Towards data standards for enterprise and farm-level analysis

In this paper we discuss data standards for enterprise and farm-level analyses, and illustrate the use of such data by an enterprise profit calculator and by a farm simulation model. We take a 'bottom-up' approach that builds incrementally on approaches and data standards that have proven useful for field-level analyses. A schedule of field operations links field-level production process to enterprise-level resource accounting. Prices convert resource use to a monetary basis. Each combination of single- versus multiple-season and deterministic versus stochastic analysis suggests a different approach to handling price data. The social and cultural factors that impinge on farm decision processes are not fully understood. We can, however, obtain useful information from analyses that are based on simplifying assumptions and modest sets of data. At its simplest, farm-level analysis may consist of aggregating enterprise production or returns across the farm. At the next level, farm analysis accounts for constraints of various resources and for off-farm income and expenditure, requiring an initial inventory of resources. Dynamic production, consumption and investment decisions add complexity at the third and most general level. Since each level of analysis builds on the models and data requirements of simpler levels, agronomic data can be shared by enterprise studies, and enterprise data used for farm-level analyses. The scope of validity of some types of data is broad enough to allow data bases to be shared among different locations. The ability to share data among applications or locations adds value to data.