scholarly journals Integration of business process and organizational data for evidence-based business intelligence

2021 ◽  
Vol 24 (2) ◽  
Author(s):  
Daniel Calegari ◽  
Andrea Delgado ◽  
Alexis Artus ◽  
Andrés Borges
Keyword(s):  
Business Process ◽  
Business Intelligence ◽  
Business Processes ◽  
Process Mining ◽  
Data Sources ◽  
Evidence Based ◽  
Process Data ◽  
Matching Problems ◽  
Data Matching ◽  
Unified View

Organizations require a unified view of business processes and organizational data for the improvement of their daily operations. However, it is infrequent for both kinds of data to be consistently unified. Organizational data (e.g., clients, orders, and payments) is usually stored in many different data sources. Process data (e.g., cases, activity in- stances, and variables) is generally handled manually or implicit in information systems and coupled with organizational data without clear separation. It impairs the combined application of process mining and data mining techniques for a complete evaluation of their business process execution. In this paper, we deal with the integration of both kinds of data into a unified view. First, we analyze data integration scenarios and data matching problems considering intra-organizational and inter-organizational collaborative business processes. We also propose a model-driven approach to integrate several data sources, generating a unified model for evidence-based business intelligence.

scholarly journals Analysis of SAP Log Data Based on Network Community Decomposition

Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 92 ◽  
Author(s):  
Martin Kopka ◽  
Miloš Kudělka
Keyword(s):  
Information System ◽  
Complex Network ◽  
Business Process ◽  
Business Processes ◽  
Process Mining ◽  
Business Case ◽  
Process Data ◽  
Computer Methods ◽  
Network Community ◽  
Cover Up

Information systems support and ensure the practical running of the most critical business processes. There exists (or can be reconstructed) a record (log) of the process running in the information system. Computer methods of data mining can be used for analysis of process data utilizing support techniques of machine learning and a complex network analysis. The analysis is usually provided based on quantitative parameters of the running process of the information system. It is not so usual to analyze behavior of the participants of the running process from the process log. Here, we show how data and process mining methods can be used for analyzing the running process and how participants behavior can be analyzed from the process log using network (community or cluster) analyses in the constructed complex network from the SAP business process log. This approach constructs a complex network from the process log in a given context and then finds communities or patterns in this network. Found communities or patterns are analyzed using knowledge of the business process and the environment in which the process operates. The results demonstrate the possibility to cover up not only the quantitative but also the qualitative relations (e.g., hidden behavior of participants) using the process log and specific knowledge of the business case.

Enterprise Integrated Business Process Management and Business Intelligence Framework for Business Process Sustainability

2018 ◽  
pp. 228-238
Author(s):  
Gaurav Kabra ◽  
Vinit Ghosh ◽  
A. Ramesh
Keyword(s):  
Business Process ◽  
Business Intelligence ◽  
Operations Management ◽  
Business Process Management ◽  
Process Management ◽  
Management Practices ◽  
Business Processes ◽  
Architecture Framework ◽  
Modern Business ◽  
Information And Communication

In the modern business scenario, organizations are vesting high efforts in managing process sustainability as part of their operations management practices. The global environmental concerns for the welfare of the society have facilitated this change. Research studies have reported Information and Communication Technology (ICT) as one of the prerequisites in developing and maintaining efficient business processes. The process sustainability related initiatives and various processes related regulatory compliances have created the need for sophisticated IT tools like BPM (Business Process Management) and BI (Business Intelligence) in organizations. Thus with the advancement of ICT, a strong desire to enhance the business process performance through BPM and BI applications is felt across organizations. However, there is scant research available on leveraging the advantages of these applications in sustainability development. Therefore, this paper aims to present a conceptual architecture framework using an integrated BPM and BI solution to develop an orientation among practitioners and academicians towards the inclusion of ICT in attaining a sustainable, energy efficient business operations or processes. The framework is based on the literature pertaining to the role of BPM and BI in process sustainability as well as from the inputs of practitioners involved in the field of BPM and BI.

scholarly journals CONDA-PM—A Systematic Review and Framework for Concept Drift Analysis in Process Mining

Algorithms ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 161
Author(s):  
Ghada Elkhawaga ◽  
Mervat Abuelkheir ◽  
Sherif I. Barakat ◽  
Alaa M. Riad ◽  
Manfred Reichert
Keyword(s):  
Systematic Review ◽  
Business Process ◽  
Continuous Monitoring ◽  
Business Processes ◽  
Process Mining ◽  
Concept Drift ◽  
Business Environments ◽  
Drift Analysis ◽  
Comprehensive Framework ◽  
Over Time

