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Modern organizations are faced with the need to rapidly respond to frequent changes arising from external business pressures. The effect of such continuous evolution eventually leads to organizational misalignment, that is, situations in which sub-optimal configurations of underlying systems significantly reduce an organization's ability to meet its strategic goals. Ensuring alignment of an organization's systems and its goals has been a concern of researchers and practitioners in the enterprise architecture (EA) domain. Unfortunately, current approaches do not adequately address alignment problems that modern organizations face. In this paper we propose that alignment concerns can be better addressed by making models the primary entities that stakeholders within and outside of an organization use to interact with the organization. We call an organization that maintains and uses an integrated set of models to manage alignment concerns a Model Driven Organization (MDO). In this paper we characterize the alignment problem, discuss the shortcomings of current alignment management approaches and present our MDO vision.
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Towards the Model Driven Organization
Tony Clark1, Vinay Kulkarni2, Balbir Barn1, Robert France3, Ulrich Frank4, and Dan
Turk3
1Middlesex University, UK
2Tata Research Development and Design Centre, India
3Colorado State University, USA
4University of Duisburg-Essen, DE
Abstract. Modern organizations are faced with the need to rapidly respond to
frequent changes arising from external business pressures. The effect of such
continuous evolution eventually leads to sub-optimal configurations of under-
lying systems that can significantly reduce an organization’s ability to provide
mission-critical or highly competitive services. There has been little attempt to
apply model driven principles to addressing these issues. We present a vision of a
Model Driven Organisation (MDO) that has the potential to increase productiv-
ity by promoting integration of business processes and collaborations across the
organisation whilst supporting safe and convenient adaptations that maintain sys-
tem integrity. The approach is based on the use of modelling languages and sim-
ulation technologies that provide usable abstractions for understanding business
contexts and goals, through to specifying IT systems, and ultimately to adapting
deployed systems. The paper motivates the problem, illustrates the vision through
a demonstration case, and concludes with an MDO research roadmap.
Keywords: Enterprise Architecture, Enterprise Modelling, Simulation.
1 Enterprise Systems: Problems and Challenges
Organizations such as banks and public sector institutions can be thought of as being
structured in three layers [1]: The strategic layer defines what an organization must
achieve in terms of its high-level goals [2], the tactical layer defines how an organi-
zation plans to behave and thereby achieve its goals, and the operational layer defines
the day-to-day running of the organization in a manner that is consistent with the or-
ganization’s plans. The operational layer of a modern organization is implemented in
terms of a collection of inter-connected IT systems that form an organizational plat-
form. An organization seeks to align its high-level goals with its platform so that its
strategy is properly supported by its IT infrastructure [3–5]. Expressing and achieving
alignment remains a key challenge for modern organizations. From a modeling per-
spective, alignment can be viewed as a refinement or realization relationship between
models of strategic goals and IT platforms.
Alignment is important to an organization for a number of reasons. A key objective
is to establish that an organization is operating correctly, where the notion of correct-
ness is defined in terms of its business goals. Other uses of alignment include supporting
acquisition and merger, where the acquiring organization wishes to determine the sim-
ilarities and differences with respect to the acquired organization in order to achieve
efficiencies. Alignment can also be used to support outsourcing, where the goals of a
service provider can be compared to a sub-set of those of the customer organization
leading to the definition of service level agreements (SLAs).
Achieving goal-platform alignment is compromised by a number of issues facing
a modern organization. The context of a modern organization is increasingly global
and includes features such as competitors, regulatory compliance, business opportuni-
ties, threats, and unforeseen events [6–8], all of which are difficult to accommodate
in a fixed structure of business goals. In addition, complex inter-dependent goals that
serve multiple stakeholders must be analysed to ensure that they are not contradictory.
Responding to changes in the external context, e.g., to seize new opportunities or to
combat external threats, requires changes to the business goals resulting in potentially
large changes in the structure and behaviour of an organization.
The operational platform of an organization consists of IT components implemented
using specific technologies. Changes in the platform can be imposed by the technology
supplier or required by the organization in order to improve efficiency or quality. Such
changes require that business alignment is re-established each time.
The scale of modern organizations is also a barrier to achieving alignment since
it leads to highly complex, dynamic, inter-connected and evolving structures that can
often only be characterized in terms of emergent behaviour. The resulting uncertainty
about the state of an organization makes it difficult to acquire knowledge about its
current state, and to construct plans that can rely on achieving a desirable future state.
