**2. Description of DairyMGT.info Decision Support Tools**

This section lists and describes the DSS object of this chapter. These DSS are categorized in main areas of dairy farm management, as they appear in the DairyMGT.info: *Tools* webpage.

#### **2.1. Nutrition and Feeding (DairyMGT.info → Tools→ Feeding)**

Dairy farmers recognize that the largest item cost in a dairy farm system is feed, whether purchased or farm-grown. Obviously the major source of income in a dairy farm operation is the milk sale. Consequently, managing and optimizing the milk income over feed cost is a critical decision that affects not only economic sustainability, but also has large impacts re‐ garding environmental stewardship[12]. Farmers also recognize that every farm is com‐ pletely different and that market conditions are constantly changing. Therefore, beyond established farm feeding rations, there is a need for tools to permanently adjust strategic feeding decisions. Take as an example corn grain and its highly volatile price. Corn is a sta‐ ple feed commodity for dairy farm feeding and consequently its price influences largely diet costs. With sudden corn price swings farmers confront permanently the question of re-con‐ sidering the amount of corn in the diet. This question can be responded by estimating the marginal value of milk (also depending on highly volatile prices) to corn according to lacta‐ tion stage and current amount of corn in the diet. The optimal use of corn would occur when the marginal value of milk equals the marginal value of corn, which at research-based feed efficiency levels [13], would solely depend on the ever-changing price relationship of milk and corn. The tool "*Corn Feeding Strategies*" shows these relationships in a graphical, dynamic, and interactive way so dairy farmers can optimize the amount of corn grain in each farm feeding group according to ever-changing market price conditions.

mental stewardship. Depending on the complexity, the specific purpose, and the requirements of dairy farm decision makers, some DSS are completely online applications, others are Macromedia Flash tools, others are Spreadsheets, and others are self-extractable

This chapter discusses the challenges on the development of these DSS with respect to the trade-offs among user-friendly design, computational detail, accuracy of calculations, and bottom line efficiency performance and effective decision-making. It portrays DSS develop‐ ment strategies, within the computational resources available, that succeeded in their pri‐ mary objective of providing dairy farm mangers fast and reliable responses to perform

The chapter reveals practical and real-life applications of a number of these DSS to demon‐ strate satisfactory system assessment, acceptable future predictability, adequate scenario

The chapter also covers aspects of DSS dissemination and adoption evaluation, including the inception and development of a dedicated webpage; local, national and international us‐

The chapter also infers the possible role of emerging and evolving new technologies such as smart phones and tablets in the intersection of DSS, real-time applications, and mobile devi‐

This section lists and describes the DSS object of this chapter. These DSS are categorized in main areas of dairy farm management, as they appear in the DairyMGT.info: *Tools* webpage.

Dairy farmers recognize that the largest item cost in a dairy farm system is feed, whether purchased or farm-grown. Obviously the major source of income in a dairy farm operation is the milk sale. Consequently, managing and optimizing the milk income over feed cost is a critical decision that affects not only economic sustainability, but also has large impacts re‐ garding environmental stewardship[12]. Farmers also recognize that every farm is com‐ pletely different and that market conditions are constantly changing. Therefore, beyond established farm feeding rations, there is a need for tools to permanently adjust strategic feeding decisions. Take as an example corn grain and its highly volatile price. Corn is a sta‐ ple feed commodity for dairy farm feeding and consequently its price influences largely diet costs. With sudden corn price swings farmers confront permanently the question of re-con‐ sidering the amount of corn in the diet. This question can be responded by estimating the marginal value of milk (also depending on highly volatile prices) to corn according to lacta‐ tion stage and current amount of corn in the diet. The optimal use of corn would occur when the marginal value of milk equals the marginal value of corn, which at research-based

ces, which is a fast growing area of development within the dairy farming industry.

**2. Description of DairyMGT.info Decision Support Tools**

**2.1. Nutrition and Feeding (DairyMGT.info → Tools→ Feeding)**

and installable programs.

144 Decision Support Systems

efficient and effective decision-making.

evaluation, and, consequently, satisfactory decision-making.

age, requested presentations, and academic publications.

