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Patterns of Digitization – What differentiates digitally mature organizations?

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This article describes the results of a survey designed to assess how companies are implementing digital transformation, including the various strategies they employ and the actions they take to achieve large-scale transformations. While a few companies seem to reach front-runner status, the majority seem to lag behind. This phenomenon is a top concern of boardrooms worldwide and motivated the development of this study. To help these organizations, we highlight differentiated strategic principles and characteristics of the companies’ design processes digitally mature companies undertake to transform their businesses. These insights should help lagging companies understand what is involved in implementing a digital transformation and what they need to do to enforce this transformation.
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Patterns of Digitization – What differentiates
digitally mature organizations?
Dr. Gerhard Gudergan
FIR Institute for Industrial
Management
RWTH Aachen University
Aachen, Germany
gudergan@fir.rwth-aachen.de
Dr. Haroon Abbu
VP/GM Analytics Practice
Bell & Howell
Durham, NC 27713
haroon.abbu@outlook.com
Prof. Paul Mugge
Center for Innovation Management
Studies
North Carolina State University
Raleigh, NC 27659
pmugge@ncsu.edu
Dr. Timothy L. Michaelis
Center for Innovation Management
Studies)
North Carolina State University
(of Affiliation)
Raleigh, NC 27659
tlmichae@ncsu.edu
Alexander Kwiatkowski
FIR Institute for Industrial
Management
RWTH Aachen University
Aachen, Germany
kwiatkowski@fir.rwth-aachen.de
Denis Krechting
FIR Institute for Industrial
Management
RWTH Aachen University
Aachen, Germany
krechting@fir.rwth-aachen.de
Abstract— This article describes the results of a survey
designed to assess how companies are implementing digital
transformation, including the various strategies they employ
and the actions they take to achieve large-scale transformations.
While a few companies seem to reach front-runner status, the
majority seem to lag behind. This phenomenon is a top concern
of boardrooms worldwide and motivated the development of
this study. To help these organizations, we highlight
differentiated strategic principles and characteristics of the
companies’ design processes digitally mature companies
undertake to transform their businesses. These insights should
help lagging companies understand what is involved in
implementing a digital transformation and what they need to do
to enforce this transformation.
Keywords— Digital Transformation, Innovation
Management, Business Model, Corporate Culture, Change
Management.
I. I
NTRODUCTION
[1] characterizes digital transformation as “the creation of,
and consequent change in, market offerings, business
processes, or models that result from the use of digital
technology”. [2] found that data-driven companies are on
average 5% more productive and 6% more profitable than
other competitors in the market. A further study confirms this
effect to an even greater extent: the so-called digital masters,
which are characterized by visionary management and digital
capabilities, are 26% more profitable compared to their
competitors. Furthermore, digitally mature companies
generate nine percent higher revenue from their physical
assets [3]. There is no doubt that digital transformation can
generate substantial economic benefits.
We also know that digital transformation is forcing
companies to rethink the role - and value - data has in their
business models [4]. In most instances, it represents a
fundamental change in the organization’s underlying mindset,
systems, and tools needed to reposition parts of, or the entire
business design [5]. Indeed, we consider digital
transformation to be a significant change in the basic pattern
of how organizations create value.
For this reason, the topic of digital transformation has
gained a tremendous amount of attention in consulting
publications and management journals [6]. This shows a
profound interest - if not an outright economic need - to better
define, understand and manage this phenomenon.
Despite the promise of creating new and productive
business designs, i.e. designs that are able to profitably
leverage the explosion occurring in communications and
computing technologies - many organizations exhibit a ‘wait
and see’ attitude to digital transformation. While a few
companies have achieved front-runner-status, the majority lag
behind [7].
To deliver substantiated advice, the goal of this paper is to
reflect on both, a profound management framework and a
large scale empirical study as well, in order to develop insights
on how more digitally mature companies behave at a strategic
level as compared to those who are less mature.
II. R
ELATION TO EXISTING
T
HEORIES
A. The Fears of Senior Management
The Enterprise Risk Management Initiative of the Poole
College of Management collaborates with Protiviti each year
to assess the top risks facing organizations. In their recent
2018 survey, Executive Perspectives for Top Risks in 2018,
they interviewed n = 728 members of the top management
teams representing industries from around the world. Sixty
seven percent of respondents rated the “rapid speed of
disruptive innovation” as the top strategic threat to their
organizations [8]. Tightly linked to the emergence of
disruptive innovations, respondents also identified their
organizations overall resistance to change as their top
operational risk. Respondents are becoming increasingly
concerned with their organizations lack of willingness to
change the business model and alter core operations in
response to changes in the business environment or industry.
