Model-driven requirements engineering in the context of erp implementation:
Introduction
Definition of Concepts
Knowledge Gap
Research Questions &Objectives
Scope of the Thesis
The Proposed Solutions:
Analysis of the ERP Reference Models (RMs) (O1)
Developing a new framework (LORS) for building the Enterprise Model (EM) (O2)
Developing a Structure Approach (SEAC) for Model Matching (O3)
Conclusion &Future Work
Developing a research proposal in the field of software engineering model dri...Dr. Hamdan Al-Sabri
Developing a research proposal in the field of software engineering model driven requirements matching as an example:
Introduction
Concept Definition
Pervious Studies
Knowledge Gap
Research Objectives
Research Significance
Research Methodology and Techniques
Delimitations and assumptions
Research Strategies
Timetable and initial division of Thesis
Conclusion
Requirements engineering as a structured process:
Requirements Engineering
Requirements Engineering Field
Why are Requirements so important?
Requirements Engineering Activities
Requirements Elements
Requirements Quality
Requirements quality indicators
Conclusion
Software requirements engineering problems and challenges erp implementation as a case study:
Requirements Engineering
Why are Requirements so important?
Purpose of Requirements Engineering
RE process inputs and outputs
Requirements Engineering Activities
Requirements Quality
Requirements quality indicators
Systems RE Standards
Requirements problems and challenges
Research Strategies in RE
RE Research directions
Conclusion
Enterprise resource planning:
What is ERP and its History ?
ERP Components.
Commercial Applications.
The steps to Successful of ERP Implementation.
Consulting Services.
ERP System Architecture.
Characteristics of ERP systems.
The software development process heavily relies on requirement engineering as it forms the base for entire process. Although software engineering is full of methods for requirement analysis, the problem we face is which method to select and how to apply it. It is expected that we should be able to get clear and complete idea about what is expected by the user from the proposed system. This puts emphasis on requirement analysis process. The method we need to adopt should enable us to get clear and complete set of requirements. The requirement engineering process dependent on abilities of the persons carrying out the process also the nature of system puts certain constraints on the process. . This paper is an attempt to look at certain problems posed by the requirement engineering process and possible corrective measures against it to help improve overall software quality.
Developing a research proposal in the field of software engineering model dri...Dr. Hamdan Al-Sabri
Developing a research proposal in the field of software engineering model driven requirements matching as an example:
Introduction
Concept Definition
Pervious Studies
Knowledge Gap
Research Objectives
Research Significance
Research Methodology and Techniques
Delimitations and assumptions
Research Strategies
Timetable and initial division of Thesis
Conclusion
Requirements engineering as a structured process:
Requirements Engineering
Requirements Engineering Field
Why are Requirements so important?
Requirements Engineering Activities
Requirements Elements
Requirements Quality
Requirements quality indicators
Conclusion
Software requirements engineering problems and challenges erp implementation as a case study:
Requirements Engineering
Why are Requirements so important?
Purpose of Requirements Engineering
RE process inputs and outputs
Requirements Engineering Activities
Requirements Quality
Requirements quality indicators
Systems RE Standards
Requirements problems and challenges
Research Strategies in RE
RE Research directions
Conclusion
Enterprise resource planning:
What is ERP and its History ?
ERP Components.
Commercial Applications.
The steps to Successful of ERP Implementation.
Consulting Services.
ERP System Architecture.
Characteristics of ERP systems.
The software development process heavily relies on requirement engineering as it forms the base for entire process. Although software engineering is full of methods for requirement analysis, the problem we face is which method to select and how to apply it. It is expected that we should be able to get clear and complete idea about what is expected by the user from the proposed system. This puts emphasis on requirement analysis process. The method we need to adopt should enable us to get clear and complete set of requirements. The requirement engineering process dependent on abilities of the persons carrying out the process also the nature of system puts certain constraints on the process. . This paper is an attempt to look at certain problems posed by the requirement engineering process and possible corrective measures against it to help improve overall software quality.
Requirements management and traceability for IIBALeslie Munday
This presentation, created for the Seattle chapter of the International Institute of Business Analysts, describes my experienes with managing requirements traceability.
Software Requirements and Specificationsvustudent1
CS510 - SRS handouts for Computer Science students of Virtual University of Pakistan.
Prepared by ForumVU.com Staff from the updated lectures and PowerPoint slides of CS510 - Software Requirements and Specifications in VU LMS.
Towards a Language for Rule-enhanced Business Process Modeling Dragan Gasevic
Presentation of the EDOC 2009 paper:
Business process modeling is a commonly used approach in the development of service-oriented architectures. The previous research on this topic demonstrated that process-oriented models might be too rigid for dynamic adaptations of the business logic. Rule-based approaches are considered an alternative, which offers more flexibility thanks to the declarative nature of rules and their underlying reasoning algorithms. However, modeling a business process through rules is a tedious process for developers in terms of the overall business process comprehension. In this paper, we propose a hybrid solution – a modeling language that integrates both rule- and process-oriented modeling perspectives. The language (Rule-based BPMN –rBPMN) is based on the integration of the Business Process Modeling Notation with the REWERSE Rule Markup Language. In this paper, after introducing rBPMN, we report on the experience in modeling of Service-Oriented Architectures (SOA) from the perspective of message exchange patterns.
http://dx.doi.org/10.1109/EDOC.2009.12
The Ontology-based Business Architecture Engineering FrameworkDmitry Kudryavtsev
Business architecture became a well-known tool for business transformations. According to a recent study by Forrester, 50 percent of the companies polled claimed to have an active business architecture initiative, whereas 20 percent were planning to engage in business architecture work in the near future. However, despite the high interest in BA, there is not yet a common understanding of the main concepts. There is a lack for the business architecture framework which provides a complete metamodel, suggests methodology for business architecture development and enables tool support for it. The ORGMaster framework is designed to solve this problem using the ontology as a core of the metamodel. This paper describes the ORG-Master framework, its implementation and dissemination.
the presentation was given within the SOMET 2011 conference: http://www.somet.soft.iwate-pu.ac.jp/somet_11/
see the text in proceedings here: http://www.booksonline.iospress.nl/Content/View.aspx?piid=21454
Kudryavtsev, D., & Grigoriev, L. (2011). The ontology-based business architecture engineering framework. In proceedings of the 10th International Conference on Intelligent Software Methodologies, Tools and Techniques (SOMET), September 28-30, 2011, Saint-Petersburg, Russia. P. 233-252.