In order to improve operational efficiency, agility and resilience, an organization
needs to be able to define, analyse and dynamically maintain its goals, structures, re-
sources and processes throughout its life-cycle, and to maintain their relationship (align-
ment) to the underlying IT platform. Current approaches to Enterprise Modelling (EM)
rely heavily on human business expertise and therefore exhibit a high degree of latency
in supporting key objectives such as alignment. We propose that Model Driven Engi-
neering (MDE) can play a key role in solving this problem, but the application of MDE
to EM is currently patchy at best.
Our proposed solution is a vision for the Model Driven Organization (MDO), where
the different layers of an organization are modelled, analysed, and can be translated
to a model of the underlying IT platform, whilst at the same time being accessible
to all organizational stakeholders. This can be viewed as generalizing the notion of
Model Driven Architecture (MDA) to the level of organizations, where the platform
independent model (PIM) contains features from the strategic and tactical layers and
the platform specific model (PSM) is the IT platform that runs the organization.
The paper is organized as follows: Section 2 reviews current approaches to EM and
MDE and lists a number of Enterprise Architecture (EA) use-cases; Section 3 defines
the vision for MDO and outlines how the EA use-cases can be addressed by a MDO;
Section 4 presents an illustrative instance of the MDO vision; Section 5 concludes by
presenting a research roadmap for achieving the vision.
Fig. 1: Enterprise Layers
2 Current Practice
The MDO mandates advances in a range of technologies and approaches. Perhaps of
most relevance is the role of EA and technologies related to MDE. This section provides
a representative overview of the current state of the art and the typical use cases that
illustrate how such frameworks are used in an enterprise setting.
2.1 Enterprise Frameworks
Currently, efforts in developing enterprise models for an organisation make use of estab-
lished frameworks for describing key concepts and thereby contributing towards an on-
tology or common vocabulary. Such a framework typically presents a collection of do-
mains focusing on describing a particular business area and could be identified as orig-
inating from frameworks such as the Zachman Framework [9]. More recently Jonkers
et al. and Frank [1, 38] introduced frameworks. Figure 1 shows a primary decomposi-
tion of a modern enterprise using aspects and layers to help describe an organization in
terms of its constituent elements as a precursor to EA modelling. Three key layers are
shown: the strategy layer describes what an organization is trying to achieve, i.e.,why
it exists; the business layer describes, in high-level terms the processes and resources
used to achieve the desired outcomes, i.e.,what the business is doing; the information
systems (IS) layer describes the configuration of systems used to run the business, i.e.,
how the business is running. Together, these layers provide the specification and imple-
mentation of an organization.
Each layer can have multiple aspects that provide a restricted perspective of a layer.
The resource aspect identifies the different types of resources that are relevant at each
layer. The structure aspect provides ontologies for describing various structuring mech-
anisms such as roles and projects at the business layer and also subsumes structures
related to information requirements. The process aspect describes various behavioural
features at different levels of abstraction ranging from value chain models at the strate-
gic layer through to transactions at the IS layer. The goals aspect focuses on intentional
aspects, again at different levels of abstraction.
Such layers and aspects provide a simplified abstraction of an organization. In re-
ality, as Jonkers et al note: ‘It is impossible and undesirable to define a strict boundary
between aspects and layers because concepts that link the different aspects and layers
play one of the most important roles in a coherent architectural description.’ In one
sense, Figure 1 merely offers a framework for a reference description, albeit one that
can be further detailed, as in the case of the Archimate Modelling Language described
by Jonkers at al (ibid), or, in our case, one that can be the basis of a reference model for
an organisation to support our notion of the MDO.
EA frameworks such as that outlined above are numerous and complex because of
the nature of the problem they are trying to address. While the Zachman Framework
is perhaps the originator, others include: the Reference Model for Open Distributed
Processing (RM-ODP) [10, 11]; Open Group’s framework TOGAF [12] and related
frameworks for the Department of Defense (DODAF [13]), Federal processing (FEAF),
UK Ministry of Defence (MODAF) [14]. Their general tendency is to add features and
descriptive capability but result in bloated, hard to manage and essentially diagrammatic
approaches.
