DSAT – Dairy Stochastic Analysis Tool

For an overview of what DSAT is,
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Dynamic Risk-Based Modeling™

Top Five Challenges to Dairy Producers

Tight Profit Margins
Demand Volatility for Dairy Products
Feed Ingredient Quality Fluctuations
New Technology and Innovation
Environmental and Sustainability Issues

Using Dynamic Risk-Based Modeling™ to Identify and Manage Business Risks

Many of the challenges faced by the dairy industry are created or intensified by market volatility, which makes it difficult to produce business projections that are useful to owners, managers, and lenders. Traditional spreadsheet-based business projections are based on a set of variables that, once set, do not change for the time span of the model. In addition, correlation among variables is neither recognized nor evaluated.

Dynamic Risk-Based Modeling uses a powerful simulation tool to account for historical volatility of variables such as feed cost, energy prices, market demand, dairy products sales and prices, and value received for byproducts, such as manure, sold or used in the dairy operation. In addition, historical correlation among variables is preserved in model projections.

As an example of variables analyzed, higher fuel prices result in higher fertilizer and energy costs. Dynamic Risk-Based Modeling accounts for this. Dynamic Risk-Based Modeling can illustrate correlations such as changing a ration ingredient that increases feed costs but may result in improved production and a potential increase in net income.

Using Dynamic Risk-Based Modeling results in a powerful management tool which provides a series of comprehensive reports showing a range of probable outcomes for each variable evaluated and the relative probability of success for each scenario considered.

What a User is Saying about DSAT

"Decision Innovation Solutions assisted us in financial and production data analysis that allowed us to determine the probable range of profitability in a rather large start-up dairy. That analysis was helpful in determining the direction of our proposal.”
Brian Thilges
Regional Manager, Iowa Farm Bureau Federation

Introducing DSAT

The Dairy Stochastic Analysis Tool (DSAT) is an example of one of many dynamic risk-based models Decision Innovation Solutions offers to assist clients better quantify and plan for risk. The DSAT model is specifically designed to help dairy owners and managers better understand the production and financial challenges they consistently face. Here are a few of the challenges the DSAT can address:

Feed Costs/Milk Production Trade-offs

While the goal of most dairy producers is to minimize feed costs, we have the ability to demonstrate that, in some cases, a higher-cost ration may prove more profitable for reasons such as improved herd health and/or increased milk production. Below is an illustration of the trade-offs between feeding a higher-cost ration (+5%) in exchange for an expected increase in milk production (+10%). On average (black line), a switch to a higher-cost ration results in a $0.25/cwt reduction in feed costs/cwt of milk shipped over the three time periods shown. Interpreted another way, 50% of the time (black line), we project feed costs to be at least $0.25/cwt less per cwt of milk shipped than under the current feeding protocol.

A New Dairy’s Selection of Source Cattle

When an expansion of an existing or a new dairy is planned, the owner and/or manager must find a balance between milk production stability and a younger average age of lactating cattle. In other words, what is the best ratio of cows purchased from existing herds (stable milk production)versus those purchased as replacement heifers? The decision has implications for both timing and volume of milk production, because a group of replacement heifers will both calve and dry up at about the same time. This directly translates to an impact on cash flow. A ratio of 60/40 (existing herds/replacements) versus a 40/60 ratio is shown in the nearby chart to have a significant impact on the 3-year average cash flow of a dairy. Similar to a stop light interpretation, green signals favorable conditions, yellow signifies cautionary conditions, and red signals unfavorable conditions.

As shown in these few examples, Dynamic Risk-Based Modeling has several distinct advantages over traditional spreadsheet modeling, the most important of that is the ability to capture historical variability and the relationships among key variables. When a farm manager has a better understanding of the variables that have the most impact on their particular farm, they can allocate their finite resources in the areas which will yield the best risk-reducing outcome.

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