It is largely believed among researchers that the software engineering methods and techniques based on mining of software repositories (MSR) have the potential of providing sound and empirical basis for Software Engineering tasks. But it has been observed that the main hurdles to adoption of the techniques are organizational in nature or people centric, for example lack of access to data, organizational inertia, general lack of faith in results achieved without human intervention, and a tendency of experts to feel that their inability to arrive at optimal decisions is rooted in someone else’s shortcomings, in this case person who files the bug. We share our experiences in developing a use case for applying such methods to the common software engineering task of Bug Triaging within an industrial setup. We accompany the well researched technique of applying textual information content in bug reports with additional measures in order to improve the acceptance and effectiveness of the system. Specifically we present: A) use of non-textual features for factoring in the decision making process that a human would follow; B) making available effectiveness metrics that present a basis for comparing the results of the automated systems against the existing practice of relying on human decision making; and C) presenting reasoning or the justification behind the results so that the human experts can validate and accept the results. We present these non-textual features and some of the metrics and discuss on how these can address the adoption concerns for this specific use case.