A Data Science Approach to Boundary Spanning Success SIGBPS Workshop on Business Processes and Services (BPS'15) 1 Towards Behavioral Measures of Boundary Spanning Success: A Data Science Approach

In recent years, the ability to mine, manage, and examine big data has sparked a strong interest among scholars and managers to leverage data science approaches for measuring and in turn enhancing the efficiency and effectiveness of various areas of knowledge management, such as boundary spanning. In this paper, we use a data science approach to delineate three distinct behavioral metrics of boundary spanning effectiveness and efficiency that are critical in determining the success of a boundaryspanning interaction—the dyadic relation between the boundary spanner and the responder, namely goal alignment, hierarchical alignment, and timeliness. These new metrics offer researchers and practitioners new means for assessing the actual rather than self-reported success of a boundary spanning activity as well as for evaluating the role of information systems in such boundary spanning interactions. Implications for research and practice are discussed.