Some of the more familiar models of bureaucratic decision-making have been developed largely in response to perceived inadequacies of the classic economic rationality model. These models, including the satisficing, disjointed incrementalism, mixed-scanning and sequential decision-making models (all based on assumptions of sub-optimality), differ in respect to logical structure, range of application, assumptions about the decision-maker and assumptions about the decision environment. On one point, however, they agree: the cost of information is a critical variable in determining decision processes and decision outcomes. Herbert Simon lead the way in arguing that the rational model is not only unrealistic but may not even be useful as an ideal since it may encourage decision-makers to lose sight of satisfactory (but not optimal) decision-making quality. I Now that incrementalism, in one form or another, is the most widely accepted version of reality, some organization theorists and public administrators have begun to be concerned with a problem that might seem to some theorists, almost reactionary: how might it be possible to provide systematically a broader and higher quality information base for public decision processes? The complexities of contemporary policy-making are such that unquestioning and uncritical acceptance of incrementalism often seems inappropriate. Many have attempted to improve on incrementalism by reducing the costs of information and have often looked to computer scientists for help. Designers of formal information systems have long been concerned (in theory, if not always performance) with reducing the marginal cost of information. In many cases the hardware solution has proven viable-especially in those instances where the information that was to be infused into decision-making processes was descriptive (rather than explanatory), easily coded, decomposible, and readily available along some convenient channel. Unfortunately, information needs in policy-making often do not fit these specifications and, to date, little progress has been made toward infusing more complex kinds of information into public decision-making.