Enterprise Architecture Alignment

108 Pages·2017·3.03 MB·English

Enterprise Architecture Alignment
Monitoring integration with a formal rule model

Programme: Open University of the Netherlands, faculty of Management, Science &
Technology
Master Business Process Management & IT

Course: IM9806 Afstudeertraject Business Process Management and IT

Student: Peter Filet
Identity number: 835281659
Date: June 4th, 2017
Mentor: dr. Rogier van de Wetering
Examiner: prof. dr. ir. Stef Joosten
Version number: 1.0
Status: Final
Abstract
Enterprise Architecture is an instrument that focuses on coherence between business processes,
information distribution and technology infrastructure of an organization. In practice, the
interrelationship between architectural aspects is not always dealt with in an integrated fashion.
Enterprise Architecture frameworks are mostly informal by nature and there is a lack of knowledge
and tools to support architects to check alignment in a formal manner. Due to volume and
complexity of holistic enterprise spanning architecture, it is increasingly challenging for organizations
to maintain overview and coherence of architectural elements. This research enables automated
rule-based monitoring consistency and coherence between elements within an EA. It does so by
creating an artifact that provides architects with the capability of monitoring validity within
ArchiMate EA models. The models are validated against formalized rules that are specified in
Relation Algebra with which coherence can be mathematically proven. The set of applied rules is
plotted onto a quality framework that calculates overall alignment of an EA model. Overall
alignment calculation of the researched cases show an overall alignment score varying from 47,53%
to 77,27%. Every single rule violation that influences the score is identified specifically. Monitoring
EA quality using formalized rules enables organizations to manage and control the process of EA
change and thus contributes to Business/IT-alignment.

Keywords

Enterprise Architecture, Business/IT-alignment, Ampersand, Formalized rules, Relation Algebra

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Summary
Considering the last few decades, organizations are increasingly served by, and even dependent on,
effective and efficient use of Information Systems and Information Technology (IS/IT). It is not
surprising that within many organizations an (IT) executive-level understanding of Business/IT-
alignment (also called alignment) is evolving and the topic gains priority on the executive agenda.
Enterprise Architecture is an instrument that focuses on coherence between the business processes,
information distribution and technology infrastructure of an organization. In practice, the
interrelationship between these different architectural aspects is not always dealt with in an
integrated fashion. Enterprise Architecture frameworks are mostly informal by nature and there is a
lack of knowledge and tools to support architects to check alignment in a formal manner. Due to
volume and complexity of holistic enterprise spanning architecture, it is increasingly challenging for
organizations to maintain overview and coherence of architectural elements covering all aspects of
the enterprise architecture. This statement is applicable for an architecture in the as-is state, but
even more when viewed from the perspective of architecture adaptation to the to-be state.
Studied literature argues that EA strengthens cohesion of business and IT. Many methods,
frameworks and techniques to this end are available, but a closing theory is not found. This is
consistent with what the researchers perceive in their daily practice: architects argue, discuss and
suggest a lot, but provide little to none hard substantiation.
The context of this research is the practice of Enterprise Architects. In order to rise above the usual
practice of "arguing”, we strive for more substantiation. We also look for theory, which is applicable
in practice. We state that tooling is possible that not only aids architects in automating the manual
task that architects need to perform to ensure coherence, but also provides the substantiation.
This research enables automated rule-based monitoring consistency and coherence between
elements within an EA. It does so by creating an artifact that provides architects with the capability
of monitoring validity within ArchiMate EA models. It involves EA models based on the ArchiMate
modeling language. The EA models are validated against formalized rules that are specified in
Relation Algebra with which coherence can be mathematically proven. The set of applied rules is
plotted onto a quality framework that calculates overall alignment of an EA model. Overall
alignment of the researched cases show an overall alignment score varying from 47,53% to 77,27%.
Each overall alignment score is based on an underlying score for quality factors like completeness
and correctness. Every single rule violation that influences the score is identified specifically.
Monitoring EA quality using formalized rules enables organizations to manage and control the
process of EA change and thus contributes to Business/IT-alignment.