In recent years, companies have learned that mistakes in the
digital economy can be lethal. For example, Blockbuster once
controlled the majority share of the movie rental business, but
failed to adapt their business model to account for digital
platforms (e.g., Netflix), which resulted in Blockbuster
declaring bankruptcy in 2010 [9].
ERM and Protiviti researchers concluded that the question
is not if digital is going to up-end their current business model,
but rather when. Even when executives are aware of emerging
technologies that obviously have disruptive potential, it is
often difficult to have the vision or foresight to anticipate the
nature and extent of change. Overcoming these hurdles
represent the major challenges leadership teams confront
when digitizing their businesses. However, there is no other
choice, because the trend towards digital transformation will
not weaken, but on the contrary, “The innovations and
disruptions of the past ten years have been nothing short of
astonishing, but they’re just the warm-up acts for what’s to
come.” [7].
B. Business Transformation Framework
Research has shown that leaders need to increase their
awareness that a differentiated approach to transformational
changes is necessary [10]. To help companies successfully
change their organizational structure and behavior, the
following conceptional framework covers the broader issue of
how digital transformations are initiated and how the
effectiveness of strategic initiatives can be sustainably
ensured. The Business Transformation Framework, proposed
by [11], breaks the process of digital transformation down into
three main phases: (1) Transformation Strategy, (2)
Transformation Design, and (3) Transformation Delivery.
Fig. 1. Business Transformation Framework
Transformation Strategy establishes the foundations for
success and encompasses strategic initiation actions to
implement the vision of the future purpose of the company.
Transformation Design defines the future business system, the
new organizational characteristics; work patterns, and the
design activities needed to implement them. The third phase,
Transformation Delivery contains the culture needed to adopt
and implement the criteria established in phase two.
Obviously, this model assumes a top-down, senior
management led, holistic transformation approach. From
experience, we know this type of an approach best accelerates
the performance of organizations that lag competitors in
becoming a digital business. MIT experts in the field of digital
transformation emphasize this statement: “The only effective
way we’ve seen to drive transformation is top-down, through
strong senior executive direction coupled with methods that
engage workers in making the change happen.” [7].
C. Digital Maturity Concept
Our definition of digitally maturity is based on the
Carnegie Maturity Model Integration (CMMI) process. [12]
defines CMMI as a process and behavioral model that helps
organizations streamline process improvement and encourage
productive, efficient behaviors that decrease risks in software,
product and service development. The CMMI model breaks
down organizational maturity into five levels (Figure 2).
Fig. 2. Staged Maturity Model
For businesses that embrace CMMI, the goal is to raise the
organization up to Level 5, the ‘optimizing’ maturity level.
CMMI considers organizations that hit Levels 4 and 5 as high
maturity, where they are “continuously evolving, adapting and
growing to meet the needs of stakeholders and customers.”
[12].
D. Strategy and Consistency Theory
In the dynamically changing economy, the configuration
of new and complex organizational forms and business
models will be the major challenge for future business. Thus,
achieving consistency in design and characteristics of the new
organization structure including strategy, technologies, skills,
activities, and behaviors is one objective of transformation
management. Consitancy is thus at the core of every strategic
initiative and its implementation [13] [14].
In this paper, we focus on two major dimensions – strategy
and design - of the business transformation framework
illustrated in Figure 1. To meet the demanded holistic
approach required from [7], the systemic and integrated
management approach of [15] will be presented to enable
transformations which are accomplished effectively. This
approach focuses on consistency among key management
dimensions as a prerequisit for success in corporate
development. The following dimensions and principles
proposed guided us for the analyses of our data in the latter of
this paper.
Bleicher [15] takes four key management dimensions to
classify strategic management activities. These are
1. Handling complexity,
2. Designing Options,
3. Developing competencies and
4. Leading the strategy process.
He further identifies fundamental strategic principles for
each dimension, which are required to achieve holistic
renewal. Following the overall structure, he suggests
1. The development of new competencies is not looking at
synergies but on radical renewal (Principle S1),
2. Handling complexity is characterized by the application
of scenarios and heuristics (Principle S2),
3. Strategic options are not predefined but matter of a
development process (Principle S3), and
4. The strategy process is not organized hierarchically but
in lateral and integrative way (Principle S4).
In order to classify the activities of the design system and
processes, Bleicher suggests the following four design
dimensions. These are Development of different Design
Perspectives, Engineering Philosophy, Goal Achievement and
Stakeholder Integration.
