Search for a command to run...
Purpose The present study gives the idea for demonstrating query and perception of good manufacturing practice (GMP) learning rate-driven performance visualization, mainly finite element equations, for the determination of intelligence and motivational blueprint inside the healthcare organizations. Design/methodology/approach In this paper, a three dimensional lattice introduced with input knowledge/standard operating procedure and GMP training handled under GMP system is considered to ensure the quality orientation in productivity with least cognitive break up or intelligence scattering by totaling the analogy wise GMP parameters and intelligence variables, i.e. operational, leadership, writing and risk taking intelligence with Galerkin equations and consequently creating image of the complete coordination. The estimation involved in applying the equation to the person working inside a sterile manufacturing area was analysed. The Newton forward difference equation has been solved with the proper level of GMP training and action sequences using numerical methods and computer program. Findings The result shows that the intelligence contribution varies over the sterile manufacturing region and that the learning desire affects the intelligence pattern. Experiment with a model GMP-compliant contraceptive pilot plant and two other industrial laboratories confirm the analytical result. Practical implications This research gives the new platform to deal with the cognitive break up concerns arise due to interdisciplinary nature of work in health care organization. Originality/value Proper execution of GMP in healthcare organization through a set of knowledge-driven GMP training invokes the intelligence of working personnel. Problem lurk in this scenario is that the intelligence revealed through these practices of manufacturing are distributed across persons, their minds, working environment and processes, which directly affect the organization’s performance. This study enlarges the literature on knowledge-driven organizational effectiveness.