Take as another example the price of the main dairy cattle feed commodities and their rela‐ tionship with milk price according to feed efficiency changes throughout lactation states. Re‐ search data indicate that the use of concentrates (i.e., corn, soybean meal) have a substantially higher impact on milk production during early or mid-lactation than in late lactation [14]. Under this premise, increased use of forages is justified in late lactation to maximize the overall milk income over feed cost, which however depends on ever-changing feed commodity prices. The tool "*Income Over Feed Cost*" graphs interactively the milk in‐ come over feed cost weekly for entire lactations and shows the impact of feed commodity prices on the dynamic milk income over feed cost value. Therefore, dairy farmers can finetune their feeding strategies to maximize their milk income over feed cost according to lacta‐ tion states and feed prices swings.

Sometimes dairy farmers need additional help on formulating their diets to optimize feed con‐ centrate supplementation. Research trails indicate that the optimal level of concentrate supple‐ ments in a diet could be achieved by using milk production response to crude protein (CP) and its components of rumen un-degradable protein (RUP), and rumen degradable protein (RDP), according to particular cow-group rations [15]. The tool "*Income over Feed Supplement Cost*" per‐ forms an optimization according to defined feed ingredients, prices, and CP (RUP, RDP) re‐ strictions to maximize the net return. The tool helps dairy farm decision makers to select the most cost effective concentrate supplements in the diet, especially from the point of view of providing adequate amounts of RUP and RDP, which not only optimizes the net return, but al‐ so reduces the amount of nitrogen excretion and hence environmental impacts.

Dairy farmers also want to know what are the best-priced feed ingredient choices in the mar‐ ket. This information would drive farmer feed purchase decisions. The tool called "*FeedVal 2012*" is a dynamic and interactive matrix that finds the estimated price of a feed as an aggre‐ gated sum of its individual nutrients values according to the nutrient content and prices of a set of defined feed ingredients available in the market. The tool then compares the actual price of a feed ingredient with its calculated price. The result is a list of ingredients with their relative pri‐ ces, indicating if an ingredient is a bargain or an expensive proposition.

Another critical factor in the quest for feed efficiency and maximum milk income over feed cost is the analysis of "benchmarking" with respect to feed efficiency, milk income, and feed costs [16]. Results from surveying dairy farm rations and farm prices reveals an impressive difference regarding to feed costs, feed consumption, and overall milk income over feed cost among otherwise similar dairy farms. A large and important opportunity exists then to im‐ prove the milk value net of the feed costs by comparing performance among farms. There‐ fore an online database structure and DSS was developed: "*Dairy Extension Feed Cost Evaluator*," Figure 1. This tool performs advanced benchmarking analyses for a group of users within a region, state, or country throughout a defined timeline by querying an online database, which is permanently being updated by the users. The tool allows users to "drilldown" the analysis and find out the driving factors for differences, an important step to‐ ward improving dairy farm feed efficiency and income over feed cost.

both, are continuously and permanently evolving. Dairy farmers need not only to keep up-todate with all these technologies, but also make the best decisions according to their own condi‐ tions [5]. Dairy farmers usually know which reproductive programs are more efficient from the reproductive point of view of getting more cows pregnant. Farmers also have a good han‐ dle on costs incurred according to reproductive programs. Nonetheless, dairy farmers have difficulty assessing the overall profitability of reproductive programs. Not surprisingly, they have long demanded for a systematic economic analysis to analyze reproductive programs. The tool "*UW-DairyRepro\$Plus*" is a complex, still user-friendly, decision support systems that assess the economic value of farm-defined alternative reproductive programs for a particular farm according to prevalent market conditions. These tools allow farmers to be highly specific regarding their current or alternative reproductive programs. Besides reporting the most im‐ portant reproductive parameters for each alternative program, the tools find the reproductive program with the best economic outcome and calculates the difference in net returns a farm

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Sex-sorted semen that increases the chance of female offspring is a relatively new technol‐ ogy being widely adopted in the dairy industry. Farm-specific sexed semen's economic value and, moreover, when and how to use it, are critical. The tool "*Economic Value of Sexed Semen for Dairy Heifers*" (Figure 2) finds interactively the gain (or loss) of different reproductive program management strategies that include sexed semen compared with

would have when using alternative reproductive programs.

**Figure 2.** Screen snapshot of DSS *Economic Value of Sexed Semen for Dairy Heifers*.

As important as to find out the value of specific-defined reproductive programs is to explore the value of improving the overall reproductive efficiency. The tool "*Dairy Reproductive Eco‐ nomic Analysis*" is a Markov-chain stochastic dynamic model packed in a simple to use on‐

solely using conventional semen [18].