In order to achieve renewal, the design dimensions are
characterized by the following principles:
1. The Development of Different Design Perspectives do
not follow a linear or convergent process. It is
characterized by cycles of analyses and synthesis
(Principle D1).
2. Engineering Philosophy is characterized the usage of
prototyping and not characterized by predefined solutions
(Principle D2).
3. Goals are achieved in an emergent process and not
achieved based on predefined solutions (Principle D3).
4. Stakeholder Integration is characterized by
collaboration and openness (Principle D4).
III. R
ESEARCH
D
ESIGN AND
M
ETHODOLOGY
A. Study Development and Data Collection
To gather relevant data we conducted an ambitious
international survey, called Patterns of Digitization. We
polled n = 559 decision makers, people in middle, senior and
executive management positions across five geographic
regions – America, Europe, Asia, Africa and Oceania. The
results provide a reasonable account of the investments made,
and the experience organizations have in initiating, designing
and scaling their digital businesses.
We asked respondents a number of standard demographic
questions, including the region and industry sector they
operate in, the company’s size, age, the number of employees,
etc. In addition, we asked them to characterize their digital
position. For example, how do they assess the organization’s
digital maturity? We also inspected the organization’s
resource allocation plan. Are the greatest percentage of the
company’s resources allocated to the optimization/automation
of existing business processes? Or are they investing in new
technologies to build up new, presumably digital, businesses?
We also asked what specific investments the company has
made in digital transformation. For example, has the
organization appointed a CDO (Chief Digital Officer),
developed a data strategy, hired or trained a number of data
scientists etc.? A portfolio of investments of this type can
greatly contribute to the success, and acceleration, of a digital
transformation initiative.
In order to analyse activities and their characteristics at the
strategic level (see section II of this paper), we asked
respondents which strategies their companies had chosen to
execute to achieve renewal. Companies have various strategic
approaches at their disposal to extend, or develop, digital
capabilities which we call initiation strategies. The following
seven Initiation Strategies were included in the survey: (1)
mergers and acquisitions, (2) digital spinoffs, (3) internal
strategic transformation, (4) ecosystem development, (5)
digital joint venture, (6) internal digital hub, and (7) internal
evolution.
We asked respondents to assess the Scale Strategies they
used namely the design principles and practices their
organizations had employed to build their digital businesses.
B. Analysis Approach
According to the maturity model of [12], in our study we
chose to group and define levels 4 and 5 as Digitally Mature
organizations; companies operating at Levels 1, 2 and 3 we
grouped as Digitally Developing organizations.
Hence, the following data splitting results from the
maturity concept discussed above: Digitally Developing with
a maturity range from 1 to 3 (n = 352) and Digitally Mature
with a maturity range from 4 to 5 (n = 145). An overall
distribution of companies’ maturity is shown in Figure 4.
Fig. 3. Maturity Distribution (n = 528)
These results are in response to question 1.5 in the survey,
where participants were asked to rate the digital maturity of
their organizations on a 5-point scale from Level 1 Ad hoc:
“No formal plan or approach”, to Level 5 Optimum: "New
business model is fully internalized; results are repeatable and
predictable."
Refering to the presented maturity model, we definitely
see Level 4 performance as being digitally mature. For
example, to achieve any of the external Initiation Strategies to
renew competences, organizations would have had to involve
‘competencies and people from outside the organization’. And
unlike Level 3, which typically concerns itself with project
performance, the goal is to institutionalize the new model at
the organization. To determine if differences existed between
these companies multiple t-tests were conducted with a
Bonferroni correction to control for the family wise error rate
regarding multiple comparisons [16]. To rank order and
directly compare the mean differences across groups, Cohen’s
d, a measure of effect size, was used [17]. For all tests, the
significance level was set to α = 0.05. IBM SPSS was the
statistical software used for all analysis.
IV. R
ESULTS
A. Company Demographics
To understand the makeup of the companies who took the
survey and their attitudes towards, and practice of digital
transformation, the company demographics are presented
below. Figure 4 shows the industry sector representation of the
organizations. While the survey covers a broad array of
industry sectors, two industries, IT and Communications (20
percent), and Consulting and Services (15 percent) dominate
the results. Despite the dominance of these two sectors, we
could find digitally mature and digitally developing
companies across all sectors.
Fig. 4. Sector Distribution in percentage
Table I shows where the organizations are geographically
located. As can be seen over 60% of companies that took the
survey predominantly operate in America. Europe follows by
a gap of 35%. Asia, Africa and Oceania trail even further.
