In order to better facilitate the need for continuous business process improvement, the application of DevOps principles has been proposed. In particular, the AB-BPM methodology applies AB testing and reinforcement learning to increase the speed and quality of improvement efforts. In this paper, we provide an industry perspective on this approach, assessing requirements, risks, opportunities, and more aspects of the AB-BPM methodology and supporting tools. Our qualitative analysis combines grounded theory with a Delphi study, including semi-structured interviews and multiple follow-up surveys with a panel of ten business process management experts. The main findings indicate a need for human control during reinforcement learning-driven experiments, the importance of aligning the methodology culturally and organizationally with the respective setting, and the necessity of an integrated process execution platform.

翻译：为了更好地满足持续业务流程改进的需求，已提出应用DevOps原则。具体而言，AB-BPM方法利用AB测试和强化学习来提高改进工作的速度和质量。本文从行业角度评估该方法，分析AB-BPM方法论及支持工具的需求、风险、机遇等方面。我们的定性分析结合了扎根理论与德尔菲研究，包括半结构化访谈和由十位业务流程管理专家组成的小组进行的多次后续调查。主要发现表明，在强化学习驱动的实验中需要人工控制，方法需要根据具体环境进行文化和组织上的对齐，以及需要一个集成的流程执行平台。