Requirements management and traceability for IIBALeslie Munday
This presentation, created for the Seattle chapter of the International Institute of Business Analysts, describes my experienes with managing requirements traceability.
Software Requirements and Specificationsvustudent1
CS510 - SRS handouts for Computer Science students of Virtual University of Pakistan.
Prepared by ForumVU.com Staff from the updated lectures and PowerPoint slides of CS510 - Software Requirements and Specifications in VU LMS.
Towards a Language for Rule-enhanced Business Process Modeling Dragan Gasevic
Presentation of the EDOC 2009 paper:
Business process modeling is a commonly used approach in the development of service-oriented architectures. The previous research on this topic demonstrated that process-oriented models might be too rigid for dynamic adaptations of the business logic. Rule-based approaches are considered an alternative, which offers more flexibility thanks to the declarative nature of rules and their underlying reasoning algorithms. However, modeling a business process through rules is a tedious process for developers in terms of the overall business process comprehension. In this paper, we propose a hybrid solution – a modeling language that integrates both rule- and process-oriented modeling perspectives. The language (Rule-based BPMN –rBPMN) is based on the integration of the Business Process Modeling Notation with the REWERSE Rule Markup Language. In this paper, after introducing rBPMN, we report on the experience in modeling of Service-Oriented Architectures (SOA) from the perspective of message exchange patterns.
http://dx.doi.org/10.1109/EDOC.2009.12
The Ontology-based Business Architecture Engineering FrameworkDmitry Kudryavtsev
Business architecture became a well-known tool for business transformations. According to a recent study by Forrester, 50 percent of the companies polled claimed to have an active business architecture initiative, whereas 20 percent were planning to engage in business architecture work in the near future. However, despite the high interest in BA, there is not yet a common understanding of the main concepts. There is a lack for the business architecture framework which provides a complete metamodel, suggests methodology for business architecture development and enables tool support for it. The ORGMaster framework is designed to solve this problem using the ontology as a core of the metamodel. This paper describes the ORG-Master framework, its implementation and dissemination.
the presentation was given within the SOMET 2011 conference: http://www.somet.soft.iwate-pu.ac.jp/somet_11/
see the text in proceedings here: http://www.booksonline.iospress.nl/Content/View.aspx?piid=21454
Kudryavtsev, D., & Grigoriev, L. (2011). The ontology-based business architecture engineering framework. In proceedings of the 10th International Conference on Intelligent Software Methodologies, Tools and Techniques (SOMET), September 28-30, 2011, Saint-Petersburg, Russia. P. 233-252.
MBSE Training Crash Course covers all the principals, theories, and techniques associated with Model-based Systems Engineering (MBSE). Model-based systems engineering (MBSE) is the formal use of modeling to provide system requirements, design, analysis, and verification and validation activities. Such activities initiate in the conceptual design stage and continue throughout development and later life cycle phases.
#MBSE Goals
Improved communications
With stakeholders
Within the engineering project teams
Across spoken language barriers
Improved quality
Early identification of requirements issues
Enhanced system design integrity
Improved specification of allocated requirements to hardware and software
Fewer errors during integration and testing
More rigorous requirements traceability
Consistent documentation
Increased productivity
#Audience
MBSE training crash course is a 4-day training designed for:
Product manager
Project director
R and D manager
Engineering manager
Systems engineer
Capability developer
Business analyst
Systems analyst
System architect
Enterprise architect
Software systems engineer
Software engineer
Design engineer
Hardware engineer
Project engineer
LSA specialist
Industrial engineer
#Training Objectives
Upon completion of MBSE training crash course, the attendees are able to:
Comprehend the general principals of systems engineering
Discuss the main characteristic of a system
Understand the overall process factors, and their relationships, which together establish the bases of systems engineering
Relate the roles of developer as supplier, developer as creator and developer as acquirer, and to position their own roles, and those of their customers (internal and external) and suppliers (internal and external) within this framework
Perform the fundamentals of some of the more important techniques of system requirements analysis, development of physical solution, development of logical solution, evaluation of solution alternatives (trade-off studies) and design iteration
Discuss the principles and major techniques of engineering management in a systems project context
Learn more about MBSE Training
https://www.tonex.com/training-courses/mbse-training-crash-course/
DESIGN AND DEVELOPMENT OF BUSINESS RULES MANAGEMENT SYSTEM (BRMS) USING ATLAN...ijcsit
Nowadays, in the world of industry end-users of business rules inside huge or small companies claims that
it’s so hard to understand the rules either because they are hand written by a specific structural or
procedural languages used only inside their organizations or because they require a certain understanding
of the back-end process. As a result, a high need for a better management system that is easy to use, easy to
maintain during the evolution process has increased. In this paper, the emphasis is put on building a
business rule management system (BRMS) as a graphical editor for editing the models in a flexible agile
manner with the assistant of ATL and Sirius frameworks within Eclipse platform. Thus, the proposed
solution, on one hand, solves the problem of wasting resources dedicated for updating the rules and on the
other hand it guarantees a great visibility and reusability of the rules.