TABLE I. L
OCATIONS OF
C
OMPANIES
S
URVEYED
Figure 5 shows company size by number of employees.
Nearly 61 % of the respondents are from large companies
(with over 200 employees) including about 35 % from
companies with over 1000 employees. About 37 % of the
respondents were from companies with less than 200
employees including 20 % from companies with less than 10
employees. Hence, the survey composition represents
companies of all sizes.
Fig. 5. Size distribution in percentage
B. Digital Mature vs. Digital Developing
To understand how the practice of Digitally Mature
companies differs from those of Digitally Developing
organizations, in particular, we examined the relevant
Strategic Principles, Key Investments and Design Principles.
1) Strategic Principles
As explained in section II of this paper, we analysed key
dimensions of strategic management regarding the principles
proposed by [15] to achieve strategic renewal. The following
presented survey results follow this structure.
a) Development of new competencies (Principle S1),
In order to develop new digital companies fast and
effectively, companies have to do both, integrating external
companies and actively investing into education programs
with a specific focus on digitization.
Figure 6 shows the success Digitally Mature organizations
are experiencing with the various surveyed Initiation
Strategies. The largest mean value difference between both
groups was measured in the success with
Merger&Acquisition.
Fig. 6. Average value comparison regarding success with initiation
strategies (1 = not successful, 5 = highly successful)
However, all other differences are significant, too. With
regard to Merger & Acquisition, the effect is to be classified
as strong, for the other two success ratings as medium strong
[17]. For exact statistical values, please see Table II. As the
data show, Initiation Strategies are externally oriented and
involve key partners.
TABLE II. S
TATISTICAL
D
ATA FOR
I
NITIATION
S
TRATEGIES
In addition, we can demonstrate with our data that digitally
mature companies (M = 1.81, SD = 0.398) invest significantly
more in building the future competencies of their employees.
Fig. 7. Average value comparison of Investments in Future Skills (1 = not
applied, 2 = applied)
This difference is also significant compared to the digitally
developing companies (M = 1.64, SD = 0.482) and the effect
size can be classified as small to medium (t
(409)
= 3.430, p <
0.01, d = 0.383).
b) Handling complexity is characterized by the
application of scenarios (Principle S2),
Digital transformation is charactrerized by a tremendous
degree of complexity, which cannot be handled by predefined
objectives. Instead, employees need the freedom to work on
ideas in a scenario-specified corridor. In order to set the course
for the future, digitally mature companies particularly
encourage their employees to work on the future and provide
the room and the freedom to do so.
Fig. 8. Average value comparison of Encouragement of Scenarios and
Heuristics (1 = Never, 5 = 100% of the time)
They also give them time and resources to pursue the best
ideas and develop new business opportunities for the
company. Both of these factors are significantly more
considered by digitally mature companies. The effect
strengths can be classified as medium. For exact data, please
see Table III.
TABLE III. S
TATISTICAL
D
ATA FOR
S
CENARIO
E
NCOURAGEMENT
c) Strategic options not predefined (Principle S3),
A key aspect in digital transformation is to allow emergent
developments and not to prespecify strategic options upfront.
This is achieved by a culture which allows fast failures and
experimentations at a strategic level. To analyse this aspect,
we asked whether at the leadership level a fast fail culture is
promoted.
Regarding this item, we also found in our data an evident
difference between mature (M = 3.82, SD = 1.075) and
developing companies (M = 3.16, SD = 1.296).
Fig. 9. Average value comparison of Fail Fast Cu lture (1 = Never, 5 = 100%
of the time)
This difference is significant with an effect size to be classified
slightly stronger than medium (t
(416)
= 4.987, p < 0.01, d =
0.554).
d) Strategy process in lateral and integrative way
(Principle S4).
Another key question is, how companies achieve the level of
integration and lateral cooperation needed to go through a
digital transformation. With regard to cross-functional
cooperation, the managers of digitally mature companies (M
= 3.97, SD = 1.012) are also significantly more active than
digital developing firms (M = 3.33, SD = 1.125).
Fig. 10. Average value comparison of Lateral Collaboration (1 = Never, 5 =
100% of the time)
This difference is also significant with an effect size to be
classified stronger than medium (t
(414)
= 5.035, p < 0.01, d =
0.562).
2) Investments
The use of funds is also essential to the success of digital
transformation. We have therefore used our data to analyse
which strategic investments the digitally mature companies do
more frequently. The next figure shows the key investment
focus of digitally mature organizations (M = 1.73, SD =
0.445) is investing in new technologies to build up new
businesses.