2.2 Enterprise Modelling and Analysis
Enterprise Modelling aims to capture the essentials of a business, its IT and its evolu-
tion, and to support analysis of this information using a coherent whole of principles,
methods, and models in the design and realisation of an enterprise’s organizational
structure, business processes, information systems and infrastructure [15]. Examples
of analysis possible using EA includes: strategic planning, process optimisation, align-
ment between business functions and IT systems and business change for describing
the current state of a business (as-is) and a desired state of a business (to-be). [16–20,
3]: As noted in section 1, of particular interest to the MDO is the historically thorny but
important issue of business and IT alignment. This was first noted in 1977 by Mclean
[21] but remains prevalent, and EA approaches have been used to address this issue
[1]. Several methods and languages have emerged to provide ‘whole’ methods for EA,
partly to address coherence issues across large EA Frameworks as described above. Ex-
ample of ‘whole’ methods are MEMO [22]. Pereira and Sousa [11] also introduced a
method that is overlayed on the Zachman framework.
In general, modelling languages for expressing features of an EA, such as Archi-
Mate [7], TOGAF and SysML, are often very broad, that is, they provide a wide range of
features for expressing concepts familiar to a business analyst, but they lack the rigour
needed to support and automate aspects of the use cases that will be described later in
this section.
Further, as the scope of EA has extended to the upper layers of the conceptual frame-
work shown in Figure 1 to address intentional modelling, several approaches have use-
ful contributions to make towards the MDO vision. Efforts to standardise intentional
modelling aspects have been consolidated in the OMG Business Motivational Model
(BMM) [6]. The foundational work for BMM can be traced back to goal oriented re-
quirements engineering (GORE) techniques [23] such as i* [24, 25] and KAOS [26, 27,
8]. Quartel et al [2] propose a language called ARMOR which provides an intentional
modelling capability to the Archimate language that relies on the limited semantics
provided by Archimate.
Approaches that support modeling different views of a system are beginning to ap-
pear in the software engineering arena [28]. These approaches utilize meta-models and
domain specific languages. These approaches are not yet supported by mainstream EM
technologies. Similarly languages and tools for EM such as ARIS [29] or MEMO [22]
focus on representing a company from different perspectives to support various kinds
of analysis. A key issue with such modelling tools is that they are not integrated with
enterprise systems. In contrast, Frank and Strecker [30] describe an approach to inte-
grate enterprise models with enterprise systems that they call self-referential enterprise
systems but the proposed technologies suffer from the limitations of main-stream pro-
gramming languages.
2.3 Architectural Styles
An EA can be organised in a variety of ways, but most involve the identification of
logical or physical business units, or components, that manage their own data and re-
sources, implement a collection of business processes, and communicate with other
components using a variety of message passing styles. A Service Oriented Architecture
(SOA) involves the publication of logically coherent groups of business functionality
as interfaces, that can be used by components using synchronous or asynchronous mes-
saging [31]. An alternative style, argued as reducing coupling between components and
thereby increasing the scope for component reuse, is Event Driven Architecture (EDA),
whereby components are event generators and consumers. EDA is arguably more real-
istic in a sophisticated, dynamic, modern business environment, and can be viewed as
a specialization of SOA where communication between components is performed with
respect to a single generic event interface [32, 33].
2.4 Model Driven Engineering
While MDE is broad in scope, we focus on those aspects that address the issues per-
tinent to the MDO vision. Many of the aspects and the associated challenges are de-
scribed in the MDE roadmap paper by France and Rumpe [34]. In particular, technol-
ogy supporting integrated use of multiple general-purpose and domain specific model-
ing languages (DSMLs) [35] may be one of the key enablers of MDO. In an MDO, use
of models expressed in different languages are inevitable, simply because of the variety
of roles that models will play in operating and evolving an organization. Furthermore,
enterprise aspects addressed by models will span different enterprise layer and levels
of abstraction, and thus technologies supporting model manipulations (e.g., model au-
thoring, versioning, transformation and composition) will also be critical to successful
realization of an MDO.
Emerging work on using models as the primary means to managing and adapting
systems at runtime (referred to as models@runtime) [36], are also applicable to MDOs.
In an MDO, models will be used operate and evolve an organization. Stakeholders (e.g.,
employees, business partners, vendors, customers) will access services provided by an
MDO by manipulating models. In addition, enterprise architects will have the capability
of evolving an enterprise through models that are, in a sense, causally connected to
underlying systems at the operational layer. This raises the models@runtime concept to
the organizational layer.
