Data clustering is an important data exploration technique with many applications in data mining. The k-means algorithm is well known for its efficiency in clustering large data sets. However, this algorithm is suitable for spherical shaped clusters of similar sizes. The quality of the resulting clusters decreases when the data set contains spherical shaped clusters with large variance in sizes. In this paper, we introduce a simple idea to overcome this problem. Our experimental results reveal that our proposed algorithm produces satisfactory results