In recent years, in order to rationalize the allocation of social resources and optimize the implementation of public management policies, scholars have conducted in-depth researches on policy effectiveness. However, at present, most of the study is still at the level of using macrolevel qualitative analysis, and lack of quantitative analysis and evaluation system for the effectiveness of policy implementation. The goal of this article is to discuss the utility evaluation system of public management policy from the perspective of social computing. First, based on the data obtained through questionnaire survey, we obtain indicators of the survey data by using factor analysis, and a new BDI (belief-desire-intention) model is created based on the observation indicators, and then the simulation platform is constructed; then, a brand new quantitative analysis method for policy optimization is proposed by using modified logistic functions as a tool. As application, we conducted the case study for the Targeted poverty alleviation policy in Yulin region (Guangxi, China), in which the key indicators for the poverty were established, and then the policy optimization suggestions were given based on the results of simulation experiments. This case study has Chinese characteristics, which might be applied to the poverty alleviation work globally.