2.5 Use-Cases for Enterprise Architecture Analysis
Enterprise Architectures are built to support use-cases related to managing and evolv-
ing an organization. For example, directive development is concerned with developing
directives that express how a business operates; business intelligence describes how a
CEO is informed of the state of the organization at any level; resource planning in-
volves the allocation of business resources to processes; impact analysis covers a vari-
ety of analyses used to measure the effect a proposed change has on an organization;
change management involves describing the context and requirements for changes in
any aspect of the business, including the construction of as-is and to-be analysis and
the calculation of the ROI for any proposed change; regulatory compliance checking
establishes that an organization meets some externally imposed constraints on its op-
erating procedures; risk analysis identifies dangers, both internal and external, that can
affect the successful operation of the organization; acquisition and merger involves the
comparison of two organizations to identify their similarities and differences with re-
spect to achieving a goal; outsourcing involves the identification of services that can be
supplied by an external partner.
Supporting the above and other EA use cases is challenging. For example, enterprise
architects need to ensure that the models accurately describe relevant aspects of an
organization at an abstraction level that supports specific purposes (e.g. the use cases
above). A significant challenge relates to supporting multiple perspectives. Support for
the separation of concerns and division of labour principles is required to deal with
system complexity and to achieve economies of scale. The accompanying demands
for different enterprise perspectives that are associated with specialized terminologies
and processes point to the need for multiple models, possibly written in a variety of
modeling languages. In order to foster collaboration across different perspectives, the
various models of an enterprise should be integrated through common concepts.
Evolving an enterprise system using current approaches is also challenging. Incom-
plete information about the current state of an organization, imprecise understanding
of the impact of a proposed change, and time-, effort- and cost-intensive introduction
of change are the principal reasons why only a few transformative projects get com-
pleted within budget, and even fewer deliver the desired ROI (Return On Investment)5.
Moreover, the need for the enterprise to remain operational while transformations are
effected adds further complexity.
3 A Vision for the Model Driven Organization
The previous sections outlined the problems facing modern organizations and moti-
vated the use of modelling as the basis for a solution. MDA seeks to solve many of
the problems associated with the development of single IT systems using model-based
techniques. We seek to establish an approach that extends the principles of MDA to an
organization in which models are the primary means for interacting with and evolving
the systems that drive the organization. We will refer to this approach as the Model
5Metrics for Enterprise Transformation http://tinyurl.com/d83ctvd
Fig. 2: The Essential Characteristics for a Model Driven Organization
Driven Organization (MDO). This section provides a definition for MDO and discusses
its key features.
def: AModel Driven Organization uses models in the analysis, design, simu-
lation, delivery, operation, and maintenance of systems to address its strategic,
tactical and operational needs and its relation to the wider environment.
Figure 2 shows the characteristics of an MDO consisting of a model of the organization
(Model of Organization), a model of the platform that runs the organization(Platform
Specific Model), and a transformation between them, as described below:
Model of the Organization: An organization consists of a collection of interacting
aspects ranging from goals and missions through to the business context. Figure 2 shows
a non-exhaustive collection of aspects. Each aspect is supported by a domain-specific
language whose models provide a basis for simulation, what-if, and if-what analysis.
A key challenge here is to find an integration mechanism for these languages that also
supports an organization’s life-cycle as it responds to changes in the business context.
Platform for Organization: An organization uses a collection of IT systems to real-
ize its business functions. A platform consists of domain specific applications, software
infrastructure, network infrastructure, hardware infrastructure. We make a distinction
between three types of IT systems strategic,tactical, and operational systems that cor-
respond to the different needs within the organization [37]. For example, a balanced
score card system is a strategic system, and payroll is an operational system. A platform
provides a collection of interfaces that can be used to drive its IT systems. Cross-cutting
concerns that involve multiple IT systems are supported by appropriate interfaces. The
life-cycle of the platform involves upgrades, interactions with external systems, config-
urations, and is supported by a dedicated interface.
