Along with enterprise transformation, enterprise re-engineering isessential for maintaining the competitiveness of an enterprise. Enterprisere-engineering addresses (emergent) changes, re-organizing, outsourcing andre-aligning alike. Re-engineering itself has drawn traction in both academiaand business. Most scholarly work in this area is confined to model-drivenanalysis, holistic frameworks for analyzing as-is/to-be enterprise models, anda few other conceptualization techniques. The practice of process redesignunderstandably takes the stage in re-engineering. Yet algorithmic techniquesthat insightfully point out how a process might be improved for proactivelyre-engineering process-intensive enterprise architecture are missing. Datascience and business intelligence have brought a refreshingly new analysis tothis mainstream problem by studying the operational history of a businessprocess to facilitate most plausible changes. In this article, we investigateenterprise process redesign taking into account enterprise’s high-level strategyand data warehouse. More specifically, we propose an approach to reasoningabout an enterprise’s strategy together with data mining rules extractedfrom the data warehouse of the enterprise. Our redesign algorithms suggest design-time changes to be made to its business processes, primarily byeliminating redundant tasks and re-ordering inefficiently-located tasks. Weanalyze the effectiveness of candidate to-be business processes with regardto business intelligence indicators. We report our work on the enterprisearchitecture developed for a retailer of low-cost domestic flights.