**Figure 1.** Screen snapshot of DSS *Dairy Extension Feed Cost Evaluator*.

Dairy farmers also require some simpler evaluation tools for feed additives. The tool "*Opti‐ gen® Evaluator*" analyzes the economic value of including this slow release urea additive while maintaining diets at the same level of protein and dry matter intake. The tool "*Dairy Ration Feed Additive Break-Even Analysis*" determines any additive's additional milk produc‐ tion needed to justify its economic inclusion in the diet.

Finally, regarding nutrition and diets, there is some evidence that dairy farmers might be over-feeding a large proportion of lactating cows when they feed the same diet ration to a large group of animals. Diets are normally formulated to provide enough nutrients to the most productive animals, which in turn gives extra nutrients to the less productive animals within the same group. Therefore, splitting lactating cows in smaller groups and offering group-specific feeding rations provide more precise nutrient requirements, increase herd's income over feed cost, and decrease nutrient excretion [17]. The tool "*Grouping Strategies for Feeding Lactating Dairy Cattle*" calculates dynamically individual cow nutrient requirements and optimizes cow grouping feeding strategies within particular farm constraints.

#### **2.2. Reproductive Efficiency (DairyMGT.info → Tools→ Reproduction)**

Reproductive efficiency plays a critical role in the economics of dairy farming. However, as‐ sess the economic value of it is extremely difficult and complex [5]. A first step on under‐ standing the economic impact of reproductive programs is to demonstrate the milk value net of feed cost dependent on the pregnancy time. The tool "*Exploring Pregnancy Timing Im‐ pact on Income over Feed Cost*" shows interactively and dynamically a cow's total milk income net of feed costs to a fixed lactation's pregnancy time and defined lactation curves. The tool illustratesand quantifies the economic value of having cows pregnant at the right time.

Dairy farmers are also required to do complex decisions regarding the best reproductive pro‐ grams for the lactating herd population. New reproductive management strategies, whether they use hormonal synchronization technologies, heat detection methods, or a combination of both, are continuously and permanently evolving. Dairy farmers need not only to keep up-todate with all these technologies, but also make the best decisions according to their own condi‐ tions [5]. Dairy farmers usually know which reproductive programs are more efficient from the reproductive point of view of getting more cows pregnant. Farmers also have a good han‐ dle on costs incurred according to reproductive programs. Nonetheless, dairy farmers have difficulty assessing the overall profitability of reproductive programs. Not surprisingly, they have long demanded for a systematic economic analysis to analyze reproductive programs. The tool "*UW-DairyRepro\$Plus*" is a complex, still user-friendly, decision support systems that assess the economic value of farm-defined alternative reproductive programs for a particular farm according to prevalent market conditions. These tools allow farmers to be highly specific regarding their current or alternative reproductive programs. Besides reporting the most im‐ portant reproductive parameters for each alternative program, the tools find the reproductive program with the best economic outcome and calculates the difference in net returns a farm would have when using alternative reproductive programs.

down" the analysis and find out the driving factors for differences, an important step to‐

Dairy farmers also require some simpler evaluation tools for feed additives. The tool "*Opti‐ gen® Evaluator*" analyzes the economic value of including this slow release urea additive while maintaining diets at the same level of protein and dry matter intake. The tool "*Dairy Ration Feed Additive Break-Even Analysis*" determines any additive's additional milk produc‐

Finally, regarding nutrition and diets, there is some evidence that dairy farmers might be over-feeding a large proportion of lactating cows when they feed the same diet ration to a large group of animals. Diets are normally formulated to provide enough nutrients to the most productive animals, which in turn gives extra nutrients to the less productive animals within the same group. Therefore, splitting lactating cows in smaller groups and offering group-specific feeding rations provide more precise nutrient requirements, increase herd's income over feed cost, and decrease nutrient excretion [17]. The tool "*Grouping Strategies for Feeding Lactating Dairy Cattle*" calculates dynamically individual cow nutrient requirements

Reproductive efficiency plays a critical role in the economics of dairy farming. However, as‐ sess the economic value of it is extremely difficult and complex [5]. A first step on under‐ standing the economic impact of reproductive programs is to demonstrate the milk value net of feed cost dependent on the pregnancy time. The tool "*Exploring Pregnancy Timing Im‐ pact on Income over Feed Cost*" shows interactively and dynamically a cow's total milk income net of feed costs to a fixed lactation's pregnancy time and defined lactation curves. The tool illustratesand quantifies the economic value of having cows pregnant at the right time.

