ArticlePDF Available

Enterprise Architectures for the Digital Transformation in Small and Medium-sized Enterprises


Abstract and Figures

The transformation towards smart connected factories causes enormous changes in mechanical engineering industry starting from the development of cyber-physical production systems up to their application in production. Enterprise architectures already offer suitable methods to support the alignment of the internal IT landscape. New demands like customer involvement, iterative development and increased business-orientation arising with these digitized products require new approaches and methods. This paper presents the foundation and the first steps aiming at the development of a method for the holistic planning of the digital transformation in small and medium-sized mechanical engineering enterprises.
Content may be subject to copyright.
Available online at
2212-8271 © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Peer-review under responsibility of the scientific committee of the 11th CIRP Conference on Intelligent Computation in Manufacturing Engineering
doi: 10.1016/j.procir.2017.12.257
Procedia CIRP 67 ( 2018 ) 540 545
11th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME '17
Enterprise architectures for the digital transformation
in small and medium-sized enterprises
David Goerziga,*, Thomas Bauernhansla,b
a Institute of Industrial Manufacturing and Management (IFF), University of Stuttgart, Nobelstrasse 12, 70569 Stuttgart, Germany
b Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Nobelstrasse 12, 70569 Stuttgart, Germany
* Corresponding author. Tel.: +49-711-970-1995 ; E-mail address:
The transformation towards smart connected factories causes enormous changes in mechanical engineering industry starting from the
development of cyber-physical production systems up to their application in production. Enterprise architectures already offer suitable methods
to support the alignment of the internal IT landscape. New demands like customer involvement, iterative development and increased business-
orientation arising with these digitized products require new approaches and methods. This paper presents the foundation and the first steps
aiming at the development of a method for the holistic planning of the digital transformation in small and medium-sized mechanical
engineering enterprises.
© 2017 The Authors. Published by Elsevier B.V.
Selection and peer-review under responsibility of the International Scientific Committee of “11th CIRP ICME Conference".
Keywords: Digital transformation; Digitization; Industry 4.0; Enterprise architectures
1. Introduction
Currently, customers increasingly strive for maximization
of personalized value. This becomes particularly obvious in
the demand for individualized products and the increasing
influence of customers on the development and the production
processes [1]. Factories can only meet this challenge by the
application of digital technologies. In Germany, the term
Industrie 4.0 represents the aspired target state. Through
improvements in information, communication and automation
technology live information is available over life cycles of
products, processes and factories. Production systems,
products and humans are closely networked. Moreover, the
resulting big data is used for holistic optimization. [2, 3, 4]
This special situation gives rise to opportunities and risks for
mechanical engineering enterprises. Based on customer data
there are numerous new possibilities for product and process
improvements including the optimization of the machining
process or spare part forecasting services. At the same time,
they are confronted with new demands. Customers not just
want to buy a physical machine but service systems,
consisting of hard- and software, that offer additional value in
their unique context [1, 4, 5]. Examples are context-based
features and information for machine operators that support
manufacturing to adapt rapidly changing customer needs. To
realize such use cases a close collaboration of manufacturers
and mechanical engineering enterprise is required. Through
this development, IT is not any longer just a technological
tool to improve the efficiency of internal processes. By
becoming an essential part of the value creation it grows up to
a new source of competitive advantage and thus takes a
transformative role [5]. The required extension of products by
digital components to the point of cyber-physical systems and
their integration into service systems leads enterprises in
mechanical engineering into a fundamental change process
the digital transformation. Besides mechanics and electronics
they now need to develop digital capabilities and implement
them into fast-changing, cross-company processes and
structures. Especially for small and medium-sized enterprises
(SMEs) this is an enormous challenge [6].
With the help of business model appraoches, many
enterprises already started to design digital value creation
concepts. But these means are very limited when it comes to
deriving and implementing processes and IT services. In
contrast to existing IT-based products, the new service logic
requires a holistic process view. To take full advantage of the
© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Peer-review under responsibility of the scientifi c committee of the 11th CIRP Conference on Intelligent Computation in Manufacturing Engineering
David Goerzig and Thomas Bauernhansl / Procedia CIRP 67 ( 2018 ) 540 – 545
digital opportunities adequate models, methods and tools are
needed [4, 7]. With enterprise architectures (EA) information
systems literature already offers a well-proven solution for
this challenge [8, 9]. The aim of this paper is to examine if
this approach is appropriate for digital transformation in
SMEs of mechanical engineering. Therefore, digital
transformation and EA are defined. Afterwards, strengths and
weaknesses of EA in the context of digital transformation in
SMEs are analyzed. In addition, this paper presents the first
steps for the development of a method for the holistic
planning of the digital transformation in small and medium-
sized mechanical engineering enterprises.
2. Digital Transformation in Small and Medium-sized
The following section outlines the state of the art in the
field of digital transformation in SMEs. First, a closer look at
the definition of digital transformation is required. In change
management, the term transformation is used to describe the
extent of strategic change. Whereas in a realignment there is
just a slight change in the way an enterprise operates, in a
transformation it changes its paradigms of doing things. [10]
As shown in figure 1 in enterprise transformation literature
the term is defined as a fundamental change during which
enterprises reinvent themselves. This contains a change of the
context in which the enterprise is active. The context includes
the way of operation and the previous sources of success.
Moreover, the enterprise substantially alters its relationships
with its key constituencies like customers, suppliers or
employees. The initial point of transformation is a radical
change in the economic or market context. This can lead
either to an experienced or an expected value deficiency and
thereby influence the speed of change. [11, 12] On this basis it
can be distinguished between an evolutionary transformation
in incremental steps and a revolutionary transformation by a
big bang. The speed of change depends in most cases on
whether the enterprise is forced to or changes proactively.
[10] Result of a transformation is a conscious and sustainable
change in business performance [11]. It may lead to new
value propositions as products and services, different ways of
interaction with the customer in terms of delivery and
provision of offers and new organizational forms to provide
these offers to the customer [12].
