Climatic variability in dryland production environments (E) generates crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement approaches seek genotypes adapted broadly to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in response to average local environmental conditions. They do not search the full spectrum of potential GME combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional broad adaptation approach) of exploiting specific adaptation arising from GME. We present an in silico analysis for sorghum production regions in Australia using the APSIM sorghum model. Crop design (G*M) is optimised for subsets of locations in the production region (specific adaptation) and compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic sub regions having substantially different frequencies of major environment types to that for the entire production region show greatest advantage for specific adaptation. While this confers yield and production risk advantages at industry scale, far greater effects would likely be possible with better predictors of environment type likelihood than that conferred by location alone.