Social network analysis. Social network analysis is a method for mapping and analysing the social interactions in an organization. Such an analysis can be based on data from surveys and observations, but nowadays the method is mostly associated with the analysis of big data emanating from email traffic, social media, smart phones and sensors. These data are captured in spider web-like network diagrams that consist of nodes (people or groups) and ties (the connections between those persons or groups) that show who is in touch with whom. In relation to briefing, the method is interesting because many clients want their building to promote interaction and collaboration. Office clients, for example, often want their building to enhance the collaboration between the departments in their organization (breaking down the silos in management parlance).Social network analysis can help with the formulation of such ambitions by providing accurate data about communication patterns. Is it true that there is little contact between departments? Which departments have a high level of centrality, talking to everybody, and which ones are peripheral, mostly talking among themselves? Where are there holes in the network that need to be filled? Clients can use these observations as input for their brief. They can investigate how the buildings design can be used to enhance specific types of interaction, looking at things like adjacencies between departments, the distances between people, circulation routes, and the positioning of natural meeting spots such as coffee machines. Just calling for two departments to be located on the same floor can already make a huge impact on their interaction. One word of caution, however: social network analysis is a fairly complex exercise. It involves large amounts of data and while some of the outcomes may be fairly obvious, substantive mathematical and methodological skills are required in interpreting the data. Another difficulty is that data tend to be privacy sensitive. Users have to be asked for their consent before data are gathered and analysed. Recommendations-Make sure that the data (e.g. from email/social media/GPS trackers) are anonymized before they are analysed. Where necessary, ask users for their consent.-Do not get lost in the (typically) immense quantity of data. Focus on general patterns and the interaction between groups rather than individuals.-Bring in external expertise or use dedicated software (e.g. NodeXL) for the analysis and visualization of data.-Define beforehand what the purpose of the analysis is and how it relates to the design of the building.-Be aware that the analysis provides a snapshot of the current situation only. Patterns may change due to changes in staffing and the adoption of new technologies and working practices.