What Automated Planning Can Do for Business Process Management

Business Process Management (BPM) is a central element of today organizations. Despite over the years its main focus has been the support of processes in highly controlled domains, nowadays many domains of interest to the BPM community are characterized by ever-changing requirements, unpredictable environments and increasing amounts of data that influence the execution of process instances. Under such dynamic conditions, BPM systems must increase their level of automation to provide the reactivity and flexibility necessary for process management. On the other hand, the Artificial Intelligence (AI) community has concentrated its efforts on investigating dynamic domains that involve active control of computational entities and physical devices (e.g., robots, software agents, etc.). In this context, Automated Planning, which is one of the oldest areas in AI, is conceived as a model-based approach to synthesize autonomous behaviours in automated way from a model. In this paper, we discuss how automated planning techniques can be leveraged to enable new levels of automation and support for business processing, and we show some concrete examples of their successful application to the different stages of the BPM life cycle

Process Selection in RPA Projects – Towards a Quantifiable Method of Decision Making

The digital age requires companies to invest in value-creating rather than routine activities to drive innovation as a future source of competitiveness and business success. Thus, many companies are reluctant to invest in large-scale, costly backend integration projects and seek adaptable solutions to automate their front-office activities. Bridging artificial intelligence and business process management, robotic process automation (RPA) provides the promise of robots as a virtual workforce that performs these tasks in a self-determined manner. Many studies have highlighted potential benefits of RPA. However, little data is available on operationalizing and automating RPA to maximize its benefits. In this paper, we shed light on the automation potential of processes with RPA and operationalize it. Based on process mining techniques, we propose an automatable indicator system as well as present and evaluate decision support for companies that seek to better prioritize their RPA activities and to maximize their return on investment

Augmented Business Process Management Systems: A Research Manifesto

Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems that draws upon trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for ABPMSs and discusses research challenges that need to be surmounted to realize this vision. To this end, we define the concept of ABPMS, we outline the lifecycle of processes within an ABPMS, we discuss core characteristics of an ABPMS, and we derive a set of challenges to realize systems with these characteristics.Comment: 19 pages, 1 figur

AI-augmented business process management systems: a research manifesto

AI-augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for ABPMSs and discusses research challenges that need to be surmounted to realize this vision. To this end, we define the concept of ABPMS, we outline the lifecycle of processes within an ABPMS, we discuss core characteristics of an ABPMS, and we derive a set of challenges to realize systems with these characteristics

Business process management and digital innovations : a systematic literature review

Emerging technologies have capabilities to reshape business process management (BPM) from its traditional version to a more explorative variant. However, to exploit the full benefits of new IT, it is essential to reveal BPM’s research potential and to detect recent trends in practice. Therefore, this work presents a systematic literature review (SLR) with 231 recent academic articles (from 2014 until May 2019) that integrate BPM with digital innovations (DI). We position those articles against seven future BPM-DI trends that were inductively derived from an expert panel. By complementing the expected trends in practice with a state-of-the-art literature review, we are able to derive covered and uncovered themes in order to help bridge a rigor-relevance gap. The major technological impacts within the BPM field seem to focus on value creation, customer engagement and managing human-centric and knowledge-intensive business processes. Finally, our findings are categorized into specific calls for research and for action to let scholars and organizations better prepare for future digital needs

Towards Smart Incident Management Under Human Resource Constraints for an IoT-BPM Hybrid Architecture

International audienceThe Internet of Things (IoT) is exploding, and this new technology affects all the layers in any enterprise architecture, from infrastructure to business. To survive this new evolution and make the most out of this paradigm shift, a communication channel must be created between Business Process Management (BPM) domain and IoT domain in order to bridge the gap between the business layer and the IoT physical layer. The allocation of business process resources to IoT events is an important step towards an end-to-end IoT-BPM integration approach to assist organizations in their scheduling and incident management journey. In this paper, we propose a combination approach which is based on (i) unsupervised machine learning algorithms to generate clusters of priorities, used to estimate incoming events priority, and to ensure a learning feedback loop that feeds forward insight to continuously adjust decisions made at each layer, and (ii) genetic algorithm (GA) to guarantee the assignment of the most critical IoT generated event to the qualified human resource while respecting several constraints such as resource availability and reliability, and taking into consideration the priority of each event that launch process instances. A case study is presented and the obtained results from our experimentations demonstrate the benefit of our approach and allowed us to confirm the efficiency of our assumptions

Gestión por procesos en la Cooperativa de Ahorro y Crédito “Nuestra Señora del Rosario” – región norte

La gestión por procesos es una manera de organizar las actividades para la satisfacción del cliente sobre las actividades de la organización. Estos son gestionados de modo estructurado y sobre su mejora se basa la de la propia organización. El objetivo general de la investigación fue describir la gestión por procesos de la entidad financiera. Tiene un enfoque cualitativo de tipo básica y el diseño es definido como Teoría Fundamentada. El instrumento utilizado fue un cuestionario bajo la forma de entrevista a profundidad. La conclusión principal fue que la gestión por procesos para la entidad se definió bajo el sustento de la revisión, construcción y diseño del Organigrama Institucional, el que se sustenta en dos niveles jerárquicos que son: el Nivel Representativo y el Nivel Ejecutivo; el Mapa de Macroprocesos, que tiene 3 niveles que son: Estratégicos o Gobernantes, Misionales o de Cadena de Valor y los de Soporte o Apoyo y, por último, las Matrices de Procesos, así como Procedimientos por cada Macroproceso. Así mismo, rediseñar el (MOF), pero dentro de esta línea de intervención, el MOF debe generarse después de la definición diseño de procesos y procedimientos de cada área, construirlo antes implica desarrollar una doble labor