Fig. 1. Process of enterprise transformation.
The term digital covers gathering, storing, processing,
providing and using information electronically with the help
of information technology (IT). Through ever lower costs and
the increasing pervasion of IT nowadays large information
volumes can be shared worldwide at minimum costs. [3, 5,
13] The internet of things brings this development to the next
level. By sensing and analyzing the context of the customer,
this approach enable enterprises to get a deep insight into the
customer motivations and create by this personalized
customer value. [3, 5] One of the consequences is an
enhancement of the relationship between provider and
customer. Through the close networking of customers and
providers digitization blurs the differences between them and
enables cooperative value generation, also referred to as co-
creation. Products evolve into services which are aiming at
maximum value for both. [5, 14] Simultaneously digital
technologies enable a fundamental reshaping of business
towards cross-functional, modular and distributed processes
[14]. This development increases business agility and
empowers enterprises to act in turbulent environments like
ecosystems. Ecosystems are self-containing and self-adjusting
systems of loosely coupled actors that jointly create value.
The basis of their relationship are institutional logics from
which a set of rules and principles is derived. The importance
of traditional, linear value chains decreases. [5, 15] A basic
instrument to leverage the advantages of ecosystems are
platforms. These modular structures facilitate the interaction
between the actors. Platforms support the installation of rules
for exchange and modular architectures. [5, 14] In summary,
digital technologies become essential part of the value
creation. For mechanical engineering enterprises as well as for
new market actors this development offers chances to create
new competitive advantages. Moreover digitization offers a
possibility to fulfill the existing customer demands for a
highly flexible supply of individual products. By reason of
these significant changes the digitization can be seen as the
initial point for a new wave of transformations.
At the moment, there is no common definition for the
digital transformation. The following literature sources give a
hint on the current discussion. Schallmo points out the
networking of the value chain for improved decision-making.
He defines digital transformation as the connection of actors
over the value chain and the application of new technologies.
In his view digital transformation demands capabilities for the
gathering, the exchange, processing and analysis of data. The
aim is to support decision processes and to initiate activities.
Digital transformation influences enterprises, business
models, processes, relationships and products to improve the
performance and scale of the enterprise. [16] According to
Matt et al. digital transformation involves the application of
digital technologies with the aim of a change of key business
operations, products, processes, organizational structures and
management concepts. The authors describe manifold benefits
like increased sales and productivity as well as innovations in
value creation and customer interaction. [7] Nandico
describes digital transformation as a change of an enterprise
with the aim to provide new or enhanced products, services or
both to the customer. A key enabler for this new offering or
enhancement is the application of information technology.
Thereby, enterprises try to create new business models,
customer experience or operating models. [8] Whereas Matt et
al. see the impact of digital transformation rather broad,
542 David Goerzig and Thomas Bauernhansl / Procedia CIRP 67 ( 2018 ) 540 – 545
Nandico concentrates on service innovation.
In this paper, digital transformation is defined as a
fundamental change process in enterprises initiated by new
competitive advantages through the evolution of IT into an
essential part of the value creation. To unlock these new
potentials enterprises evolve their products into services and
start to operate together with their customers in co-creation
aiming at value maximization. Important enabler are context-
sensitive systems that help to adapt the services to the
individual and situational requirements of customers. In order
to be capable of offering these digitized services enterprises
have to think in modular, cross-functional and distributed
business processes that allow them the integration into
ecosystems. Result of the change is the ability to create
personalized customer value at costs of mass production.
Figure 2 summarizes the definition based on figure 1.
Hereby, several requirements for planning and
development tools arise. Since it aims for the realization of
innovative forms of value creation, an approach should be
able to integrate ecosystems and platforms. Secondly, in order
to create customer-oriented and context-based solutions, the
approach should allow the analysis and documentation of the
close interaction with the customer and a quick adaption of
the necessary processes to changing market contexts. Because
a digital transformation is a fundamental change process an
approach should help enterprises to create a clear
transformation strategy and to provide a clear vision of the
future state to get the commitment of all stakeholders.
SMEs have special characteristics that influence the
process of digital transformation and thus lead to
requirements concerning the supporting tools. SMEs are very
limited in their resources. On the one hand, their employees
mostly do not have the required skills. Furthermore, they are
tied to day-to-day business and are therefore not available for
the development of new solutions. On the other hand, SMEs
have only limited financial resources. Thus they cannot afford
expensive external support. For digital transformation
methods, this means that they should have very little demands
for IT-capabilities and be very time-efficient. Moreover, it
should be possible to apply them with a minimum of external
support. Because of the financial shortage, SMEs are
dependent on the success of the realized projects. Therefore,
the expected returns of every project must exceed their costs
and risks. A method for digital transformation should offer a
good cost-benefit ratio. Since in SMEs the important decision
are made by the CEO, he should be involved in the decision-
making process. Another demand of SMEs is a clear
description of how the results shall be realized. [6]
Enterprises in mechanical engineering are characterized by
the development and system integration of long-lasting capital
goods which are sold in a business-to-business relationship.
The enterprises have a strong focus on product and
technology innovation. [15] Currently, software services play
a tangential role. They are mostly used to raise margins or to
offer additional value to the customer. Software development
and networking of machines are still a challenge for the
branch. Thus, tools for digital transformation in mechanical
engineering enterprises should be easy to use and understand
in order to involve all relevant stakeholders. Additionally,
they need to draw a clear picture of the transformation process
and the expected results.
Fig. 2. Elements of digital tran sformation.
