Idea Identification Model to Support Decision Making

Innovation is not a trivial process and ideas are the raw material of this process. Oriented systems to idea management domain seek to identify and develop effective and efficient ideas. However, there are challenges such as information overload with ideas submissions peaks and trivial description of collecting ideas, thereby making the process of selection and identification of relevant ideas. By using clustering techniques can bring together groups of similar ideas making easy the information visualization. The objective of this study is to present an ontology-based model and cluster analysis to support the Idea Management in order to contribute in the decision making process. The demonstration of feasibility of the proposed model was carried out through the development of a prototype. The prototype was used in two study scenarios using ideas collected from the websites of Starbucks (R) and Dell (R) companies. It was found that when analyzing groups of similar ideas, patterns and trends can be highlighted. As a result, this work presents a model to assist in decision making and in the process of identification and selection of ideas for implementation.