The operations and supply chain management the normative assumption holds that a product's structural and functional elements are fixed pre-production to support efficiency of operations. Firms moving from manufacturing to service are faced with delivering resource for customers in context and absorbing variety in use provides them with a number of challenges. This paper examines AM as a technology that efficiently provides high variety that meets emergent user demand. A single case study is undertaken, drawing upon design change data and in-depth interviews with industry experts. Findings show that in non-digitised environments, introducing design changes to modular products through life creates complexity, where complexity refers to increasing interdependencies between components in the product architecture that lead to increased coordination costs between internal and external supply chains. We find that advances in AM can act as a supply chain solution, managing complexity and allowing products and supply chains to efficiently and effectively adapt close to context of use. Findings suggest that existing theory must expand beyond the normative assumption that the physical product is fixed and the intangible service elements adapt to absorb variety, to include cases where the tangible product can absorb variety to meet emergent need.

Statistical agencies and other government bodies increasingly use secure remote research facilities to provide access to sensitive data for research and analysis by internal staff and third parties. Such facilities depend on human intervention to ensure that the research outputs do not breach statistical disclosure control (SDC) rules. Output SDC can be principles-based, rules-based, or something in between. Principles-based is often seen as the gold standard statistically, 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 these statistical advantages. 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 popular conceptualisation of customer demand from the operations management literature and apply it to the problem of output checking. We demonstrate that principles-based output SDC addresses user and agency requirements more effectively than other approaches, and in a way which encourages user buy-in to the process. We also demonstrate how the principles-based approach aligns better with the statistical and staffing needs of the agency.