3. Embedding Enterprise Architectures in the Digital
The initial point of digital transformation is a digital
business strategy. This is an organizational strategy that aims
to create differential value by applying digital resources in
formulation and execution. It goes far beyond traditional IT
strategy which considers IT as a tool for improvement of
business processes. It contains scope, scale and speed of
digital business strategy as well as sources of business value
creation and capture. [14] Since the digital transformation is a
complex process for implementation, more details are
required. That is why a business model is derived from the
digital business strategy. In the past businesses operated in a
relatively stable environment with limited operative
possibilities. For business managers, it was possible to derive
processes directly from strategy. With increasing digitization
the situation becomes more complex. The application of IT-
based processes not only expanded the possibilities of doing
things, the things themselves also got more complex. [17]
That is why new methods, models and tools are needed which
help to put the strategy into action. Matt et al. propose the
development of a digital transformation strategy. It contains
essential decisions on technology, structure, financials and
value creation. [7] This approach helps to detail important
issues of digital business strategy but is still on an abstract
level. With business models, there is an approach that helps
enterprises to make strategy more explicit. [17] A business
model describes how organizations create value. It contains
activities and resources that create customer value and,
therefore, lead to revenues. [18] Business models are made for
the elaboration of value generation, but they are not suitable
for planning the implementatio of processes and services. [17]
Thus, another approach is needed to design and implement
processes and synchronize IT activities. In information
systems research many authors claim the application of EA
for implementation of business transformation. [9] The
question is if they are also useful for digital transformation.
EA can be comprised as a complete description of an
enterprise. It describes the essential business artifacts and
their relationship. Therefore, EA contains a set of principles,
methods and models that help enterprises to design and realize
its organizational structure as well as the fitting business
processes, information systems and infrastructure. [19, 20, 21]
The central aim of EA is creating transparency by
documenting the actual situation. Thus, it aims at giving an
enterprise the control over its complexity, processes and
information systems. Additional aims are data demand and
interface analysis. Secondly, by providing an overview of the
essentials of the enterprise, EA helps to control and conserve
its most stable parts. As a third task, EA supports enterprises
David Goerzig and Thomas Bauernhansl / Procedia CIRP 67 ( 2018 ) 540 – 545
to transfer strategy to daily processes. The fourth aim for EA
is that it can be understood by all involved stakeholders. A
fifth aim is that EA supports holistic optimization and
identification of simplification. [19, 20]
Besides this very general characterization of EA and its
tasks, there are many different definitions and EA frameworks
with different scopes and focuses. Important distinguishing
features are the supported enterprise layers. There are five
possible layers. In the strategic layer, an EA defines for
example products, interaction with suppliers and customers.
In the organizational layer, the architect elaborates business
processes, information flows and roles. The integration layer
considers applications, services and interfaces. Whereas the
software layer defines data structures and software
components, the IT infrastructure layer works out hardware
and network components as well as software platforms. Most
EA approaches focus on organizational, integration and
software layer. First well-known approaches were the
Zachman framework and ARIS. Today, TOGAF is the most
common framework. [20]
4. Criticism on Enterprise Architectures as an Instrument
for Digital Transformation
At first sight, EA could be a great support for digital
transformation in SMEs of mechanical engineering. But
currently, this approach is not very common in business
transformation. In the literature, the development of the
application of EA for business transformation is discussed
only in a few publications. Especially in SMEs it is unknown
and not used. Although there are enterprises which already
align strategy and processes, they do not use EA. [6, 22]
There are several possible reasons for this situation.
An important aim of EA is to bring people of different
fields together and to create solutions that are understood by
all of them. Though this is a very important concern in major
changes, in practice there is a wide gap between business
transformation and EA. Because of their origin in different
disciplines, each approach uses different languages,
description techniques and tools. Business transformation has
a stronger focus on processes. Although EA has the word
enterprise in its name it is strongly rooted in IT. Strategy and
processes are only considered marginally and with an IT-
focus. Thus, the application of EA is mostly limited to IT
departments. Publications argue that EA is thus to abstract.
That is why there is often a lack of management support. [19,
In SMEs EA frameworks are not understood. TOGAF, for
example, creates a complete view of an enterprise. But the
approach is also very difficult to implement. It needs an
extensive training and certification for use. EA frameworks
are extensive and complex and difficult to handle. Although
this challenge is widely known there are only a few
approaches in literature to cope with this. Even the official
TOGAF documentation points out that a reduction of the
framework is recommended. But there is no information given
which parts should be eliminated for the application in SMEs.
Despite this situation, the application of EA in SMEs is barely
noticed in research. [6, 20]
Besides these hurdles in business transformation, new
challenges arise with digital transformation. Due to
digitization, a short time-to-market and the inclusion of
customers into the development processes of the fast-
changing service systems become highly important. EA, in
contrast, follows the traditional waterfall approach of
developing detailed and completed architectures and
implement them afterwards. In this view, information systems
are quite stable. During this process, there is no space for
quick adaptions and iterative development. The focus on
detailed planning leads to a conflict with newer agile
approaches. [8] These approaches base upon an incremental
development and a high involvement of customers. This leads
to less effort, increased velocity and an excellent customer
satisfaction. [23] Additionally to the changes in the
development approach also the system boundaries of EA are
realigned. With digital transformation, there is a fundamental
change in business processes and organizational structures.
This entails a strong business orientation and creates a
demand for deep integration of digital strategies and business
models. Currently, there is a rather neglected integration and a
concentration on the integration of applications and
infrastructure. Through the use of standardized platforms,
these challenges recede into background. At the same time,
the borders between market actors get fuzzy or in some
aspects even disappear. Digitized products gather customer
data and adapt to the context. To cope with this situation IT
frameworks need to think in a service-oriented way and
unlock the potentials of ecosystems and platforms. Only in
this way it is possible to create individual, customer-oriented
solutions. Up to now, EA frameworks are not capable of this.
[8, 22] EA is used to plan and maintain the current state of
stable internal information systems. There are only limited
ways for doing things. In the future, there will be a large
demand for the agile development of target states. Moreover,
the transformation process itself becomes more important,
especially when it comes to the development of smart
products, processes and services. This all creates new tasks
for EA in the life cycles of applications. [20, 22] Table 1
compares the features of EA with the most important
challenges of digital transformation.
