Introduction: Organizations require more productivity and efficiency in their business processes every day. Currently, various tools provide support to optimize time and resources according to the complexity of the activities of the business processes. However, by automating processes, few companies can define a successful workflow, thus failing to anticipate the difficulties in a production environment. Consequently, it is impossible to provide an early solution to problems, which implies cost overruns, loss of time, and in some cases, affectation of the organization's human talent. Objective: This article presents a generic service model for the automatic improvement of business processes that allows identifying bottlenecks, reprocesses, failures, and delays when analyzing the event logs of a business process. It also summarizes the implementation of the bottleneck management service to support decision-making in a simulated process, applying regression models to predict the performance of manual process activities based on delays and queue lengths. By predicting performance and making resource allocation suggestions, the level of process improvement was determined. Method: The research was conducted following the Iterative Research Pattern proposed by Pratt. First, the main problems in process management were identified, then a review of the state of the art was carried out to find out the proposed solutions to these problems. A solution model independent of the process management software used was proposed, and finally, two evaluations were carried out, one at a conceptual level with the focus group technique and the other based on the implementation of one of the proposed services and data collected from an experiment in a business process simulator. Results: The conceptual evaluation of the services proposed in the model was conducted by a group of experts, based on the design and content guidelines of the BPMN modeling nomenclature standard, giving a rating of 4.8 out of 5.0 for each service. Experimentation with the business process simulator and the recommendations provided by the implemented service (bottleneck management) made it possible to evaluate the reduction in the processing time of the instances of a process in relation to the added resources. Conclusions: The proposed model is composed of three main services, bottleneck management, resource management, and input management. The first service helps to establish the corrective measures so that the process flows and the instances of this do not get stuck in specific tasks or activities, which helps to improve the response time and the quality of the service. Resource management seeks to optimize the execution time of manual activities and input management seeks to ensure that an instance of the process has the data and documents required to be processed from start to finish, avoiding reprocessing and improving the quality of the data received and processed.
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