Designing a Process Mining-Enabled Decision Support System for Business Process Standardization in ERP Implementation Projects

Process standardization allows to optimize ERP systems and is a nec-essary step prior to ERP implementation projects. Traditional approaches to standardizing business processes are based on manually created "de-jure" process models, which are distorted, error-prone, simplistic, and often deviating from process reality. Theoretically embedded in the organizational contingency theory as kernel theory, this paper employs a design science approach to design a process mining-enabled decision support system (DSS) which combines bottom-up process mining models with manually added top-down standardization infor-mation to recommend a suitable standard process specification from a repository. Extended process models of the as-is process are matched against a repository of best-practice standard process model using an attributebased process similarity matching algorithm. Thus, the DSS aims to reduce the overall costs of process standardization, to optimize the degree of fit between the organization and the implemented processes, and to minimize the degree of organizational change re-quired in standardization and ERP implementation projects. This paper imple-ments a working prototype instantiation in the open-source process analytics platform Apromore based on a real-life event log and standardization attributes for the Purchase-to-Pay and Order-to-Cash processes from three SAP R/3 ERP systems at the industry partner

Comparing Concept Drift Detection with Process Mining Software

Organisations have seen a rise in the volume of data corresponding to business processes being recorded. Handling process data is a meaningful way to extract relevant information from business processes with impact on the company's values. Nonetheless, business processes are subject to changes during their executions, adding complexity to their analysis. This paper aims at evaluating currently available process mining tools and software that handle concept drifts, i.e. changes over time of the statistical properties of the events occurring in a process. We provide an in-depth analysis of these tools, comparing their differences, advantages, and disadvantages by testing against a log taken from a Process Control System. Thus, by highlighting the trade-off between the software, the paper gives the stakeholders the best options regarding their case use

The modelery: a collaborative web based repository

Software development processes are known to produce a large set of artifacts such as models, code and documentation. Keeping track of these artifacts without supporting tools is not easy, and making them available to others can be even harder. Standard version control systems are not able to solve this issue. More than keeping track of versions, a system to help organize and make artifacts available in meaningful ways is needed. In this paper we review a number of alternative systems, and present the requirements and the implementation of a collaborative web repository which we developed to solve this issue.Project LATiCES: Languages And Tools for Critical rEal-time Systems (Ref. NORTE-07-0124-FEDER-000062) is financed by the North Portugal Regional Operational Programme (ON.2 - O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF), and by national funds, through the Portuguese funding agency, Fundacão para a Ciência e a Tecnologia (FCT)

The Modelery: a model-based software development repository

Purpose – This paper aims to present the Modelery, a platform for collaborative repository to support model-based software development. The Modelery is a Web platform, composed both by a Web page and Web services for interoperability. Design/methodology/approach – By performing a study in the existing platforms, it was possible to achieve a set of issues to tackle. The issues enabled the possibility to define a set of requirements that allowed the authors to design a new platform, and to perform a model-driven software development process, which started from the requirements until reaching the final software solution. Findings – With this work, it was possible to perform a survey on the currently available artifacts repositories, categorize them and identify their shortcomings. This was essential to define the set of requirements for a new platform to overcome the identified issues. This process leads to a platform able to improve the currently available solutions, and validated in the scientific community. In this paper, the authors also explore the applications of the repository. First, they use the Modelery to replace an older model’s repository. Second, they have enabled the communication between other tools and the Modelery via Web services. Originality/value – This work presents a new Web repository for software artifacts aimed at supporting researchers and software developers. The presented platform is an improvement over other platforms on the integration of artifacts repository, social functionalities and scientific publications integration. The authors conclude this paper by comparing the achieved platform in terms of functionalities, against the other analyzed platforms

Process Mining Meets Visual Analytics: The Case of Conformance Checking

Conformance checking is a major function of process mining, which allows organizations to identify and alleviate potential deviations from the intended process behavior. To fully leverage its benefits, it is important that conformance checking results are visualized in a way that is approachable and understandable for non-expert users. However, the visualization of conformance checking results has so far not been widely considered in research. Therefore, the goal of this paper is to develop an understanding of how conformance checking results are visualized by process mining tools to provide a foundation for further research on this topic. We conduct a systematic study, where we analyze the visualization capabilities of nine academic and seven commercial tools by means of a visual analytics framework. In this study, we find that the ``Why?'' aspect of conformance checking visualization seems already be well-defined, but the ``What?'' and ``How?'' aspects require future research

Design of Data-Driven Decision Support Systems for Business Process Standardization