Business processes evolve over time to adapt to changing business environments. This requires continuous monitoring of business processes to gain insights into whether they conform to the intended design or deviate from it. The situation when a business process changes while being analysed is denoted as Concept Drift. Its analysis is concerned with studying how a business process changes, in terms of detecting and localising changes and studying the effects of the latter. Concept drift analysis is crucial to enable early detection and management of changes, that is, whether to promote a change to become part of an improved process, or to reject the change and make decisions to mitigate its effects. Despite its importance, there exists no comprehensive framework for analysing concept drift types, affected process perspectives, and granularity levels of a business process. This article proposes the CONcept Drift Analysis in Process Mining (CONDA-PM) framework describing phases and requirements of a concept drift analysis approach. CONDA-PM was derived from a Systematic Literature Review (SLR) of current approaches analysing concept drift. We apply the CONDA-PM framework on current approaches to concept drift analysis and evaluate their maturity. Applying CONDA-PM framework highlights areas where research is needed to complement existing efforts.

scholarly journals Exploring location-dependency in process modeling

2014 ◽  
Vol 20 (6) ◽  
pp. 794-815 ◽  
Author(s):  
Xinwei Zhu ◽  
Jan Recker ◽  
Guobin Zhu ◽  
Flávia Maria Santoro
Keyword(s):  
Business Process ◽  
Process Modeling ◽  
Context Awareness ◽  
Business Processes ◽  
Flow Patterns ◽  
Control Flow ◽  
Process Models ◽  
Location Awareness ◽  
Process Data ◽  
Content Type

Purpose – Context-awareness has emerged as an important principle in the design of flexible business processes. The goal of the research is to develop an approach to extend context-aware business process modeling toward location-awareness. The purpose of this paper is to identify and conceptualize location-dependencies in process modeling. Design/methodology/approach – This paper uses a pattern-based approach to identify location-dependency in process models. The authors design specifications for these patterns. The authors present illustrative examples and evaluate the identified patterns through a literature review of published process cases. Findings – This paper introduces location-awareness as a new perspective to extend context-awareness in BPM research, by introducing relevant location concepts such as location-awareness and location-dependencies. The authors identify five basic location-dependent control-flow patterns that can be captured in process models. And the authors identify location-dependencies in several existing case studies of business processes. Research limitations/implications – The authors focus exclusively on the control-flow perspective of process models. Further work needs to extend the research to address location-dependencies in process data or resources. Further empirical work is needed to explore determinants and consequences of the modeling of location-dependencies. Originality/value – As existing literature mostly focusses on the broad context of business process, location in process modeling still is treated as “second class citizen” in theory and in practice. This paper discusses the vital role of location-dependencies within business processes. The proposed five basic location-dependent control-flow patterns are novel and useful to explain location-dependency in business process models. They provide a conceptual basis for further exploration of location-awareness in the management of business processes.

scholarly journals No Longer Out of Sight, No Longer Out of Mind? How Organizations Engage with Process Mining-Induced Transparency to Achieve Increased Process Awareness

2021 ◽  
Author(s):  
Julia Eggers ◽  
Andreas Hein ◽  
Markus Böhm ◽  
Helmut Krcmar
Keyword(s):  
Business Process ◽  
Process Management ◽  
Business Processes ◽  
Process Mining ◽  
Process Analysis ◽  
Structured Interviews ◽  
Business Process Analysis ◽  
Starting Point ◽  
Shared Awareness ◽  
Induced Transparency

AbstractIn recent years, process mining has emerged as the leading big data technology for business process analysis. By extracting knowledge from event logs in information systems, process mining provides unprecedented transparency of business processes while being independent of the source system. However, despite its practical relevance, there is still a limited understanding of how organizations act upon the pervasive transparency created by process mining and how they leverage it to benefit from increased process awareness. Addressing this gap, this study conducts a multiple case study to explore how four organizations achieved increased process awareness by using process mining. Drawing on data from 24 semi-structured interviews and archival sources, this study reveals seven sociotechnical mechanisms based on process mining that enable organizations to create either standardized or shared awareness of sub-processes, end-to-end processes, and the firm’s process landscape. Thereby, this study contributes to research on business process management by revealing how process mining facilitates mechanisms that serve as a new, data-driven way of creating process awareness. In addition, the findings indicate that these mechanisms are influenced by the governance approach chosen to conduct process mining, i.e., a top-down or bottom-up driven implementation approach. Last, this study also points to the importance of balancing the social complications of increased process transparency and awareness. These results serve as a valuable starting point for practitioners to reflect on measures to increase organizational process awareness through process mining.