Platform Specific Model: The PSM is a model that is used to express configurations
of the IT systems supported by the platform described above. A PSM is derived from a
Model of the Organization by a semantics preserving transformation. This requires that
both the organizational modelling language and the PSM language have well-defined
semantics. Our proposal is that realizing the MDO vision is beneficial for an organi-
zation as it becomes possible to perform what,why and how analysis on its structure
and behaviour, where this would otherwise be very difficult or impossible. Making the
dependencies explicit has at least two benefits: system integrity is improved because the
model allows the effects of change to be propagated throughout the organization; trans-
parency is improved due to a reduction in the complexity of the organization through
the use of domain specific models. Note that in both cases we talk of improvements
because there will always be parts of a system that rely on human control and expertise,
and which cannot be modelled. Since dependencies are made explicit, it is possible to
precisely measure the effect of a given change and also to provide organizational views
from different perspectives. Consider the enterprise use-cases outlined in section 2. Our
vision for the MDO must be seen to support these use-cases in a way that increases
organizational effectiveness. In all cases domain-specific modelling will be used to pro-
vide languages that support the various layers and aspects of an organization. Below we
revisit each use-case in turn and discuss how MDE can help:
Directive Development: Directives place constraints on how a business operates and
as such acts as domain specific invariants on business processes. Expressing both busi-
ness processes and associated directives as invariant models allows the directives to be
continuously applied to the processes as they are enacted. Domain specificity allows
directive violations to be reported to the appropriate stakeholders.
Business Intelligence: Business intelligence can be achieved by expressing both the
state and objectives of a business as models. Since the definition of an objective is that
it must be measurable then it will be possible to use the state model to provide all
management stakeholders with real-time views of current progress against objectives
(and therefore overall goals).
Resource Planning: Plans can be constructed by comparing goal models with models
of resources and of business processes. The dependencies between these models will
allow changes to the aims, processes or internal organization of the business to be prop-
agated. For example, the impact of the ability of an organization to achieve its goals can
be determined after a reduction in a specific type of resource.
Impact Analysis: This requires modelling dependencies between elements in an orga-
nization. We envisage a situation where all aspects of an organization are represented
in a model and therefore changes to any aspect or level can be propagated throughout.
Change Management: Proposed changes are analysed by constructing a model of a
business as-is and to-be. Since our approach is to model all aspects of an organization,
it is possible to precisely compare the two models and to establish that measures such
as KPIs are maintained or improved by the proposed change. Model transformation
techniques can be used to define organizational change. Furthermore, the models can
be used as the basis for checking or even automatically constructing a change plan
model.
Regulatory Compliance: This is achieved by providing the regulatory body with ev-
idence that required processes are being implemented. If an organization is run from
models then this is easily achieved by auditing the models. Furthermore, if regulations
are published as models, including descriptions of valid evidential compliance, then it
would be possible to upload the regulation model and for an organization to be auto-
matically configured to provide the required evidence.
Risk Analysis: Analysis of risk can be achieved using models in a number of ways. In-
ternal risks impact the ability of a business to achieve its goals and therefore analysis of
models provides a way to both statically and dynamically quantify risks. For example,
the reliability profile for an IT component can be used as part of a simulation to deter-
mine the probability of a given business goal failing. External risks are more difficult to
quantify, however intentional models can be used to attribute probabilities to external
events acting as obstacles for organizational goals. For example, the likelihood of a key
customer moving to a competitor.
Acquisition and Merger: This is a special case of business change where one organi-
zation assimilates another. Modelling can play a key role here by supporting the com-
parison of the two organizations and determining similarities and differences. Domain
specific model comparison can be used to automatically determine which processes of
an acquired business are already performed by the acquiring business and to compare
the efficiency of both. Model merge techniques can be used to compare different possi-
ble outcomes of an acquisition. Modelling can also help support speculative acquisition
by comparing the goal models of two companies.
Outsourcing: This provides an opportunity for using model transformation and model
slicing techniques. Given a model of an organization and a service provider it will be
possible to isolate that part of an organization to be outsourced and then to transform the
organization by slicing. Models of service level agreements can be used to automatically
check required levels of provision.
Organizational modelling provides opportunities for standardization through frame-
works and languages. In turn, repositories of good practice can be established and pos-
sibly accredited so that quality levels of organizational behaviour can be defined.