A Topic Model of Analytics Job Adverts (The Operational Research Society 55th...Michael Mortenson
This presentation presents recent research into definitions of analytics through analysis of related job adverts. The results help us identify a new categorisation of analytics methodologies, and discusses the implications for the operational research community.
A Topic Model of Analytics Job Adverts (Operational Research Society Annual C...Michael Mortenson
This presentation presents recent research into definitions of analytics through analysis of related job adverts. The results help us identify a new categorisation of analytics methodologies, and discusses the implications for the operational research community.
Technological Hpothesis Research Plan In The CRM Future1Ram Srivastava
We studied some of following technology hypothetical research model/framework for CRM technology research
Technology Acceptance Model (TAM)
Task-Technology Fit Models (TTF)
Computer Self-Efficacy (CSE)
We are finding that Technology Acceptance Model (TAM) is the simple and would be appropriate for CRM technology research
This presentation was given by Professor June Sung Park in Korea Advanced Institute of Science and Technology, Chairman of SEMAT Executive Committee, in the Essence Information Day held in OMG Technical Meeting in Berlin, Germany on June 20, 2013.
The presentation illustrates how one can standardize and integrate a variety of software engineering methods used in an enterprise by expressing all practices and methods in terms of the Essence kernel.
Using a kmerp framework to enhance enterprise resource planning (erp) impleme...Dr. Hamdan Al-Sabri
Using a KMERP Framework to Enhance Enterprise Resource Planning (ERP) Implementation:
Abstract
Introduction
Background and Related Work
The Methodology for ERP Implementation with KM
Benefits of ERP systems
Most reasons for failure the ERP
The Methodology for KM Implementation
The relationship between KM and ERP
The knowledge challenges in ERP implementation
Motivation for develop KMERP Framework,
The proposed Framework
Implementation KMERP Framework on ERP
Type of knowledge required to manage ERP
Conclusions and further work
Development of E-government: a STOPE view:
Uses STOPE-based development (Strategy / Technology / Organization / People /Environment) to examine and contribute the transition.
Uses TQM and BRB and six sigma to maximize the benefits.
E government an analysis of the present and suggestions for the futureDr. Hamdan Al-Sabri
E-Government an Analysis of the present and suggestions for the future:
E-Government, has significantly contributed to the quality governance and, more importantly, has emerged as an efficient and effective quality tool for the people.
P2P collaboration systems: Peer-to-peer (P2P) systems inherently support redundancy, scalability, fault tolerance, and load balancing P2P systems support these features at a lower cost than client/server systems.
In a P2P collaboration system, users share the resources necessary to host and distribute articles that can be modified by any other user such as Wikipedia.
Data warehouse systems adopt a multidimensional data model tackling the challenges of the online analytical processing (OLAP).
Standard data warehouse systems do not provide methodological guidelines for managing heterogeneous dimensions.
In relational OLAP systems, multidimensional views of data, or data cubes, are structured using a star or a snowflake schema consisting of fact tables and dimension hierarchies.
Decision support systems: An interactive computer-based system that helps decision makers in the solution of semi-structured and unstructured problems.
Decision Support Systems
Decision Making
Type of Decision-makings
Phases of Decision Making
Decision Support Framework
Components of DSS
Types of DSS
Information systems:
Information System is a framework in which the coordination between human resources and material resources to transform inputs into outputs (information).
Exploratory data analysis data visualization:
Exploratory Data Analysis (EDA) is an approach/philosophy for data analysis that employs a variety of techniques (mostly graphical) to
Maximize insight into a data set.
Uncover underlying structure.
Extract important variables.
Detect outliers and anomalies.
Test underlying assumptions.
Develop parsimonious models.
Determine optimal factor settings
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
Multimedia networking:
Multimedia
Characteristics of multimedia
Components of Interactive Multimedia
Multimedia Classification
Multimedia Requirements
Multimedia Applications
Networked Multimedia
Challenges of multimedia networking
Major Components of Multimedia Networking
Technologies of Multimedia Networking
MM Networking Applications
Multimedia &Protocols :TCP vs. UDP
Multimedia Networking Systems
Multimedia on the Internet
Properties of current Internet
Multimedia & Security
Multimedia networking:
The term ‘multimedia’ refers to diverse classes of media employed to represent information.
The term ‘Networked Multimedia’ refers to the transmission and distribution of multimedia information on the network
SOA platform for a ComprehensiveEmergency System (CES):
Comprehensive Emergency System(CES) is a comprehensive platform to link hospitals, ambulances, and operator by transferring patient data and electronic health record in addition to location by GPS.
we need to use SOA approach to integrate all applications based on web services and Mobile web services.
At the end of this project, we are supposed to have SOA platform for CES.
