Improving Organizations by Replacing the "Mechanical" Model with the "Organic" one

Organizations are currently viewed as artificial structures. However, in our opinion, organizations seem to match a biological structure much better. This paper explores this new approach with some interesting conclusions and results: organizations aim at perpetual exis-tence and continuous adaptation. We advance the ideas of organizational "instincts", organizational pathology and organizational optimization using genetic algorithms. In competitive markets, organizations are in a natural selection process, which actually is part of a natural genetic algorithm. This process may be simulated in an artificial multidisciplinary optimization environment, based on minimizing a Total Costs and Risks objective function. Unlike the gradient optimization methods, the genetic algorithms may be applied to such problems with thousands of degrees of freedom. This opens the way to the organizational structure optimization through genetic algorithms.