Fig. 11. Average value comparison of Key Investments Focus (1 = not
applied, 2 = applied)
Compared to digital developing enterprises (M = 1.47, SD =
0.45), this difference is also significant and the effect size can
be classified as a medium strong (t
(557)
= 5.595, p < 0.01, d =
0.555).
Figure 12 displays the key investments made by digitally
mature organizations. As assumed, most companies have not
implemented corresponding transformation steps yet.
Fig. 12. Average value comparison of Key Investments (1 = not applied, 2 =
applied)
All displayed items in this figure were significantly
different. Regarding effect sizes can be classified as weak to
medium. For exact values, please see Table IV.
TABLE IV. S
TATISTICAL
D
ATA FOR
K
EY
D
IGITAL
I
NVESTMENTS
Appointing a CDO was one of the least popular actions,
but for a Digitally Mature organization, it is likelier, as are
hiring or training data scientist and moving your products and
services to the cloud. Digitally Mature organizations align
resources to their digital strategy.
3) Design Principles
As explained in section II, the following result structure
follows the design principle structure of [15].
a) Development of different design perspectives
Flexibility is necessary to meet the constantly changing
customer expectations. One way to meet this demand is to
integrate Design Thinking into corporate business processes.
With our data, we were able to prove that digitally mature
companies (M = 3.62, SD = 1.101) do this much more
frequently than digitally developing companies (M = 3.04,
SD = 1.283).
Fig. 13. Average value comparison Design Thinking usage (1 = Never, 5 =
100% of the time)
This approach difference is also significant with an effect size
to be classified stronger than medium (t
(420)
= 4.376, p < 0.01,
d = 0.485).
b) Engineering Philosophy through prototyping
A further central step is to adapt the development process to
the accelerated markets and the faster available customer
feedback. One possibility herefore is Prototyping, which
enables an iterative learning and development process.
Our data also showed that digitally mature companies (M =
3.73, SD = 1.127) use this alternative development approach
significantly more often than digitally developing firms (M =
3.07, SD = 1.278).
Fig. 14. Average value comparison Prototyping usage (1 = Never, 5 = 100%
of the time)
This difference is significant with a effect size slightly
stronger than medium (t
(257.793)
= 5.31, p < 0.01, d = 0.551).
c) Emergent Processes, not predefined solution
Another factor for flexibility is iterative and short-sequential
project management. Developments Sprints, for example, are
designed to respond to emergent requirements as quickly as
possible. Here, too, we were able to prove that this design
principle is much more important to the managers of digitally
mature companies (M = 3.84, SD = 1.031) than that of
digitally developing companies (M = 3.18, SD = 1.278).
Fig. 15. Average value comparison Emergent Processes (1 = Never, 5 =
100% of the time)
This difference is significant with a effect size slightly
stronger than medium (t
(418)
= 5.1, p < 0.01, d = 0.568).
d) Stakeholder Integration
An important question in the creation of digital innovation is
how companies manage to integrate the different
expectations of various stakeholders. Our data show, that
digital mature companies (M = 3.86, SD = 1.031) openly
communicate with customers, suppliers and business partners
more than digital developing firms (M = 3.21, SD = 1.228).
Fig. 16. Average value comparison of Open Stakeholder Integration (1 =
Never, 5 = 100% of the time)
This difference is significant with a medium strong effect size
(t
(421)
= 5.261, p < 0.01, d = 0.584).
V. C
ONCLUSION
The main purpose of our study is to identify business
practices that will help organizations compete effectively in
an increasingly digital world. For the advice based on
Bleicher's theory [15], we were able to prove conclusively that
in all cases, the more digitally mature companies realized the
suggested principles more frequently. We call these
similiarities in strategic steps Patterns of Digitization. Of
course, the successful implementation of digital
transformation is always strongly dependent on context and
sector. However, the principles presented offer first guidance
based on theory and reinforced by empirical data.
Investing in employees’ education as well as encouraging
and providing space for their ideas is a good way to go.
Furthermore, a culture that accepts fast failure has a positive
effect on this explorative behavior, too. Concerning the
investments, it is obvious that above all the personnel also
assumes a central role again. Digitally Mature Companies
invest in CDO's and as well in Data Scientists. They also use
technologies like the cloud to enable faster processing.