التعريف بنظام قاعدة الإنتاج العلمي
الرؤية والرسالة
الأهداف
إطار النظام
اللجنة الإشرافية
الوحدات الإدارية للنظام
إجراءات عمل النظام
التعامل مع نظام قاعدة الإنتاج العلمي (الباحث)
الباحث، رئيس القسم، عميد الكلية، ممثل عمادة البحث العلمي
التعامل مع نظام قاعدة الإنتاج العلمي (طلاب الدراسات العليا)
الطالب، ممثل عمادة الدراسات العليا، ممثل عمادة البحث العلمي
سجل الإنتاج العلمي قواعد البيانات الشهيرة- الحقيبة التدريبيةDr. Hamdan Al-Sabri
المقدمة
أهمية سجل الإنتاج العلمي
وسائل توثيق سجل الإنتاج العلمي
نظام قاعدة الإنتاج العلمي
إدارة سجل الإنتاج العلمي بإستخدام الباحث العلمي Google Scholar))
الشبكات الإجتماعية الأكاديمية: ResearchGate) (Academia.edu) )
إدارة سجل الإنتاج العلمي بإستخدام موقع هوية الباحث ReseachID))
إدارة سجل الإنتاج العلمي بإستخدام موقع هوية الباحث ReseachID))
الموقع الرسمي الخاص بعضو هيئة التدريس ومن في حكمهم
كيفية التأكد من ان المجلة ضمن قواعد بيانات (WoK)
كيفية التأكد من ان البحث ضمن قواعد بيانات (WoK)
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Model driven requirements engineering in the context of erp implementation
1. Model-Driven Requirements Engineering in the Context
of ERP Implementation
Presented by: Dr. Hamdan M. Al-Sabri
College of Computer and Information Sciences
Information Systems Department
2. Outlines
Introduction
Definition of Concepts
Knowledge Gap
Research Questions &Objectives
Scope of the Thesis
The Proposed Solutions:
Analysis of the ERP Reference Models (RMs) (O1)
Developing a new framework (LORS) for building
the Enterprise Model (EM) (O2)
Developing a Structure Approach (SEAC) for Model
Matching (O3)
Conclusion &Future Work
2017
by, Dr. Hamdan M. Al-Sabri
3. Introduction
A paradigm shift to COTS (ERP)
The trade-off of the COTS
Enterprises COTS (ERP)
Paradigm shift
Business/IT Alignment Problem
ERP
Functionality
Enterprises'
Structure
Gap
How can we specify the gap and take
right actions to bridge these gap?
Black-box
functionality
Limited
customization
and testing
Implementation
Challenges
Dependence on
the vendor
Cost (-)
Development
Effort (-)
Developme
nt Time (-)
System
Stability (+)
Product
Maturity (+)
Multiple
Vendors (+)
Well-Tested
(+)
2017
by, Dr. Hamdan M. Al-Sabri
4. Definition of Concepts (ERP)
Enterprise Resource Planning (ERP)
The ERP Package Levels
The ERP Implementation Approaches
Obstacles to ERP Implementation
Literature Review
Concept
Definition
Knowledge
Gap
Theoretical
Framework
Modules
Components (BP)
Functionality
Data
ERP
Package
Change IT package
ERP Imp.
approaches
IT-
driven
Process
-driven
Hybrid
Change Enterprise
Change both
(IT & Enterprise)
Obstacles to
ERP
Implementation
Difficult to
understa.
Complex
Design
Risk
Costly
Difficult to
modify
Gap
between
Enterprise
&ERP
Failure to
define the
requirem.
Accelerates the imp. (+)
Reduces cost main. (+)
Provides a high-quality (+)
Bug-free solution
Best Practice (+)
Upgrade (+)
Increase cost (-)
Increase time (-)
Testing problems (-)
Lose best practice (-)
Upgrade expenses (-)
( + )
( - )
2017
by, Dr. Hamdan M. Al-Sabri
5. Definition of Concepts (RE)
Requirements Engineering (RE)
Literature Review
Concept
Definition
Knowledge
Gap
Theoretical
Framework
Requirements Engineering (RE)
Traditional RECOTS RE
IT-driven Imp.
Approach
Process-driven
Imp. Approach
Hybrid-driven
Imp. Approach
ProductProcess
Elicitation Analysis Specification Validation Management
Requirement Development Requirement Management
Functional Requirements None-Functional Requirements
- Cost
- Marketing
- Organization
- Distribution
- Documentation
2017
by, Dr. Hamdan M. Al-Sabri
6. Definition of Concepts (RM)
Reference Models (RMs)
Purposes &advantages of the RMs
Reference Model Classification
ERP-Specific Reference Models
Advantages of the RMs
Cost reduction
Quality improvement
Time reduction
Risk reduction
Basis for benchmarking
Purposes of the RMs
Software selection
Software development
Software implementation
Documenting and improving BPs
User training and education
RMs
Classifi.
Industry
RMs
Procedural
RMs
Software
RMs
Enterprise
RMs
Business process RM
Function RM
System organization RM
Data RM
Literature Review
Concept
Definition
Knowledge
Gap
Theoretical
Framework
2017
by, Dr. Hamdan M. Al-Sabri
7. Definition of Concepts (MM)
Mode Matching (MM)
Literature Review
Concept
Definition
Knowledge
Gap
Theoretical
Framework
MM Algorithms (Similarity Functions)
Model Mapping
Diagram VS Model Semantics
Comparing two models
Model 1 Model 2
•Lexical Matching (String,
Semantic SFs)
•Structural Matching SFs
•Behavioral Matching SFs
Model Mapping
Model 1 Model 2
(1,1) Correspondence
(1,0) Correspondence
(0,1) Correspondence
Diagram Model Semantics
2017
by, Dr. Hamdan M. Al-Sabri
8. Knowledge Gap
Literature Review
Concept
Definition
Knowledge
Gap
Theoretical
Framework
Business/ IT alignment Problem (ERP, Enterprise)
Process-driven Hybrid
Solve Problem by using RM & Model Matching
IT-driven
Advantages &disadvantage of the implementation approaches (LR)
1999 2001 2003 2005 2007 2009 2011 2013 2015
Rolland
2016
Zoukar
StembergerSoffer
Juntao
Aversano
Ling
Millet
Pajk
Panayiotou
Process-driven
Hybrid
1. Neglect the IT-driven imp. approach.
2. Using different levels of model abstraction during MM.
3. Model matching based on human reasoning (experts& users).
4. High level comparison by using goals & strategies.
5. Not evaluating the approaches or frameworks.
6. Specifying the gaps without bridging them.
2017
1. Focus on IT-driven Approach.
2. Specifying the suitable abstraction level (RMs).
3. Automated matching (new structure approach).
4. Specifying the gaps with bridging them.
by, Dr. Hamdan M. Al-Sabri
9. Research Questions &Objectives
Objective 1
Analysis the ERP reference models to determine a suitable level and
the critical factors that assists in the model-matching process to
determine the areas of change in the enterprise.
