LAUSR

Statistical agencies and other government bodies are increasingly using secure remote research facilities to provide access to sensitive data for research as an efficient way to increase productivity. Such facilities depend on human intervention to ensure that the research outputs do not breach statistical disclosure control (SDC) rules. Output SDC can be either principles-based, rules-based, or ad hoc. Principles-based is often seen as the gold standard when viewed in statistical terms, as it improves both confidentiality protection and utility of outputs. However, some agencies are concerned that the operational requirements are too onerous for practical implementation, despite the evidence to the contrary. This paper argues that the choice of output checking procedure should be seen through an operational lens, rather than a statistical one. We take a standard model of operations management which focuses on understanding the nature of inputs, and apply it to the problem of output checking. We demonstrate that the principles-based approach addresses user and agency requirements more effectively than either the rulesbased or ad hoc approaches, and in a way which encourages user buy-in to the process. We also demonstrate how the principles-based approach can be aligned with the statistical and staffing needs of the agency.