Dairy farmers are also required to do complex decisions regarding the best reproductive pro‐ grams for the lactating herd population. New reproductive management strategies, whether they use hormonal synchronization technologies, heat detection methods, or a combination of

and optimizes cow grouping feeding strategies within particular farm constraints.

**2.2. Reproductive Efficiency (DairyMGT.info → Tools→ Reproduction)**

ward improving dairy farm feed efficiency and income over feed cost.

146 Decision Support Systems

**Figure 1.** Screen snapshot of DSS *Dairy Extension Feed Cost Evaluator*.

tion needed to justify its economic inclusion in the diet.

Sex-sorted semen that increases the chance of female offspring is a relatively new technol‐ ogy being widely adopted in the dairy industry. Farm-specific sexed semen's economic value and, moreover, when and how to use it, are critical. The tool "*Economic Value of Sexed Semen for Dairy Heifers*" (Figure 2) finds interactively the gain (or loss) of different reproductive program management strategies that include sexed semen compared with solely using conventional semen [18].

**Figure 2.** Screen snapshot of DSS *Economic Value of Sexed Semen for Dairy Heifers*.

As important as to find out the value of specific-defined reproductive programs is to explore the value of improving the overall reproductive efficiency. The tool "*Dairy Reproductive Eco‐ nomic Analysis*" is a Markov-chain stochastic dynamic model packed in a simple to use on‐ line application. This tool integrates detailed parameters of pregnancy, abortion, and culling risks to perform iterations during 9 lactations until a herd reaches a steady state [19]. Then, the economic value of a reproductive program is determined by using predicted milk pro‐ duction curves, calve value, replacement costs, and other economic figures. The end result is a net return tied to a reproductive performance.

place cows. This tool, in addition, calculates the expected herd demographics and the aver‐ age herd net return for better and additional dairy farm management and decision-making.

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**Figure 3.** Screen snapshot of DSS *The Economic Value of a Dairy Cow*.

**2.4. Production and Productivity (DairyMGT.info → Tools→ Production)**

which can be accomplished by using the tool "*Milk Curve Fitter,"* Figure 4.

Dairy farmers face several decisions regarding production-related issues. In order to make best decisions, they would like to know how their farm milk production profile compares to other similar farms. Besides milk amount produced per animal, the shape of the herd's lactation curves is critical to pinpoint management weaknesses and strengths of a particular farm. The tool "*Lactation Benchmark Curves for Wisconsin*" displays different parity lactation curves for different production levels herds obtained by processing 3.6 million lactation records. Dairy farmers can define their own lactation curves to assess their production performance com‐ pared with the benchmarked records. Similarly, farmers find great benefit of projecting their own lactation curves and compare specific dairy herd cows to the standards of the whole herd,

#### **2.3. Heifer Management and Cow Replacement (DairyMGT.info → Tools→ Heifers / Replacement)**

Whether farmers raise replacement heifers or not, they benefit from decisions related to this dairy farming enterprise. One first step on the economic decision about heifers is to determine the overall cost associated with rearing heifers according to estimated time to first calving. The tool "*Heifer Break-Even*" calculate the daily and accumulated cost for rearing heifers up to 12 months, 24 months, and beyond 24 months according to farm-defined prices for forages, corn, and soybean meal. Farmers use this tool to decide if to raise their own heifers, use custom-rais‐ ing heifer services, or simply buy heifer replacements, according to market prices.

When farmers raise heifers on-farm, another decision comes along: to use or not to use acceler‐ ated feeding programs for boosting the early development of calves. The tool "*Cost-Benefit of Accelerated Feeding Programs*" gives dairy farmers the opportunity to compare hand-by-hand their current heifers' feeding program with an alternative accelerated feeding program within farm defined conditions. This tool shows economic differences at weaning and calving and cal‐ culates the amount of milk amount that would be needed to pay for heifer rearing costs.

In addition to the decisions of raising heifers and if to use accelerated feeding programs, dai‐ ry farmers want to know the number of heifers needed to maintain (or increase) the herd size according to farm long-term goals, reproductive efficiency, and heifers' culling rates. The tool "*Heifer Replacement*" calculates the number of replacement animals needed (spring‐ er heifers) responding to farm specific data inputs.