Literature Review
Concept
Definition
Knowledge
Gap
Theoretical
Framework
Research Question 1
RQ1: What is an appropriate ERP reference model for specifying
enterprise areas of change in the context of IT-driven ERP
implementation and through the model matching?
1. In the context of IT-driven ERP Implementation
2. In the context of Model Matching
Business process RM
Function RM
System organization RM
Data RM
How can we specify the enterprise areas of change in the
context of model matching and IT-driven imp. approach?
2017
by, Dr. Hamdan M. Al-Sabri
10. Research Questions &Objectives…
Objective 2
Developing a framework for building the enterprise model that
compared with ERP reference models.
Literature Review
Concept
Definition
Knowledge
Gap
Theoretical
Framework
Research Question 2
RQ2: How to systematically gather information regarding
enterprise as-is business process requirements in an informal
environment and by non-expert users?
ERP Reference Model
(RM)
Enterprise Model
(EM)
2017
by, Dr. Hamdan M. Al-Sabri
11. Research Questions &Objectives…
Objective 3
Developing a structural approach that includes a model-matching
techniques to measure the similarity between the enterprise model
and the ERP reference model.
Literature Review
Concept
Definition
Knowledge
Gap
Theoretical
Framework
Research Question 3
RQ3: What are the techniques (similarity functions) and strategies
used to measure model matching?
RM EM
Model Matching Structural Approach
Generate 4 Reports2017
by, Dr. Hamdan M. Al-Sabri
12. Scope of the Thesis
Solve Business/IT Alignment Problem
COTS RE/ ERP Imp. Approaches
Types of the RMs
Model Matching Application Domain
Literature Review
Concept
Definition
Knowledge
Gap
Theoretical
Framework
IT (ERP) Business
Gap
Bridge the Gap by take advantage RM & MM
IT-Driven Approach
BP-Driven Approach
Hybrid Approach
Industry RM
Software RM
Procedural RM
Company RM
ERP-Specific RM
Web Service Discovery
and Integration
Retrieving Scientific
Workflows
Retrieving Business
Processes in Repository
Autocompletion
Mechanism for Modeling
Processes
Delta Analysis/ Assure
compliance
Facilitate Reuse
Simplify changes
Merge processes
Automate Execution
Version Management
Model
Matching
between RMs
and EMs
2017
by, Dr. Hamdan M. Al-Sabri
13. Objective 1: Analysis of the ERP Reference Models (RMs)
Problem Solving
Objective 1 Objective 2 Objective 3
(OMG) BPMN IMWG
Representation (XML)
Process Models
Exists
Process Models
Not Exists
Enterprise
Process Models
Developing As-Is Process by User-
Centered LORS Framework
Using
Using
ERP RM
Representation
ERP vendor Terminology
Objective
2
Objective
1
Business process RM
Function RM
System organ. RM
Data RM2017
by, Dr. Hamdan M. Al-Sabri
14. Research Methodology (O1)
Problem Solving
Objective 1 Objective 2 Objective 3
Modules
Components
Functionality
Goal of the Selection
Alternatives of the Selection
Main Criteria for Comparison
ERP Levels
Reference
Models (RM)
Understand the key concepts and principles
Investigate the business engineering by using the
reference models
Review the academic literature on reference
models comparison criteria
Study and analyze the ERP reference model types
(alternatives)
Apply decision making technique (AHP) to select
an appropriate ERP reference model
Literature Review (search in the popular scientific
database and ERP vendor website)
Present results (select an appropriate ERP
reference model using AHP)
1
2
3
4
5
6
7
System Organizational RM
Business Process RM
Function RM
Data/Objects RM
2017
by, Dr. Hamdan M. Al-Sabri
15. Criteria for Comparing Reference Models
Problem Solving
Objective 1 Objective 2 Objective 3
Evaluation criteria Reference Evaluation criteria Reference
Model Scope
(Rosemann and
van der Aalst,
2007)
Completeness
(Fettke and Loos, 2003,
Sadowska, 2015)
Model Granularity Precision
Model Views Consistency
Model Integration degree Extensibility
