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Within organizations, individuals are surrounded by performance goals—quotas, standards, “bogeys,” deadlines—which, whether set by themselves or others, are expected to influence their performance. Should these goals be set at, or close to, previously attained levels or far above them?

The assignment model of linear programming is here extended to allow for vector optimizations and dynamic interactions between assigned personnel and positions in each of which a variety of possible measures and approaches are explored. Formulations involving people-to-people as well as people-to-position matchings are also examined from the standpoint of organizations in which jobs may be fitted to people or vice versa as well as in weighted combinations. Possible uses of such models for dealing with the problems of placing disadvantsged or handicapped persons are noted, but the analysis stops short of the still further possibilities offered by new types of machine-technology and information systems designs.

Funding of research projects is considered as encompassing three stages: (1) an initial short run plan for funding based upon projected regular demands and availability subject to random deviations; (2) adjustment of the initial plan to take into account the actual regular demands and availability and the funding of significant break-throughs which occur at random intervals preempting other demands; and (3) a plan for longer-run availability and demands which constitute a "posture" desired subsequent to the funding adjustments of (2). The essence of the distribution of the unexpected demands is multi-modality with low probability of occurrence but high resource demand when they do occur. This approach represents a substantial departure from the usual planning model development which produces only an optimal plan based on forecasted developments without provision for adjustment when the forecasted events actually materialize and additional unexpected demands are placed on resources. The adjustment process explored here--which provides the mechanism for optimal implementation of the original plan or control of resource allocation-enables optimal response to information received in "real-time" avoiding the frequently observed over- or under-response to receipt of such information without reference to the impact of the interim decision on future capabilities.

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