Furthermore, we could show that alternative approaches are
more often used by digitally mature firms. In terms of
customer and stakeholder integration, as well as in the
methodical approach (Design Thinking, Prototyping,
Developing Sprints), digitally mature companies use these
approaches significantly more often than their competitors.
The proposed holistic approach is based on a complete
structural reformatting, which requires a great deal of
commitment and courage on the part of the managers. The
digital transformation offers various setting options that must
be continuously and consistently adjusted. The differentiated
practice presented provide an excellent template for
organizations engaged in this task. Managers need to realize
that digital maturation is a natural process, but it will not
happen automatically. Digital maturity is the process of your
whole company learning how to respond appropriately to the
emerging digital competitive environment. As stated, the
trend towards digital transformation will not decrease, but on
the contrary, it will increase. Hence, further empirical pattern
detection is vital and the connection to companies overall
success has to be further investigated.
VI. A
CKNOWLEDGEMENT
The research project is funded by the German Federal
Ministry of Education and Research within the research
program Innovations for Tomorrow's Production, Services
and Work under the registration number 02K14A221 and
managed by the Project Management Agency Karlsruhe
(PTKA). Any opinions, findings, and conclusions or
recommendations expressed in this paper are those of the
authors and do not necessarily reflect the views of the
correspondent institutions. The authors thank the
organizations studied for taking the questionnaire.
Furthermore, special thanks go to the generous support of the
CIMS at the North Carolina State University.
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... According to consistency theory, which has been shown to be of importance in digital transformation [31], it is vital to note that digital strategies are not going to be successful on a standalone basis. The purpose of a digital transformation is to positively change value creation processes by means of digital technologies [3]. ...
... Other elements of complexity leadership, such as honest, dissonant dialogs and openness to bottom-up innovations [33], can also contribute. The latter factor has emerged as particularly important in the context of digital transformation [31]. Ideally, measures of digital transformation ensure that complexity is reduced, thus enabling increased value creation. ...
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The digital transformation of industry and society continues to advance. While some companies are achieving trailblazer status, others are finding it difficult to manage or even initiate the necessary changes. Top-level leaders play a central role in these transformational processes, as they have the opportunity to directly or indirectly influence decisive variables. In this article, we present the results of interviews with 13 digital leaders who have successfully implemented the necessary changes for the digital transformation of their companies. The results of the interviews provide key dimensions for leaders to digitally transform their companies.
... According to consistency theory, which has been shown to be of importance in digital transformation [31], it is vital to note that digital strategies are not going to be successful on a standalone basis. The purpose of a digital transformation is to positively change value creation processes by means of digital technologies [3]. ...
... Other elements of complexity leadership, such as honest, dissonant dialogs and openness to bottom-up innovations [33], can also contribute. The latter factor has emerged as particularly important in the context of digital transformation [31]. Ideally, measures of digital transformation ensure that complexity is reduced, thus enabling increased value creation. ...
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**This manuscript has been accepted as FULL PAPER to be presented at ICE2021 - International Conference on Engineering, Technology, and Innovation Conference on Information Systems and Technologies, to be held in Cardiff, UK June 23 - 26, 2021. Author copy of the working/submitted manuscript is available here. Full accepted paper will be published in Proceedings by IEEE Digital Xplore. In the mean time, please feel free to reach out if you need full manuscript.*** The digital transformation of industry and society continues to advance. While some companies are achieving trailblazer status, others are finding it difficult to manage or even initiate the necessary changes. Top-level leaders play a central role in these transformational processes, as they have the opportunity to directly or indirectly influence decisive variables. In this article, we present the results of interviews with 13 digital leaders who have successfully implemented the necessary changes for the digital transformation of their companies. The results of the interviews provide key dimensions for leaders to digitally transform their companies.
... Digital transformation is a significant change in the basic pattern of how organizations create value [13]. Data-driven companies are on average 5% more productive and 6% more profitable than other competitors in the market. ...
Conference Paper
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Companies are increasingly looking for ways to understand and innovate their business models by leveraging digital transformation. Evolving consumer attitudes and behaviors, technological advances, new competitive pressures, and laser thin margins—accelerated by the COVID-19 pandemic—are driving digital transformation in the grocery business. We introduce a conceptual model of digital grocery ecosystem to advance our understanding of digital transformation of the grocery business. We analyze digital transformation initiatives of the top five grocery companies in the United States using inductive research and content analysis. We find that brick and mortar, e-commerce companies, as well as new start-ups, are making major investments in all aspects of the digital grocery ecosystem—the online shopping experience for the digital consumer, digital store operations, pickup and delivery mechanisms, and advanced analytical and digital marketing capabilities. Retailers are also connecting their investments to enhanced customer loyalty, revenue, and ultimately profit.
