The purpose of this paper is to analyze the 24 mail center's efficiency and productivity changes from first quarter to fourth quarter of 2008 using window analysis and Malmquist productivity index. Row views of window analysis results make it possible to determine trends and/or observed behavior with the same data set, and column views to examine the stability of results across different data sets. Malmquist productivity indexes greater than unity translate into improvements in productivity, and less than unity mean deterioration in performance over time. The results of this study suggest that DEA models under dynamic situations such as window analysis and Malmquist productivity index enable us to comprehend the efficiency and productivity changes over time and to show the direction of improvements.