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Action Fields of Digital Transformation - A Review and Comparative Analysis of Digital Transformation Maturity Models and Frameworks


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For many organisations, digital transformation is a strategic priority in order to renew their business and stay competitive. However, managers find it difficult to set and implement digital agendas because they are unsure about the process, topics and setup. In order to provide management with an overview of the most important topics, a literature review has identified eighteen validated digital maturity models and frameworks which describe various dimensions or action fields to be considered for a digital transformation strategy. In a comparative analysis of over one hundred described dimensions, the most often cited dimensions were identified, namely strategy, the organisation, corporate culture, technology, the customer and people (employees). The six identified dimensions/action fields provide an important framework for businesses to succeed in digital transformations.
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Jimmy Bumann, Marc K. Peter
Action Fields of Digital Transformation - A Review and Comparative
Analysis of Digital Transformation maturity Models and Frame-
Digital Transformation, Frameworks, Strategy, Digital Maturity Models, Organization,
Corporate Culture, Technology, Customers, Employers
For many organisations, digital transformation is a strategic priority in order to renew
their business and stay competitive. However, managers find it difficult to set and im-
plement digital agendas because they are unsure about the process, topics and setup.
In order to provide management with an overview of the most important topics, a liter-
ature review has identified eighteen validated digital maturity models and frameworks
which describe various dimensions or action fields to be considered for a digital trans-
formation strategy. In a comparative analysis of over one hundred described dimen-
sions, the most often cited dimensions were identified, namely strategy, the organisa-
tion, corporate culture, technology, the customer and people (employees). The six
identified dimensions/action fields provide an important framework for businesses to
succeed in digital transformations.
Für viele Unternehmen ist die digitale Transformation eine strategische Priorität, um
ihr Geschäft zu erneuern und wettbewerbsfähig zu bleiben. Führungskräfte haben je-
doch Schwierigkeiten bei der Erstellung und Umsetzung digitaler Agenden, da sie be-
züglich Prozess, Themen und Struktur unsicher sind. Um dem Management einen
Überblick über die wichtigsten Themen zugänglich zu machen, hat eine Literaturre-
cherche achtzehn validierte digitale Reifegradmodelle und Konzepte identifiziert, die
verschiedene Dimensionen (oder Handlungsfelder) beschreiben, welche für eine digi-
tale Transformationsstrategie zu berücksichtigen sind. In einer vergleichenden Ana-
lyse von über hundert beschriebenen Dimensionen wurden die am häufigsten
genannten Dimensionen identifiziert, nämlich die Strategie, die Organisation, die Un-
ternehmenskultur, Technologien, die Kundinnen und Kunden sowie die Mitarbeiten-
den. Die sechs identifizierten Dimensionen/Handlungsfelder bieten ein wichtiges Mo-
dell für eine erfolgreiche digitale Unternehmenstransformation.
1 Introduction
Digital technology is an integral part of our society and economy (Andersson et al.,
2018; Gimpel et al., 2018). Across industries, management faces increasing pressure
to make digital transformation a strategic priority and embrace the opportunities pre-
sented by emerging digital technology (Christensen, 1997; Horlacher & Hess, 2016;
Smolinski et al., 2017; Zavolokina, Dolata & Schwabe, 2016). The challenge of digital
transformation goes along with several other challenges such as the changing cus-
tomer behaviour, high regulatory requirements and shrinking margins (Smolinski et al.,
2017). Moreover, new disruptive players for instance FinTech entrepreneurs in the
banking sector - but also established large technology companies attack existing in-
cumbents in virtually all of their services (Accenture, 2015; Grebe et al., 2016; Mead,
2016). Hence, industries and organisations within need to react and adopt to the new
digital challenges. The question for them is not when to make digital transformation a
strategic priority, but how to embrace it and position it as a competitive advantage
(Hess et al., 2016; Van der Zande, 2018).
Unfortunately, many executives still struggle to set and implement digital agendas be-
cause they are unsure about the process, topics and setup (Hebbert, 2017; Peter,
2017; Römer et al., 2017). Bughin & Van Zeebroeck (2017) assert that managers are
aware of the need and urgency to react, but they only have little guidance to determine
the right course of action; and following Hess et al. (2016), they are struggling to keep
up with the new digital reality. A recent study (Bughin & Van Zeebroeck, 2017) con-
firmed that only a small minority of companies are successfully undertaking digital
transformation consistent with a clearly articulated corporate strategy. Furthermore,
Gimpel et al. (2018) revealed that most research output has focused on specific facets
of digital transformation or case-based evidence. However, there seems to be a lack
of an understanding as to what management should investigate and cover when un-
dertaking digital transformation initiatives. This lack of an integrated approach to
develop a company-wide digital transformation strategy is likewise identified by Hess
et al. (2016); Hyvönen (2018) and Ismail, Khater & Zaki (2017).
A few researchers such as Gimpel et al. (2018); Peter (2017) and Valdez-De-Leon
(2016) made attempts to close this gap by proposing well-founded, cross-industry
frameworks of action fields for digital transformation. Gimpel et al. (2018) argue that
the relevance of the action fields strongly depends on industry and company specific
On the practical side, consulting firms have published several practice-oriented publi-
cations about digital transformation. This also includes digital maturity models which
assess the digital maturity of an organisation without, in many cases, proposing con-
crete actions to enhance their digital maturity. On the academic side, however, re-
search insights in this field are limited (Gsell, 2017). This research gap leads to the
enquiry into the identification and validation of the dimensions or rather action fields of
digital transformation.
2. Digitisation, Digitalisation and Digital Transformation
In the wider field of digital transformation, additional terms appear next in the literature,
including “digitisation” and “digitalisation”. Although the three concepts have distinct
meanings, they often are used interchangeably as research confirmed (Bloomberg,
2018). While Bounfour (2016) has already revealed a lack of clear definitions, Unruh
& Kiron (2017) assert that no consensus on the difference of these terms exist and
their definition strongly hinge on the person or organisation using them. Literature tries
to describe the three terms based on their scope (i.e. a narrow to broad perspective).
The first phase of transformation is described as digitisation, which Maltaverne (2017)
refers to as “the conversion from analogue to digital” (e.g. digitisation of data). Digital-
isation is the second phase and means “the process of using digital technology and
the impact it has” (e.g. digitalisation of a process). Unruh & Kiron (2017) have a similar
understanding and describe digitalisation as “the innovation of business models and
processes that exploit digital opportunities”.