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Table of content

Abstract ............................................................................................................................................................ 2
Summary .......................................................................................................................................................... 3
1. Introduction ............................................................................................................................................ 7
1.1. Introduction ................................................................................................................................... 7
1.2. Context ........................................................................................................................................... 8
1.3. Coherent research projects ........................................................................................................ 11
1.4. Relevance ..................................................................................................................................... 12
1.5. Problem statement ...................................................................................................................... 13
1.6. Research objective....................................................................................................................... 14
2. Literature study .................................................................................................................................... 15
2.1. Results and conclusions .............................................................................................................. 15
3. Empirical research objective ............................................................................................................... 22
4. Research method ................................................................................................................................. 23
4.1. Research strategy ........................................................................................................................ 23
4.2. Research approach ...................................................................................................................... 24
4.3. Data collection ............................................................................................................................. 27
4.3.1. EA models ............................................................................................................................ 27
4.3.2. Alignment heuristics ........................................................................................................... 28
4.4. Reliability and validity ................................................................................................................. 29
4.5. Research environment ................................................................................................................ 30
5. Research execution .............................................................................................................................. 32
5.1. Validation of alignment heuristics ............................................................................................. 32
5.2. Translating alignment heuristics to ADL .................................................................................... 33
6. Research results ................................................................................................................................... 36
7. Discussion ............................................................................................................................................. 39
7.1. Model alignment results ............................................................................................................. 39
7.2. Limitations .................................................................................................................................... 41
8. Conclusions and recommendations ................................................................................................... 42
8.1. Conclusion .................................................................................................................................... 42
8.2. Recommendations for further research .................................................................................... 43
9. Reflection .............................................................................................................................................. 44
9.1. Product ......................................................................................................................................... 44
9.2. Process .......................................................................................................................................... 44
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9.3. Lessons learned............................................................................................................................ 45
References ..................................................................................................................................................... 46
Appendix 1 – Literature study approach, execution and detailed results ................................................ 49
Appendix 2 – Description of quality factors and attributes ....................................................................... 53
Appendix 3 – Alignment heuristics .............................................................................................................. 55
Appendix 4 – Ampersand script casus ArchiMetal ..................................................................................... 57
Appendix 5 – Ampersand script casus ArchiSurance ................................................................................. 59
Appendix 6 – Ampersand script casus Belastingdienst (NTCA) ................................................................. 61
Appendix 7 – Ampersand script casus Belastingdienst (NTCA) – meta-model ........................................ 63
Appendix 8 – Ampersand script casus Belastingdienst (NTCA) – rule TV067 .......................................... 72
Appendix 9 – Ampersand script casus Ministerie van Defensie (MOD-NL) ............................................. 73
Appendix 10 – Ampersand script casus Ministerie van Defensie (MOD-NL) – rule TV053 ..................... 75
Appendix 11 – Ampersand script casus Ministerie van Defensie (MOD-NL) – rule TV065 ..................... 76
Appendix 12 – Ampersand script casus Ministerie van Defensie (MOD-NL) – rule TV067 ..................... 78
Appendix 13 – Ampersand script casus OpenDay ...................................................................................... 80
Appendix 14 – Ampersand script casus EIRA .............................................................................................. 82
Appendix 15 – Ampersand script rule TV002 ............................................................................................. 84
Appendix 16 – Ampersand script rule TV008 ............................................................................................. 86
Appendix 17 – Ampersand script rule TV022 ............................................................................................. 88
Appendix 18 – Ampersand script rule TV023 ............................................................................................. 89
Appendix 19 – Ampersand script rule TV027 ............................................................................................. 90
Appendix 20 – Ampersand script rule TV040 ............................................................................................. 92
Appendix 21 – Ampersand script rule TV042 ............................................................................................. 93
Appendix 22 – Ampersand script rule TV043 ............................................................................................. 94
Appendix 23 – Ampersand script rule TV057 ............................................................................................. 95
Appendix 24 – Ampersand script rule TV065 ............................................................................................. 96
Appendix 25 – Rule candidates .................................................................................................................... 97
Appendix 26 – Alignment calculation example ........................................................................................ 104
Appendix 27 – Alignment measurement of case models ........................................................................ 105

