The success of public Social Media has led to the emergence of Enterprise Social Software (ESS), a new type of collaboration software for organizations that incorporates ``social features{''}. Surveys show that many companies are trying to implement ESS but that adoption is slower than expected. We believe that in order to understand the issues with its implementation we need to first examine and understand the ``social{''} interactions that are taking place in this new kind of collaboration software. We propose Social Collaboration Analytics (SCA), a specialized form of examination of log files and content data, to gain a better understanding of the actual usage of ESS. Our research was guided by the CRISP-DM approach. We first analyzed the data available in a leading ESS. Together with leading user companies of this ESS, we then developed a framework for Social Collaboration Analysis, which we present in this paper.