Improving Data Quality in Intelligent eCRM Applications

2018 ◽  
pp. 1616-1626 ◽  
Author(s):  
Bashar Shahir Ahmed ◽  
Fadi Amroush ◽  
Mohammed Ben Maati
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Business Process ◽  
Business Intelligence ◽  
Business Processes ◽  
Global Market ◽  
Integrated Systems ◽  
Business Intelligence Systems ◽  
Tools And Techniques

Today most of the businesses are in continuous search of sophisticated tools and techniques to progressively grow their business. And therefore, the use of intelligence systems has found its pace in the global market. The intelligence systems has mostly effected the E-CRM as it is the most critical and central part for the growth of the business. The E-CRM approaches have enhanced drastically with an integration of the business intelligence systems and organizations are now diligently striving for excellence by gaining benefit from these integrated systems. However, there are many organizations which lag behind in escalating their progress and growth as they have not yet understand how to improve the data quality by using business intelligence systems and therefore used it for decision making. Hence, the following research is conducted to study the implementation trends of Intelligence E-CRM in business process and how the business intelligence systems could help in improvising the data quality and the business processes.

scholarly journals Methods of structural analysis of business processes

2018 ◽  
Vol 210 ◽  
pp. 04016
Author(s):  
Jarosław Koszela
Keyword(s):  
Structural Analysis ◽  
Business Intelligence ◽  
Business Processes ◽  
Process Mining ◽  
Central Element ◽  
Structural Similarity ◽  
Similarity Analysis ◽  
Large Sets ◽  
Analysis Methods ◽  
Analytical Processing

The article outlines selected methods for analyzing business processes: their definitions and instances. The methods for analytical processing of processes constitute a component of the Business Intelligence environment - process warehouses, including methods for analytical processing and exploration of the collected process definitions and instances - i.e. process mining. One of the main elements of the analysis of processes is to determine the similarity between them. In systems for analyzing large sets of elements, the method of determining similarity should be efficiency because is the basis for others analysis methods, e.g. clustering, classification, etc. A method for analyzing structural similarity of business processes, based on the similarity of sequences of genetic tags of such processes, was presented using the similarity analysis methods based on the editing distance and the developed methods of structural similarity: GNM, DNM, GCM, DCM. The presented similarity methods were used to clustering processes and to determine the central element of the cluster. The developed methods form the basis for the development of similarity methods extended to aspects of semantic similarity of business processes and methods of analysis and exploration of processes.

Improving Business Processes by Visual Workflow Platform

2011 ◽  
Vol 204-210 ◽  
pp. 1051-1056
Author(s):  
Lang Cai Cao ◽  
Jian Luo
Keyword(s):  
Business Process ◽  
Business Processes ◽  
Business Environment ◽  
Work Efficiency ◽  
Process Data ◽  
Business Units ◽  
High Level ◽  
Share Information ◽  
Track Status ◽  
Current Business

With ever-changing and fast-changing in current business environment, traditional business process is more and more incapable to meet the demand to share information, visualize both high-level and detailed process data, track status and expedite business processes. To address these challenges, the visual workflow platform is introduced. As proven by an industrial case, the workflow platform can greatly help business units to improve work efficiency.

scholarly journals Generating Block-Structured Parallel Process Models by Demonstration

2021 ◽  
Vol 11 (4) ◽  
pp. 1876
Author(s):  
Julijana Lekić ◽  
Dragan Milićev ◽  
Dragan Stanković
Keyword(s):  
Business Process ◽  
Business Processes ◽  
Process Mining ◽  
Original Method ◽  
Process Models ◽  
Programming By Demonstration ◽  
Event Logs ◽  
Process Specification ◽  
Common Purpose ◽  
Block Structured

Programming by demonstration (PBD) is a technique which allows end users to create, modify, accommodate, and expand programs by demonstrating what the program is supposed to do. Although the ideal of common-purpose programming by demonstration or by examples has been rejected as practically unrealistic, this approach has found its application and shown potentials when limited to specific narrow domains and ranges of applications. In this paper, the original method of applying the principles of programming by demonstration in the area of process mining (PM) to interactive construction of block-structured parallel business processes models is presented. A technique and tool that enable interactive process mining and incremental discovery of process models have been described in this paper. The idea is based on the following principle: using a demonstrational user interface, a user demonstrates scenarios of execution of parallel business process activities, and the system gives a generalized model process specification. A modified process mining technique with the α|| algorithm applied on weakly complete event logs is used for creating parallel business process models using demonstration.

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