This paper aims at setting the context for "Identity Analytics" within enterprises and paving the path towards new R&D opportunities. In our vision, Identity Analytics is about explaining and predicting the impact of identity and identity management (along with other related aspects, such as users' behaviours) on key factors of relevance to decision makers (e.g. CIOs, CISOs), in complex enterprise scenarios - based on their initial assumptions and investment decisions. Ultimately the goal is to provide rigorous techniques to help decision makers gain a better understanding of the investment trade-offs within the identity space (e.g. investing in technologies vs. changing processes vs. investing in users' education, etc.). This means providing "decision support" and "what-if analysis" capabilities to decision makers enabling them to explore these investment trade-offs, formulate new policies and/or justify existing ones. Our vision of "Identity Analytics" is introduced and discussed, along with the methodology that we intend to adopt. There are many research opportunities and challenges in this space: we believe that a scientific approach is required, involving the usage of modelling and simulation techniques, coupled with the understanding of involved technologies and processes, human behaviours and economic aspects. To ground some of the concepts discussed in this paper, we provide an illustration of Identity Analytics focusing on emerging "web 2.0 enterprise collaborative data sharing", where unstructured information is created, stored and shared by people in collaborative contexts, within and across organisations. We demonstrate how trade-offs can be explored using the modelling approach hence allowing decision makers to explore the different impacts of policy choices. 22 PagesExternal Posting Date: July 6, 2008 [Fulltext].Approved for External PublicationInternal Posting Date: July 6, 2008 [Fulltext]
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