In summary, EA is a very strong approach for
development, maintenance and documentation of information
systems. It offers a wide variety of tools and models and has
proven its effectiveness in many projects. But while topics
like digital transformation are hyped, EA becomes less
important. The main objection is that EA is too complex and
deeply rooted in IT. That is why this approach is not
understood by business and also not by SMEs of mechanical
engineering. But especially major change processes need a
clear that is understood by all. Another point of criticism is
that EA offers an extensive and inflexible way of planning.
But currently, agile methods change the way software is
planned and developed. Through the digital transformation,
new hurdles like a stronger customer integration and
ecosystems arise. Needed are approaches that look closer at
customer needs and offer an iterative development. Therefore,
lightweight planning tools with a strong business focus, which
can be understood by each stakeholder, have to be developed.
544 David Goerzig and Thomas Bauernhansl / Procedia CIRP 67 ( 2018 ) 540 – 545
Table 1. Features of enterprise architectures comp ared to the new challenges
of digital transformation.
Enterprise architecture
Digital transformation
Target groups
specialized staff,
IT-architects, …
Stable information
Fast changing
service systems
Waterfall approach
Agile approaches
Organizational layer,
integration layer,
software layer,
infrastructure layer
Strategic layer
business model layer
organizational layer
integration layer
Value stream
Information systems for
stable value chains and
customer needs
Ecosystems and context-
sensitive value crea tion
Life cycle
Agile development,
usage, maintenance
5. Approach for Digital Transformation in Small and
Medium-sized Enterprises
The previous analysis shows that EA offers a high
potential for the implementation of digital transformation. But
concurrently there are also weaknesses in existing approaches.
Especially an involvement of business could not be achieved.
Moreover, there are new challenges for EA. With the
development of the last years, an agile development of
business gets more importance. Additionally, the ecosystems
and smart products become part of the architecture. In this
paper, we present the first steps for a new EA approach for
digital transformation in SMEs. As previously analyzed, an
approach for realization of digital transformation has to be
much more agile and therefore nearer to the customer. That is
why agile development methods are the basis of the
developed approach.
As shown in figure 3, the approach is divided into a macro
and a micro cycle. The macro cycle defines the architecture of
the entire SME. In the micro cycle single functions are
implemented and tested. Besides the incrementally developed
macro and micro cycle there are two quite stable fields which
help to conserve the digital strategy of an enterprise. The
digital business strategy is the initial point of the approach. It
contains basic decisions concerning speed, scale and scope of
the digital technology application in the enterprise. As
described by Matt et al. it is essential to derive a
transformation strategy out of the digital business strategy.
Here, technological and organizational principles for the
implementation are defined. In contrast to Matt et al., in this
approach value creation and financial aspects are not
considered as stable enough and are, therefore, defined in the
business model.
The first step of the macro cycle is to derive the business
model from the digital business strategy. As described earlier,
the business model contains information like value
proposition, customer segments or revenue streams. The
second step is to elaborate an ideal architecture. The aim of
this step is to detail the business model in a very rough way.
The ideal architecture contains descriptions of the main
processes, main IT services and information that is needed for
realization. An important feature is that there are no
restrictions. The target of the ideal architecture is to give the
architect room for new ideas without considering legacy
systems or strategic restrictions. Afterwards, the real
architecture is derived from the ideal architecture. In this step,
the transformation strategy and the current architecture are
considered. Since the fundamental change during a digital
transformation should be realized incrementally, there are
always legacy systems and interfaces that have to be taken
into account. Nevertheless, the architect should not continue
to use legacy systems at any price. The architecture backlog
follows similar ideas as the product backlog in the scrum
approach. Based on the differences between current and real
architecture, user stories are defined in the architecture
backlog. These user stories are capsuled service systems with
defined interfaces. A defined set of user stories can run
through the micro cycle independently from other user stories.
They describe the users, the desired functionality and the
benefit. There are no details about used software or hardware.
The aim of this is to create free space for the development
team. Within the backlog, user stories are prioritized.
Moreover, it is defined which user stories are built by the
enterprise and which are provided by partners within the
ecosystem. Services that are part of the core competence or
are not available on the market are developed single-
After running through the macro cycle the micro cycle can
be started for the first time. This cycle begins with choosing
the prioritized user stories from the backlog. The amount
depends on the speed of change an enterprise aims for. Next
step is the built or the service selection phase. During the built
phase, the developers implement the user stories in a sprint.
But in most cases the selection of services off the shelf is the
better choice. Especially when a service is not part of the core
competence and is already available on the used platform, an
internal development should be avoided. After
implementation or purchase, each user story is tested. Testing
can be realized either together with a test customer or in a
testbed as provided by different organizations (e.g. research
institutes, universities …). In Germany, the I4KMU project
offers SMEs help when it comes to testing of I4.0-relevant
technologies. They are supported to find a fitting test
environment. [24] Next step is the review. There are three
possible decisions. The first possibility is that the user story is
marked as done. Then the teams start with the next user story.
The second possibility is that adaptions are required and the
micro cycle has to start again. The third possibility is that
there are findings that have an impact on the whole
architecture. Then the macro cycle starts again. With the first
pass of the macro cycle, the architecture is still very rough.
With every pass, there are more details. The macro cycle
should always give enough space for decisions in the micro
David Goerzig and Thomas Bauernhansl / Procedia CIRP 67 ( 2018 ) 540 – 545
Fig. 3. Agile enterprise architecture for digital transformation.
6. Conclusion and Outlook
In this paper, we analyzed the content of the digital
transformation. Furthermore, we took a closer look at possible
methods and tools for the implementation of product ideas
with a special focus on process implementation. Thereby we
found that currently used approaches are not sufficient for
SMEs in mechanical engineering. Main challenges are the
high complexity of the approaches and the infeasibility for the
fast development of new solutions. That is why we presented
a new lightweight, agile approach.