Model purposes User-friendliness
Model Use Economic efficiency
Model Availability Syntactic Criteria (Van Belle, 2006,
Overhage et al., 2012)Model Explanation Semantic Criteria
Model Alternative Pragmatic Criteria
Model Guidelines Model Size
(Mendling et al., 2006a)
Model Benchmarking Model Complexity
Model General Characteristics
(Fettke et al.,
2006)
Model Error Patterns
Model Constructions
Model Application
2017
by, Dr. Hamdan M. Al-Sabri
16. Apply AHP technique to select an appropriate
ERP RM (Step 1)
Problem Solving
Objective 1 Objective 2 Objective 3
Goal Criteria Alternatives
Select a suitable
ERP RMs
C1: Model Scope
C2: Model Abstraction
C3: Model Granularity
C4: Model Views
C5: Model Purpose
C6: Model Simplicity
C7: Model Availability
C8: Ease of Use for
Model Matching
C9: Model Target
Audience
System Org. RM
Business Process RM
Function RM
Data/Objects RM
1
2017
by, Dr. Hamdan M. Al-Sabri
17. Pairwise comparison of main criteria in the
context of ERP RM evaluation (Step 2)
Problem Solving
Objective 1 Objective 2 Objective 3
# Criteria to be
compared
Priorities
assigned
# Criteria to be
compared
Priorities
assigned
# Criteria to be
compared
Priorities assigned
1 C1 vs. C2 2:1 13 C2 vs. C7 4:1 25 C4 vs. C8 1:3
2 C1 vs. C3 3:1 14 C2 vs. C8 1:5 26 C4 vs. C9 2:1
3 C1 vs. C4 1:1 15 C2 vs. C9 3:1 27 C5 vs. C6 1:2
4 C1 vs. C5 1:2 16 C3 vs. C4 1:1 28 C5 vs. C7 3:1
5 C1 vs. C6 1:4 17 C3 vs. C5 1:2 29 C5 vs. C8 1:2
6 C1 vs. C7 5:1 18 C3 vs. C6 1:4 30 C5 vs. C9 3:1
7 C1 vs. C8 1:3 19 C3 vs. C7 3:1 31 C6 vs. C7 7:1
8 C1 vs. C9 4:1 20 C3 vs. C8 1:6 32 C6 vs. C8 2:1
9 C2 vs. C3 2:1 21 C3 vs. C9 3:1 33 C6 vs. C9 4:1
10 C2 vs. C4 1:2 22 C4 vs. C5 1:3 34 C7 vs. C8 1:4
11 C2 vs. C5 1:3 23 C4 vs. C6 1:4 35 C7 vs. C9 1:2
12 C2 vs. C6 1:5 24 C4 vs. C7 3:1 36 C8 vs. C9 4:1
Legend:
Criteria Priorities:
1: equal importance, 2: weak importance, 3: moderate importance, 4: moderate importance plus, 5: strong
importance, 6: strong importance plus, 7: very strong importance, 8: very strong importance plus, 9: extreme
importance.
# Main Criteria Weight
C1 Model Scope 0.086
C2 Model Abstraction 0.058
C3 Model Granularity 0.060
C4 Model Views 0.071
C5 Model Purpose 0.137
C6 Model Simplicity 0.299
C7 Model Availability 0.036
C8 Ease of Use for Model Matching 0.204
C9 Model Target Audience 0.049
2
4
3 Consistency Ratio (CR) = 0.06
2017
by, Dr. Hamdan M. Al-Sabri
18. Evaluation of the ERP Reference Models
Problem Solving
Objective 1 Objective 2 Objective 3
Business Process RM Function RM System Org. RM Data/Objects RM
C1 0.0283 0.0232 0.0238 0.0107
C2 0.0206 0.0134 0.0175 0.0066
C3 0.0212 0.0142 0.0179 0.0066
C4 0.023 0.0185 0.0202 0.0091
C5 0.045 0.0374 0.0189 0.0355
C6 0.0865 0.0749 0.0846 0.0529
C7 0.0098 0.0099 0.0061 0.0099
C8 0.0596 0.0489 0.0536 0.0417
C9 0.0132 0.0125 0.0112 0.0119
0.0283
0.0232
0.0238
0.0107
0.0206
0.0134
0.0175
0.0066
0.0212
0.0142
0.0179
0.0066
0.023
0.0185
0.0202
0.0091
0.045
0.0374
0.0189
0.0355
0.0865
0.0749
0.0846
0.0529
0.0098
0.0099
0.0061
0.0099
0.0596
0.0489
0.0536
0.0417
0.0132
0.0125
0.0112
0.0119
Evaluation of the ERP Reference Models
C1 C2 C3 C4 C5 C6 C7 C8 C9
0.3072 0.2529 0.2538 0.1849
The final ranking of alternatives based on all criteria (C1-C9)
1 3 2 4
5
2017
by, Dr. Hamdan M. Al-Sabri
19. Limitations and Implications of the Research
(O1)
Problem Solving
Objective 1 Objective 2 Objective 3
Limitation (O1)
This research is restricted to IT-driven implementation approach.
This research is limited to nine evaluation criteria with more
emphasis on model matching criterion.
Admittedly, balancing the subjective judgment and consistency ratio
was a crucial issue with AHP technique.
Implication (O1)
The research provided valuable insights on the type of RMs and its
relation with implementation approach.
The research could stimulate the vendors to focus on reference
model’s quality that helps a lot at the implementation stage.