Increasingly dynamic environments require organizations to engage in business process standardization (BPS) in response to environmental change. However, BPS depends on numerous contingency factors from different layers of the organization, such as strategy, business models (BMs), business processes (BPs) and application systems that need to be well-understood (“comprehended”) and taken into account by decision-makers for selecting appropriate standard BP designs that fit the organization. Besides, common approaches to BPS are non-data-driven and frequently do not exploit increasingly avail-able data in organizations. Therefore, this thesis addresses the following research ques-tion: “How to design data-driven decision support systems to increase the comprehen-sion of contingency factors on business process standardization?”. Theoretically grounded in organizational contingency theory (OCT), this thesis address-es the research question by conducting three design science research (DSR) projects to design data-driven decision support systems (DSSs) for SAP R/3 and S/4 HANA ERP systems that increase comprehension of BPS contingency factors. The thesis conducts the DSR projects at an industry partner within the context of a BPS and SAP S/4 HANA transformation program at a global manufacturing corporation. DSR project 1 designs a data-driven “Business Model Mining” system that automatical-ly “mines” BMs from data in application systems and represents results in an interactive “Business Model Canvas” (BMC) BI dashboard to comprehend BM-related BPS con-tingency factors. The project derives generic design requirements and a blueprint con-ceptualization for BMM systems and suggests an open, standardized reference data model for BMM. The project implements the software artifact “Business Model Miner” in Microsoft Azure / PowerBI and demonstrates technical feasibility by using data from an educational SAP S/4 HANA system, an open reference dataset, and three real-life SAP R/3 ERP systems. A field evaluation with 21 managers at the industry partner finds differences between tool results and BMCs created by managers and thus the po-tential for a complementary role of BMM tools to enrich the comprehension of BMs. A further controlled laboratory experiment with 142 students finds significant beneficial impacts on subjective and objective comprehension in terms of effectiveness, efficiency, and relative efficiency. Second, DSR project 2 designs a data-driven process mining DSS “KeyPro” to semi-automatically discover and prioritize the set of BPs occurring in an organization from log data to concentrate BPS initiatives on important BPs given limited organizational resources. The project derives objective and quantifiable BP importance metrics from BM and BPM literature and implements KeyPro for SAP R/3 ERP and S/4 HANA sys-tems in Microsoft SQL Server / Azure and interactive PowerBI dashboards. A field evaluation with 52 managers compares BPs detected manually by decision-makers against BPs discovered by KeyPro and reveals significant differences and a complemen-tary role of the artifact to deliver additional insights into the set of BPs in the organiza-tion. Finally, a controlled laboratory experiment with 30 students identifies the dash-boards with the lowest comprehension for further development. Third, OCT requires organizations to select a standard BP design that matches contin-gencies. Thus, DSR project 3 designs a process mining DSS to select a standard BP from a repository of different alternative designs based on the similarity of BPS contin-gency factors between the as-is process and the to-be standard processes. DSR project 3 thus derives four different process model variants for representing BPS contingency factors that vary according to determinant factors of process model comprehension (PMC) identified in PMC literature. A controlled laboratory evaluation with 150 stu-dents identifies significant differences in PMC. Based on laboratory findings, the DSS is implemented in the BPM platform “Apromore” to select standard BP reference mod-els from the SAP Best Practices Explorer for SAP S/4 HANA and applied for the pur-chase-to-pay and order-to-cash process of a manufacturing company

Äriprotsessimudelite ühildamine

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Ettevõtted, kellel on aastatepikkune kogemus äriprotsesside haldamises, omavad sageli protsesside repositooriumeid, mis võivad endas sisaldada sadu või isegi tuhandeid äriprotsessimudeleid. Need mudelid pärinevad erinevatest allikatest ja need on loonud ning neid on muutnud erinevad osapooled, kellel on erinevad modelleerimise oskused ning praktikad. üheks sagedaseks praktikaks on uute mudelite loomine, kasutades olemasolevaid mudeleid, kopeerides neist fragmente ning neid seejärel muutes. See omakorda loob olukorra, kus protsessimudelite repositoorium sisaldab mudeleid, milles on identseid mudeli fragmente, mis viitavad samale alamprotsessile. Kui sellised fragmendid jätta konsolideerimata, siis võib see põhjustada repositooriumis ebakõlasid -- üks ja sama alamprotsess võib olla erinevates protsessides erinevalt kirjeldatud. Sageli on ettevõtetel mudelid, millel on sarnased eesmärgid, kuid mis on mõeldud erinevate klientide, toodete, äriüksuste või geograafiliste regioonide jaoks. Näiteks on äriprotsessid kodukindlustuse ja autokindlustuse jaoks sama ärilise eesmärgiga. Loomulikult sisaldavad nende protsesside mudelid mitmeid identseid alamfragmente (nagu näiteks poliisi andmete kontrollimine), samas on need protsessid mitmes punktis erinevad. Nende protsesside eraldi haldamine on ebaefektiivne ning tekitab liiasusi. Doktoritöös otsisime vastust küsimusele: kuidas identifitseerida protsessimudelite repositooriumis korduvaid mudelite fragmente, ning üldisemalt -- kuidas leida ning konsolideerida sarnasusi suurtes äriprotsessimudelite repositooriumites? Doktoritöös on sisse toodud kaks üksteist täiendavat meetodit äriprotsessimudelite konsolideerimiseks, täpsemalt protsessimudelite ühildamine üheks mudeliks ning mudelifragmentide ekstraktimine. Esimene neist võtab sisendiks kaks või enam protsessimudelit ning konstrueerib neist ühe konsolideeritud protsessimudeli, mis sisaldab kõikide sisendmudelite käitumist. Selline lähenemine võimaldab analüütikutel hallata korraga tervet perekonda sarnaseid mudeleid ning neid muuta sünkroniseeritud viisil. Teine lähenemine, alamprotsesside ekstraktimine, sisaldab endas sagedasti esinevate fragmentide identifitseerimist (protsessimudelites kloonide leidmist) ning nende kapseldamist alamprotsessideks

Process Mining Meets Visual Analytics: The Case of Conformance Checking

Conformance checking is a major function of process mining, which allows organizations to identify and alleviate potential deviations from the intended process behavior. To fully leverage its benefits, it is important that conformance checking results are visualized in a way that is approachable and understandable for non-expert users. However, the visualization of conformance checking results has so far not been widely considered in research. Therefore, the goal of this paper is to develop an understanding of how conformance checking results are visualized by process mining tools to provide a foundation for further research on this topic. We conduct a systematic study, where we analyze the visualization capabilities of nine academic and seven commercial tools by means of a visual analytics framework. In this study, we find that the ''Why?'' aspect of conformance checking visualization seems already be well-defined, but the ''What?'' and ''How?'' aspects require future research.Comment: Submitted to HICSS-56 (2023