A Collaborative Algorithm for Computer-Supported Idea Selection in the Front End of Innovation

At the first gate of an innovation process, a group of experts has to partition a large number of ill-defined ideas into two sets: those that are to remain under consideration and those that are to be eliminated. We propose a collaborative algorithm to perform this task which is based on a method used in computer-based sorting. The design goal of our algorithm was to combine individual and group decision-making to achieve an optimal balance between speed and simplicity on the one hand and quality of result on the other. The algorithm was compared experimentally with individual and group methods using a test set consisting of 125 ideas. The measures of quality of the new method were close to those of the group result, while its execution time and cognitive load were close to those of the individual method. We conclude that our algorithm is well-suited to the given task.