Managing Data & Analytics Use Cases

Abstract

IT projects have, compared to other domains, higher failure rates. This phenomenon is even more pronounced in the Data & Analytics (D&A) context. We notice that shortcomings in existing D&A development and operation frameworks are one major reason for D&A project delay, misorientation and failure and that mitigation of the shortcomings promises improvements for development and operations practices. We propose the D&A stage gate process as a guiding framework to manage D&A use cases along six stages: ideate, pre-assess, assess, prototype, develop, and operate. We define the sequence of actions required to develop D&A use cases efficiently, value-centered and comprehensively. Our results show that especially prior to use case development, ideation and assessment remain underrepresented, portfolio aspects are missed and no solid go- and kill criteria are operationalized. We further acknowledge that D&A use cases come in great diversity and that they are embedded in a highly dynamic environment complicating their value-effective management. To address this, we assess these differentiating and dynamic factors of D&A use cases and evaluate their influence on management practices. We designed the stage gate process in collaboration with a panel of 17 industry experts across three iterative cycles and assessed our findings through an ex-post evaluation with three industry cases. The resulting design principles and best practices offer practitioners structured points of intervention to close the persistent gap between D&A technological potential and actual business value realization.