Finally, digital transformation is the broadest of the three terms and encompasses the
whole enterprise, not just a specific process. Maltaverne (2017) describes it as the
designing of “new ways of doing things that generate new sources of value”. According
to Unruh & Kiron (2017) it is “[…] a systems-level transition that alters behaviours on a
large scale” and it arises when new digital business models and processes restructure
economies. Digital transformation is customer-driven and requires cross-cutting organ-
isational change along with the implementation of digital technologies (Bloomberg,
2018; Peter, 2017). Reddy and Reinartz (2017) define digital transformation as “[…]
the use of computer and internet technology for a more efficient and effective economic
value creation process” and in a broader sense “[…] it refers to the changes that new
technology has on the whole; on how we operate, interact, and configure, and how
wealth is created within this system”. Hebbert (2017) also asserts the dissimilarity of
different definitions and in her opinion, real digital transformation is “[…] about a com-
pany’s ability to react and successfully utilise new technologies and procedures – now
and in the future”. The three terms/concepts are summarised and visualised in figure 1.
Fig. 1: Definition of Digitisation, Digitalisation and Digital Transformation (based on Maltaverne, 2017)
Digital transformation, which is the focus of this book chapter, offers great opportunities
and simultaneously high risk for organisations (Moreno et al., 2015). Bughin & Van
Zeebroeck (2017) point out that organisations which don’t react to digital disruption, or
only partially, are very likely to take major hits on their revenue and profits.
In order to plan and execute digital transformation, organisations must have a clear
strategy and place “digital” at the heart of their business strategies (Gill & Vanboskirk,
2016). Ismail, Khater & Zaki (2017) and Kane et al. (2015) argue that several studies
of success stories revealed that the enhanced competitive positioning of successful
companies do primarily depend on strategies which their leaders deploy and only sec-
ondarily on the technologies they adopt. Therefore, digital transformation is driven by
strategy, not technology. McKeown & Philip (2003) stated a while ago that business
transformation is an overarching concept which incorporates several competitive strat-
egies that companies must adopt if they want to bring significant improvements in busi-
ness performance A few researchers (Hess et al., 2016; Ismail, Khater & Zaki, 2017;
Matt, Hess & Benlian, 2015; McDonald, 2012; Singh & Hess, 2017) even contemplate
that such an important and challenging strategic topic as digital transformation requires
a standalone strategy which is not part of any other functional or organisational strat-
egy. Such a company-wide overarching digital transformation strategy goes beyond
functional thinking and holistically addresses the opportunities as well as the risks orig-
inating from digital technologies (Singh & Hess, 2017). Moreover, such a strategy will
support organisations in their digital transformation journey and it can act as an unifying
concept to coordinate, prioritise and implement all of the digital transformation efforts
(Hess et al., 2016; Singh & Hess, 2017). Hence, Ismail, Khater & Zaki (2017) propose
to position digital transformation at the level of a business strategy. It is argued that
this should permit organisations to incorporate the numerous opportunities presented
in the digital environment in a way which is difficult for competitors to replicate (Ismail,
Khater & Zaki 2017; Ross, Sebastian & Beath, 2017). Figure 2 visualises the position-
ing of the digital transformation strategy in the context of business and functional strat-
Fig. 2: Positioning of Digital Transformation Strategy (based on Ismail, Khater & Zaki, 2017)
3 Review of Digital Transformation Frameworks
Becker, Knackstedt & Pöppelbuss (2009) assert that although many maturity models
have been developed in recent years, the procedures and methods that led to these
models have been vaguely documented. Therefore, the authors tried to develop a
manual for methodically well-designed maturity models. Their seven-step development
process was applied and further developed to a four-step process by Egeli (2016) and
Neff et al. (2014). Unless maturity models which aim to assess the digital maturity of
organisations, the envisaged framework with action fields should rather propose differ-
ent dimensions, which then will be analysed to define different actions or strategies
that help organisations to conduct a successful transformation. Most maturity models
are also divided into different dimensions or action fields. The methodology for the
development and identification of a generic and supported digital transformation frame-
work partly relates to a simplified methodological approach suggested by Becker,
Knackstedt & Pöppelbuss (2009), Egeli (2016) and Neff et al. (2014).
The first step of the literature review consists of the problem identification: The need
and practical relevance for a wider and validated (i.e. grounded) digital transformation
framework has already been discussed before. For the second step, existing digital
maturity models and transformation frameworks shall be identified. Here, a literature
review has revealed existing digital transformation frameworks. According to Webster
& Watson (2002) a structured approach consists of the querying of leading scholarly
databases using different keywords and includes backward and forward searches on
the basis of relevant articles. Following the literature review, these models and frame-
works shall then be compared and evaluated regarding their dimensions. In the third
step, a new framework shall be defined according to the results of the comparison, i.e.
comparative analysis. For each defined dimension, an additional literature review will
help to determine and describe the sub-dimensions. In the fourth and final step, the
framework shall be validated in the market. This book chapter covers sections one to
three, while the framework validation is still ongoing.
The literature review resulted in almost one hundred articles about digital transfor-
mation maturity models and frameworks. Only those from peer-reviewed journals and
where the dimensions were validated though research were considered for further
analysis. This resulted in a total of eighteen articles. The models and frameworks vary
in terms of origin, industry limitation (if any), and their academic or practical background
and/or purpose. In addition, the rather heterogeneous frameworks strongly varied in
terms of the amount of information disclosed. Some frameworks such as Berghaus,
Back & Kaltenrieder (2017) or Schäfer et al. (2015) included broad and deep infor-
mation about the sub-categories and the methodological approach, whereas other au-
thors decided to only disclose a small amount of information. For a framework to be
considered as a relevant one for the purpose of a comparative analysis, the relevant
authors had to provide an elaborate maturity model or framework. Moreover, the frame-
work either had to stem from researchers or from organisations with a sound reputa-
tion, such as international consultancy firms. For the comparative analysis, a concept-
matrix – as suggested by Webster & Watson (2002) – has been employed. The major-
ity of frameworks are maturity models which aim to assess the digital maturity of an
organisation either with a self-assessment or with an assessment through a third party,
where some frameworks purely provide an overview for digital transformation topics.
The first reviewed model from Anderson & William (2018) describe Deloitte’s digital
maturity model, which focuses on the telecommunications industry. The model evalu-
ates digital capabilities across five clearly defined business dimensions to create a
wider view of digital maturity across the organisation. The dimensions include strategy,
technology, operations, organisation and culture, along with the customer. The model
provides guidelines for a clear path throughout the transformation journey. A similar,
but cross-industry digital maturity model from the University of St. Gallen and Cross-
walk is described by Berghaus, Back & Kaltenrieder (2017): Since its launch in 2014,
the two parties have been examining the digital maturity of organisations in Switzer-
land, Germany and Austria. It is a self-assessment survey which comprises of nine
dimensions, including the customer experience, product innovation, strategy, the or-
ganisation, process digitisation, collaboration, information technology, culture and ex-
pertise, and transformation management. A third digital maturity model is provided by
De Carolis et al. (2017): The digital readiness assessment maturity model relates to
the manufacturing industry and includes four different dimensions, which assess vari-
ous areas in which manufacturing key processes can be grouped. The analysis dimen-
sions in this model include process, monitoring and control, technology, and the organ-
isation. Finally, Gill & Vanboskirk (2016) present the cross-industry Forrester digital
maturity model 4.0: The model helps organisations to assess their overall digital read-
iness across the four dimensions of culture, technology, the organisation, and insights.