Dairy farmers would need to buy (or sell) springing heifers if the number of he replace‐ ments is fewer (or greater) than the required number to achieve the goal of maintaining or expand the herd size. Consequently, they need support on estimating the right price to pay (or to sell) springing heifers. The tool "*Value of a Springer*" performs a projection of the net return an animal would have under farm specific conditions. This value indicates the value of a replacement to break-even its costs. Because of the uncertainty in the milk price, milk production, and the productive lifetime, the model presents outcomes under different price and lifetime scenarios, so farmers can make decisions based on their assertion of the future prices and their risk preferences.

Furthermore, dairy farmers need to make critical decisions if to keep or replace a cow from the herd. The optimal decision will depend on which alternative would bring a greater net return in the future. The tool "*The Economic Value of a Dairy Cow*" (Figure 3) is a complex Markov-chain simulation model, still a user-friendly application that calculates interactively the economic value of a cow (or the value of each single cow in a herd) compared with its replacement [20]. Farmers use this value to make more informed decisions if to keep or re‐ place cows. This tool, in addition, calculates the expected herd demographics and the aver‐ age herd net return for better and additional dairy farm management and decision-making.


**Figure 3.** Screen snapshot of DSS *The Economic Value of a Dairy Cow*.

line application. This tool integrates detailed parameters of pregnancy, abortion, and culling risks to perform iterations during 9 lactations until a herd reaches a steady state [19]. Then, the economic value of a reproductive program is determined by using predicted milk pro‐ duction curves, calve value, replacement costs, and other economic figures. The end result is

**2.3. Heifer Management and Cow Replacement (DairyMGT.info → Tools→ Heifers /**

ing heifer services, or simply buy heifer replacements, according to market prices.

Whether farmers raise replacement heifers or not, they benefit from decisions related to this dairy farming enterprise. One first step on the economic decision about heifers is to determine the overall cost associated with rearing heifers according to estimated time to first calving. The tool "*Heifer Break-Even*" calculate the daily and accumulated cost for rearing heifers up to 12 months, 24 months, and beyond 24 months according to farm-defined prices for forages, corn, and soybean meal. Farmers use this tool to decide if to raise their own heifers, use custom-rais‐

When farmers raise heifers on-farm, another decision comes along: to use or not to use acceler‐ ated feeding programs for boosting the early development of calves. The tool "*Cost-Benefit of Accelerated Feeding Programs*" gives dairy farmers the opportunity to compare hand-by-hand their current heifers' feeding program with an alternative accelerated feeding program within farm defined conditions. This tool shows economic differences at weaning and calving and cal‐ culates the amount of milk amount that would be needed to pay for heifer rearing costs.

In addition to the decisions of raising heifers and if to use accelerated feeding programs, dai‐ ry farmers want to know the number of heifers needed to maintain (or increase) the herd size according to farm long-term goals, reproductive efficiency, and heifers' culling rates. The tool "*Heifer Replacement*" calculates the number of replacement animals needed (spring‐

Dairy farmers would need to buy (or sell) springing heifers if the number of he replace‐ ments is fewer (or greater) than the required number to achieve the goal of maintaining or expand the herd size. Consequently, they need support on estimating the right price to pay (or to sell) springing heifers. The tool "*Value of a Springer*" performs a projection of the net return an animal would have under farm specific conditions. This value indicates the value of a replacement to break-even its costs. Because of the uncertainty in the milk price, milk production, and the productive lifetime, the model presents outcomes under different price and lifetime scenarios, so farmers can make decisions based on their assertion of the future

Furthermore, dairy farmers need to make critical decisions if to keep or replace a cow from the herd. The optimal decision will depend on which alternative would bring a greater net return in the future. The tool "*The Economic Value of a Dairy Cow*" (Figure 3) is a complex Markov-chain simulation model, still a user-friendly application that calculates interactively the economic value of a cow (or the value of each single cow in a herd) compared with its replacement [20]. Farmers use this value to make more informed decisions if to keep or re‐

a net return tied to a reproductive performance.

er heifers) responding to farm specific data inputs.

prices and their risk preferences.