... Digital transformation is a significant change in the basic pattern of how organizations create value [13]. Data-driven companies are on average 5% more productive and 6% more profitable than other competitors in the market. ...
Conference Paper
Full-text available
Companies are increasingly looking for ways to understand and innovate their business models by leveraging digital transformation. Evolving consumer attitudes and behaviors, technological advances, new competitive pressures, and laser thin margins-accelerated by the COVID-19 pandemic-are driving digital transformation in the grocery business. We introduce a conceptual model of digital grocery ecosystem to advance our understanding of digital transformation of the grocery business. We analyze digital transformation initiatives of the top five grocery companies in the United States using inductive research and content analysis. We find that brick and mortar, e-commerce companies, as well as new start-ups, are making major investments in all aspects of the digital grocery ecosystem-the online shopping experience for the digital consumer, digital store operations, pickup and delivery mechanisms, and advanced analytical and digital marketing capabilities. Retailers are also connecting their investments to enhanced customer loyalty, revenue, and ultimately profit.
... It involves leadership, talent development, culture, organization, and strategy [4]. Digital transformation is a significant change in the basic pattern of how organizations create value [5]. Data-driven companies are on average 5% more productive and 6% more profitable than other competitors in the market. ...
Chapter
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Companies are increasingly looking for ways to understand and profitably leverage digital transformation with a vast amount of new communications and computing technologies. Despite the potential for digital transformation to generate substantial economic benefits, very few businesses have undergone successful digital transformations. However, evolving consumer attitudes and behaviors, technological advances, new competitive pressures, and laser thin margins, accelerated by the COVID-19 pandemic, are driving digital transformation in the grocery business. Brick and mortar, e-commerce companies, as well as new start-ups, are making major investments in all aspects of the digital grocery ecosystem—the online shopping experience, automated picking, delivery, and the digital supply chain. Retailers are connecting their investments to enhanced customer loyalty, revenue, and ultimately profit. This research—based on inductive methods—aims to discuss key drivers and technologies utilized in digital grocery business and contributes by introducing a model of digital grocery ecosystem to better understand digital transformation of the grocery business.
... Due to the use of digital technologies, organizations need to make changes to many elements, including its strategy and culture [31]. It is difficult to estimate the level of change that will occur when a new technology is introduced [32]. ...
... It involves leadership, talent development, culture, organization, and strategy [4]. Digital transformation is a significant change in the basic pattern of how organizations create value [5]. Data-driven companies are on average 5% more productive and 6% more profitable than other competitors in the market. ...
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Companies are increasingly looking for ways to understand and profitably leverage digital transformation with a vast amount of new communications and computing technologies. Despite the potential for digital transformation to generate substantial economic benefits, very few businesses have undergone successful digital transformations. However, evolving consumer attitudes and behaviors , technological advances, new competitive pressures, and laser thin margins , accelerated by the COVID-19 pandemic, are driving digital transformation in the grocery business. Brick and mortar, e-commerce companies, as well as new start-ups, are making major investments in all aspects of the digital grocery ecosystem the online shopping experience, automated picking, delivery, and the digital supply chain. Retailers are connecting their investments to enhanced customer loyalty, revenue, and ultimately profit. This research-based on inductive methods-aims to discuss key drivers and technologies utilized in digital grocery business and contributes by introducing a model of digital grocery ecosystem to better understand digital transformation of the grocery business. NOTE: Published version is now available as a book chapter here: https://link.springer.com/chapter/10.1007%2F978-3-030-72660-7_32 Part of book series "Advances in Intelligent Systems and Computing" by Springer. Cite this paper as: Abbu H.R., Fleischmann D., Gopalakrishna P. (2021) The Digital Transformation of the Grocery Business - Driven by Consumers, Powered by Technology, and Accelerated by the COVID-19 Pandemic. In: Rocha Á., Adeli H., Dzemyda G., Moreira F., Ramalho Correia A.M. (eds) Trends and Applications in Information Systems and Technologies. WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1367. Springer, Cham. https://doi.org/10.1007/978-3-030-72660-7_32
... Studies have shown that the digital efforts of digitally mature companies are initiated and tracked almost twice as often from the CEO Suite [8]. Leaders of digitally mature companies collaborate with cross functional counterparts to achieve the level of integration and lateral cooperation needed to go through digital transformation at a significantly higher rate compared to leaders of digitally developing companies [17]. ...
