Determining the return on investment of data quality, accuracy, and precision is part science, part art, part knowledge, part faith. When do the costs of ostensibly better data outweigh the benefits? Better quality data has a cost at every step, but how do we judge the cost/benefit ratio? The conflict arises when the end user wants greater quality than is currently provided or even possible. How can an agency determine if the data is truly good enough.