**Replacement)**

148 Decision Support Systems

#### **2.4. Production and Productivity (DairyMGT.info → Tools→ Production)**

Dairy farmers face several decisions regarding production-related issues. In order to make best decisions, they would like to know how their farm milk production profile compares to other similar farms. Besides milk amount produced per animal, the shape of the herd's lactation curves is critical to pinpoint management weaknesses and strengths of a particular farm. The tool "*Lactation Benchmark Curves for Wisconsin*" displays different parity lactation curves for different production levels herds obtained by processing 3.6 million lactation records. Dairy farmers can define their own lactation curves to assess their production performance com‐ pared with the benchmarked records. Similarly, farmers find great benefit of projecting their own lactation curves and compare specific dairy herd cows to the standards of the whole herd, which can be accomplished by using the tool "*Milk Curve Fitter,"* Figure 4.

**2.5. Price Risk Management and Financial Assessment (DairyMGT.info → Tools→**

sess farm financial performance compared with peers [22].

Unfavorable prices of milk and feed commodities together with increased price volatility create large uncertainty in the dairy farm business. Recent unprecedented uncertain times have prompted to re-visit farm's financial status and look for alternatives to stabilize net re‐ turns. It is critical to explore price risk management alternatives such as the relatively new revenue insurance program called Livestock Gross Margin for Dairy (LGM-Dairy) and to as‐

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In brief, the LGM-Dairy can protect the net margin (milk value less feed cost or milk income over feed cost) at a much lower cost than using comparable options in the future markets. The tool "*LGM-Analyzer*" (Figure 5) is an online, easy-to-use, suite of real-time, data intense, simulation, and optimization integrated modules to help on the decision of using LGM-Dai‐ ry. The *LGM-Analyzer* not only replicates the official premium calculation from the U.S. De‐ partment of Agriculture Risk Management Agency, but also is capable of perform historical sensitivity analysis as well as complex optimizations to minimize the premium cost at a lev‐ el of target guaranteed income over feed cost. This suite of tools is also capable of comparing the LGM-Dairy with more traditional price risk management tools such as puts (Class III milk) and calls (corn and soybean meal) for feeds as bundled price options. The *LGM-Ana‐ lyzer* connects live with the dairy and grain-based futures and market (through a structured query language) to determine the premium cost a particular farmer could expect according to a guarantee income over feed cost ("*Premium Estimator*"). Furthermore, a unique module ("*Least Cost Optimizer*") lets the user to minimize the LGM-Dairy premium cost at a defined level of income over feed cost insured. Other tools in the area of analysis of the LGM-Dairy include the "*LGM-Dairy Feed Equivalent*," a tool to covert feed diet ingredients to corn and soybean meal equivalents needed for a LGM-Dairy contract and the "*Net Guarantee Income over Feed Cost*," a tool to help dairy farmers determine the income over feed cost to break-

even all other costs of production, which should be covered by using LGM-Dairy.

fies cash excesses and shortfalls well in advance of their occurrence.

Also, performing a farm's financial benchmark assessment is critical in the process of meas‐ uring the financial health of a dairy farm. Moreover, this is usually required by lenders in order to consider loan applications. The "*Wisconsin Dairy Farm Benchmarking Tool*" is a data‐ base application that calculates 15 financial ratios including variables of liquidity, solvency, profitability, repayment capacity, and financial efficiency for a group of more than 500 Wis‐ consin dairy farms during a period of 10 years. The tool then compares each one of these ratios with those of a particular farm. Therefore, farmers can assess their financial health compared with their peers. Furthermore, the tool provides a *DuPont* analysis, in which a farm is compared against the population with respect to revenue and profit generated for every dollar invested. Another related tool, "*Working Capital Decision Support System*" assists dairy farmers in identifying cash flows, project expected incomes and expenses, and identi‐

**Financial)**

**Figure 4.** Screen snapshot of DSS *Milk Curve Fitter*.

As a result of benchmarking their herd's lactation curves, dairy farmers may contemplate a new set of decisions to improve productive performance such as switching the number of milking times per day [21] or re-consider the use of recombinant bovine somatotropin (rbST), a synthetic metabolic hormone that improves milk productivity. The tool "*Economic Analysis of Switching from 2X to 3X Milking*" performs a farm-specific partial budgeting anal‐ ysis of the projected gain (or loss) when a farmer decides to milk 3 times a day instead of 2 times. The tool "*Economic Analysis of using rbST*" displays the economic gain (or loss) of us‐ ing rbST as an interactive sensitivity analysis according to ever-changing milk price and esti‐ mated milk increase because of rbST under specific farm conditions.

