ABSTRACT
Traditional data management techniques that work well at a departmental or system level are incomplete and insufficient for addressing enterprise data management needs. Lean principles and techniques, which have matured over many years in other process areas, can be combined with traditional practices to form Lean data management. Data management is defined by the Data Management Association as “the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise.” Data management first emerged in the 1980s as computer systems evolved from sequential processing of data to direct random-access disk storage. Lean data management by contrast shows how marketing, sales, finance, customer service, manufacturing, research and development, and operations can work together to derive value from a wide spectrum of information value streams across the enterprise. Enterprise data management is also an integration problem, and as such, the examples and case studies in Lean integration are applicable.
