A Digital Classification System to Assess Project Failures

Abstract:
Failure classification schemes are often used to categorize events that cause failures in projects. Despite the frequent publication of studies on project failure and success classification, there has been no analysis of failure classification schemes. Specifically, an open question concerns the similarities and differences of failure classification schemes between and within disciplines. Answering this question will provide insight into the applicability of a scheme across a range of disciplines and the challenges that may exist when multiple disciplines are collaborating on a project. Understanding the contents and nature of failure classification schemes is critical to improving theoretical study and practical implementation of schemes on projects.

The research presented in this presentation identifies 400 failure classification schemes through a systematic review, extracts over 4000 perceived causes of failure from the schemes as meta-data, and analyzes the schemes with a focus on disciplinary differences in the perceived causes of failure. Meta-analysis of the perceived causes of failure in the 400 failure classification schemes identifies that the content of failure classification schemes are diverse, both within and across disciplines. Significant differences are shown between schemes used in different disciplines. Within disciplines, the schemes show patterns in the perceived causes of failure that appear most frequently and there are some common perceived causes of failure among many disciplines. The findings of the research conclude that caution must be taken if applying a scheme across multiple disciplines.