OPTIMAL ENTERPRISE RESULTS IN THE CLINICAL RESEARCH ENVIRONMENT.

Abstract

Even the best scientific minds cannot repeatedly produce desired results when working in sub-optimal systems. Complex enterprises are difficult to understand and manage. Cause-and-effect relationships are often separated in time and space, making real improvements challenging. To understand how complex systems work it is essential that we employ tools that accurately map and quantify the dynamics that drive results. Computer modeling and simulation (CMAS) is a valuable design, planning, management, and overall analytical decision-support tool to achieve effective and efficient results. CMAS could become a ubiquitous tool in the lengthy and complex environment of the clinical research (CR) enterprise. Without the comprehensive understanding gained when applying CMAS, organizations may continue to be overwhelmed by problems such as unnecessary bottlenecks, high costs, low productivity, and the inability of retaining critical staff. The approach explained here may complement or even replace traditional methods when organizations pursue greater enterprise capability.