This paper presents our initial efforts towards building a cognitive analytics framework for change management. We propose a novel predictive algorithm for change risk calculation based on historical change failures, server failures, change triggered incidents as well as expert user input. Our predictive algorithm provides significant improvement over traditional risk assessments in proactively capturing problematic changes when tested with real client account data.