There is an international tendency toward increased demand for both cost-efficiency and high reliability of power distribution systems. To meet these demands, asset management methods, including reliability analyses, have been developed. These reliability analyses often utilize only mean values and hence do not take into consideration the consequences of severe events. This paper proposes a framework for more detailed quantitative risk analysis methods. The aim is to allocate resources more cost-effectively. The suggested framework is exemplified and evaluated by implementing it within the analyses of a real power distribution system. The main concept is to divide comprehensive projects into minor analyses and then in a final step compile the results. The proposed analysis framework can be used independently or combined with earlier proposed vulnerability methods. The latter provides a two-dimensional analysis framework. It is shown that totally different investment alternatives could be preferred depending on whether a traditional analysis method using average values is employed compared with the proposed analysis framework, which also considers severe system states. This demonstrates the risks involved in using average values and the strength of the proposed method. Furthermore, it is shown that already available information can be used for improved asset management decision support. In addition, the performed case study gives combined reliability and weather statistics useful as reference material.