Linearization and discretization risks in knowledge management

Abstract

Abstract The purpose of this paper is to analyze the limitations induced in Knowledge Management by the processes of linearization and discretization, which happen frequently in decision-making. Linearization is a result of applying linear thinking models in decision-making, regardless of the complexity of knowledge management phenomena. Knowledge and all the other intangible resources are nonlinear entities and they should be evaluated with nonlinear metrics. However, in many situations managers use simple solutions based on linear thinking models and get large errors in their decision-making, with significant negative consequences in management. Also, linear thinking model is dominant in legislation, which may lead to significant errors in managerial decision-making. Discretization is a process in which an entity with a continuous representation, like a knowledge field, is transformed into a piecewise entity to be handled more easily. Also, social media uses discretized systems for different evaluations which should be interpreted accordingly. For instance, counting the number of “like” on Facebook for a certain message or image may lead to the conclusion that friendship is proportional with the number of “friends”, which might not be in concordance with reality. Knowledge management is a complex activity dealing with knowledge, which means nonlinear entities. Using linear thinking models and discretization methods in evaluations and decision-making may lead to significant errors and negative consequences.