Unleashing textual descriptions of business processes

Textual descriptions of processes are ubiquitous in organizations, so that documentation of the important processes can be accessible to anyone involved. Unfortunately, the value of this rich data source is hampered by the challenge of analyzing unstructured information. In this paper we propose a framework to overcome the current limitations on dealing with textual descriptions of processes. This framework considers extraction and analysis and connects to process mining via simulation. The framework is grounded in the notion of annotated textual descriptions of processes, which represents a middle-ground between formalization and accessibility, and which accounts for different modeling styles, ranging from purely imperative to purely declarative. The contributions of this paper are implemented in several tools, and case studies are highlighted.This work has been supported by MINECO and FEDER funds under grant TIN2017-86727-C2-1-R.Peer ReviewedPostprint (author's final draft

DETECTING ROLE INCONSISTENCIES IN PROCESS MODELS

Business process models capture crucial information about business operations. To overcome the challenge of maintaining process definitions in large process repositories, researchers have suggested methods to discover errors in the functional and the behavioral perspectives of process models. However, there is a gap in the literature on the detection of problems on the organizational perspective of process models, which is critical to manage the resources and the responsibilities within organizations. In this paper, we introduce an approach to automatically detect inconsistencies between activities and roles in process models. Our approach implements natural language processing techniques and enterprise semantics to identify ambiguous, redundant, and missing roles in textual descriptions. We applied our approach on the process model repository of a major telecommunication company. A quantitative evaluation of our approach with 282 real-life activities displayed that this approach can accurately discover role inconsistencies. Practitioners can achieve significant quality improvements in their process model repositories by applying the approach on process models complemented with textual descriptions

Challenges and opportunities of applying natural language processing in business process management

The Business Process Management (BPM) field focuses in the coordination of labor so that organizational processes are smoothly executed in a way that products and services are properly delivered. At the same time, NLP has reached a maturity level that enables its widespread application in many contexts, thanks to publicly available frameworks. In this position paper, we show how NLP has potential in raising the benefits of BPM practices at different levels. Instead of being exhaustive, we show selected key challenges were a successful application of NLP techniques would facilitate the automation of particular tasks that nowadays require a significant effort to accomplish. Finally, we report on applications that consider both the process perspective and its enhancement through NLP.Peer ReviewedPostprint (published version

Bridging the gap between textual and formal business process representations

Tesi en modalitat de compendi de publicacionsIn the era of digital transformation, an increasing number of organizations are start ing to think in terms of business processes. Processes are at the very heart of each business, and must be understood and carried out by a wide range of actors, from both technical and non-technical backgrounds alike. When embracing digital transformation practices, there is a need for all involved parties to be aware of the underlying business processes in an organization. However, the representational complexity and biases of the state-of-the-art modeling notations pose a challenge in understandability. On the other hand, plain language representations, accessible by nature and easily understood by everyone, are often frowned upon by technical specialists due to their ambiguity. The aim of this thesis is precisely to bridge this gap: Between the world of the techni cal, formal languages and the world of simpler, accessible natural languages. Structured as an article compendium, in this thesis we present four main contributions to address specific problems in the intersection between the fields of natural language processing and business process management.A l’era de la transformació digital, cada vegada més organitzacions comencen a pensar en termes de processos de negoci. Els processos són el nucli principal de tota empresa i, com a tals, han de ser fàcilment comprensibles per un ampli ventall de rols, tant perfils tècnics com no-tècnics. Quan s’adopta la transformació digital, és necessari que totes les parts involucrades estiguin ben informades sobre els protocols implantats com a part del procés de digitalització. Tot i això, la complexitat i biaixos de representació dels llenguatges de modelització que actualment conformen l’estat de l’art sovint en dificulten la seva com prensió. D’altra banda, les representacions basades en documentació usant llenguatge natural, accessibles per naturalesa i fàcilment comprensibles per tothom, moltes vegades són vistes com un problema pels perfils més tècnics a causa de la presència d’ambigüitats en els textos. L’objectiu d’aquesta tesi és precisament el de superar aquesta distància: La distància entre el món dels llenguatges tècnics i formals amb el dels llenguatges naturals, més accessibles i senzills. Amb una estructura de compendi d’articles, en aquesta tesi presentem quatre grans línies de recerca per adreçar problemes específics en aquesta intersecció entre les tecnologies d’anàlisi de llenguatge natural i la gestió dels processos de negoci.Postprint (published version

Searching textual and model-based process descriptions based on a unified data format

Documenting business processes using process models is common practice in many organizations. However, not all process information is best captured in process models. Hence, many organizations complement these models with textual descriptions that specify additional details. The problem with this supplementary use of textual descriptions is that existing techniques for automatically searching process repositories are limited to process models. They are not capable of taking the information from textual descriptions into account and, therefore, provide incomplete search results. In this paper, we address this problem and propose a technique that is capable of searching textual as well as model-based process descriptions. It automatically extracts activity-related and behavioral information from both descriptions types and stores it in a unified data format. An evaluation with a large Austrian bank demonstrates that the additional consideration of textual descriptions allows us to identify more relevant processes from a repository

A Method to Improve the Early Stages of the Robotic Process Automation Lifecycle

The robotic automation of processes is of much interest to organizations. A common use case is to automate the repetitive manual tasks (or processes) that are currently done by back-office staff through some information system (IS). The lifecycle of any Robotic Process Automation (RPA) project starts with the analysis of the process to automate. This is a very time-consuming phase, which in practical settings often relies on the study of process documentation. Such documentation is typically incomplete or inaccurate, e.g., some documented cases never occur, occurring cases are not documented, or documented cases differ from reality. To deploy robots in a production environment that are designed on such a shaky basis entails a high risk. This paper describes and evaluates a new proposal for the early stages of an RPA project: the analysis of a process and its subsequent design. The idea is to leverage the knowledge of back-office staff, which starts by monitoring them in a non-invasive manner. This is done through a screen-mousekey- logger, i.e., a sequence of images, mouse actions, and key actions are stored along with their timestamps. The log which is obtained in this way is transformed into a UI log through image-analysis techniques (e.g., fingerprinting or OCR) and then transformed into a process model by the use of process discovery algorithms. We evaluated this method for two real-life, industrial cases. The evaluation shows clear and substantial benefits in terms of accuracy and speed. This paper presents the method, along with a number of limitations that need to be addressed such that it can be applied in wider contexts.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-

Between overt and covert research: concealment and disclosure in an ethnographic study of commercial hospitality

This article examines the ways in which problems of concealment emerged in an ethnographic study of a suburban bar and considers how disclosure of the research aims, the recruitment of informants, and elicitation of information was negotiated throughout the fieldwork. The case study demonstrates how the social context and the relationships with specific informants determined overtness or covertness in the research. It is argued that the existing literature on covert research and covert methods provides an inappropriate frame of reference with which to understand concealment in fieldwork. The article illustrates why concealment is sometimes necessary, and often unavoidable, and concludes that the criticisms leveled against covert methods should not stop the fieldworker from engaging in research that involves covertness