Object-oriented analysis methods can be grouped into data-driven and behavior-driven approaches. With data-driven approaches, object models are developed based on a list of objects and their inter-relationships, which describe a static view of the real world. With behavior-oriented approaches, a system usage scenario is analyzed before developing the object models. Although qualitative comparisons of these two types of methods have been made, there was no statistical study has evaluated them based on controlled experiments. This paper proposes the patterned object-oriented method, POOM, which is a behavior-oriented approach, and compares it to OMT, a data-driven approach, using small team experiments. The effectiveness of POOM is shown in terms of productivity and homogeneity.