Forrester reviews and updates the model periodically for continued relevance and ac-
Gimpel et al. (2018) provide a framework of action fields for cross-industry application.
This digital transformation framework consists of six actions fields, including the cus-
tomer, the value proposition, operations, data, the organisation and transformation
management. Moreover, each action field includes four action items. The action fields
of customer and value proposition take an external perspective, whereas operations
and the organisation take an internal view. The action field data links both perspectives,
whereas transformation management addresses how to progress from an “as-is” to a
digitally enhanced “to-be” state. By considering these action fields, organisations will
ensure that they develop a wider yet concrete perspective on digital transformation.
Here, Gunsberg et al. (2018) describe an organisational agility maturity model for uni-
versities. The authors identified the baseline model required to measure whole-of-or-
ganisation agility. The authors completed a qualitative single case study within a uni-
versity. The following high-level categories are considered: Leadership and manage-
ment, innovation, strategy, culture, learning and change, along with structure. Isaev,
Korovkina & Tabakova (2018) provide a cross-industry company readiness evaluation
for digital business transformations. Their quantitative model evaluates the current
state/readiness of an organisation’s IT department in terms of digital transformation
since this will determine the organisation’s overall potential for further development.
Seven dimensions were determined which influence the overall success, including
strategy, the organisation, relationships with users, partnerships, operations, technol-
ogies, and innovation.
Another cross-industry model, derived in collaboration with Deloitte, is presented by
Kane et al. (2016). The authors suggest a model which aligns culture, people, structure
and tasks so that executives can effectively address the challenges of a constantly
changing digital landscape. They also describe the strategy dimension as a separate
component. For the telecommunications industry, Newman (2017) presents a practical
approach to transformation, backed by global advisory firms. The model can be used
to provide a snapshot of an organisation, identify possible investment priorities and
manage the journey itself. The model has five dimensions, including the customer,
strategy, technology, operations, culture, people and the organisation. From Forrester,
in collaboration with Huawei, Roland Berger, SAP and others, Open Roads (2017)
provides a cross-industry “Open Digital Maturity Model” tool. It enables organisations
to benchmark their current digital status against their aspirations and other relevant
parties. The intended outcome of an assessment are measurable goals that will help
the assessed organisation accelerate its digital transformation progress. The six di-
mensions include strategic dynamism, digital culture, talent and skills, the optimal cus-
tomer experience, data centricity, service innovation and optimized delivery, and digital
technology leadership.
A Swiss study (Peter, 2017) aimed to reveal the current situation of digital transfor-
mation within Swiss organisations. It enabled the identification of seven cross-industry
action fields. They include customer centricity, digital business development, digital
leadership and culture, process engineering, digital marketing, new technologies,
along with the cloud and data. A separate digital maturity assessment and transfor-
mation canvas for strategy workshops, based on the seven action fields, are available.
A broad German cross-industry digital maturity model is described by Peyman et al.
(2014) and Schäfer et al. (2015): Their model consists of thirty-two individual criteria in
eight dimensions. The dimensions include strategy, leadership, products, operations,
culture, people, governance, and technology. The model provides an excellent basis
for organisations to classify themselves into a category of digital maturity. However, it
does not provide any guidance to increase the maturity level of an organisation. A
practical cross-industry model is presented by Rogers (2016) with a Digital Transfor-
mation Playbook. According to Rogers, digital forces reshape five key domains of strat-
egy, which include customers, competition, data, innovation and value. These five do-
mains describe the landscape of digital transformation. Here, digital technologies are
redefining many of the underlying principles of strategy and changing the rules by
which organisations must operate in order to succeed.
For the manufacturing industry, the digital future readiness transformation model pre-
sented by Schlaepfer et al. (2017) aims to reflect the current level of readiness of Swiss
consumer businesses and industrial organisations for the digital future. The model was
developed via face-to-face interviews with senior management of Swiss manufacturing
firms. To determine the future readiness of an organisation, they defined four dimen-
sions in the transformational model: The organisation, the culture, people and the dig-
ital environment. Schumacher, Erol & Sihn (2016) also describe a maturity model for
Industry 4.0 readiness and maturity for the manufacturing industry. The empirically
grounded maturity model encompasses nine dimensions and sixty-two items to be as-
sessed. The nine dimensions include products, customers, operations and technology
in order to assess the basic enablers, while strategy, leadership, governance, culture
and people allow for the inclusion of organisational aspects into the assessment.
Valdez-De-Leon (2016) presents a digital maturity model for the telecommunications
industry. The model aims to offer a structured view of digital transformation that can
help organisations to benchmark themselves against peers as they advance their
transformation. The model includes the seven dimensions of strategy, organisation,
culture, value chain/eco-system, operations, technology, and innovation. A cross-in-
dustry digital readiness assessment is provided by Wallner (2016) in collaboration with
2b Ahead and KPMG: It’s aim is to provide an accurate picture of an organisation’s
digital readiness, portrayed in seven key areas. They include strategy, culture, moni-
toring, customers, the organisation and control, technology management, as well as
people and capabilities. Finally, Westerman et al. (2011) describe a cross-industry dig-
ital transformation roadmap for “billion-dollar organisations”, supported by Capgemini
Consulting. They propose a framework which consists of three building blocks, includ-
ing the customer experience, operational processes, and business models.
The eighteen identified models and frameworks include 115 dimensions (an average
of six per model/framework). Table 1 provides an overview of the models/frameworks
and their dimensions/action fields.
Table 1: Comparison of existing Digital Transformation Models and Frameworks (own illustration)
The analysis identifies the six most applied dimensions/action fields, namely technol-
ogy, culture (in 13 models/frameworks), technology (12), strategy (11), organisation
(10), customer/s (10) and people/employees (9). The threshold was defined at 40%,
meaning that these dimensions appear in at least 40% of the total group of frameworks
and models, or in other words, in almost every second framework.
While three models cover all six dimensions (Berghaus et al., 2017; Newman, 2017;
and Wallner, 2016), other wider models such as Anderson & William (2018), Open
Roads (2017) and Schumacher, Erol & Sihn (2016) incorporate five of them, but in
exchange they additionally cover other action fields/dimensions such as leadership,
governance, innovation, or data centricity. Further often applied dimensions include
operations, innovation, products, and leadership. The results depict that in average,
6.4 action fields/dimensions are covered. With nine different dimensions (or eleven,
depending on the definition), the model from the University of St. Gallen and Crosswalk
(2017) covers most dimensions. On the other hand, the oldest model from 2011, cre-
ated by the MIT Center for Digital Business and Capgemini Consulting, includes three
“building blocks”.
