In many of the articles and explanations of AgOptimizer we talk about optimising the profit for one particular livestock such as cattle or sheep. However in reality many agribusinesses have multiple operations including both cattle and sheep and some form of farming operation. From a purely mathematical and computational point of view the complexity of such an operation increases on an exponential scale whilst for the farmer, the complexity is likely to only increase on a linear scale.
The difference between the complexity on a theoretical level and a practical level to me is indicative that many complex variables (such as the amount of land devoted to each individual enterprise) is being determined by using simplifying assumptions, constraints and the effect of this is that huge portions of potential decisions are not being considered given that a particular variable is in effect being “locked down”.
As humans we often undertake simplifying decision making using a similar criteria. An example may be the decision to buy a new casual shirt. There may be 5 potential retailers that you could buy the shirt, but many individuals will trust one particular shop from previous experience and although they could theoretically find a better shirt in one of the remaining 4 retailers, they simplify the decision by going to one particular retailer that they trust will have a shirt. These types of assumptions or “ways of doing things” can be an effective way to minimize complex decision making, however in the case of a large scale business, it can mean that more profitable ways of doing business are not being given sufficient consideration.
The optimisation of decision making across different livestock / farming enterprises or even across multiple properties can deliver agribusinesses substantial improvements in profit and computational power to the farm gate.