A maturity model for media asset management development and verification in a mixed methods approac

Keywords: Media asset management (MAM), maturity models, business process management (BPM), performance measurement, performance improvement, mixed methods research. Media asset management (MAM) is a key factor in efficient and effective marketing processes, which is why the market for media asset management is expected to grow tremendously in the future. In the meantime, best-in-class companies have centralised their access to all digital media assets to assure that all process members are able to benefit from media assets they are authorised to use. Modem information technology (IT) systems support the lifecycle of media assets. Marketing often entails performing a number of repetitive activities, thus forcing companies in this field to further increase their focus on business process management (BPM). The large amount of digital media files produced for all forms of communication can be traced back inter alia to the enormous relevance of social media. Media asset management systems (MAMSs) help organise and optimise media logistics, thereby yielding a very quick return on investment (ROI). As MAM is a relatively new topic, performance measurement systems in this area are underrepresented. Maturity models are used to measure, assess and optimise processes. They have high practical relevance. Over 100 different maturity models currently exist. They are used to compare best practices against real processes, to identify strengths and weaknesses as well as potential for optimisation and to provide advice on further steps. The research presented here develops and verifies a Media Asset Management Maturity Model (MAM3) and is therefore situated directly at the interface between MAM and maturity models. Hence, the MAM3 closes the gap described above. The model was developed and verified in a mixed methods approach. Initially it was built on basis of a broad literature review. Afterwards it was discussed with several experts with experience in the adjacent areas. Experts involved came from a software vendor, from large, globally operating companies that have used MAMSs for a long time, from consulting companies (inter alia top 5) or had an academic background. This procedure assured that the most relevant perceptions were considered. Changes based on this stage were later components of an in-depth quality assurance interview triangulation). Ultimately, the final model was tested in a quantitative survey with customers of a leading software vendor of MAMSs in Germany. One outcome was that all maturity categories established are positively related to performance in the area of media asset management. Furthermore the Media Asset Management Maturity Model has a high impact on management practice. Relevant variables that contribute to higher performance in the media asset management environment are decrypted and patterns are identified. The model offers the ability to guide managers through this complex topic and is a helpful instrument in the area of MAM. With a broader adoption in the future and the establishment of industry sector- and size-specific benchmarks, the benefits of using this tool will increase even more.