Intra-field variability has received much attention in arable and horticultural contexts. It has resulted in increased profitability as well as reduced environmental footprint. However, in a pastoral context, the value of understanding intra-field variability has not been widely appreciated. In this programme, we used available technologies to develop multiple data layers on multiple fields within a dairy farm. This farm was selected as it was already performing at a high level, with well-developed existing infrastructure and high production metrics. All of the fields on this farm were around 4 hectares and had established pastures based on perennial ryegrass/white clover. We developed high resolution data layers on pasture height, soil electroconductivity and soil texture at a pixel size of approximately 4m. Maps of the pasture height of individual fields sampled at the same interval post-grazing (~21 days) were then combined to produce a whole-farm map of relative pasture production. This revealed a strong interaction between irrigation performance, soil bulk density and pasture growth. These patterns had not previously been noted by farm management. In addition, several zones were identified that showed lower relative pasture yield, subsequently demonstrated to be due to high densities of soil-dwelling pasture pests (scarab larvae). As a result of this information, management decisions were made to improve irrigator performance – especially the uniformity of water application – and to address the pest problem by applying a prototype biopesticide. Modelling of the improvements in pasture production that were expected as a result of these decisions predicted an increase in total pasture production to more than 20 t DM/ha/yr (~10%). This exceeds the accepted pasture production expectations for this region and sets a new target for irrigated dairy farms.