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List of tables
Table 1: Effect of quality factors on overall quality (Moody & Shanks, 2003) ....................................... 17
Table 2: Similarity mapping quality factors and attributes ...................................................................... 18
Table 3: Design Science research guidelines (Hevner & Chatterjee, 2010) ............................................ 25
Table 4: Rule translation validation ............................................................................................................ 39

List of figures

Figure 1: Research related to TOGAF ADM and ArchiMate (TOG, 2016) ................................................ 10
Figure 2: Architecture aspects and layers in ArchiMate 3.0 (TOG, 2016) ............................................... 10
Figure 3: Three research projects aiming to support EA coherence using formal methods ................. 12
Figure 4: Research model ............................................................................................................................ 24
Figure 5: Design Science research cycles (Hevner & Chatterjee, 2010) .................................................. 26
Figure 6: Overview of research environment ............................................................................................ 30
Figure 7: Ampersand output example ........................................................................................................ 31
Figure 8: ArchiMate visualization of rule TV065 ........................................................................................ 33
Figure 9: Total relationship .......................................................................................................................... 33
Figure 10: Simplified meta model generated by Ampersand ................................................................... 35
Figure 11: Overview of research cases and rule specifications ................................................................ 35
Figure 12: Alignment measurement result ArchiSurance......................................................................... 36
Figure 13: Overview of violations in ArchiSurance .................................................................................... 37
Figure 14: Detailed view of violations in ArchiSurance (partial) .............................................................. 37
Figure 15: ArchiMate view on Financial Application ................................................................................. 38

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1. Introduction
1.1. Introduction

Considering the last few decades, organizations are increasingly served by, and even dependent on,
effective and efficient use of information systems and information technology (IS/IT). Research
shows that alignment of business and IT (also called alignment) affects organizational performance
(Gerow, Grover, & Thatcher, 2015; Van de Wetering, Mikalef, & Pateli, 2017b). Alignment literature
generally identifies a positive relationship between the degree of alignment and business
performance. However in minority, there are studies that report alignment resulting in non-existent
or negative influence on business performance. This is also referred to as the “alignment paradox”,
wherein a decrease in organization productivity and competitiveness has been detected.
Researchers argue that alignment causes rigidity resulting to stagnation of maneuverability which is
required in response to changes in the business environment (Gerow, Thatcher, & Grover, 2014).
Alignment between business and IT offers value to organizations and contributes to organizational
success (Castellanos & Correal, 2013; Chan & Reich, 2007; Saat, Franke, Lagerstrom, & Ekstedt,
2010). It is not surprising that within many organizations on (IT) executive-level understanding of
Business/IT-alignment is evolving and the topic gains priority on the executive agenda (Gerow et al.,
2015; Gerow et al., 2014; Gregor, Hart, & Martin, 2007; Pereira & Sousa, 2005).

Research is available on the contribution of Enterprise Architecture (from here on referred to as EA)
to Business/IT-alignment. In available literature, EA is generally considered an important instrument
to contribute to Business/IT-alignment (Alaeddini & Salekfard, 2011; Castellanos & Correal, 2013;
Gregor et al., 2007; Kang, Lee, & Kim, 2010; Pereira & Sousa, 2005; Sousa, Pereira, & Marques,
2004).

Continuous change in demands that originate from the environment of the enterprise due to
environmental hostility, customer needs or competitive stimuli, but also by the changing needs of
stakeholders, creates a constant pressure on organizational performance, profitability and business
continuity. Nowadays, the pace at which changes in the environment of an enterprise occur
increases strongly. This forces an organization to develop dynamic capabilities to be able to adapt to
changes, thus increasing complexity in both the environment and information technology
(Hinkelmann et al., 2015; Steenbergen, 2011; Ullah & Lai, 2013; Van de Wetering & Bos, 2016; Van
de Wetering, Mikalef, & Pateli, 2017a; Van de Wetering et al., 2017b).

