Women engage in a wide range of activities in the fisheries and in fishing communities which is vital to a community’s well-being. They play a very crucial role in though their contribution is invisible and unacknowledged. In Kerala almost 50 percent of the posts harvesting activities of the marine fisheries are undertaken by them. The 26th December 2004 Tsunami significantly affected the coastal villages of Kerala. A vast majority of the coast dwelling people were affected by the huge and wide spread destruction of the tragedy. In order to provide relief and rehabilitation to the affected, Department of Fisheries ,Kerala implemented multiple programs, which were christened under a common livelihood program named “Theeramythri” under the Society for Assistance to Fisherwomen (SAF).The SAF visions to initiate, encourage and strengthen locally organized activity groups among fisherwomen, thereby providing assistance for expertising their business development skill, resource utilization and management, performance improvement, networking and marketing. The Theeramythri programme facilitates and handholds fisherwomen to engage in gainful self-employment for their economic and social emancipation. Among the total 2500 microenterprise groups formed initially as part of various Tsunami rehabilitation programs, only 1000 are operationalat present. Around 500 groups reduced their operations and became dormant due to various reasons. The present study gauges to provide a comprehensive picture about the reasons for the non-performance of SAF groups in Kerala with special focus on its technical, economic, institutional and social impacts. The study identifies the attributes determining the non-performance and the role of different stake holders in the non-functioning of the micro enterprise units. The study also aims at developing valid measures for revamping/strengthening/reconstituting the group and also facilitating innovative ideas for overcoming the vulnerability of an activity group. Statistical and economic tools such as percentage analysis, Garrette ranking technique, weighted average analysis and cluster analysis have been employed to analyze the data.