Next steps planned for the development of this approach
are the detailed definition of the single steps and their
integration with each other and with the digital business and
digital transformation strategy. Here, one challenge is to
identify and test a suitable SME-oriented notation for
modeling the business processes, services landscape and
ecosystems. Another task is to optimize the cycles and test
their comprehensibility in SMEs. It is planned to validate this
in several projects with SMEs of mechanical engineering.
[1] Bauernhansl T, Hörcher G, Röhm M, Bressner M. Neupositionierung
einer nationalen Technologieplattform: Strat egien für die deutsche
Produktionsforschung. Zeitschrift für wirtschaftlichen Fabrikbetrieb 2017;
[2] Kagermann H. Chancen von Industrie 4.0 nutzen. In: Vogel-Heuser B,
Bauernhansl T, ten Hompel M, editors. Handbuch Industrie 4.0 Bd.4.
Allgemeine Grundlagen. 3rd ed. Berlin, Heidelberg: Springer; 2017. p.
[3] Lemke C, Brenner W. Einführung in die Wirtschaftsinformatik:
Verstehen des digitalen Zeitalters. Berlin: Springer Gabler; 2015.
[4] Böhmann T, Leimeister JM, Möslein K. Service-Systems-Engineering.
Wirtschaftsinformatik 2014; 56:8390.
[5] Lusch RF, Nambisan S. Service Innovation: A service-dominant logic
perspective. MIS Quarterly. 2015; 39:15575.
[6] Bernaert M, Poels G, Snoeck M, de Ba cker M. Enterprise Architecture
for Small and Medium-Sized Enterprises: A Starting Point for Bringing
EA to SMEs, Based on Adoption Models. In: Devos J, van Landeghem H,
Deschoolmeester D, editors. Information Systems for Small and Medium-
sized Enterprises. Berlin, Heidelberg: Springer; 2014. p. 6796.
[7] Matt C, Hess T, Benlian A. Digital Transformation Strategies. Bus Inf
Syst Eng 2015; 57:33943.
[8] Nandico OF. A Framework to Support Digital Transformation. In: El-
Sheikh E, Zimmermann A, Jain LC, editors. Emerging Trends in the
Evolution of Service-Oriented and Enterprise Architectures. Cham:
Springer; 2016. p. 113-38.
[9] Gardner D, Fehskens L, Naidu M, Rouse WB, Ross JW. Point-
Counterpoint: Enterprise Architecture and Enterprise Transformation as
Related but Distinct Concepts. Journal of Enterprise Transformation
2012; 2:28394.
[10] Balogun J. Strategi c change. Management Quarterly 2001; 10:211.
[11] Purchase V, Parry G, Valerdi R, Nightingale D, Mills J. Enterprise
Transformation. Why Are We Interested, What Is It, and What Are the
Challenges? Journal of Enterprise Transformation. 2011; 1:1433.
[12] Rouse WB. A theory of enterprise transformation. Syst. Engin. 2005;
[13] Tapscott D. The digital economy: Promise and peril in the age of
networked intelligence. New York: McGraw-Hill; 1996.
[14] Bharadwaj A, El Sawy OA, Pavlou PA, Venkatraman N. Digital
Business Strategy. Towards a Next Generation of Insights. MIS Quarterly
2013; 37:47182.
[15] Paulus-Rohmer D, Schatton H, Bauernhansl T. Ecosystems, Strategy and
Business Models in the age of Digitization - How the Manufacturing
Industry is Going to Change its Logic. Procedia CIRP. 2016; 57:813.
[16] Schallmo D. Jetzt digital transformieren. Wiesbaden: Springer; 2016.
[17] Al-Debei MM, El-Haddadeh R, Avison D. Defining the Business Model
in the New World of Digital Business. Proceedings of the Fourteenth
Americas Conference on Information Systems. 2008; 14:1551-72.
[18] Osterwalder A, Pigneur, Y. Business Model Generation: A Handbook for
Visionaries, Game Changers, and Challengers. New York: Wiley; 2011.
[19] Lankhorst M. Enterprise Architecture at Work. Modelling,
Communication and Analysis. 3rd ed. Berlin Heidelberg: Springer; 2013.
[20] Aier S, Riege C, Winter R. Unterneh mensarchitektur
Literaturüberblick und Stand der Praxis. Wirtsch. Inform. 2008; 50:292
[21] Schekkerman J. How to survive in the jungle of en terprise archit ecture
frameworks. Creating or choosing an enterprise architecture framework.
3rd ed. Victoria: Trafford; 2006.
[22] Aier S, Weiss S, Winter R, Rytz B. Untangling EA's Long Path of
Becoming a Partner for Business Transformation. The Case of Swiss
Federal Railways. IEEE 20th International EDOCW. 2016; 20:91-7.
[23] Rubin KS. Essential Scrum. A practical guide to the most popular agile
process. Upper Saddle River, NJ: Addison-Wesley; 2012.
[24] Issa, A.; Lucke, D.; Bauernhansl, T.: Mobilizing SMEs towards Industrie
4.0-enabled Smart Products. Procedia C IRP. 2017; 58.
... There have been several types of research reports that business intelligence and dynamic capabilities are significantly correlated in the area of business and management studies. Although most researchers in the field consider business intelligence a single capability, such as Big Data Analytics Capability [52], a tool of Big Data Decision-making [53], or a technique for enhancing Operational Research [37], it can be considered a trigger of dynamic capabilities [19]. Business intelligence plays an important role in creating knowledge and developing dynamics capabilities within firms. ...
... Previous studies highlight several advantages of dynamic capabilities within organizations [53] reports that the dynamic capabilities approach helps managers to create a competitive advantage. In the same vein, the dynamic capabilities strategy is asserted to be an encouraging approach to improving the understanding of critical innovation management for environmental sustainability [54]. ...