EA is an instrument that focuses on coherence between business processes, information distribution
and technology infrastructure of an organization. In practice, the proper interrelationship between
these different architectural aspects is not always dealt in an integrated fashion (Castellanos &
Correal, 2013). EA, especially with (medium) large enterprises, quickly becomes large and complex.
In addition, the effort to maintain EA is often carried out by a group of architects, each with their
specific area of interest or specialty (Steenbergen, 2011). EA frameworks are mostly informal of
nature and there is a lack of knowledge and tools to support Enterprise Architects to check this
alignment in a formal manner (Castellanos & Correal, 2013; Wegmann, Balabko, Lê, Regev, &
Rychkova, 2005).

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This research aims to enable automated rule-based monitoring consistency and coherence between
elements within an EA, aiding architects in achieving alignment. It involves an EA model specified in
the ArchiMate modeling language. The EA model is validated against formalized rules that are
specified in Relation Algebra with which coherence can be measured, monitored, and
mathematically proven. The set of applied rules is plotted onto a quality framework that enables
calculating overall alignment of an EA model. Overall alignment of the researched cases show an
overall alignment score varying from 47,53% to 77,27%. Each overall alignment score is based on an
underlying score for quality factors like completeness and correctness. Every single rule violation
that influences the score is identified specifically. Monitoring EA quality using formalized rules
enables organizations to manage and control the process of EA change and thus contributes to
Business/IT-alignment.

Chapter 1 Introduction forms the introduction of this thesis and describes the context, relevance,
problem statement and objective for this research study. This research study is conducted in
coherence with two other research studies in the field of EA alignment. Paragraph 1.3 specifically
describes the relation between the studies. Chapter 2 describes the results of the literature study.
Chapter 3 and 4 describe the goal, design and setup of the empirical part of this research. Chapter 5
describes the findings that emerged in the execution phase. An overview of the results is presented
in chapter 6. Chapter 7 contains issues and views that require discussion. Chapter 8 concludes the
empirical research and provides suggestions for further research and development of the artifact.
Chapter 9 then describes the personal reflection of the author, reflecting on the entire research
period from both a process- and product-related perspective.

1.2. Context

The context of Enterprise Architecture, Business/IT-alignment and other relevant concepts to this
research study is described in this paragraph.

Gerow et al. (2014) describes Alignment as ‘the degree to which the needs, demands, goals,
objectives, and/or structures of one component are consistent with the needs, demands, goals,
objectives, and/or structures of another component (Nadler & Tushman, 1983)’. In the IT strategy
literature, researchers suggest realizing the full potential of IT requires aligning some or all of four
business and IT components – business strategy, IT strategy, business infrastructure and processes,
and IT infrastructure and processes. Hence, IT-business strategic alignment refers to the appropriate
and timely fit between two or more of these components such that management of the business
and IT remain in harmony (Chan & Reich, 2007; Luftman, Papp, & Brier, 1999). On the basis of a
review of the IT strategy approaches to alignment, Henderson and Venkatraman (1999) Strategic
Alignment Model (SAM) describes four fundamental components of strategic choices to help
organizations realize the full potential of IT.
Although obtaining alignment is worth the effort due to its positive contribution to business
performance, maintaining alignment provides a lasting effect. EA’s are subject to continuous change
originating from the enterprise environment. In business, change is constant and misalignment
between business and IT is inevitable. By adapting the EA, Business/IT-alignment can be restored.
Business/IT-alignment is essential to sustain performance, effectiveness and competitiveness of
organizations (Gerow et al., 2015; Gregor et al., 2007; Steenbergen, 2011; Van de Wetering & Bos,
2016).
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The internal EA alignment is described by Sousa et al. (2004) as ‘the issue of alignment based on the
coherency between elements of Business Architecture, elements of Information Architecture and
elements of Application Architecture. The more elements each of these Architectures has, the richer
and more complex is the concept of alignment, because more rules and heuristics need to be stated
to govern the relation between these elements. So, in order to build up alignment, one must first
clarify the elements of each architecture’.
Achieving alignment also requires understanding of the concept of misalignment. A Business/IT-
alignment model (BITAM) defines mappings between three layers of a business system: business
models, business architectures and IT architectures. Misalignments in BITAM are defined as
improper mappings between the layers (Chen, Kazman, & Garg, 2005). El-Telbany and Elragal (2014)
define misalignment as ‘the continuous efforts, involving management and information systems, of
consciously and coherently detecting and testing for the interrelation of all components of the
business-IT relationship; where a change in one would instantly influence the other, contributing to
the organization’s performance over time’. This research focuses on monitoring and managing the
continuous changes in these interrelations. For this, we need a perceptible and automatically
processable, thus formalized, form of modeling components and its interrelations.