Some dairy farmers are also interested in the possibility of either expand or modernize their farm facilities or increase their herd size. Therefore, they require support on impor‐ tant decisions that will drive the future of the dairy farm operation. The tool "*Decision Support System Program for Dairy Production and Expansion*" is a Spreadsheet application that allows dairy farmers to outline their current farm conditions regarding herd struc‐ ture and market conditions, define a possible plan of expansion or modernization includ‐ ing required loans (for facilities and animals), and project the cash flow of the entire farm up to a period of 54 months in the future.

#### **2.5. Price Risk Management and Financial Assessment (DairyMGT.info → Tools→ Financial)**

Unfavorable prices of milk and feed commodities together with increased price volatility create large uncertainty in the dairy farm business. Recent unprecedented uncertain times have prompted to re-visit farm's financial status and look for alternatives to stabilize net re‐ turns. It is critical to explore price risk management alternatives such as the relatively new revenue insurance program called Livestock Gross Margin for Dairy (LGM-Dairy) and to as‐ sess farm financial performance compared with peers [22].

In brief, the LGM-Dairy can protect the net margin (milk value less feed cost or milk income over feed cost) at a much lower cost than using comparable options in the future markets. The tool "*LGM-Analyzer*" (Figure 5) is an online, easy-to-use, suite of real-time, data intense, simulation, and optimization integrated modules to help on the decision of using LGM-Dai‐ ry. The *LGM-Analyzer* not only replicates the official premium calculation from the U.S. De‐ partment of Agriculture Risk Management Agency, but also is capable of perform historical sensitivity analysis as well as complex optimizations to minimize the premium cost at a lev‐ el of target guaranteed income over feed cost. This suite of tools is also capable of comparing the LGM-Dairy with more traditional price risk management tools such as puts (Class III milk) and calls (corn and soybean meal) for feeds as bundled price options. The *LGM-Ana‐ lyzer* connects live with the dairy and grain-based futures and market (through a structured query language) to determine the premium cost a particular farmer could expect according to a guarantee income over feed cost ("*Premium Estimator*"). Furthermore, a unique module ("*Least Cost Optimizer*") lets the user to minimize the LGM-Dairy premium cost at a defined level of income over feed cost insured. Other tools in the area of analysis of the LGM-Dairy include the "*LGM-Dairy Feed Equivalent*," a tool to covert feed diet ingredients to corn and soybean meal equivalents needed for a LGM-Dairy contract and the "*Net Guarantee Income over Feed Cost*," a tool to help dairy farmers determine the income over feed cost to breakeven all other costs of production, which should be covered by using LGM-Dairy.

**Figure 4.** Screen snapshot of DSS *Milk Curve Fitter*.

150 Decision Support Systems

up to a period of 54 months in the future.

As a result of benchmarking their herd's lactation curves, dairy farmers may contemplate a new set of decisions to improve productive performance such as switching the number of milking times per day [21] or re-consider the use of recombinant bovine somatotropin (rbST), a synthetic metabolic hormone that improves milk productivity. The tool "*Economic Analysis of Switching from 2X to 3X Milking*" performs a farm-specific partial budgeting anal‐ ysis of the projected gain (or loss) when a farmer decides to milk 3 times a day instead of 2 times. The tool "*Economic Analysis of using rbST*" displays the economic gain (or loss) of us‐ ing rbST as an interactive sensitivity analysis according to ever-changing milk price and esti‐

Some dairy farmers are also interested in the possibility of either expand or modernize their farm facilities or increase their herd size. Therefore, they require support on impor‐ tant decisions that will drive the future of the dairy farm operation. The tool "*Decision Support System Program for Dairy Production and Expansion*" is a Spreadsheet application that allows dairy farmers to outline their current farm conditions regarding herd struc‐ ture and market conditions, define a possible plan of expansion or modernization includ‐ ing required loans (for facilities and animals), and project the cash flow of the entire farm

mated milk increase because of rbST under specific farm conditions.

