ALIGNING THE EWS METHODOLOGY TO THE IMPROVEMENT OF DECISION MAKING PROCESS IN MANAGEMENT

The authors’ intention was to correlate the traditional body of knowledge in decision making associated to data gathering and problem solving in order to help the decision makers in their to prioritize scarced resources with the attempt to provide a more systematic and improve Early Warning System (EWS) methodology. In order to mitigate the risks in business decision making, different approaches are possible, enlisting here uncertainty assessment and various forecasting techniques. Early Warning Systems are represented by a measure of a certain indicator meant to signal the increasing degree of confidence that a certain event could cause damages or bring negative impacts.The idea is to identify the EWS as a new tool used to increase the effect of corrective actions in a system under stress or under turbulent influence form the outside context. Best practices of designing early warning systems in fields as monitoring natural hazards (such as flood or earthquakes) or in supervising banking performance in the current crisis are reported as a starting point in improving and then enlarging the body of knowledge in decision analysis. The interest in connecting EWS methodology to decision science leads to empowering knowledgeable individuals to make more reliable decisions, to acknowledge the increased complexity in the actual business climate and to recognize how the systems under study are threatened by hazards/unexpected/unforeseen situations. This may enable the individuals/groups in charge with management decisions to act under sufficient time and in an appropriate manner to reduce the possibility of personal injury, loss of life and damage to property and the environment