Full-text available
While the issue of business intelligence is rapidly gaining popularity across a wide range of domains, the majority of research treats it as a single capability or technique, such as big data analytics capability. However, as a tool for Big Data Decision-making or technique for enhancing operational research technique, there is still a low amount of work that examines business intelligence as a tool to develop dynamic capabilities of the organization and to contribute to sustainable innovation, in particular in the digital age. Therefore, to address this gap, this chapter aims to discuss how organizations can use technologies, including business intelligence as a tool for creating new knowledge, which in turn helps organizations to improve their dynamic capabilities and achieve sustainable innovation. Recognizing how these firms’ dynamic capabilities are started building, achieved sustained, enlarged, utilized, evolved, and phased out in phrases of their constituent micro-foundations. So, this study suggests business intelligence as a process that helps organizations collect and transform data into information and knowledge, which contributes to building dynamic capabilities. It is important for managers to understand how these firms’ dynamic capabilities are started building, achieved sustained, enlarged, utilized, evolved, and phased out in phrases of their constituent micro-foundations.
... As a conclusion to their research, Liao and Wang offered an in-depth TOGAF analysis of an actual business transformation occurring at a large worldwide chemical corporation, extracting the architectural framework that this company may have employed to change into a lean enterprise. TOGAF generates a comprehensive image of an organization [22]. TOGAF also helps Intel IT execute the company's digital transformation plans, and Intel is investing in resources with expertise in this framework [23]. ...
The SARS-CoV-2 pandemic and the global response to contain its spread and deaths have been unprecedented, according to UNICEF research on COVID-19 released in 2021. Many steps had been taken by countries worldwide, particularly those in South Asia. As of May 17th, 2020, Indonesia reported a total of 17,514 daily positive cases. It has been confirmed that the majority of cases throughout the archipelago occur primarily on Java, particularly in the Greater Jakarta, Greater Bandung, Semarang, Solo, and Greater Surabaya areas. The research object of this paper is a system integrator company located in, Central Jakarta. The company's business is badly impacted by this pandemic. The company provides nearly all ICT solutions, yet improving their internal systems is an issue that has never been brought up. Due to physical distance regulations, leading workers to work from home. To keep the business running, the company began using email as their only tool to run the whole system, which is not effective and causing a crisis for the company. The purpose of this paper is to propose a digital transformation plan as a solution and to support business continuity by utilizing TOGAF ADM. Doi: 10.28991/HIJ-2023-04-01-01 Full Text: PDF
... The question of whether EAM enables digitalization has been raised by . The role enterprise architecture plays in the digitalization of manufacturing enterprises was investigated by Goerzig and Bauernhansl (2018). They state that enterprise architecture responds to the challenges encountered in digitalization projects. ...
Full-text available
Many companies digitally transform their business models, processes, and services. They have also been using Enterprise Architecture Management approaches for a long time to synchronize corporate strategy and information technology. Such digitalization projects bring different challenges for Enterprise Architecture Management. Without understanding and addressing them, Enterprise Architecture Management projects will fail or not deliver the expected value. Since existing research has not yet addressed these challenges, they were investigated based on a qualitative expert study with leading industry experts from Europe. Furthermore, potential benefits of digitalization projects for Enterprise Architecture Management were researched. Our results provide a theoretical framework consisting of five identified challenges, triggers and a number of benefits. Furthermore, we discuss in what ways digitalization and EAM is a promising topic for future research.
... One of the most commonly mentioned requirements for successful DT is the need for a digital strategy (Hess et al., 2016). It is often considered as a starting point for any DT efforts (Catlin, Scanlan, & Willmott, 2015;Goerzig & Bauernhansl, 2018). The digital strategy consolidates and aligns the IT and business strategy (Berghaus & Back, 2016) and spans the entire company (Hirte & Roth, 2018). ...
Full-text available
Purpose Digital transformation (DT) projects are complex and often unsuccessful. While researchers have suggested many guidelines and best practices on how to successfully roll out DT projects and how they are spread among a large number of scientific papers. The aim of this paper is to synthesize these guidelines into clear overviews. Design/methodology/approach A systematic literature review was conducted on both Scopus and Web of Science to search for papers suggesting DT guidelines or best practices. In total, 150 papers dealing with DT and guidelines were fully analyzed. Findings Eight main DT guidelines were found and each one was expanded with several best practices on how to implement these. The results are eight tables giving an overview of the commonly agreed-upon best practices for each DT guideline. Research limitations/implications These overviews are useful for both researchers and practitioners, to guide future work and to be inspired respectively. This paper calls for more research on how these guidelines are followed in practice, how these differ per industry and what their impact is on the overall success of DT projects. Originality/value The synthesis of DT guidelines organized into an accessible format has not yet been conducted before, and can serve as a seminal pinpoint for future research.
Full-text available
Esta pesquisa teve como objetivo verificar a percepção dos profissionais da contabilidade sobre a transformação digital. A transformação digital por meio de sistemas e tecnologias inteligentes conectadas a dados surge em quantidade e velocidade exponencial como facilitadora para a informação precisa e de qualidade. As tecnologias estão sendo inseridas de tal forma a repensar processos, conhecimentos, habilidades e atitudes do profissional da contabilidade diante da percepção da transformação digital. Como procedimento metodológico, optou-se por uma abordagem qualitativa por meio da análise de conteúdo. Aplicaram-se entrevistas em profundidade com representantes de classe, entidades contábeis e instituições relacionadas à área contábil. Os resultados demonstraram que a transformação digital pode contribuir para o desenvolvimento da profissão contábil e das organizações, pois as tecnologias desafiam o contador e provocam novos insights para as competências essenciais, como forma de inovação, para monetizar novos negócios e criar oportunidades. Na pesquisa surgiu o termo digitização, em que o profissional tem ciência dos benefícios da adaptação e mudança em modelagem de processos contábeis. Além disso foram encontrados dilemas, como a reinvenção de modelos de negócios a profissionais autônomos e pequenos escritórios de contabilidade e a insegurança do envelhecimento do profissional frente a TD.
