Model-Driven ERP Requirements Engineering

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

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

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

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

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

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

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
Diagram Model Semantics
2017

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.

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

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

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

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

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

Research Methodology (O1)
Problem Solving
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

Criteria for Comparing Reference Models
Problem Solving
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

Apply AHP technique to select an appropriate
ERP RM (Step 1)
Problem Solving
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

Pairwise comparison of main criteria in the
context of ERP RM evaluation (Step 2)
Problem Solving
# 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

Evaluation of the ERP Reference Models
Problem Solving
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

Limitations and Implications of the Research
(O1)
Problem Solving
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

2017

Objective 2: The LORS Framework for Developing the Enterprise
Model (EM)
Problem Solving
(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

Problem Solving
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

Important Concepts for Objective 2
Problem Solving
BPMN
Business Process Refinement
BPMN MIWG
2017

A LORS (List, Order, Refinement, Serialization)
Framework
Problem Solving
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

A LORS framework meta-model
Problem Solving
2017

Criteria for Evaluating the Frameworks
Problem Solving
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

(O2)
Problem Solving
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

Objective 3: The SEAC (Specifying Enterprise Areas of Change)
Approach for Model Matching
Problem Solving
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

Problem Solving
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

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
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

The SEAC Approach
Problem Solving
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 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

Application Scenario and Discussion
Problem Solving
Model Semantics (EM)
Model Semantics (RM)
2017

Problem Solving
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

Phase 2: Measure the Similarity of FAs
Problem Solving
Phase 1
Step 2.3
Step 2.1
Phase 2
Step 2.2
Step 2.4
Step 2.6
Step 2.5
𝑆𝑖𝑚 𝑂𝑣𝑒𝑟𝑎𝑙𝑙 𝐹𝐴 𝑅𝑀, 𝐹𝐴 𝐸𝑀 =
2∗# 1↔1 FA correspondences
# 𝐹𝐴 𝑅𝑀+# 𝐹𝐴 𝐸𝑀
=
2∗3
3+4
= 0.86%
(RM FAs)
(RM FAs)Mapping
2017

Problem Solving
Elements of RM
Phase 3: Measure the Similarity of BP Structure
Step 3.2
2017
Elements of EM
Step 3.1
Phase 3

Phase 4: Measure the Similarity among FAs'
elements ((1-1) correspondences)
Problem Solving
Phase 4
Phase 1
Step 4.2
Step 4.1
Step 2.4
Step 4.3
Step 4.6
Step 4.5
2017

Outputs of SEAC Approach: Generate the
Reports
Problem Solving
1
2
3
4
2017

Measures of Match Quality
Automatic matching 𝐴 𝑚 VS Real matching 𝑅 𝑚
Problem Solving
Using: Precision, Recall, and F-measure
Results
2017

(O3)
Problem Solving
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

Conclusion
RM and Enterprise Systems
Business Process RE (LORS Framework)
Model Matching (SEAC Approach(
Conclusion
2017

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
2017

Model-Driven ERP Requirements Engineering

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