Since each model has its unique characteristics, strength and weaknesses, the com-
parison led to several challenges. Firstly, some models used a certain topic as a main
dimension whereas others used it indirectly as well, but only as a sub-dimension. For
instance, researchers like Isaev, Korovkina & Tabakova (2018) or Valdez-De-Leon
(2016) used “eco-systems and partnerships” as a dimension, whereas other authors
defined it as a sub-category of another dimension. Anderson & William (2018) consider
eco-systems under the strategy dimension, whereas Schlaepfer et al. (2017) catego-
rise eco-systems under the organisation dimension. Since the aim of this comparison
was to identify the most frequently used top dimensions, the concept-matrix generally
only covered the high-level dimensions of each framework/model and neglected the
Secondly, for certain dimensions with the same meaning, slightly different terms were
used by different authors. For instance, dimensions such as information technology
(Berghaus et al., 2017) and technology management (Wallner, 2016) were summa-
rized in the technology dimension. This also refers to other examples such as customer
centricity (Peter, 2017) or customer experience (Berghaus et al., 2017; Open Roads,
2017) which were combined in the customer dimension. On the other hand, several
authors aggregated different topics in one dimension. For instance, Anderson & Wil-
liam (2018) combined organisation and culture, Peter (2017) combined digital leade-
rship and culture, and Berghaus et al. (2017) combined culture and expertise. In order
to increase comparability and consistency levels, in such cases, both terms were con-
sidered separately since other authors listed the terms individually. In the last case,
expertise was first listed as a new additional dimension. However, the author later re-
vealed that the people dimension mainly refers to capabilities and skills of employees.
Thus, expertise was consequently also moved into this dimension. The comparative
analysis was therefore also an iterative process.
And finally, most models and frameworks are generic, similar to these of a general
business model canvas, while others, for instance Gill & Vanboskirk (2016), Gimpel et
al. (2018), Gunsberg et al. (2018), Peter (2017), Rogers (2016), Schlaepfer et al.
(2017) and Westerman et al. (2011), include digital transformation specific dimensions,
which are, in many cases, new to the portfolio of pre-digital area management topics.
4 Digital Transformation Action Fields
As identified in the comparative analysis, six action fields/dimensions are dominating
a potential generic cross-industry digital transformation framework. The framework di-
mensions include business strategy, the organisation, culture, technology, the cus-
tomer, and people (figure 3).
Fig. 3: Digital Transformation Framework (own illustration)
This section defines and describes each action field/dimension and reveals how differ-
ent activities can support organisations on their digital transformation journey. In order
to determine the relevant content of each action field/dimension, the sub-dimensions
of the comparison matrix of models and frameworks were also considered.
The literature revealed theoretical concepts regarding strategy and pinpoints the im-
portance of building a sophisticated digital strategy for successful digital transfor-
mation. However, the review also showed a prevailing disagreement in research about
what kind of strategy is required and where to position it. While some researchers (e.g.
Chan & Reich, 2007; Luftman, 1999; Sabherwal & Chan, 2001) support the traditional
alignment view which claims that IT strategy is a subordinated functional-level strategy
that must be aligned with the firm’s business strategy, other researchers in later publi-
cations argue that it requires a digital business strategy which reflects a fusion between
IT and business strategy (e.g. Bharadwaj et al., 2013). A third group (e.g. Hess et al.,
2016; Ismail, Khater & Zaki (2017) even proclaims that such an important topic requires
a separate overarching digital transformation strategy which is not part of any other or
functional or organisational strategy and coordinates the many independent drivers of
digital transformation.
Although several different views prevail, the literature agrees on the imperative of a
formulated digital strategy. Researchers of other digital transformation models assert
that digital strategies of successfully transformed organisations are not only well doc-
umented, but also communicated in the organisation and internalised by employees of
all levels. Furthermore, the availability of sufficient resources must be ensured and the
strategy should be regularly updated and put to the test (Kane et al., 2016; Peyman et
al., 2014; Schumacher, Erol & Sihn, 2016). It is the duty of management to communi-
cate the developed vision and strategy to the organisation and to provide the neces-
sary support to implement the transformation roadmap (Svahn et al., 2017). Moreover,
organisations should pro-actively and systematically explore and evaluate new trends
(e.g. technologies and customer behaviour) in order to identify new business opportu-
nities (Berghaus et al., 2017; De Carolis et al., 2017) and thus, provide input to strategy
Berghaus et al. (2017) and Schlaepfer et al. (2017) consider partnerships and eco-
systems an important element of this dimension (it could be argued that they also be-
long to the strategy dimension, however, they are more closely aligned to the organi-
sational set-up, as for instance described by Schlaepfer et al. (2017)). Hence, organi-
sations must embrace a collaborative and partnership driven approach by actively pur-
suing and fostering respectful relationships with various stakeholders (Dintrans et al.,
2017). While initially seen as competitors, partnerships should leverage each other’s
numerous strengths to meet increasing customer needs, but organisations must en-
sure that they can add their own added value to retain control over the customer rela-
tionship (Bose, Price & Bastid, 2018; Dintrans et al., 2017). For Gimpel et al. (2018),
this dimension also encompasses the organisation’s agility, which refers to its ability to
respond quickly to changes in the technology or market environment. Here, organisa-
tions should move away from traditional hierarchies and embrace leaner and flatter
organisational structures which empowers employees and allow greater agility and
faster decision making (WEF, 2016).
In recent years, many organisations also established the role of Chief Digital Officer
(CDO) to spearhead the digital transformation journey. Other researchers argue that
the organisation must also enable and encourage cross-functional collaboration within
the firm (Gill & Vanboskirk, 2016; Gunsberg et al., 2018; Schumacher et al., 2016).
Furthermore, organisations should engage in corporate venturing and create small in-
novative units (e.g. innovation labs or digital factories) which reduces time to market
(Schlaepfer et al., 2017). This means that cross-functional teams (e.g. developers, IT
experts, designers and product owners) come together in an organisational construct
known as “digital factory” to build something new for the organisation by working in
agile sprints and using methodologies such as design thinking. They constantly test,
refine and iterate the product and finally integrate it into the broader business (Bhapkar
& Dias, 2017). It is evident that in the organisation dimension, there is a strong link to
culture, as described in the next section.
Corporate culture and its focus on the future play a pivotal role for successful digital
transformation. Hofstede, Hofstede & Minkov (2010) define organisational culture as
“[…] the collective programming of the mind that distinguishes the members of one
organisation from others”. Schlaepfer et al. (2017) suggest to create a “passionate pi-
oneer culture”, allowing employees to pursue ideas in a interdiciplinary and decentral-
ised way and organise their own activities. A study (Kane et al., 2016) revealed that
the organisational cultures of digitally maturing firms all have common characteristics
such as rapid experimentation, an expanded appetite for risk, and an investment in
talent. In addition, they value soft skills in leaders more than technical strength. These
features are supported by Schlaepfer et al. (2017) who claim that company culture
must allow freedom to experiment, room for creativity and continous try-outs. This is
often referred as a “fail forward culture”, meaning that the culture allows to experiment
and to then learn from mistakes. However, the establishment of such a culture requires
a strong and continuous commitment from the board and C-level executives which
must back the digital strategy (Andriole, 2017; Gill & Vanboskirk, 2016). Hence, suc-
cesful digital transformation requires strong digital leaders which are not imperatively
high-tech wizards, but have the ability to manage complexity, inspire and develop dis-
tinct digital cultures conducive to success and promote the development of innovative
digital solutions despite investment risks (Berghaus et al., 2017; Gill & Vanboskirk,
2016; Kane et al., 2016).