Small and Medium-sized Enterprises (SME's) are prevalent in the South African Industry and have been globally recognized for their contributions to economic development, job creation, poverty alleviation, and innovation. Although SME's are aware and can benefit significantly from digital systems, the time, skills, and finances required to develop SME-specific systems are prohibitive. This is because the ability to define sensor to enterprise systems demands for SME's is dependent on specific needs. The current solutions that are offered to SME's are stand-alone and not integrated. This research provides insights into the engagement and development of a demand-driven SME ecosystem. The research provides insights into the digital system priorities of some 200 South African SME's. Based on the analysis of the survey conducted, the researchers designed and developed the initial four systems for SME's out of the 10 identified. This paper covers the data gathering, design, and delivery phase of the 4 functions.
Full-text available
Today, small and medium-sized enterprises (SMEs) are the bedrock of most economies. Additionally, they have the potential to become the foundation of sustainable economic growth if given the right tools and support. In order to stay competitive, SMEs have to adapt permanently both in products and production. Approaches related to the vision of Industrie 4.0 (I4.0) and Smart Factories can help SMEs to address these challenges. The use cases, implementation examples and recommendations of the “Plattform Industrie 4.0” provide a basis for these approaches. However, the success of these approaches will depend on whether or not SMEs will adopt and implement them. Nevertheless, the barriers for adopting I4.0 approaches and technologies are still high. Specialized research institutions in Germany – so-called I4.0 test environments – have a broad infrastructure for developing and testing I4.0-relevant technologies, such as production machines and equipment or ICT testing facilities.
Full-text available
The digital transformation of people's everyday life is progressing; almost everybody uses connected devices, shares information and builds a network according to the existing preferences or needs. A similar development takes place in the industrial environment, e.g. the IT- and software industry is already organized in deeply connected ecosystems. In ecosystems there are different strategic roles an organization can play, which affects an organization's business strategy. If the firm is aware of this fact, it can adapt its strategy after having analyzed its position in the surrounding ecosystem. The strategy is implemented by an according business model. This business model will cause the active change of the organization's role in the ecosystem and the digitization offers opportunities for implementation. This development is also going to change the traditional manufacturing sector. Thus, the change of the industry logic needs to be integrated into strategic decisions to be competitive in the future. In this paper an approach to handle these developments in the organization's environment is addressed. The model of the ecosystem is transferred to the manufacturing industry. Based on this transfer and analysis, a roadmap for a consistent alignment of a firm in an ecosystem is suggested.
Full-text available
An enterprise architecture tries to describe and control an organisation?'s structure, processes, applications, systems and techniques in an integrated way. The unambiguous specification and description of components and their relationships in such an architecture requires a coherent architecture modelling language. Lankhorst and his co-authors present such an enterprise modelling language that captures the complexity of architectural domains and their relations and allows the construction of integrated enterprise architecture models. They provide architects with concrete instruments that improve their architectural practice. As this is not enough, they additionally present techniques and heuristics for communicating with all relevant stakeholders about these architectures. Since an architecture model is useful not only for providing insight into the current or future situation but can also be used to evaluate the transition from ?as-is? to ?to-be?, the authors also describe analysis methods for assessing both the qualitative impact of changes to an architecture and the quantitative aspects of architectures, such as performance and cost issues. The modelling language and the other techniques presented have been proven in practice in many real-life case studies. So this book is an ideal companion for enterprise IT or business architects in industry as well as for computer or management science students studying the field of enterprise architecture. © Springer-Verlag Berlin Heidelberg 2005. All rights are reserved.
Full-text available
In this article, we offer a broadened view of service innovation-one grounded in service-dominant logic-that transcends the tangible-intangible and producer-consumer divides that have plagued extant research in this area. Such a broadened conceptualization of service innovation emphasizes (1) innovation as a collaborative process occurring in an actor-to-actor (A2A) network, (2) service as the application of specialized competences for the benefit of another actor or the self and as the basis of all exchange, (3) the generativity unleashed by increasing resource liquefaction and resource density, and (4) resource integration as the fundamental way to innovate. Building on these core themes, we offer a tripartite framework of service innovation: (1) service ecosystems, as emergent A2A structures actors create and recreate through their effectual actions and which offer an organizing logic for the actors to exchange service and cocreate value; (2) service platforms, which enhance the efficiency and effectiveness of service exchange by liquefying resources and increasing resource density (facilitating easy access to appropriate resource bundles) and thereby serve as the venue for innovation; and (3) value cocreation, which views value as cocreated by the service offer(er) and the service beneficiary (e.g., customer) through resource integration and indicate the need for mechanisms to support the underlying roles and processes. In discussing these components, we consider the role of information technology-both as an operand resource and as an operant resource- and then examine the implications for research and practice in digitally enabled service innovation.
Full-text available
Over the last three decades, the prevailing view of information technology strategy has been that it is a functional-level strategy that must be aligned with the firm's chosen business strategy. Even within this socalled alignment view, business strategy directed IT strategy. During the last decade, the business infrastructure has become digital with increased interconnections among products, processes, and services. Across many firms spanning different industries and sectors, digital technologies (viewed as combinations of information, computing, communication, and connectivity technologies) are fundamentally transforming business strategies, business processes, firm capabilities, products and services, and key interfirm relationships in extended business networks. Accordingly, we argue that the time is right to rethink the role of IT strategy, from that of a functional-level strategy-aligned but essentially always subordinate to business strategy-to one that reflects a fusion between IT strategy and business strategy. This fusion is herein termed digital business strategy. We identify four key themes to guide our thinking on digital business strategy and help provide a framework to define the next generation of insights. The four themes are (1) the scope of digital business strategy, (2) the scale of digital business strategy, (3) the speed of digital business strategy, and (4) the sources of business value creation and capture in digital business strategy. After elaborating on each of these four themes, we discuss the success metrics and potential performance implications from pursuing a digital business strategy. We also show how the papers in the special issue shed light on digital strategies and offer directions to advance insights and shape future research.