2017
by, Dr. Hamdan M. Al-Sabri
21. Objective 2: The LORS Framework for Developing the Enterprise
Model (EM)
Problem Solving
Objective 1 Objective 2 Objective 3
(OMG) BPMN IMWG
Representation (XML)
Process Models
Exists
Process Models
Not Exists
Enterprise
Process Models
Developing As-Is Process by
User-Centered LORS Framework
Using
Using
ERP RM
Representation
ERP vendor Terminology
Objective
2
Objective
1
ERP (RM)
Enterprise
Model (EM)2017
by, Dr. Hamdan M. Al-Sabri
22. Research Methodology (O2)
Problem Solving
Objective 1 Objective 2 Objective 3
Present the LORS Framework
7
Functional Areas (Business units)
Activities
Workflow
Business Rules and Events
Business Process Frameworks
Business Process PrinciplesUnderstand the as-is business process
Explore the business process components
Investigate the vendor's terminology
Review the model refinement processes
Study the BPMN serialization based on BPMN
MIWG formats
Literature Review (search in the popular
scientific databases)
1
2
3
4
5
6
Frameworks
Guidelines
Rules, Styles and methods
Quality Dimensions
2017
by, Dr. Hamdan M. Al-Sabri
23. Important Concepts for Objective 2
Problem Solving
Objective 1 Objective 2 Objective 3
BPMN
Business Process Refinement
BPMN MIWG
2017
by, Dr. Hamdan M. Al-Sabri
24. A LORS (List, Order, Refinement, Serialization)
Framework
Problem Solving
Objective 1 Objective 2 Objective 3
List FAs
List the ACs in
each FA
List the BRs in
each FA
List the EVs in
each FA
Order the FAs Order the ACs in FAs Order the BRs in FAs
Order the EVs in each FAs Link between FAs
List Phase
Refinement (LPR)
Order Phase
Refinement (OPR)
Serialization Phase
Refinement. (SPR)
FAs, ACs, BRs, EVs
Extract the
Elements
Construct the
Model
Semantics
Mapping the
Elements
Generate the
Model
Semantics
PreparationPhase(Optional)
BasedonVendors'Terminology List Phase (L)
Order Phase (O)
Refinement
Phase (R)
Serialization
Phase (S)
FAs
ACs
BRs
EVs
AutomatedManual
Validas-isBPModelSemantics
2017
by, Dr. Hamdan M. Al-Sabri
25. A LORS framework meta-model
Problem Solving
Objective 1 Objective 2 Objective 3
2017
by, Dr. Hamdan M. Al-Sabri
26. Criteria for Evaluating the Frameworks
Problem Solving
Objective 1 Objective 2 Objective 3
Evaluation criteria Reference Evaluation criteria Reference
Strictly (Mentzas et al.,
2001)
Expressibility (Lu and Sadiq,
2007b)Simplicity Adaptability
Complexity Dynamism
Ease of use Flexibility
Managerial implications Complexity
Adequacy (Lam, 2002) Simplicity (Avison and
Fitzgerald, 2003)Flexibility of implementation Flexibility
Supportive Visibility
Simplicity User involvement
Supportive
Evaluation Process
Case Study (Purchase Materials Process)
The framework evaluation process indicates that the LORS
framework is simple, flexible, visible, interactive, and dynamic.
2017
by, Dr. Hamdan M. Al-Sabri
27. Limitations and Implications of the Research
(O2)
Problem Solving
Objective 1 Objective 2 Objective 3
Limitation (O2)
The LORS framework is restricted to the as-is business process
(Process Model/Descriptive Model).
This research is limited to model semantics (model definitions), and
the graphical definition is not addressed in this research because it is
not important in model matching.
Implication (O2)
The LORS framework helps non-expert users to capture as-is BP
without required either modeling experience or development skills.
This research is the cornerstone for further studies in the field of
business process capture or BP- RE.
2017
by, Dr. Hamdan M. Al-Sabri
29. Objective 3: The SEAC (Specifying Enterprise Areas of Change)
Approach for Model Matching
Problem Solving
Objective 1 Objective 2 Objective 3
RM
EM
Matching
RM Semantics
EM Semantics
By
Assigned the Corresp. Type
Functional
Area (FAs)
Activity
(ACs)
Sequence
Flow (WFs)
Connectors
(BRs)
(1 𝑅𝑀−1 𝐸𝑀)
Correspondence
Mapping ↔
(1 𝑅𝑀 − 0 𝐸𝑀)
Correspondence
Add Action
(0 𝑅𝑀 − 1 𝐸𝑀)
Correspondence
Delete Action
(1 𝑅𝑀 − 1 𝐸𝑀)
Correspondence
Move Action
Element Labels Element StructuresElement Types
Partial Mapping
Total Mapping
No Mapping
Objective
3
2017
by, Dr. Hamdan M. Al-Sabri
30. Research Methodology (O3)
Problem Solving
Objective 1 Objective 2 Objective 3
String Similarity Functions
Semantic Similarity Functions
Structural similarity Functions
Binary Similarity Functions
Application Scenario (Case Study)
Evaluate the Results (Measure the
Match Quality)
Analysis the Literature Review
Frameworks, Approaches, Phases, and
elements of matching
Study model matching algorithms
Explore the aggregation of similarity values
strategies
Investigate the select match candidates' values
strategies
Develop the SEAC approach
Evaluate the SEAC approach
Literature Review (search popular scientific
databases)
1
2
3
4
5
6
MaxN, MaxDelta, Threshold, and
Dice coefficient strategy
Max, Weighted, Average, and Min
strategy
Select a suitable aggregation + match
candidates values strategies
Select a suitable string- based similarity
function
Select a suitable semantic- based
similarity function
Design the SEAC reports
2017
by, Dr. Hamdan M. Al-Sabri
31. Strategies of the SEAC Approach
Select a Suitable String-based SF
Select a Suitable Semantic SF
Select a Suitable Aggregation Strategy
Choose Match Candidates Values Str.
