Organisations with high-performing data and analytics capabilities are more successful than organisations with lower analytics maturity. It is therefore necessary for organisations to assess their analytics capabilities and needs in order to identify and evaluate areas of improvement that need to be addressed. This was the purpose of this case study conducted on a region in a global B2B organisation, which has a centrally established analytics function on corporate level, wanting the use of analytics to be integrated in more of the region’s processes and analytical capabilities and resources being used as efficient as possible.To fulfil the thesis purpose, empirical data was collected through qualitative interviews with employees on corporate level, more quantitative interviews with regional employees and a questionnaire issued to regional employees. This was complemented with a thorough literature study which provided the analytics maturity models used for identifying the current capabilities on a holistic level of the region, as well as analytics setups, Lean Six Sigma and Knowledge Management. Results show a relatively low analytics maturity due to e.g. insufficient support from management, unclear responsibility of analytics, data not being used correctly or requested enough and various issues with competence, tools and sources.This study contributes to analytics research by identifying that analytics maturity models available free of charge only are good for inspiration and not full use when used in a large company. Furthermore, the study shows that complexities arise when having a central analytics function with low analytics maturity while other parts of the company face analytics problems but no indications are given on who and what to proceed on or not. This study therefore results in contributing with a proposition for companies wanting to increase its analytics maturity that this could be facilitated by establishing networks for analytics. Combining literature and empirics show that networks enable investigation of the analytics situation while at the same time enabling increased sharing, collaboration, innovation, coordination and dissemination. By making Lean Six Sigma a central part of the network analytics will be used more and better while at the same time increasing the success-rate of change and improvements projects.