Several definitions of EA are found in contemporary scientific literature. In the context of this
research, EA is described by Lankhorst (2005) as a ‘coherent whole of principles, methods, and
models that are used in the design and realization of an enterprise’s organizational structure,
business processes, information systems, and infrastructure.’. An EA is typically described using
models, covering a holistic view of an organization. Due to complexity of an EA description, many
frameworks were developed to assist in this task (Hinkelmann et al., 2015). Matthes (2011) reports
more than 50 EA frameworks. Two EA frameworks are briefly mentioned here, which are widely
used. In this research, we focus on the framework that is related to a modelling language that is
widely used and supports automated processing.
The Zachman framework (Zachman, 2002) is an enterprise ontology that provides a fundamental
structure for EA. It is represented in a two-dimensional model that enables different persons to
observe the same thing (i.c. an enterprise) from various perspectives. According to Hinkelmann et al.
(2015), Zachman gives no advice on how the EA description should look like. Therefore the OMG1
has developed several modelling languages for EA modelling: Business Process Model and Notation-
BPMN (OMG, 2011) and Case Management Model and Notation – CMMN (OMG, 2014) and the
Business Motivation Model – BMM (OMG, 2015) and the UML language which is used in software
development. The purpose of these graphical modelling languages is to support communication
between human stakeholders. They are not intended to use for machine interpretation, which
makes them unsuitable for this research study.
The other well-known EA framework is TOGAF (TOG, 2011), which is composed of a set of closely
interrelated architectures: Business Architecture, Information Systems (Application and Data)
Architecture and Technology (IT) Architecture. TOGAF also includes a set of tools in order to
enable EA teams to picture the present and future state of the architecture. TOGAF can be used in
conjunction with ArchiMate (TOG, 2016). Figure 1: Research related to TOGAF ADM and ArchiMate
(TOG, 2016) depicts the relation between TOGAF, ArchiMate and the focus of this research.

1 The Object Management Group (OMG) is an international, open membership, not-for-profit technology standards
consortium, founded in 1989. OMG standards are driven by vendors, end-users, academic institutions and government
agencies. OMG Task Forces develop enterprise integration standards for a wide range of technologies and an even wider
range of industries. Source: http://www.omg.org/gettingstarted/gettingstartedindex.htm
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Figure 1: Research related to TOGAF ADM and ArchiMate (TOG, 2016)

The ArchiMate standard is based on the ISO/IEC/IEEE 42010 standard, and introduces an integrated
language for describing EA’s. ArchiMate fits into the TOGAF framework as it provides concepts for
creating a model that correlates to its three architecture layers. The ArchiMate modelling language
is based on a formal foundation, which makes it fit for machine interpretation and thus offers
possibilities for automated validation (Lankhorst, 2005). An ArchiMate model is mapped into
architectural layers and aspects, as depicted in Figure 2: Architecture aspects and layers in
ArchiMate 3.0.

Figure 2: Architecture aspects and layers in ArchiMate 3.0 (TOG, 2016)
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