Digital representation of an innovation cycle in the FMCG industry

Abstract

Companies often find it difficult to depict a continuous innovation and project process and to live it in daily practice. At the same time, companies are also faced with the challenges of exploiting current and new potentials of process digitalization. This thesis deals with how an innovation cycle can be mapped digitally and which concrete opportunities for improvement result from this. Innovation software platforms are offered as a commercially available solution for this.In recent years, these platforms have taken up new technologies like Artificial Intelligence for more intelligent search tasks and more customer benefits.Digital trend radar and AI-supportedpatent searches can open up new potentialsespecially in the areas of the marketresearch, technologywatchingand trend intelligence. The master thesis examines the evolution of this software and how it supports promising practices in innovation management.It is shown that modern Innovation Platforms support all phases of the innovation cycle and enhanceadaptive intelligence. Idea generation is spread across the whole company and digital collaboration enables a transparent evaluation and selection of ideas.The advantages and functions of innovation software are then discussed in a case study to determine the concrete requirements of a company in the food industry. The case study deals with how information on trends in the food industry should be collected and structured. It is about how new ideas for food products should be evaluated and prioritized. Finally, the question of how the introduction of such software would affect the team culture is also addressed. Based onempirically evaluated interview questions,a target process is worked out which couldbe used in the innovation softwareworkflow. The result isan implementation plan for the introduction of such software.