Full-text available
In recent years, firms in almost all industries have conducted a number of initiatives to explore new digital technologies and to exploit their benefits. This frequently involves transformations of key business operations and affects products and processes, as well as organizational structures and management concepts. Companies need to establish management practices to govern these complex transformations. An important approach is to formulate a digital transformation strategy that serves as a central concept to integrate the entire coordination, prioritization, and implementation of digital transformations within a firm. Despite first research efforts and the frequent challenges encountered in practice, academia still lacks specific guidelines for firms on how to formulate, implement, and evaluate digital transformation strategies.
Full-text available
Service-Systems-Engineering (SSE) stellt die systematische Gestaltung und Entwicklung von Servicesystemen in den Mittelpunkt des Forschungsinteresses. Servicesysteme ermöglichen interaktive Wertschöpfung durch eine auf ein Wertversprechen ausgerichtete Konfiguration von Akteuren und Ressourcen. Weil diese Konfiguration unter anderem die Servicearchitektur, die Technologie, die Information und physische Artefakte in der Nutzung einschließt, handelt es sich um soziotechnische Systeme. Die Wirtschaftsinformatik kann mit ihrer interdisziplinären Tradition und Integrationsfähigkeit eine führende Rolle im Verständnis und der Entwicklung dieser Systeme spielen. SSE verdeutlicht das Potenzial, das die Entwicklung anwendbarer Theorien, Methoden und Ansätze der systematischen Gestaltung, Entwicklung und Pilotierung von Servicesystemen besitzt. Dies gilt umso mehr, wenn diese auf einem verbesserten Verständnis der grundlegenden Wirkprinzipien dieser Systeme beruhen. In diesem Zusammenhang stellen sich insbesondere drei zentrale Forschungsherausforderungen: 1.) die Entwicklung von Servicearchitekturen, 2.) die Entwicklung neuer Interaktionsformen mit Servicesystemen sowie 3.) die Mobilisierung von Ressourcen für Servicesysteme. Letzteres bezeichnet eine IT-gestützte Ausweitung des Zugriffs auf und der Nutzung von Ressourcen. Die Forschung in diesem Kontext ist vor allem deshalb herausfordernd, weil die Entwicklung von Modellen, Methoden und Artefakten in Servicesystemen oft die Einbettung in reale oder sogar neuartige Servicesysteme erfordert. Daher erscheinen methodisch vor allem die Pilotierung IT-basierter Innovationen, gestaltungsorientierte Forschung sowie Aktionsforschung sinnvoll. Als eine integrative Disziplin ist die Wirtschaftsinformatik besonders gut positioniert, um die Forschung zur evidenzbasierten Gestaltung der Architekturen, Interaktionen und Ressourcenzugängen von Servicesystemen zu befördern und wichtige Beiträge zu einer Konstruktionslehre für Servicesysteme zu leisten. Abstract Service systems engineering (SSE) focuses on the systematic design and development of service systems. Guided by a value proposition, service systems enable value co-creation through a configuration of actors and resources (often including a service architecture, technology, information, and physical artifacts), therefore constituting complex socio-technical systems. IS research can play a leading role in understanding and developing service systems. SSE calls for research leading to actionable design theories, methods and approaches for systematically designing, developing and piloting service systems, based upon understanding the underlying principles of service systems. Three major challenges have been identified: engineering service architectures, engineering service systems interactions, and engineering resource mobilization, i.e. extending the access to and use of resources by means of IT. Researching SSE is challenging. Assessing the models, methods, or artifacts of SSE often requires embedded research within existing or even novel service systems. Consequently, approaches such as piloting IT-based innovations, design research or action research are the most promising for SSE research. As an integrative discipline, IS is in a unique position to spearhead the efforts in advancing the architecture, interaction, and resource base of service systems with evidence-based design.
Kurzfassung Die nationale Technologieplattform MANUFUTURE © -DE wurde im Jahr 2006 gegründet und vertritt seitdem die Interessen deutscher produzierender Unternehmen bei der Ausgestaltung von nationalen und europäischen Forschungsprogrammen. Unter Federführung des Fraunhofer-Instituts für Produktionstechnik und Automatisierung IPA wird die nationale Plattform in einem vom Bundesministerium für Bildung und Forschung (BMBF) geförderten Projekt seit Beginn 2016 neu positioniert. Dieser Beitrag zeigt die argumentative Herleitung der strategischen Handlungssäulen entlang des industriellen Transformationsprozesses, auf deren Basis prioritäre Forschungsthemen im Hinblick auf die Produktion 2030 identifiziert wurden.
Mit einem Anteil von 22,4 Prozent am Bruttoinlandsprodukt (BIP) ist das produzierende Gewerbe das Rückgrat der deutschen Wirtschaft. (vergl. Bundesministerium für Wirtschaft und Technologie, 2013). Im Vergleich: der Anteil des produzierenden Gewerbes am BIP in den USA liegt bei 11,9 Prozent, in Frankreich und Großbritannien bei 10 Prozent (vergl. Heymann, Vetter, 2013). Jährlich produziert die deutsche Wirtschaft einen enormen Handelsüberschuss. Diese Wettbewerbsfähigkeit der deutschen Industrie war entscheidend, um die Finanz- und Wirtschaftskrisen in der jüngsten Vergangenheit erfolgreich zu bewältigen. Konkurrenzfähiger Industriestandort und führender Fabrikausrüster zu sein, muss jedoch immer wieder aufs Neue erarbeitet werden.