Suppose you have been building a model using the k-means clustering algorithm and you keep finding that a certain variable is essentially ignored by the model (in other words, the variable is very similarly distributed across all clusters). Describe a method that can be used to exaggerate or minimize the impact of a variable when using k-means clustering. Why does this method work?