To achieve the vision, an organization will be represented by a set of integrated
models as described in [38], each of which supports a specific perspective of an enter-
prise and associated tools [30]. Depending on preferences and skills, the models can
be represented using, for example, graphical diagrams, text, tables, and cover different
levels of abstraction from the instance-level to meta-levels. Thus, model-centric sys-
tems provide users with versatile tools to navigate, analyze, modify and interact with
the organization and with other stakeholders that have different perspectives.
4 An Illustration of the Model Driven Organization
Figure 2 shows an overview of the features of an MDO. The general structure can be
specialized to a domain by limiting the operational aspects and addressing a specific
class of platforms. In practice, it is likely there there will be many different MDO in-
stances that target different domains. This section provides an overview of such an
instance in terms of a requirements for an MDO IT Plant followed by a description of
the key features that such an MDO might contain.
4.1 Example MDO
Organizations use IT systems as a basis for their strategic, tactical and operational re-
quirements. We will refer to the systems collectively as an IT Plant (ITP). The costs
associated with these systems are categorized as either transactional (run the business)
or transformational (change the business). Reducing such costs are a significant issue
for any organization. Outsourcing may be used to bring down the costs by transferring
development and maintenance of IT systems to low cost geographies. Other approaches
involve consolidation and rationalization of hardware infrastructure, harmonization of
technology infrastructure.
Outsourcing and hardware consolidation are fast approaching the point of diminish-
ing (if not zero) return and harmonization of software infrastructure can bring only so
much benefit. Individual systems within a traditional ITP are typically associated with
specific functional requirements. Therefore any amount to improvement to an individ-
ual IT system is unlikely to guarantee improvement in the ITP as a whole. Thus, the
current practice seems to be approaching its limits in terms of cost effectiveness.
Consider a service provider who wishes to supply a domain-specific ITP. The provider
will want to cater to the IT needs of multiple organizations through a single multi-
tenant ITP using a flexible and low-cost configuration mechanism. Each customer must
be able to easily determine whether the service provider can meet their functional and
non-functional requirements. Conversely, the service provider must be able to easily
demonstrate that they meet the requirements of each customer to the IT services it
manages without duplicating the ITP for each new customer. Such a service provider
represents a new business model that enables servicing of transactional and transforma-
tional IT needs in outcome-based pricing and on operational risk sharing basis. Clearly
a win-win situation for both organizations and ITP providers.
The MDO framework shown in figure 2 can be specialised to support the ITP out-
lined above as follows:
Model of the Organization: An organization will specify their IT needs in terms of
models including descriptions of processes, services, data, user experience, NFC, SLA,
pricing and risk. Current EA practice advocates use of a subset of these models but only
as blue prints that need to be interpreted by a human expert. On the contrary, an MDO
supports analysis and simulation for functional and non-functional properties. Variabil-
ity will be explicit in these models wherever required. Thus, the organization model
(PIM) can be used as the basis for a commercial agreement between the organization
and the service provider.
Platform for the Organization: The platform in this case is the ITP providing domain
specific interfaces that can be used to configure and run IT applications.
Platform Specific Model: The service provider will use a domain-specific language to
express the features of the IT applications run on the platform. The language will sup-
port IT-level concepts such as processes, workflows, test-cases, and services. The lan-
guage will support analysis and simulation so that the provider can supply the customer
with concrete evidence that the required services can be provided and meet defined
Fig. 3: An example Organization Model
quality criteria. The PSM language will use product-line and variation-point techniques
to ensure that both inter- and intra-customer variation requirements can be met. The
PSM is used to control the platform; this can be through a variety of techniques such as
code generation, executable models and configuration of tables that control choices on
the platform.
The MDO ITP process involves the construction of an organizational model, pos-
sibly containing variation points. Such a model will be constructed by the customer,
most likely assisted by a consultant. The service provider will use the analytical and
simulation properties of the PIM language to supply a cost to the customer. This is
achieved through the use of a semantics preserving transformation from the PIM to the
PSM, effectively compiling the PIM into a form that can be used to run on the platform,
thereby significantly reducing the cost to the service provider. The transformation will
be performed by a service provider expert, possibly assisted by a knowledge based sys-
tem that is used to manage expertise in matching organizational requirements to the ITP.
The rest of this section provides a simple example of such an MDO ITP.
4.2 Model of the Organization
Figure 3 shows a simple model that could be used to capture part of the IT needs of an
organization. Each function corresponds to a required service. In this particular class
of organization, each function requires some authorization and there are a number of
function types and authorization types. For example, if the organization is a bank then
functions might be grouped in terms of accounts, shares or bonds, and the authorization
might be grouped in terms of security levels.
