Assessing business process complexity based on textual data: Evidence from ITIL IT ticket processing

Abstract

PurposeThis study aims to draw the attention of business process management (BPM) research and practice to the textual data generated in the processes and the potential of meaningful insights extraction. The authors apply standard natural language processing (NLP) approaches to gain valuable knowledge in the form of business process (BP) complexity concept suggested in the study. It is built on the objective, subjective and meta-knowledge extracted from the BP textual data and encompassing semantics, syntax and stylistics. As a result, the authors aim to create awareness about cognitive, attention and reading efforts forming the textual data-based BP complexity. The concept serves as a basis for the development of various decision-support solutions for BP workers.Design/methodology/approachThe starting point is an investigation of the complexity concept in the BPM literature to develop an understanding of the related complexity research and to put the textual data-based BP complexity in its context. Afterward, utilizing the linguistic foundations and the theory of situation awareness (SA), the concept is empirically developed and evaluated in a real-world application case using qualitative interview-based and quantitative data-based methods.FindingsIn the practical, real-world application, the authors confirmed that BP textual data could be used to predict BP complexity from the semantic, syntactic and stylistic viewpoints. The authors were able to prove the value of this knowledge about the BP complexity formed based on the (1) professional contextual experience of the BP worker enriched by the awareness of cognitive efforts required for BP execution (objective knowledge), (2) business emotions enriched by attention efforts (subjective knowledge) and (3) quality of the text, i.e. professionalism, expertise and stress level of the text author, enriched by reading efforts (meta-knowledge). In particular, the BP complexity concept has been applied to an industrial example of Information Technology Infrastructure Library (ITIL) change management (CHM) Information Technology (IT) ticket processing. The authors used IT ticket texts from two samples of 28,157 and 4,625 tickets as the basis for the analysis. The authors evaluated the concept with the help of manually labeled tickets and a rule-based approach using historical ticket execution data. Having a recommendation character, the results showed to be useful in creating awareness regarding cognitive, attention and reading efforts for ITIL CHM BP workers coordinating the IT ticket processing.Originality/valueWhile aiming to draw attention to those valuable insights inherent in BP textual data, the authors propose an unconventional approach to BP complexity definition through the lens of textual data. Hereby, the authors address the challenges specified by BPM researchers, i.e. focus on semantics in the development of vocabularies and organization- and sector-specific adaptation of standard NLP techniques.

Dynamic market complexity and service value advantage: an empirical investigation of business process management

“…For this study, we use complexity theory as an overarching theory. Conceptualizing dynamic market requirements with complexity perspective allows the analysis to be relevant and rigorous (Rizun et al, 2021;Cunha and Joao Vieira, 2006;Varnali, 2019). Figure 1 shows the conceptual framework from complexity theory perspective in three organizational processes: Sensing is a value discovery process that understands the nature of market challenges and conceives tangible dynamic market expectations (Eldor, 2020;Felin and Powell, 2016).…”

“…For this study, we use complexity theory as an overarching theory. Conceptualizing dynamic market requirements with complexity perspective allows the analysis to be relevant and rigorous (Rizun et al. , 2021; Cunha and Joao Vieira, 2006; Varnali, 2019).…”

Multiple Severity-Level Classifications for IT Incident Risk Prediction

“…The classifiers involved are KNN, DT, NB, Logistic Regression (LR), and SVM. Following their previous rulebased implementations [12]- [14], they have proposed a semisupervised classification algorithm named QuickSuccess. They have performed analysis for multi-label classification (High, Medium and Low).…”

Method to Address Complexity in Organizations Based on a Comprehensive Overview

“…Besides, another group of studies aiming to deal with process complexity in organizations consider it from the specific perspective of process models, workflows, and event logs [27][28][29]. Another rather unconventional approach to process complexity is suggested in [30]. The authors study the complexity of IT Service Management processes through the lens of textual data massively generated in the organizations and the related readability and understandability of textual work instructions.…”

“…Subsequently, we pose a question about how we can obtain this information. Textual data generated inside and outside organizations remain one of the most valuable types of unstructured data [30,[48][49][50]. Hence, we consider textual complexity as the third type of complexity, which, among others, reflects the people component in organizations.…”