market access problems.According to animal population and distance from MCC to Dairy plant five MCC locations were recommended.Milk volume, initial unit cost and good quality milk received by dairy plant were also estimated according MCC location.

Table 2 .
Stochastic variables affect project NPV and at different MCC locations

Table 3 .
MCC location, animal population and distance from Dairy plant Raw milk selling price volatility and it is effect on NPV.Cost of operation and it is effects on NPV and annual increase in sales price and unit cost.Totalmilkcollectionvolume for year one and thereafter.Annualgrowth of milk collection for each MCC location.Percentage of good milk received at Dairy plant each year. Discount rate and it is effect on project viability and NPV.
The main risk and uncertainty variables identified in MCC Project were:  Project capital increase and it is effect on NPV.Raw milk availability and it is effect on MCC yield and NPV.