Crowdsourcing has become a very popular field over the last decade. Many applications where crowdsourcing can be used have been identified. This thesis project researches if some of these crowdsourcing applications can also be applied for internal crowdsourcing, where the crowd consists out of the firm’s employees to improve a company’s innovation process. Crowdsourcing bring many opportunities for improving the innovation process, as it can help to involve and connect a larger amount of employees in the innovation process that can boost the creativity or simply reach out to more resources within a company. The research project is conducted in cooperation with Robert Bosch GmbH, which sets the context for the case study. Based on the case study at Bosch, two use cases were identified that can improve the innovation process within tech-driven multinationals. The first and most relevant type is related to crowdsourcing solutions to specific problems, often referred as expert sourcing. In this type the focus lays on identifying the experts within the company that are then invited to solve very specific problems. The second type is related to crowdsourcing ideas. Other companies like IBM or Dell have already applied this type. In this context, it has been shown, that the second type should only be used for specific projects, as there are other more efficient alternatives available. To define when each crowdsourcing type is applicable during the innovation process, several contextual factors were identified. One major factor is the expected knowledge distribution about the problem to be solved by the crowd, which has been transferred to the long-tail distribution theory. Moreover, intellectual property and confidentiality are factors to differentiate the type of crowdsourcing that has to be used. In addition, a framework has been developed to codify the information about both crowdsourcing types. By applying the framework to the Bosch context, a best practice guide for future crowdsourcing campaign initiators was created.