Along with enterprise transformation, enterprise re-engineering is essential for maintaining the competitiveness of an enterprise. Enterprise re-engineering addresses (emergent) changes, re-organizing, outsourcing and re-aligning alike. Re-engineering itself has drawn traction in both academia and business. Most scholarly work in this area is confined to model-driven analysis, holistic frameworks for analyzing as-is/to-be enterprise models, and a few other conceptualization techniques. The practice of process redesign understandably takes the stage in re-engineering. Yet algorithmic techniques that insightfully point out how a process might be improved for proactively re-engineering process-intensive enterprise architecture are missing. Data science and business intelligence have brought a refreshingly new analysis to this mainstream problem by studying the operational history of a business process to facilitate most plausible changes. In this article, we investigate enterprise process redesign taking into account enterprise’s high-level strategy and data warehouse. More specifically, we propose an approach to reasoning about an enterprise’s strategy together with data mining rules extracted from the data warehouse of the enterprise. Our redesign algorithms suggest design-time changes to be made to its business processes, primarily by eliminating redundant tasks and re-ordering inefficiently-located tasks. We analyze the effectiveness of candidate to-be business processes with regard to business intelligence indicators. We report our work on the enterprise architecture developed for a retailer of low-cost domestic flights.

随着企业转型，企业再造对于保持企业竞争力至关重要。企业再造解决（紧急）变化、重组、外包和重新调整等问题。重新设计本身在学术界和商业界都受到关注。该领域的大多数学术工作仅限于模型驱动分析、用于分析现状/未来企业模型的整体框架以及一些其他概念化技术。流程重新设计的实践可以理解为重新设计的阶段。然而，缺少能够深刻地指出如何改进流程以主动重新设计流程密集型企业架构的算法技术。数据科学和商业智能通过研究业务流程的运营历史以促进最合理的变化，为这一主流问题带来了令人耳目一新的新分析。在本文中，我们研究了考虑到企业高层战略和数据仓库的企业流程重新设计。更具体地说，我们提出了一种推理企业战略的方法以及从企业数据仓库中提取的数据挖掘规则。我们的重新设计算法建议对其业务流程进行设计时更改，主要是通过消除冗余任务和重新排序定位低效的任务。我们根据商业智能指标分析候选业务流程的有效性。