Hess et al. (2016) confirmed that an essential dimension of digital transformation strat-
egy is the organisation’s approach to the use of new digital technologies. While market
followers apply widely validated technology solutions, market leaders explore and ex-
ploit emerging technology such as artificial intelligence, machine learning, the block-
chain or the Internet of Things (Hess et al., 2016; Ismail, Khater & Zaki, 2017). There-
fore, the technology dimension focuses on the organisation’s use and adoption of
emerging technologies. Gill & Vanboskirk (2016) suggest in their model that firms
should have a collaborative, flexible and iterative approach towards technology devel-
opment and leverage modern architectures such as the cloud and application program-
ming interfaces (APIs) to promote flexibility as well as speed. The use of APIs enables
organisations to incorporate state-of-the art technology from the eco-system into the
key areas in which partnerships are required (Nienaber, 2016). Berghaus et al. (2017)
and Gill & Vanboskirk (2016) consider the flexibility to shift priorities and teams an
important factor in the technology dimension. However, many organisations face the
challenge of legacy IT systems which are often at the heart of the IT infrastructure,
which hinder organisations in their innovation endeavour and damage their agility
(Rosner, 2018). While some organisations tackle the herculean task to digitise to the
core and reduce their dependencies, other firms just “put on digital lipstick” (Vinayak,
2018) by delivering new front-end systems and a well-designed website. A recent study
within the Swiss banking industry found that only 58% of them are convinced that their
existing IT architecture is "fit enough" to master the challenges of the future (Schwaller
et al., 2019). With growing threats of cybercrime, IT security becomes increasingly im-
portant for organisations. Hence, employees should strictly adhere to IT security rules
and organisations test various threat scenarios to ensure IT operations and data avail-
ability (Berghaus et al., 2017).
The changing customer behaviour and increasing popularity of digital channels force
organisations to bridge the digital and physical world by offering seamless hybrid inter-
action channels (Gasser et al., 2018; Nüesch, Alt & Puschmann, 2015; Puschmann,
2017). This means that customers should have the possibility to interact with organi-
sations either through classical or digital channels and therefore, organisations must
ensure a content consistent and channel appropriate designed customer experience
on all digital and non-digital channels (Berghaus et al., 2017; Peter, 2017). Although
more and more services can be fully completed online, most organisations only take
one step at a time and focus on digitising existing products, rather than to provide new,
innovative services (Ehlerding et al., 2018). Moreover, organisations should harness
the benefits of digital technologies by collecting customer data and using customer
insights, for instance to predict customer behaviour and to provide tailored and per-
sonalised products and services with a better customer experience (Anderson & Wil-
liam, 2018; Berghaus et al., 2017; Gimpel et al., 2018; Schumacher et al., 2016). Here,
Von Leipzig et al. (2017) state that today’s customers do not only expect organisations
to react to their demands, but they even expect them to anticipate their future needs
before they identify those themselves. Finally, Gimpel et al. (2018) suggest that organ-
isations should involve customers in the innovation and product development process.
The people dimension particularly encompasses the employee with their skills and ca-
pabilities. Andersson et al. (2018) argue that apart from the many technological re-
sources which are necessary for successful digital transformation, it also requires new
human skills and experiences with different digital technologies. Cascio & Montealegre
(2016) assert an increasing skills gap between the existing labour force and the skills
required to compete in a VUCA world (a volatile, uncertain, complex and ambiguous
world). A large study conducted by the World Economic Forum (WEF) predicts and
increasing skills demand for cognitive abilities, systems skills and complex problem-
solving skills for the near future (WEF, 2016b). Hence, organisations must develop and
implement appropriate training schemes and educate, train and develop digital skills
as well as entirely new skills to reinforce the employability and personal development
of their employees (Mettling & Barré, 2016; Schlaepfer et al., 2017). Organisations
should also rethink the way training is executed and offer a broad range of training
options such as employee boot camps, hackathons, massive online courses, and ro-
tation opportunities (WEF, 2016). Dreischmeier, Close & Trichet (2015) claim that lead-
ing players actively pursue collaboration with universities, incubators and other institu-
tions in order to gain access to critical talents. In a global study, 76% of the digitally
maturing organisations indicated that they provide their employees with resources and
training opportunities to develop digital acumen, which demonstrates the importance
of talent development for a successful transformation (Kane et al., 2016). Moreover,
organisations should create an attractive and flexible workplace of the future. This
could be achieved by offering home office, mobile working, desk sharing and digital
workspaces which increases employee motivation, decreases infrastructure cost and
in turn, helps attracting digital savvy millennials (Schlaepfer et al., 2017; WEF, 2016).
In summary, the six action fields or dimensions of digital transformation, as unveiled
by the literature review, provide a framework for organisations to master their digital
transformation journey. Figure 4 summarises the identified dimensions/action fields
and developed framework by further specifying the sub-dimension.
Fig. 4: Digital Transformation Framework with Sub-Dimensions (own illustration)
5 Conclusion
Digital transformation requires cross-cutting organisational change along with the im-
plementation of digital technologies. To validate these and other important dimensions
for successful digital transformation, this literature review identified and analysed eight-
een confirmed digital maturity models and frameworks which describe various dimen-
sions that shall be considered for a digital transformation strategy. A comparative anal-
ysis of over one hundred described dimensions identified the most often cited dimen-
sions, namely strategy, organisation, corporate culture, technology, the customer/s
and people/employees. These six action fields, together with optional additional dimen-
sions, should therefore be discussed in all digital transformation strategies.
The task was challenging since some models defined (or labelled) a certain topic as a
main dimension whereas others used it as well, but only as a sub-dimension. In addi-
tion, for some dimensions with the same meaning, slightly different terms were used
in the identified literature.
Finally, many frameworks and models are generic, similar to those of a general busi-
ness strategy or business model canvas, while others include digital transformation
specific dimensions, which are additions to the existing topics previously discussed in
business strategy development and implementation. This means that organisations
need to decide whether they want to completely redefine their strategy (which leads to
the application of more generic models) or confirm and/or enrich their existing strategy
with the digital topics of the new, digital area.
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... When the SAIs' ecosystem is affected by a technological-driven change, they may or may not respond to that by adapting and innovating to meet up new societal demands. DT is a holistic approach to change involving not only the technology but also other nontechnological aspects such as strategy, organizational culture, and leadership (Bumann & Peter, 2019, 2016. ...
