"Building Institutional Capacity for Data-Informed Decision Making" is the third installment of the Cutting Edge series, which aims to help colleges engage faculty, scale successful interventions, and create a strong culture of evidence through use of data to strengthen their institutional change and student success efforts. Though the…

Technology can be an obstacle or an advantage to cooperative data sharing within and between colleges and universities. Taking a technology-oriented approach before the technology is ripe for general use can be counterproductive. Many technical difficulties can be overcome by encouraging consortium staff to promote new methods of information…

Models for college and university Interinstitutional data sharing are redefined by examining the organization and activities of existing data-sharing groups across 11 dimensions: data-sharing purpose; nature of data-sharing structures; definer of process; calendar; scope of surveys; participant characteristics; source of data-sharing initiative;…

The costs to colleges and universities of establishing a data-sharing exchange are examined, and it is argued that in most cases, the financial costs are minimal when compared to the potential opportunity cost of making decisions without access to good comparative information. (Author/MSE)

Before joining a data-sharing consortium, colleges and universities must address issues regarding goals and expectations, including why comparative data are needed, information types needed, needed comparisons, selection of institutions for comparison, data accessibility, time requirements, costs, and need for technical expertise. (MSE)

A set of general policies or ground rules is desirable for colleges and universities planning to participate in both basic and more complex data exchanges with other institutions. Participation in data exchange is enhanced by well-defined and comparable institutional memberships, clear organizational objectives and data, high-quality and timely…