An organization has a collection of goals that define what it is trying to achieve
and also define what must hold in order for authorization to be valid. The goals are
structured in and/or trees. We will use this feature to represent a variation point in the
required service provision.
As an example, consider the Banking industry. A Bank is an Organization that has
Goals. Some goals that Banks have are Make Money for Shareholders,Comply with
Regulations, and Provide Security and Privacy for Customers and Transactions, among
others. Examples of Functions that Banks have are Manage Deposits,Manage Auto-
matic Transactions,Process Inter-bank Transactions, and Issue Bonds. Banks also have
(a) Accredited Organization (b) Non-Accredited Organization
Fig. 4: Variations on a bond purchase
various Authorizations performed for these Functions. Some of these might include Se-
curity Authorization and Regulatory Oversight Authorization. Much more detail would
be desired in a full model of Banking, but this illustrates how the meta-model in Figure
3 could be instantiated into a model of a real-world organization.
As an example of how models can be used in a MDO, consider a scenario in which a
bank requires a bond purchase service from a provider who implements an ITP. Such an
operation requires authorization from several agents within the organization. Normally
such authorization requires 3 people; this is called 6-eye authorization. However, if the
bank has been accredited by the FSA then the regulation can be satisfied with 2 people:
4-eye authorization.
Figure 4 shows the organizational models for two different organizations. The first
is an accredited bank and the goal associated with the authorization type requires that
the number of people associated with each authorization for the bond buying function
is a minimum of 4. The second is a non-accredited bank, therefore the goal requires 3
people.
Since the requirements for the bond buying service are explicitly expressed as part
of the organizational model, the service provider can configure the ITP to give an appro-
priate level of checking to each different customer. This might take the form of sending
2 or 3 secure emails to people in the appropriate roles and waiting to receive replies
containing secure sign-off.
Fig. 5: Organization with variation
(a) Platform Specific Model (b) Input to Platform
Fig. 6: Platform specific bond purchasing
The ITP might use variation in its implementation to service both customers in fig-
ure 4, however the different types of organization do not require any variability in their
provision. Consider the case of a company that currently is not accredited but expects to
achieve FSA accreditation in the near future. Their bond buying service will need 6-eye
authorization initially, but will want to change to 4-eye if they achieve accreditation.
Furthermore they do not want to pay extra for this change of service because they will
inform the ITP in advance.
Figure 5 shows an organizational model for such a company. The variation point
is achieved by including a boolean property called accreditation that is used in the
goal of the authorization type. The ITP can take account of such variations in order
to pre-configure the service. Since models are used to express the requirement and to
configure the ITP, it is possible for the service provider to manage the cost of providing
the variability by generating the service variations from the organizational model.
4.3 Platform Specific Models
A customer provides an organizational model of their IT requirements which is trans-
formed into a platform specific model used to configure the service provider’s ITP.
Figure 6(a) shows a simple model of processes that could use used as the target of such
a transformation. Processes are used to realize the functions required by customers, a
process may have a number of pre-defined variants each of which is implemented using
an orchestration of services enacted by agents. The model is very simple and achieves
variability through pre-defined process variations. In practice we envisage sophisticated
methods from the field of product-line engineering to be applied in order to achieve the
maximum static and dynamic flexibility.
Figure 6(b) shows an instance of the platform specific model that corresponds to the
transformation of the organizational model shown in figure 5 which, in turn, subsumes
the organizational models shown in figure 4.
5 A Research Roadmap for the Model Driven Organization
Realizing the MDO vision described in section 3 requires input from many research
fields including Enterprise Modelling, Enterprise Architecture and Model Based Engi-
neering. In practice, we envisage a situation where there may be a large number of MDO
categories each of which is specialized to a particular domain and which requires input
from specific sub-fields. The MDO requirements are reviewed with respect to the state
of the art in section 2 and performs a gap-analysis in order to speculate on a possible
MDO research roadmap.
Model of Organization: Features of an organization such as goals, processes, organi-
zational structure, services, data, risk, value, etc., and inter-relationships between them
need to externalized. Work on these aspects is typically reported independently, for ex-
ample [39–42]6, 7 8. There is little work reported on modeling the inter-relationships
between these models. Individual models (especially [40–42]) require human experts
for interpretation and lack a precise semantics (effectively being ‘correct by definition’)
necessary to support analysis and semantics preserving transformations.
