Data Envelopment Analysis is a linear programming technique for assessing the e ciency and productivity of decision making units (DMUs). Over the last decade, DEA has gained considerable attention as a managerial tool for measuring performance. The flexibility in selecting the weights in standard DEA models deters the comparison among DMUs on a common base. Moreover, these weights are unsuitable to measure the preferences of a decision maker (DM). For dealing with these two di culties simultaneously; we use preference common weights. This paper uses preference common weights for time-series evaluations to calculate the global Malmquist productivity index (MPI) so that the productivity of changes of all DMUs have a common basis for comparison, and DM’s preference information is incorporated in calculating global MPI. The Malmquist Productivity Index (MPI) suggests a convenient way of measuring the productivity change of a given unit between two consequent time periods.