Problem Solving
Objective 1 Objective 2 Objective 3
Analyze six string similarity functions:
Levenshtein
Smith-Waterman
Jaro
Jaro–Winkler
QGrams Distance
Cosine Similarity
Based on six criteria :
Loss of insignificant words
Small changes
Rearrangement of words
Punctuation
Case
Spacing
SSF/Criteria Loss
of ins.
word
Small
changes
Rearrang.
of words
Punctua. Case Spacing Average
Jaro-
Winkler
High Very
High
Very bad Very
high
Low High 73%
Semantic similarity algorithms:
Corpus-based
Knowledge-based
Wu & Palmer’s + WordNet
There are four aggregation strategy :
Weighted Max Average Min
There are four Strategies for selecting match
candidates values :
MaxDelta MaxN Threshold Dice coefficient
2017
by, Dr. Hamdan M. Al-Sabri
32. The SEAC Approach
Problem Solving
Objective 1 Objective 2 Objective 3
Outputs of SEAC Approach: Generate the Reports
Report 1: Enterprise Adoption Readiness Assessment Report
(EARAR)
Report 2: Enterprise Areas of Change Report (EACR)
Report 3: Similarity Percentage Report (SPR) Report 4: Gap Percentage Report (GPR)
Phase 2: Measure the Similarity among FAs
Step 2.1: Calculate the Jaro–Winkler
similarity (string similarity matrix)
Step 2.2: Calculate Wu & Palmer similarity
(semantic similarity matrix)
Step 2.3: Aggregate two
matrices (max strategy)
Step 2.4: Select the matching candidates
(MaxN, and threshold Strategies)
Step 2.5: Mapping and specify the action (Add,
Delete, and Move strategies)
Step 2.6: Calculate the
overall similarity of FAs
Phase 1: Preprocessing
Step 1.1: Extract the elements' labels
from model semantics
Step 1.2: Process the elements' labels
Step 1.3: Store elements' labels in
arrays
Phase 3: Measure the Similarity of BP Structure
Step 3.1: Establish an adjacency matrix of 𝐹𝐴 𝑅𝑀 and 𝐹𝐴 𝐸𝑀 Step 3.2: Calculate the binary similarity (Jaccard)
Phase 4: Measure the Similarity among FAs' elements ((1-1) correspondences)
Step 4.1: Calculate similarity among functional area
activities (such as steps in Phase 2: 2.1 – 2.5)
Step 4.2: Calculate similarity among functional area
business rules (such as steps in Phase 2: 2.1 – 2.5)
Step 4.1.1: Calculate the overall
similarity obtained in Step 4.1
(Average)
Step 4.2.1: Calculate the overall
similarity obtained in Step 4.2
(Average)
Step 2.3: Calculate the
overall similarity of 𝐹𝐴 𝐴𝐶𝑠
and 𝐹𝐴 𝐵𝑅𝑠
Reference Models (RMs) (Model
Semantics)
Enterprise Models (EMs) (Model
Semantics)
ProcessInputsOutputs
Inputs: Model Semantics
(RM, EM)
Phase 1: Preprocessing
Phase 2: Measure the Similarity
among FAs Phase 3: Measure the Similarity of
BP Structure
Phase 4: Measure the Similarity among FAs'
elements ((1-1) correspondences)
Outputs: Generate the
Reports
2017
by, Dr. Hamdan M. Al-Sabri
33. Application Scenario and Discussion
Problem Solving
Objective 1 Objective 2 Objective 3
Model Semantics (EM)
Model Semantics (RM)
2017
by, Dr. Hamdan M. Al-Sabri
34. Phase 1: Preprocessing
Problem Solving
Objective 1 Objective 2 Objective 3
Encoding Elements(RM)
Encoding Elements(RM)
RM FAs Labels
Sym. Elem. Label Prepro.
FR1 Warehouse -
FR2 Purchasing -
FR3 Accounting -
EM FAs Labels
Sym. Element Label Prepro.
FE1 Budget planning -
FE2 Store -
FE3 Buying -
FE4 Account -
2017
by, Dr. Hamdan M. Al-Sabri
36. Problem Solving
Objective 1 Objective 2 Objective 3
Elements of RM
Phase 3: Measure the Similarity of BP Structure
Step 3.2
2017
Elements of EM
Step 3.1
Phase 3
by, Dr. Hamdan M. Al-Sabri
37. Phase 4: Measure the Similarity among FAs'
elements ((1-1) correspondences)
Problem Solving
Objective 1 Objective 2 Objective 3
Phase 4
Phase 1
Step 4.2
Step 4.1
Step 2.4
Step 4.3
Step 4.6
Step 4.5
2017
by, Dr. Hamdan M. Al-Sabri
38. Outputs of SEAC Approach: Generate the
Reports
Problem Solving
Objective 1 Objective 2 Objective 3
1
2
3
4
2017
by, Dr. Hamdan M. Al-Sabri
39. Measures of Match Quality
Automatic matching 𝐴 𝑚 VS Real matching 𝑅 𝑚
Problem Solving
Objective 1 Objective 2 Objective 3
Using: Precision, Recall, and F-measure
Results
2017
by, Dr. Hamdan M. Al-Sabri
40. Limitations and Implications of the Research
(O3)
Problem Solving
Objective 1 Objective 2 Objective 3
Limitation (O3)
This research was limited to process matching between RM and EM
(delta analysis or assured compliance) in the context of IT-driven
implementation.
The current investigation was limited by (1-1) mapping, where one
RM corresponded with an EM.
Implication (O3)
On the practical side, it can help reduce the effort, time, and cost
needed for COTS (ERP) implementation.
Predefining the enterprise areas of change could help in change
management and user satisfaction.
On the commercial side, these findings could help vendors
understand enterprise readiness, select the appropriate
implementation strategies.
2017
by, Dr. Hamdan M. Al-Sabri
42. Conclusion
RM and Enterprise Systems
Business Process RE (LORS Framework)
Model Matching (SEAC Approach(
Conclusion
Objective 1 Objective 2 Objective 3
2017
by, Dr. Hamdan M. Al-Sabri
43. Future Work
Specifying the IT infrastructure using RMs
BP Refinement process
Explore complex mappings (N-M)
Estimate the budget, time, and cost by MM
Future Work
Objective 1 Objective 2 Objective 3
2017
by, Dr. Hamdan M. Al-Sabri