Hong-Mei Chen
Rick Kazman
ABSTRACT
This article articulates the requirements for an effective big data value engineering method. It then presents a value discovery method, called Eco-ARCH (Eco-ARCHitecture), tightly integrated with the BDD (Big Data Design) method for addressing these requirements, filling a methodological void. Eco-ARCH promotes a fundamental shift in design thinking for big data system design -- from "bounded rationality" for problem solving to "expandable rationality" for design for innovation. The Eco-ARCH approach is most suitable for big data value engineering when system boundaries are fluid, requirements are ill-defined, many stakeholders are unknown and design goals are not provided, where no architecture pre-exists, where system behavior is non-deterministic and continuously evolving, and where co-creation with consumers and prosumers is essential to achieving innovation goals. The method was augmented and empirically validated in collaboration with an IT service company in the energy industry to generate a new business model that we call "eBay in the Grid".
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