Despite the varying degrees of success, there is no doubt that the integrated management approach to predicting growth and feed intake, significantly enhances the decision-making process for producers. It quantifies both the technical and financial outcomes to production stimuli, and therefore eliminates the need for educated guesses. This paper outlines key components of an integrated simulation model, “Watson” and how it has been applied within Nutreco Canada. “Watson” was developed by integrating the science and practice of pig production into an easy to use Web-based software application. The science and theoretical framework have been extensively validated with over 20 trials conducted to test significant drivers and components of the model. Its framework is unique and flexible to allow the prediction of voluntary feed intake, as well as predicting performance and financial outcomes reasonably accurately under commercial conditions. One of the main purposes of “Watson” is to integrate the complex interactions between the animal, its environment and its diet into a management system that accurately predicts the animal’s performance under commercial conditions, including cause and effect responses to any change in the production environment. Therefore, the application of “Watson” provides solutions to a number of production, economic, and nutritional changes as well as assisting in the diagnosis of potential production problems. Outputs from “Watson” allow the producer to monitor current performances with expected performances and therefore identify periods of slower growth during rather than after the grower/finisher period. In addition, performances can be benchmarked against other producers or previous close-outs. Clearly, as feed and hog prices change so to will the optimum marketing strategy change for a producer. “Watson” has the dual capacity to access and utilize existing branded products, or perform least cost formulations for individual customers based on the predicted nutrient requirements of their genetics, health status and their ingredients. With these features it is possible to determine the optimum nutrient requirements based on the producer’s economic or performance objective, for different nutrient density of the diets, and for different feed budgets; minimize under and over-feeding nutrients; and estimate the impacts of alternative technologies such as Paylean. Of particular importance is the ability to define optimum feeding strategies based on current feed ingredient prices, as well as future ingredient prices. Therefore, responses in gross profit to changing energy density and/or the lysine:energy ratio of the diet can be predicted. One of the consequences of being able to predict daily feed intake and lean tissue deposition is the ability to determine the amount of nutrient excretion, especially nitrogen and phosphorus excretion. For every simulation it is possible to determine the total amount of N and P that is excreted per pig per closeout period. Where N and P excretion is closely regulated, “Watson” can be used to develop feeding programs, including diets and feed budgets, which will reduce excretion of N and P. The ability to make well informed economic decisions in a complex and constantly changing production environment is becoming increasingly dependent on the application of integrated management models. “Watson” can dynamically assimilate the whole production process in order to predict the cause and effect responses to vectors of change within the commercial production environment.