Analysis and Simulation: There is a need to establish functional and extra-functional
properties of an organizational model in qualitative and/or quantitative terms. Due to the
inherent uncertainty in the domain, fuzzy or probabilistic techniques may help address
qualitative analysis [43]. Analysis techniques exist for individual aspects of an organi-
zation, but method support and technology to combine the results of individual analysis
is lacking. At present it is not possible to simulate all aspects of an organization. Opera-
tional system models can be constructed for certain aspects of an organization in terms
of a small set of primitives and powerful simulation machinery [44] and it may be pos-
sible to extend this approach to other aspects of an organization by including features
such as planning [45] and model checking.
Contract Specification: The relationship between the PIM and the PSM can be viewed
as a contract between the organizational needs and the platform services in a par-
ticular domain. To be effective the relationship needs to utilize model transformation
techniques. However, most current transformation techniques have been developed to
address software development concerns and are weak in terms of verification. Model
transformations for MDO will need to transform constraints (e.g., SLAs), architectures,
process descriptions, non-functional properties, etc. Given the complexity of the source
model, such a transformation will be large and therefore MDO refinement techniques
(possibly aided using a KBS) might be appropriate.
Platform for Organization: The organizational platform must be modelled in suffi-
cient detail so that an implementation of a configurable extensible platform can be de-
rived and used (under human supervision) to monitor, evolve and adapt the organiza-
tion. A method, either manual or partially automated is needed to establish verification
through traceability between the contract specification (PIM) and platform specifica-
tion (PSM). Modelling has been shown to support single IT systems in terms of user
interface, data and data access, on-line and batch functionality, reports, etc., to sup-
port design-time and run-time configuration of a single IT system [46], and to gener-
ate efficient implementations [47]. It is also possible to specify interactions between
6Business Process Model Notation (BPMN), v. 2.0, 2011. OMG: www.omg.org/spec/
BPMN/2.0
7The Web Service Modeling Language WSML http://www.wsmo.org/TR/d15386607/
d16.1/v0.3/20070209/d16.1v0.3_20070209.pdf
8UML 2.0 Superstructure Specification.OMG, Needham (2004)
applications as an orchestration or choreography 6. However, little work is reported
on application architecture to support unforeseen extensibility. The adaptation concept
needs to be extended individually to every constituent such as business processes, ser-
vices, databases, user interfaces, etc., and collectively to the whole platform. This would
involve building further on the ideas of software product lines [48] and architecture de-
scription languages [49].
Testing the Platform: At present it is possible to specify application behavior and to
generate test cases and test data for coverage related assurance [50]. Emerging work
described product-line testing for a set of applications that exhibit high commonality
and well-defined variability [51]. Automation harnesses for regression testing have been
around for years, however, incremental i.e., change-specific testing is still a problem.
Moreover, these ideas need to be extended to cover the whole platform. Another, and
probably more important, problem is to establish testability of the platform.
Deploying the Platform: It is unlikely that an organization will run entirely as an
MDO. Partial migration to an MDO leads to dependency issues between the platform
and the non-platform IT systems and will require modification or decommissioning.
The identification of such dependencies may require analysis of existing systems, prob-
ably in terms of their execution logs. These activities need to be automated and verified
where possible.
Domain Models: Realising the MDO will require input from many different stake-
holders and domains of expertise. Many of the modelling techniques needed to imple-
ment an MDO will cut across domains such as banking, insurance, telecom, etc. This
will require advances in domain engineering, ontologies, meta-modelling, and domain-
specific language engineering in order to achieve the level of integration required.
6 Conclusion
This exploratory paper describes the problems that occur when modern organizations
seek to achieve strategic alignment of business goals with IT systems and to support
EA use-cases. Our proposal is to move towards a Model Driven Organization whereby
Model Based Engineering techniques are used to allow stakeholders to specify, analyse
and interact with an organization through the use of platform independent models that
are translated into technology specific models suitable for deployment on an organiza-
tion platform. Our vision generalizes the notion of MDA so that it can be applied at the
enterprise level and thereby address alignment problems. We have provided a research
roadmap that indicates where research effort is required in order to achieve the vision.
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