... Drawing from the available DT literature (Bumann & Peter, 2019;Parker et al., 2016;Verhoef et al., 2021) and sociotechnical theory (Leavitt, 1965;Clark, 1972;Bostrom & Heinen, 1977;Nograšek & Vintar, 2014), we derived the following DT framework (Figure 1). Sociotechnical theory, for example, suggests that to digitally transform an organization, it must consider the different relationships between the different subsystems of an organization (Leavitt, 1965). ...
... The five elements of the DT framework need to be considered with a holistic approach (Bumann & Peter, 2019;Parker et al., 2016), taking into consideration not only the technological aspects but mostly the other nontechnological ones and the existing interrelations. ...
The ongoing transformation of supreme audit institutions (SAIs) external environment is changing the demands and expectations of its stakeholders. The changing environment triggered by technological advancements, increased demand for accountability, and transparency means a change in the way auditing is done. The literature provides evidence of an ongoing technological innovation within the private sector audit. Private sector auditing research has focused mainly on technology adoption and use failing to address the umbrella concept of digital transformation (DT), some even consider processes of DT such as technology adoption and use to be DT. The public sector auditing literature is still yet to commence DT‐related research. This study seeks to fill in this gap and after presenting what DT entails, we applied an exploratory approach through semistructured interview responses, together with other documents from SAIs, to understand how SAIs currently perceive DT and what are their current reactions or actions to transform. The paper analyzes and discusses how SAIs perceive and define the DT phenomenon. The results show that most SAIs still do not master the concept of DT, as they often refer to technology adoption or automation of auditing processes to be DT, notwithstanding a great majority acknowledges the need for DT but lacks the right strategy and resources in place. We saw a few proactive SAIs who are futuristic on the contrary a majority are reacting to change when the need arises, especially during the audit process. The paper provides one of the first empirical investigations into the current DT of public audits. It also proposes a general framework suitable for analyzing the factors involved in the DT in SAIs.
... Now, the topical issue of numerous studies of researchers, economists, public and state specialists, etc. is developing of the digital transformation, through which it will be possible to determine the digital transformation strategies and ways to implement them. Such issues for the digital transformation of various areas are actively explored by the following researchers as J. Bumann [51], M.K. Peter [51] (general research), M.W. Wildan [52], A.I. Umri [52], H.U. Hashim [52], A.R.A. Dahlan [52] (economy, business), J.M. Pawlowski [28], A. Rof [53], A. Bikfalvi [53], P. Marqus [53], T. Muluk [54], T. Nanaeva [55], D. Nguyen [56] (education), I. Mergel [57], N. Edelmann [57], N. Haug [57] (public administration) and others. ...
... Now, the topical issue of numerous studies of researchers, economists, public and state specialists, etc. is developing of the digital transformation, through which it will be possible to determine the digital transformation strategies and ways to implement them. Such issues for the digital transformation of various areas are actively explored by the following researchers as J. Bumann [51], M.K. Peter [51] (general research), M.W. Wildan [52], A.I. Umri [52], H.U. Hashim [52], A.R.A. Dahlan [52] (economy, business), J.M. Pawlowski [28], A. Rof [53], A. Bikfalvi [53], P. Marqus [53], T. Muluk [54], T. Nanaeva [55], D. Nguyen [56] (education), I. Mergel [57], N. Edelmann [57], N. Haug [57] (public administration) and others. ...
... Based on the analysis of the considered researches [28,[51][52][53][54][56][57][58] the authors of this paper proposed a general model of digital transformation ( figure 10). ...
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The paper is devoted to the analysis of the digital transformation processes that are currently taking place in the economy, production, education and society as a whole. The main reason digital transformation is impact of the digital technologies. Modern digital technologies, services and systems are extremely important for social development. One of the key issues for the implementation of digital transformation is changes in the way of thinking and requirements for the competencies of workers in the industry. First of all, it is connected with people's understanding of digital transformation processes and with their ability to use digital technologies effectively. For specifying Ukrainian educators' awareness level about digital transformation processes, there were conducted survey. Research results have shown that there is a need to increase their awareness level about digital transformation processes. Based on the analysis of the considered researches the authors have developed a generalized model of digital transformation for enterprises, businesses and educational institutions.
... A comparison of eighteen digital transformation frameworks and models with 115 dimensions [22] revealed six strategic action fields of digital transformation, namely (1) strategy (the importance of building a sophisticated digital strategy for successful digital transformation), (2) organization (a collaborative and partnership driven approach by actively pursuing and fostering respectful relationships with various stakeholders), (3) culture (with digital leaders who have the ability to manage complexity, inspire and develop distinct digital cultures conducive to success and promote the development of innovative digital solutions despite investment risks), (4) technology (the organization's approach to the use of new digital technologies), (5) customer (the changing customer behavior around digital requirements), and (6) people (the organization's employees with their skills and capabilities). ...
Associative business structures (business associations) and non-associative business structures (those without any formal or juridical associative agreement) provide platforms to share knowledge, gain insights and collaborate. One additional benefit to participate in these structures is the opportunity for business development. In some cases, and especially for SME, they provide important market opportunities and access to relevant stakeholders. A literature review aimed to identify the concepts described about associative and non-associative business structures in the context of the digital age and digital transformation. The most often referenced concepts (business networks/business relationships, the diversity of actors in a network/business ecosystems, innovative networks, and stakeholder networks/business associations) and not yet prominent concepts (digital associations/digital networks, digital ecosystems/digital environment and digital entrepreneurship, e-markets/e-business environment and e-clusters/e-hubs/digital innovation hubs) provide input and ideas of how associative business structures could be supportive and relevant on the SME business development journey in the digital era.
... Results of the study further showed that over 12 months, approximately 48 percent of decision-makers state that adopting emerging technology is the main strategic goal of their company while raising productivity by 41 percent and enhancing safety by 34 percent. Bumann & Peter (2016), confirmed that technological advancement has a far-reaching impact on digital disruption since big data and clouding dramatically reduce digital disruption-related costs. also noted that technology advances can provide significant value that is not associated with work replacement which can allow companies to find new ways to identify customer needs, enhance operations through the use of predictive maintenance software, optimize work documentation and react quickly to changes that affect product quality. ...
