The skyline queries are often used in several recommendation applications. Most existing related works have focused on skyline computation in many multidimensional data. However, these works do not consider an interesting query generated from non-skyline point. In this paper, we propose a new query, called skyline minimum vector which finds the minimum vector for making a non-skyline point into a skyline. The skyline minimum vector means the minimum cost for becoming a skyline. We use the Manhattan distance between skyline and query point in order to evaluate the cost. Also, we propose basic algorithm and optimized algorithm for getting skyline minimum vector. The proposed query will be very useful in many decision-making applications.