Also, performing a farm's financial benchmark assessment is critical in the process of meas‐ uring the financial health of a dairy farm. Moreover, this is usually required by lenders in order to consider loan applications. The "*Wisconsin Dairy Farm Benchmarking Tool*" is a data‐ base application that calculates 15 financial ratios including variables of liquidity, solvency, profitability, repayment capacity, and financial efficiency for a group of more than 500 Wis‐ consin dairy farms during a period of 10 years. The tool then compares each one of these ratios with those of a particular farm. Therefore, farmers can assess their financial health compared with their peers. Furthermore, the tool provides a *DuPont* analysis, in which a farm is compared against the population with respect to revenue and profit generated for every dollar invested. Another related tool, "*Working Capital Decision Support System*" assists dairy farmers in identifying cash flows, project expected incomes and expenses, and identi‐ fies cash excesses and shortfalls well in advance of their occurrence.


simplified version of nutrient balance between nitrogen and phosphorus manure excre‐ tion for a fast assessment is the tool with name *"Dairy Nutrient Manager."* Also related, the "*Grazing-N*" is an application that balances nitrogen for dairy farms with grazing ac‐ tivities and the "*Seasonal Prediction of Manure Excretion,*" as its name says, helps dairy farmers project seasonally the amount of cow manure (and consequently nutrients in the

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**3. Decision Support Systems Development: Challenges and Trade-offs**

tools and a discussion of the approaches used for the software applications.

A number of methodologies and software applications were used to develop the decision support tools above described (Table 1). The goal always remained to provide solid, but user-friendly DSS tools. The methodology as well as the software application approach fol‐ lowed the tool development and the ultimate goal pursued and not vice versa. It was usual to combine and adapt methodologies within a particular tool development. Following is a succinct description of the most important methodologies used for the DairyMGT.info DSS

manure) will be produced and will be needed to be recycled.

**Figure 6.** Screen snapshot of DSS *Dynamic Dairy Farm Model*.

**Figure 5.** Screen snapshot of DSS *LGM-Analyzer*.

#### **2.6. Environmental Stewardship (DairyMGT.info → Tools→Environment)**

The dairy farm business faces important challenges regarding increased environmental scrutiny. An increasingly important dairy farm management task is to maintain a farm nutrient balance and therefore avoid over-concentration of nutrients in or around the farm. Opportunities exist to better utilize nutrients in dairy farming and not only im‐ prove the balance of nutrients coming in and going out of the farm, but also decrease fer‐ tilizer expenses and therefore environmental concerns. Depending on the farm herd and crop characteristics, additional expenses might be required to comply with environmental regulations. In any case, an economic assessment along with the environmental require‐ ments promotes better decision-making. A series of decision support tools deal with these sensitive aspects of dairy farming. The tool "*Dynamic Dairy Farm Model*" (Figure 6) is an integrated, whole-farm, simulation and optimization model that maximizes the net eco‐ nomic return while minimizing nitrogen leaching to surface and ground water sources. A simplified version of nutrient balance between nitrogen and phosphorus manure excre‐ tion for a fast assessment is the tool with name *"Dairy Nutrient Manager."* Also related, the "*Grazing-N*" is an application that balances nitrogen for dairy farms with grazing ac‐ tivities and the "*Seasonal Prediction of Manure Excretion,*" as its name says, helps dairy farmers project seasonally the amount of cow manure (and consequently nutrients in the manure) will be produced and will be needed to be recycled.

**Figure 6.** Screen snapshot of DSS *Dynamic Dairy Farm Model*.

**Figure 5.** Screen snapshot of DSS *LGM-Analyzer*.

152 Decision Support Systems

**2.6. Environmental Stewardship (DairyMGT.info → Tools→Environment)**

The dairy farm business faces important challenges regarding increased environmental scrutiny. An increasingly important dairy farm management task is to maintain a farm nutrient balance and therefore avoid over-concentration of nutrients in or around the farm. Opportunities exist to better utilize nutrients in dairy farming and not only im‐ prove the balance of nutrients coming in and going out of the farm, but also decrease fer‐ tilizer expenses and therefore environmental concerns. Depending on the farm herd and crop characteristics, additional expenses might be required to comply with environmental regulations. In any case, an economic assessment along with the environmental require‐ ments promotes better decision-making. A series of decision support tools deal with these sensitive aspects of dairy farming. The tool "*Dynamic Dairy Farm Model*" (Figure 6) is an integrated, whole-farm, simulation and optimization model that maximizes the net eco‐ nomic return while minimizing nitrogen leaching to surface and ground water sources. A
