| Abstrakt: |
A basic challenge in drug development and clinical trial is the need to achieve throughput across numerous concurrent projects. Each project may operate under unique conditions and present numerous management challenges that cross organizational boundaries. This issue goes beyond complexity. Management in this environment requires a sort of organizational and operational calculus for controlling and understanding large volumes of clinical data gathered to serve project momentum leading, ideally, to a new drug application. In a traditional model, data are sampled and analyzed through various reporting and representation techniques as business or operational processes generate them. This yields indicators on which some decision can be based. “Business intelligence” is a phrase commonly identified with these methodologies.In the pharmaceutical industry, common business intelligence models offer only a partial solution. This paper outlines a more comprehensive methodology based on “process intelligence.” Process intelligence represents an understanding of key business data in the context of its relationship to strategy, organizational priorities, and work process momentum. Organizations exercising process intelligence are flexibly adaptive and oriented toward maximizing business throughput and quality. Several attributes identify process intelligence: integration, aggregation, transformation, communication, and orchestration. Each of these attributes is described and analyzed in this paper. |
