Automatic Identification of Structural Process Weaknesses – Experiences with Semantic Business Process Modeling in the Financial Sector

Business process reengineering (BPR) has been a core research topic for at least the last twenty years. As banks have realized the need to look on their business in a process-oriented way, they have been engaged in numerous business process reengineering projects to make their organizations more efficient. However, the success of BPR projects in banks varies significantly and it remains a challenge to systematically discover weaknesses in business process landscapes. Based on the Semantic Business Process Modeling Language (SBPML) this paper introduces a new approach for pattern-based automatic process model analysis, with a focus on identifying structural process weaknesses such as organizational process fragmentation, possibly unnecessary process complexity or multiple resource usage or other process inefficiencies. Additionally, this approach also allows for a benchmarking of different process path alternatives in the same process or among different processes. In this article, this approach is applied and evaluated in the financial sector, but it can possibly also be used in other domains. It contributes to a more efficient and more effective identification of possible weaknesses in process models in comparison to today’s manual analysis of process models

Experimental Evaluation of a Process Benchmarking Tool in a Green Business Process Management Context

Using a combination of metamodels, ontologies, green performance indicators and metrics, we apply a novel approach in Semantic Business Process Benchmarking to the area of Green Business Process Management (Green BPM). Up to now, process benchmarking has mainly been a manual process; the approach described and empirically evaluated in this paper partially automates the time-consuming and costly process analyses while introducing more flexibility regarding varying terminology, level of abstraction and modeling notation. Also, overviews of literature relevant to the field of Green Semantic BPM and commonly applied metrics in a Green BPM context are given

Supporting Business Process Improvement through Business Process Weakness Pattern Collections

A main task of Business Process Management is to identify weaknesses in business processes that may result in monetary or quality-related drawbacks in order to eliminate them subsequently. A common way to identify weaknesses is to analyze process models. While this has traditionally been done manually, recent work proposes using automatic model query approaches promising time and money savings. Query approaches take (weakness) patterns as input and return all process model subsections that match these patterns, hence may be subject to weaknesses. Although numerous model query approaches have been developed, collections of weaknesses do virtually not exist. To exploit the benefits of model querying, a weakness collection would be highly desirable. In this paper, we provide a first version of a weakness pattern collection, which we identified in an empirical study on several hundreds of weakness-afflicted process models and assess its usefulness through applying it to another process model collection

BUSINESS PROCESS MODEL ANTI-PATTERNS: A BIBLIOGRAPHY AND TAXONOMY OF PUBLISHED WORK

Patterns have been proven to be useful for documenting reusable solutions to common problems. A recently published bibliography of business process model patterns shed light into the various types of patterns by providing a systematic categorization of these patterns. In this way, such classification improves the understanding of business process model patterns. Anti-patterns document a counterproductive solution to a commonly occurring problem. While a classification for the large body of literature on business process model patterns is available, a structured bibliography of anti-patterns is missing. Related work on anti-patterns discusses patterns for common modeling errors, problems in business process models as well as in the business processes. Modeling experts should be aware of all these types of anti-patterns. To fill this gap, this paper presents a bibliography of business process model anti-patterns and a taxonomy of anti-patterns that has been developed using an established approach for taxonomy development. Both are based on an literature review and are valuable for people during the design and analysis phases of business processes since knowledge about anti-patterns in business process models helps for increasing their quality. Our overview should also be useful for developers of modeling tools who wish to make the modeler aware of potential modeling problems

AN EMPIRICAL ASSESSMENT OF THE USEFULNESS OF WEAKNESS PATTERNS IN BUSINESS PROCESS REDESIGN

Business Process Management (BPM) is a topic with growing relevance for businesses as well as public organisations. Until today, the analysis part of a BPM cycle is mostly done manually. Process modelling methods are not designed to allow for automated analysis. Our aim is to show that meaningful weakness patterns that support semi-automatic analysis of business process diagrams (BPD) can be defined when a semantically enhanced modelling method is used. We derive exemplary weakness patterns by analysing literature and interviews from a business process redesign project. These are applied to a set of process models, in which occurrences of these weaknesses are being searched automatically. A comparison of achieved and expected results indicates that our approach helps to identify weaknesses within the processes and therefore supports business process analysis endeavours

Challenging Problems in Data Mining and Data Warehousing

Data mining is a process which is used by companies to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their customers and develop more effective marketing strategies as well as increase sales and decrease costs. It depends on constructive data collection and warehousing as well as computer processing. Data mining used to analyze patterns and relationships in data based on what users request. For example, data mining software can be used to create classes of information. When companies centralize their data into one database or program, it is known as data warehousing. Accompanied a data warehouse, an organization may spin off segments of the data for particular users and utilize. While, in other cases, analysts may begin with the type of data they want and create a data warehouse based on those specs. Regardless of how businesses and other entities systemize their data, they use it to support management's decision-making processes

Business Capability Mining - Opportunities and Challenges

Business capability models are widely used in enterprise architecture management to generate an abstract overview of an organization’s business activities to reach its business objectives. The creation and maintenance of these models are associated with a huge manual workload. Research provides insights into opportunities for automated modeling of enterprise architecture models. However, most models address the application and technology layer and leave the business layer largely unexplored. Particularly, no research has been conducted on the automated generation of business capability models. This research paper uses 19 semi-structured expert interviews to identify possible automated modeling opportunities of business capabilities and related challenges and to jointly develop a business capability mining approach. This research benefit both, practice and research, by describing a situation-based business capability mining approach and identifying appropriate implementation scenarios

Supporting Information Systems Analysis Through Conceptual Model Query – The Diagramed Model Query Language (DMQL)

Analyzing conceptual models such as process models, data models, or organizational charts is useful for several purposes in information systems engineering (e.g., for business process improvement, compliance management, model driven software development, and software alignment). To analyze conceptual models structurally and semantically, so-called model query languages have been put forth. Model query languages take a model pattern and conceptual models as input and return all subsections of the models that match this pattern. Existing model query languages typically focus on a single modeling language and/or application area (such as analysis of execution semantics of process models), are restricted in their expressive power of representing model structures, and/or abstain from graphical pattern specification. Because these restrictions may hamper query languages from propagating into practice, we close this gap by proposing a modeling language-spanning structural model query language based on flexible graph search that, hence, provides high structural expressive power. To address ease-of-use, it allows one to specify model queries using a diagram. In this paper, we present the syntax and the semantics of the diagramed model query language (DMQL), a corresponding search algorithm, an implementation as a modeling tool prototype, and a performance evaluation

Policy-Making Model of the Ministry of Industry, Mine and Trade Based on Digital Transformation

Purpose: The purpose of this study is a policy-making model of the Ministry of Industry, Mine and Trade (MIMT) based on digital transformation is presented. Method: The study is an applied-developmental study in terms of purpose and cross-sectional survey research. A semi-structured interview and Likert scale questionnaire were used to collect data. The reliability of the questionnaire was assessed using Cronbach's alpha and combined reliability. The statistical population includes experts in the automotive industry until the theoretical saturation was reached and 15 experts participated. Using Cochran's formula for indeterminate populations, 365 people were calculated as a sample and cluster sampling method. To analyze the data, the grounded theory analysis method was used to identify the research indicators, and to validate and present the final model, the structural equation modeling method and LISREL software were used. Findings: it can be acknowledged that before deciding to transform processes and enter the digital arena, it is necessary to assess the readiness of the organization as well as its human resources to accept this change Conclusion: the implementation of the automotive industry policy for digital transformation will make the Ministry of Industry, Mine, and Trade the digital leader in the automotive industry

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