Toward Big Data Value Engineering for Innovation

被引:0
|
作者
Chen, Hong-Mei [1 ]
Kazman, Rick [2 ,3 ]
Garbajosa, Juan [4 ]
Gonzalez, Eloy [5 ]
机构
[1] Univ Hawaii Manoa, Shiciler Coll Business, Honolulu, HI 96822 USA
[2] Univ Hawaii Manoa, Honolulu, HI 96822 USA
[3] SEI CMU, Pittsburgh, PA USA
[4] Tech Univ Madrid UPM, Madrid, Spain
[5] Indra Software Labs, Madrid, Spain
关键词
Big Data; Value Discovery; Value Engineering; Architecture Landscape; Ecosystem; Innovation; Energy Industry;
D O I
10.1145/2896825.2896837
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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 nondeterministic 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".
引用
收藏
页码:44 / 50
页数:7
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