The computer age, and the extensive storage and rapid retrieval of information it has ushered in, has transformed the way institutions regard data. Today, data are no longer considered solely the inputs and outputs of business transactions; they also are viewed as an institutional resource much the way fiscal, physical, and human capital assets are.
Like all complex organizations, institutions of higher education must be able to assess their current position and evaluate the effects of policy decisions. Data, appropriately summarized and analyzed, provide valuable insights into an institution's progress in meeting its planning aspirations and strategic goals. In particular, time-series comparisons and appropriate ratios provide strategic indicators and benchmarks that help explain an institution to itself. It is this need to provide support for decision making that led to the creation of the institutional research function at campuses across the country.
Institutional leaders today require information about a spectrum of input and output variables, such as student preparedness and enrollment profiles, faculty composition and costs, and learning outcomes. For example, an institution wishing to measure its progress toward building a diverse faculty may ask, How many women are tenured faculty today compared with five years ago and ten years ago? or What is the ratio of minority students to minority faculty compared with the ratio of majority students to majority faculty? Answers to these questions may provide a good understanding of an institution's progress toward its own aspirations.
While institutions may be able to amass and analyze their own inforrnation, without good comparative data, institutions lack the normative measures with which to assess the efficacy of policies and practices. The increasing need for peer comparisons to provide a context for their own analyses has prompted institutions to initiate the practice of data sharing. Today, because information