Recursos

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.

Informal caregivers take care of someone (usually a close family member) who suffers from a chronic illness. In this stressful situation, caregivers have a high risk of depression or loneliness, because their social network is weakened. Most existing proposals focus on helping caregivers fulfill caregiving tasks, instead of providing support for their mental wellbeing (e.g. identifying early stages of social isolation). We present a prototype ambient interface, called EmoTree, that makes communication frequency tangible by using a metaphor of a tree, and investigate user perception and motivation of use. People found Emotree to be interesting and enjoyable (78%), and useful (54%) unless the user does not suffer some type of problem (69%). Our preliminary results show the interface is easy to use and has an adequate representation of communication frequency. Our next step will make a second assessment with informal caregivers in their real context.

Nowadays, business corporations are immersed in a competitive world, in which there is current need to revise and renovate traditional business models. Information technologies offer the possibi- lity of defining new business strategies through the use of technology innovation and all of its recent breakthroughs. The virtualization of IT recourses shelters the creation of an IT platform composed of replicates of actual computers machines built on a software base. The objective of this article is to present a panoramic view of the main features, types, uses, and current trends offered by the advantages of this technology.

Dynamic resource allocation is considered a major challenge in the context of business process management. At the operational level, flexible methods that support resource allocation and which consider different criteria at run-time are required. It is also important that these methods are able to support multiple allocations in a simultaneous manner. In this paper, we present a framework based on multi-factor criteria that proposes a recommender system which is capable of recommending the most suitable resources for executing a range of different activities, while also considering individual requests or requests made in blocks. To evaluate the proposed framework, a number of experiments were conducted using different test scenarios. These scenarios provide evidence that our approach based on multi-factor criteria successfully allocates the most suitable resources for executing a process in real and flexible environments. In order to demonstrate this assertion, we use a help-desk process as a real case study. 

The BPIC Challenge 2017 provides an event log based on a real financial entity that represents the loan approval process triggered by the clients’ applications submission. The mentioned log consists of 31,509 cases, there are 4,047 variants and from the whole process are recognized 26 activities. The analysis was done using process mining tools and spreadsheet manipulation. The challenge proposed four questions that would allow us to explore certain subsets of the data and analyze them. The first question is about the throughput times of the process; the second question concerns about the conversion rate of multiple and single offer cases; the third question try to discover the system users influence in the final outcome of its clients application; and the fourth questions is about the behavior of clients whose offers are cancelled. We found that clients were slower than bank’s workers and this happens in spite of the type of case. Also, the system user - client affects the final status of a given offer and that the value of this type of interaction can be quantified. Besides, the conversion rate is similar between single and multiple offers. We proposed an inactivity model to make predictions about the possible outcomes given certain characteristic of each case. Finally, we give some recommendations to handle these situations.

Global healthcare services have evolved over time, and nowadays they are expected to follow high-quality optimized standards. Analyzing healthcare processes has become a relevant field of study, and different techniques and tools have been developed to promote improvements in the efficiency and effectiveness of these processes. There is a research field called process mining that can be used to extract knowledge from the event data stored in the hospital information systems. With the help of this, it is possible to discover the real executed process, examine its performance and analyze the resource interaction during its execution. The goal of this article is to provide a bibliographic survey about the use of process mining algorithms, techniques, and tools in the analysis of healthcare processes, providing a general overview about the main approaches previously used and the information required to apply them in the medical field. We provide important insights about data, algorithms, techniques and methodologies that are required to help answer medical expert questions about their processes, motivating and inspiring a broader usage. So, if we have the information and it is possible to analyze and understand the healthcare processes, why are we not doing it?

This paper gives a general look about the forensic computer science, its definition and main character- istics. Also, it shows the importance that the forensic computer science is put into practice in an effective way, together with the support that receives from the technology tools. Finally, explains the applica- tion that has this science in Costa Rica, as well the existent legislation for computer science crime in the country.

Purpose – Human resource allocation is considered a relevant problem in business process management (BPM). The successful allocation of available resources for the execution of process activities can impact on process performance, reduce costs and obtain a better productivity of the resources. In particular, process mining is an emerging discipline that allows improvement of the resource allocation based on the analysis of historical data. The purpose of this paper is to provide a broad review of primary studies published in the research area of human resource allocation in BPM and process mining. Design/methodology/approach – A systematic mapping study (SMS) was conducted in order to classify the proposed approaches to allocate human resources. A total of 2,370 studies published between January 2005 and July 2016 were identified. Through a selection protocol, a group of 95 studies were selected.

Findings – Human resource allocation is an emerging research area that has been evolving over time, generating new proposals that are increasingly applied to real case studies. The majority of proposed approaches relate to the period 2011-2016. Journals and conference proceedings are the most common venues. Validation research and evaluation research are the most common research types. There are two main evaluation methods: simulation and case studies.

Originality/value – This study aims to provide an initial assessment of the state of the art in the research area of human resource allocation in BPM and process mining. To the best of the authors’ knowledge, this is the first research that has been conducted to date that generates a SMS in this research area.