Maya Lincoln

Searching business process repositories using operational similarity

Effective retrieval of relevant know-how segments from business process repositories can save precious employee time and support non-expert users in locating and reusing process data. We present a methodology for searching repositories and retrieving relevant process segments, using business logic that is extracted from real-life process models. The analysis of a process repository enables the construction of three taxonomies with which it is possible to process the search intention in operational terms. We tested the method on the Oracle ERP Business Process Model (OBM), showing the approach to be effective in enabling the search of business process repositories.

Accelerated enterprise process modeling through a formalized functional typology

An enterprise process model encompasses a set of business processes implemented or to be implemented in the enterprise. As such, it expresses the requirements of the organization and thus constitutes a compulsory prerequisite for the successful implementation of process-based IT systems such as ERP, SCM and CRM. However, there is a lack of an enabling science to guide the generation of an individualized process model for a particular enterprise. Conceptually, content based enterprise process modeling – itemizing the processes carried out within the enterprise – is based on the assumption of similarity between enterprises that operate within a given industrial sector, so that a generic model should be applicable, with some customization, to all enterprises within that sector. Our approach is based upon the premise that enterprises are characterized by their functionalities, rather than by their end products or technologies. We thus propose a method which enables the functionality of a specific enterprise to be defined; and from this definition a unique enterprise process model can be generated to constitute a statement of the business processes of the enterprise.

Content-based validation of business process modifications

Researchers become increasingly interested in developing tools for evaluating the correctness of business process models. We present a methodology for content-based validation of changes to business processes, relying on an automatic extraction of business logic from real-life business process repositories. Each process step in a repository is automatically transformed to a descriptor - containing objects, actions, and related qualifiers. From the collection of descriptors we induce taxonomies of action sequence, object lifecycle, and object and action hierarchies that form the logical foundation of the presented validation process. The method utilizes these taxonomies to identify process deficiencies that may occur due to process model modification, and suggests alternatives in order to correct and validate the models.

Semantic Machine Learning for Business Process Content Generation

Business process modeling is considered a manual, labor intensive task. It requires significant domain expertise and may be prone to errors or inconsistencies due to reliance on human factors. Hence, automation through reuse of predefined process models is becoming a common practice for generating new models. In this work we extend a previously proposed generation method by adding semantic learning capabilities that opt to improve the quality of generated business process models. The learning mechanism analyzes, in real-time, the linguistic relationships between process descriptors and adjusts them according to human inputs that are accumulated during the modeling process. To demonstrate the method we present a case-study from the food manufacturing industry. To estimate the applicative value we further experimented the method on a real-life process repository, showing that the learning mechanism increases the effectiveness of the previously suggested method for automating the design of new business process models.

ERP reference process models: from generic to specific

Generic reference models are based on the assumption of similarity between enterprises – either cross industrial or within a given sector. The research describes a validated reference metamodel, based on an empirical study of enterprises from various industrial sectors. Drawing on the metamodel, we suggest a methodology and tools for the design and generation of individualized business process models.

Ontology Based Method for Supporting Business Process Modeling Decisions

This work suggests a method for machine-assisted support of business process modeling decisions, based on business logic that is extracted from process repositories using a linguistic analysis of the relationships between constructs of process descriptors. The analysis enables the setup of a descriptor space, in which it is possible to analyze business rules and logic. The suggested method aims to assist process designers in modeling decision making, based on knowledge that is encapsulated within existing business process repositories. The method is demonstrated using a real-life process repository from the higher-education industry.

Applications for Business Process Repositories Based on Semantic Standardization

In recent years, researchers have become increasingly interested in developing frameworks and tools for the generation, customization and utilization of business process model content. One of the enabling central techniques for automated repository standardization is Natural Language Processing (NLP). This work reviews previous works on NLP standardization, and presents a set of derived Business Process Management (BPM) applications. We then discuss how these applications can be extended and improved for better utilization of the process repositories by (1) deploying a larger set of semantic models; and (2) integrating complementing applications.

Natural Language Processing for Risk Identification in Business Process Repositories

In recent years, researchers have become increasingly interested in developing methods and tools for automating the design of governance, risk and compliance (GRC) models. This work suggests a method for machine-assisted identification and design of new risks, based on business logic that is extracted from real-life process repositories using a linguistic analysis of the operational similarity between process conducts. The suggested method can assist process analysts, audit executives and risk managers in identifying new organizational risks while making use of knowledge that is encoded in existing process repositories. The suggested framework was tested on the ProcessGene process repository, showing our approach to be effective in enabling the identification and design of new risks within real-life business process models.

Business Process Search within Unstructured Repositories

In recent years, researchers have become increasingly interested in developing frameworks and tools for searching business process model repositories. While research on searching structured repositories has been extensive, little attention was dedicated to searching business process content within unstructured repositories, such as the Web. We demonstrate why current search technologies are not useful for extracting process content from the Web, and explain the core reasons for the deficiency. We then present a framework for overcoming this material weakness, and discuss possible applications for realizing the suggested method.

ProcessGene view: an integrated visualization of business process models

One of the main challenges in the field of business process management is creating visibility into the business of organizations. The prevailing approach utilizes conceptual business process modeling as the foundation for creating and managing this visibility. Our approach aims to extend previous academic and industry efforts in this field by suggesting a systematic business process visualization method - featuring the multi-faceted visualization interfaces to an existing process model. Each interface encapsulates the data in a different manner- aiming to serve different user populations as well as different use-cases. To test and illustrate the suggested method we implemented it as an add-on to an off-the-shelf BPM software suite.