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The purpose of this research was to determine the impact of advancement of technology, competitive pressure, and user expectation on continues digital disruption using perceive ease of use role as a mediator. This study proposed a conceptual framework to investigating the significant factors of the various variables through critical evaluation of associated theoretical models, literature studies, and empirical tests. The proposed conceptual framework examined 292 final samples from targeted populations aged 18 years or older, working with digital technologies in Kuala Lumpur, Malaysia, using a positivism research philosophy and explanatory research design. The Survey questionnaires collected were extensively tested for reliability and validity. Empirical data were analyzed using “Exploratory Factor Analysis” (EFA), “Confirmatory Factor Analysis” (CFA), and “Structural Equation Modeling” (SEM) via AMOS 22 software. Research findings indicate that advancement of technology has an insignificant negative impact on continuous digital disruption. User expectation has a positive, negligible effect on digital disruption. However, competitive pressure showed a negative impact on continuous digital disruption. The role of perceived ease of use as a mediator on continuous digital disruption indicated a positively negligible impact. Perceived ease of use role as a mediator on competitive pressure and user expectations showed a positive marginal effect. Lastly, perceived ease of use as a mediator for advancement of technology was negatively insignificant. In conclusion, all the hypotheses proposed were rejected based on these findings, except for hypothesis (H2). The main contribution of this paper was to determine the actual factors contributing to the unceasing digital disruption in organizations and institutions and also identify the correlation between advancement of technology, user expectations, and competitive pressure on continuous digital disruption, using perceive ease of use role as a mediator. Keywords Advancement of Technology, Competitive Pressure, User Expectation, Continuous Digital Disruption, Digitalization, Digital Technologies, Perceive Ease of Use
... A conceptual digital transformation framework in the context of the mining sector Source: Developed by authors adapting [18][19][20] With reference to the summarized literature, four key action fields or managerial dimensions can be distinguished to be included in a cross-industry digital transformation framework: digital business strategy, technologies and business processes at the firm level, /202131504006 E3S Web of Conferences 315, 04006 (2021) VI th International Innovative Mining Symposium digital culture and competent leadership, as well as stakeholder analysis and engagement. ...
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Across the industries, management faces increasing pressure to make digital transformation a strategic priority and embrace the opportunities offered by digitalization, and the mining sector is not an exception in this regard. Whereas it is recognized that within the mining industry digitalization will be a driving force that has a great potential to transform the nature of companies and their interaction with stakeholders at every stage of the value chain, there seems to be a lack of an understanding as to what should be investigated from a managerial perspective for the successful undertaking of the digital transformation initiatives. The paper aims to provide a descriptive overview of the global industry trends with regard to digital technologies in the mining sector, as well as develop a conceptual digital transformation framework that is intended to improve business’ digitization processes for the mining companies by identifying the core managerial areas on which attention should be focused in order to ensure effective implementation of the digital transformation strategy. These main action fields, along with optional additional dimensions could be further elaborated depending on the organizational context and industry environment, and should be taken into consideration when planning and organizing activities directed at delivering effective digital transformations.
... A conceptual digital transformation framework in the context of the mining sector Source: Developed by authors adapting [18][19][20] With reference to the summarized literature, four key action fields or managerial dimensions can be distinguished to be included in a cross-industry digital transformation framework: digital business strategy, technologies and business processes at the firm level, /202131504006 E3S Web of Conferences 315, 04006 (2021) VI th International Innovative Mining Symposium digital culture and competent leadership, as well as stakeholder analysis and engagement. ...
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In today’s business environment, sustainability is becoming an increasing issue for decision-makers, because it is concerned with sustainable development in terms of environmental, economic, and social dimensions. In view of this, mining companies worldwide understand the significance of the strategic approach to sustainability management. However, the formulation and implementation of the appropriate sustainability strategy in order to gain a competitive advantage of sustainability initiatives may be a challenging task for organizations. The paper aims to clarify the concept of sustainable competitiveness in the context of the mining industry and define the main focus areas of strategic sustainability management at the firm level. Based on a literature review a conceptual framework for strategic sustainability management of mining companies is presented, which includes key drivers and organizational factors that should be taken into account to embed efficiently the sustainability strategies into the business practice. From a management viewpoint, the presented framework can be conceptualized at the firm level as a business model which is oriented towards the achievement of competitive advantage, long-term value creation, and enhancing corporate sustainability performance of the mining operators.
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The monograph is devoted to topical issues of training pre-service teachers of computer science for teaching educational robotics in secondary education. There is an analysis of the state of the research problem, scientific substantiation and development of a model of building educational robotics competences of pre-service teachers of computer science. The pedagogical conditions of building competences are determined. Moreover, there is substantiation of the main components of the developed methodical system on the basis of pedagogically balanced and harmonious combination of traditional methodical systems of training and modern information and communication technologies. The issue of its introduction into the educational process of pre-service teachers of computer science is considered. According to the proposed methodical system of preparation of pre-service teachers of computer science for teaching educational robotics, the result of training is the built educational robotics competences of pre-service teachers of computer science. Монографія присвячена актуальним питанням підготовки майбутніх учителів інформатики до навчання освітньої робототехніки в закладах середньої освіти. В роботі проаналізовано стан проблеми дослідження; розроблено структуру компетентностей учителя в галузі освітньої робототехніки; науково обґрунтовано і побудовано модель формування компетентностей у галузі освітньої робототехніки майбутніх учителів інформатики; визначено педагогічні умови їх формування. Теоретично обґрунтовано основні компоненти розробленої методичної системи на основі педагогічно виваженого і гармонійного поєднання традиційних методичних систем навчання й сучасних інформаційно-комунікаційних технологій; розглянуто питання її впровадження в освітній процес майбутніх учителів інформатики. Результатом навчання, згідно із запропонованою методичною системою підготовки майбутніх учителів інформатики до навчання освітньої робототехніки в закладах середньої освіти, є сформовані компетентності у галузі освітньої робототехніки майбутніх учителів інформатики.
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Purpose The purpose of this paper is to identify the baseline model required to measure whole-of-organisation agility within a university information services division. The paper seeks to analyse the process of identifying and applying such a model. Design/methodology/approach The qualitative methodology applied is that of a single case study. The organisation analysed was an Australian university’s information services division. A structured survey, based on Wendler (2014), was administered to all staff as part of a multi-phased approach, thus facilitating a triangulation process. Findings The current research has confirmed the applicability of Wendler’s model to the higher education information technology sector. Application of the model establishes not only a baseline agility maturity score across the whole-of-organisation but also provides granular scores based on organisational units. Triangulation of survey results is recommended to achieve a more in-depth perspective. Research limitations/implications Further research comparing similarly and differently sized universities could provide valuable insights. More research is needed to extend the applicability of Wendler’s model to a wider range of domains and industries. Practical implications The grouping of survey questions under particular broad themes reflected the strategic focus of the division being surveyed. Organisations implementing the proposed model will need to select themes that correspond with their respective strategic goals and culture. Originality/value The paper has extended the research and resultant model developed by Wendler by applying them not only to both managers and staff but also to a different domain, specifically higher education.
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Digitisation forms a part of Industrie 4.0 and is both threatening, but also providing an opportunity to transform business as we know it; and can make entire business models redundant. Although companies might realise the need to digitise, many are unsure of how to start this digital transformation. This paper addresses the problems and challenges faced in digitisation, and develops a model for initialising digital transformation in enterprises. The model is based on a continuous improvement cycle, and also includes triggers for innovative and digital thinking within the enterprise. The model was successfully validated in the German service sector.
