The purpose of this study is to identify and prioritize 30 decision support capabilities. Not limited to quantitative analysis techniques, the highest priority capabilities included explicit knowledge access and reliability, timely risk management, ability to communicate decisions and learn from their implementation.
To meet the needs of AKEs, it is critical developers implement the right capabilities. This requires a unified approach that identifies a complementary decision support set of capabilities. Using a triangulation approach of qualitative architecting and quantitative survey processes, this study evaluates enterprise‐specific operating environment and business models. It expands the integrated informed decision cycle model to identify decision making, decision implementation, and knowledge management‐related capabilities.
Agile knowledge‐based enterprises (AKEs) drive a need for a more aware, inclusive, and responsive decision support system. Goldman et al. observe that organizations are responding to these needs in a piecemeal fashion. Although significant research exists on knowledge management, decision analysis, and other decision support applications, Vahidov and Kersten assert that researchers and developers lack a unified decision‐support approach. Without such an overarching framework for identification and evaluation of needed capabilities, investment choices can provide incompatible or wrong capabilities with substantial chance of missing needed capabilities. All of these situations lessen the return on investment expected from a unified approach.
The combined capability set informs organization infrastructure investment for future evaluation and development of decision support.
