Recursos

The structure and the way in which organizations manage their projects have evolved. Agile software development has emerged as an alternative to manage projects management processes more efficiently. Process mining allows the analysis of project historical information and proposing improvements for agile processes. A systematic mapping study (SMS) was conducted to classify the proposed approaches in agile development methodologies that uses process mining. A total of 502 studies were identified, and finally 6 studies were selected and analyzed according to distinct aspects. Conference proceedings is the most common venue. There is a concentration of approaches published that comes from Asia and Europe. Disco tool is the most frequently used tool. Meanwhile, the process discovery being the most relevant process mining type used by researchers in this research area. There are two evaluation methods reported as being used: case study and running example, where Scrum is the most frequently methodology used. To the best of our knowledge, this is the first research that has been conducted to generate a SMS in this research area.

Allocating the most appropriate resource to execute the activities of a business process is a key aspect within the organizational perspective. An optimal selection of the resources that are in charge of executing the activities may contribute to improve the efficiency and the performance of the business processes. Despite the existence of resource metamodels that seek to provide a better representation of resources, a detailed classification of the allocation criteria that have been used to evaluate resources is missing. In this paper, we provide an initial proposal for a resource allocation criteria taxonomy. This taxonomy is based on an extensive literature review that yielded 2,370 articles regarding the existing resource allocation approaches within the business process management discipline, from which 95 articles were considered for the analysis. The proposed taxonomy points out the most frequently used criteria for assessing the resources from January 2005 to July 2016.

Chronic pain reduces quality of life and affects patients' emotional well-being. When technologies for monitoring and reporting emotions are applied to people suffering from chronic pain, mental health problems may be detected, allowing health professionals to improve patients' treatments and understand their patients in real contexts. However, older patients with chronic pain are limited by their knowledge about technology. Our work aims to understand how to design wearable devices that allow older adults to input complex information such as pain levels and emotional states.

XXXVI Conferencia Latinoamericana en Informática (CLEI)

In healthcare, developing high procedural skill levels through training is a key factor for obtaining good clinical results on surgical pro- cedures. Providing feedback to each student tailored to how the student has performed the procedure each time, improves the effectiveness of the training. Current state-of-the-art feedback relies on Checklists and Global Rating Scales to indicate whether all process steps have been performed and the quality of each execution step. However, there is a process perspective not successfully captured by those instruments, e.g., steps performed but in an undesired order, part of the process repeated an unnecessary number of times, or excessive transition time between steps. In this work, we propose a novel use of process mining techniques to effectively identify desired and undesired process patterns regarding rework, order, and performance, in order to complement the tailored feed- back of surgical procedures using a process perspective. The approach has been effectively applied to analyze a real Central Venous Catheter installation training case. In the future, it is necessary to measure the actual impact of feedback on learning.

The BPI Challenge 2017 provides a real-life event log com- posed by loan applications and offers, generated by a bank to analyze the data and improve their processes. This paper analyzes the through- put times of the process, in particular the difference between the time spent in the company’s systems waiting for processing by a user and the time spent waiting for an input from the applicant. Moreover, we evaluated the influence of the frequency of incompleteness on the final outcome and if the quantity of offers requested by the customer matters. Other interesting trends are analyzed, such as efficient use of resources, business rules compliance and identification of behavioral patterns at dif- ferent times of the day. Results show that a lack of customer requests for completion does not improve the credit approval rate and that this rate decreases when there are more offers. Also, the more the users engage in the case, the greater the approval rate, but the throughput times get longer as well.

Dynamically allocating the most appropriate resource to execute the different activities of a business process is an important challenge in business process management. An ineffective allocation may lead to an inadequate resources usage, higher costs, or a poor process performance. Different approaches have been used to solve this challenge: data mining techniques, probabilistic allocation, or even manual allocation. However, there is a need for methods that support resource allocation based on multi-factor criteria. We propose a framework for recommend- ing resource allocation based on Process Mining, that does the recommendation at sub-process level, instead of activity-level. We introduce a resource process cube that provides a flexible, extensible and fine-grained mechanism to abstract historical information about past process executions from process event logs. Then, several metrics are computed over the cube, considering different criteria: fitting between resources expertise and the expertise required to perform an activity, past performance (frequency, duration, quality and cost), and resources workload. These metrics are combined to obtain a final recommendation ranking based on the BPA algorithm. The approach is applied to a help desk scenario to demonstrate its usefulness.

This article describes the process of implementing a business process management supported by a service-oriented architecture from a business perspective. Also, it is to suggest how you can do to effectively balance the use of BPM and SOA as an entity differentiator for modern companies that drive the achievement of agile and flexible processes in their businesses.

In the context of the International Business Process Challenge (BPIC, 2018) which is centered this year on the European Agri- cultural Guarantee Fund process, this essay present the results of the study of several questions made by the authors of this document. The first inquiry was to determine the differences between the cases in which the Payment Application was approved in the first attempt, versus the cases with a rejected Payment Application document, showing a loop path for rejected cases and an analysis with suggestions to improve the main process. The second question is related to the differences that can be perceived between the longest cases and the shortest, and it was found a ”trigger” that can be used to determine whether or not a particular case will last longer than usual. The third question was asked in order to determine if there are patterns in the processes that could help pre- dict which cases will be reopened. After they are reopened, the research group also study whether they behave similarly to the rest of the cases, where they found that this does not happen in a lot of cases. In the fourth question were determined the differences between the processes of the rejected and the approved cases, where it was found that perhaps it is possible to determine sooner whether a case is going to be rejected or not.

This paper analyses a loan application process of a Dutch Financial Institute proposed by the BPIC Challenge 2017 using process mining tools and techniques. Several filters and performance and organizational analysis are executed in order to observe underlying patterns that may explain some of the bottlenecks of the process, time spent on certain activities and their acceptance rate. Also, we proposed a recommender system to assist client profiling. Our results also include observations regarding to customer communication.