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Die Digitale Transformation hat Hochkonjunktur: Seit etwa 2014/2015 gehört dieses Schlagwort zum Handwerk aller Mitarbeitenden in Beratungsfirmen und auf Geschäftsleitungs-, Abteilungs- und Projektleitungsebenen. Die Treiber der Digitalen Transformation sind unzählige neue Datenquellen, neue Technologien sowie Anforderungen vom Markt und von Geschäftspartnern. Durch diesen Druck entstehen Potenziale, welche Unternehmen und die öffentliche Verwaltung aktiv und in einer gesunden Balance nutzen können. Die Prozessoptimierung und der Einsatz moderner Technologien werden gerade bei KMU gefördert, um den neuen Kundenanforderungen gerecht zu werden. In Grossunternehmen findet sich zudem der Druck nach Kosteneinsparungen unter den drei grössten Treibern. Primär werden durch die Digitale Transformation das Geschäftsmodell und die Unternehmensprozesse erneuert, aber auch der Einfluss auf die Unternehmenskultur und neue Führungsansätze stehen weit oben auf der Prioritätenliste. Um einen Einblick in die Digitale Transformation von Schweizer Unternehmen zu schaffen, hat die FHNW Hochschule für Wirtschaft mit der Unterstützung von Sponsoren und Partnern eine grosse Studie zu den Rahmenbedingungen und Projekten der Transformationsvorhaben durchgeführt. 2'590 Befragte aus 1'854 Unternehmen haben sich beteiligt. Dies hat die Grundlage für einen Gesamtüberblick über den aktuellen Stand der Digitalen Transformation geschaffen. Im Zentrum der Publikation steht ein Praxismodell mit den sieben Handlungsfeldern der Digitalen Transformation. Aus über 4'250 Themennennungen wurden die wichtigsten Handlungsfelder bestimmt. Die Handlungsfelder werden mit Checklisten und Fallstudien aus den jeweiligen Gebieten sowie Fachartikeln für die Praxis von einem erfahrenen Autorenteam bereichert. Obwohl die Studie für KMU angelegt war, sind die Ergebnisse und der Praxisleitfaden auch für Grossunternehmen relevant. Aus der Praxis für die Praxis: Die Forschungsresultate und der Praxisleitfaden für die Digitale Transformation. Unter Mitarbeit und mit Beiträgen von Martina Dalla Vecchia, Andrea Eichmüller, Susan Göldi, Stella Gatziu Grivas, Alexander Jungmeister, Jonas Konrad, Nora Kradolfer, Corin Kraft, Ulrich Pekruhl, Marc K. Peter, Dino Schwaferts, Luzia Sennrich, Martha Streitenberger, Joachim Tillessen, Toni Wäfler, Hans Friedrich Witschel und Cécile Zachlod.
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“The most profound technologies are those that disappear… They weave themselves into the fabric of everyday life until they are indistinguishable from it” wrote computer scientist and visionary Mark Weiser nearly 25 years ago in his essay “The Computer for the 21st Century.” It turns out he was right: in the age of “Industry 4.0”, digital technologies are the core driver for the manufacturing transformation. In fact, the introduction of such technologies allows companies to find solutions capable to turn increasing complexity into opportunities for ensuring sustainable competitiveness and profitable growth. Nonetheless, the effective implementation in manufacturing still depends on the state of practice: it may slow down, or even worst, may prevent from implementation. Indeed, we assume that a minimum level of capabilities is required before implementing the digital technologies in a company. Based on this concern, our research question is “are manufacturing companies ready to go digital?”. This paper wants to illustrate a “tool” to answer this question by building a maturity assessment method to measure the digital readiness of manufacturing firms. Based on the inspiring principles of the CMMI (Capability Maturity Model Integration) framework, we propose a model to set the ground for the investigation of company digital maturity. Different dimensions are used to assess 5 areas in which manufacturing key processes can be grouped: (1) design and engineering, (2) production management, (3) quality management, (4) maintenance management and (5) logistics management. Thus, the maturity model provides a normative description of practices in each area and dimension, building a ranked order of practices (i.e. from low to high maturity). A scoring method for maturity assessment is subsequently defined, in order to identify the criticalities in implementing the digital transformation and to subsequently drive the improvement of the whole system. The method should be useful both to manufacturing companies and researchers interested in understanding the digital readiness level in the state of practice.
Digital products and services are an integral part of everyday life, both for individuals and for organizations. The impact of digitalization is therefore often a tremendous one, forcing organizations to react to changing business rules and to leverage opportunities associated with digital technologies. Accordingly, the role of the Chief Information Officer (CIO) is frequently a flexible one in the sense that it encompasses a much broader perspective on organizations than before. Most of the CIOs or newly appointed Chief Digital Officers (CDOs) whom we interviewed in the course of our study are very much aware of the need for change catalyzed by emerging digital technologies, but they typically lack comprehensive knowledge on how to scope digital transformation initiatives. Against this background, we set out to develop and validate a holistic framework of action fields for digital transformation. Our framework builds on extant literature and a series of exploratory interviews with over 50 organizations and has been validated in numerous contexts. In this paper, we present our framework and demonstrate its application at ZEISS, one of the organizations participating in our study.
Dieser Herausgeberband eröffnet dem Leser die Grundlagen des Innovationsmanagements und präsentiert vielfältige Best Practices und Methoden zur Bewältigung des digitalen Wandels in der Finanzbranche. Hochkarätige Autoren, die den massiven Umbruch in der Branche mit Innovationen begleiten, geben Entscheidungsträgern in Banken, Versicherungsunternehmen und FinTechs auf diese Weise wertvolle Inspiration zur Weiterentwicklung ihrer Unternehmen. Der Inhalt • Innovationsmanagement in der Finanzbranche • Innovative Technologien und Produkte • Regulatorische Chancen und Herausforderungen • Aktuelle Entwicklungen und Zukunft des Finanz-Ökosystems Die Herausgeber Prof. Dr. Remigiusz Smolinski beschäftigt sich seit einigen Jahren theoretisch und praktisch mit den Themen Innovationen, Innovationsmanagement und Unternehmenswachstum. Er leitet das Innovationmanagement der comdirect bank AG und unterrichtet weltweit an renommierten Business Schools. Moritz Gerdes ist als Business Development & Innovation Manager für die Entwicklung innovativer Produkte und den zukunftsgerichteten Ausbau des Geschäftsmodells der comdirect bank AG zuständig. Martin Siejka ist Co-Leiter der comdirect Start-up Garage und als Business Development & Innovation Manager für die Geschäftsmodellinnovationen bei der comdirect Bank AG zuständig. Zudem ist er als Dozent an der ISM - International School of Management tätig. Mariusz Cyprian Bodek ist Gründer und Leiter der comdirect Start-up Garage sowie CEO und Managing Partner der BEAM Consulting GmbH.