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Researchers and practitioners frequently assume that big data can be leveraged to create value for organizations implementing it. Decisions for big data idea generation and implementation need careful consideration of multiple factors. However, no scientifically grounded and unbiased method to structure such an assessment and to guide implementation exists yet. This paper describes a methodology based on IT value theory and workgroup ideation guiding big data idea generation, idea assessment and implementation management. Distinct business and data driven perspectives are distinguished to account for big data specifics. Enterprise Architecture Management and Business Model Generation techniques are used in individual steps for execution. A first prototypical application in the context of Supply Chain Management illustrates the applicability of the method.
Vanauer et al. (Thu,) studied this question.