Conference Paper
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This article describes digital leadership-specifically character and competency-that differentiate digitally mature organizations from digitally developing organizations. We assess the differentiated actions of leaders of digitally mature organizations and discuss their results. The study is based on Patterns of Digitization survey with insights from 559 decision makers across five geographic regions-America, Europe, Asia, Africa, and Oceania designed to assess how companies are implementing digital transformation, the various strategies they employ, the investments they make, and the actions they take to achieve large-scale institutionalized digital transformations. The insights gleaned from the study should help lagging companies understand what is involved in implementing a digital transformation and what they need to do to catch up.
Article
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Overview: The digital transformation of organizations continues at a frenetic pace. While some companies have achieved trailblazer status, others are finding it difficult to change and therefore are lagging. Digital leaders play a pivotal role in this transition because they can increase the confidence of their organizations behind these often risky and disruptive initiatives. In this article, we present our efforts to i) separate the practices of digitally developing and digitally mature organizations-particularly those of their leaders, ii) determine the specific trust-building actions of digitally mature leaders, iii) develop a scale to measure the human dimensions of digital leaders, and iv) discuss the future development of a reliable scale and self-assessment tool that digital leaders can use to assess their own readiness to accelerate digital initiatives. Keywords: digital leadership, trust, digital transformation, leadership assessment
Chapter
Viele Branchen stehen am Anfang der digitalen Transformation bzw. werden bereits grundlegend von ihr verändert. Im Zeitalter der digitalen Transformation steht somit die Frage im Mittelpunkt, wie Unternehmen die notwendigen Veränderungen angehen und den Erfolg der Transformation gewährleisten können. Datenbasierte Dienstleistungen sind dabei ein konsequenter nächster Schritt im Wandel der Unternehmen vom Investitionsgüterhersteller zum Lösungsanbieter. Nichtsdestotrotz scheitern viele Premiumhersteller trotz ihrer hohen digitalen Wettbewerbsfähigkeit bei der Entwicklung und Einführung von datenbasierten Dienstleistungen (Kagermann et al. 2015, S. 18 f.). Der Beitrag zeigt zunächst Merkmale und Ausprägungen datenbasierter Dienstleistungen auf. Da sich die klassischen Methoden des Service Engineerings nicht ausreichend schnell an digitalisierte Komponenten und geänderte Voraussetzungen angepasst haben, wird mit dem Smart Service Engineering ein neuer Ansatz vorgestellt, der agile und kundenorientierte Methoden implementiert. Zuletzt werden Muster und Entwicklungspfade der digitalen Transformation detailliert analysiert und Handlungsempfehlungen für Anbieter datenbasierter Dienstleistungen abgeleitet.
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Rapid and pervasive digitization of innovation processes and outcomes has upended extant theories on innovation management by calling into question fundamental assumptions about the definitional boundaries for innovation, agency for innovation, and the relationship between innovation processes and outcomes. There is a critical need for novel theorizing on digital innovation management that does not rely on such assumptions and draws on the rich and rapidly emerging research on digital technologies. We offer suggestions for such theorizing in the form of four new theorizing logics, or elements, that are likely to be valuable in constructing more accurate explanations of innovation processes and outcomes in an increasingly digital world. These logics can open new avenues for researchers to contribute to this important area. Our suggestions in this paper, coupled with the six research notes included in the special issue on digital innovation management, seek to offer a broader foundation for reinventing innovation management research in a digital world.
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In this paper the authors present an integrated framework that could help stimulate an organisation to become data-driven by enabling it to construct its own Data-Driven Business Model (DDBM) in coordination with the six fundamental questions for a data-driven business. There are a series of implications that may be particularly helpful to companies already leveraging ‘big data’ for their businesses or planning to do so. By utilising the blueprint an existing business is able to follow a step-by-step process to construct its own DDBM centred around the business’ own desired outcomes, organisation dynamics, resources, skills and the business sector within which it sits. Furthermore, an existing business can identify, within its own organisation, the most common inhibitors to constructing and implementing an effective DDBM and plan to mitigate these accordingly. Within the DDBM-Innovation Blueprint inhibitors are colour-coded and ranked from severe (red) to minor (green). This system of inhibitor ranking represents the frequency and severity of inhibitor, as perceived by 41 strategy and data-oriented elite interviewees.
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Unique customer solutions which integrate products and services into a high value offering have the potential to successfully differentiate from competition even prices are dictating product markets. However, companies face tremendous challenges to develop customer solutions. Service engineering is considered to be the scientific discipline which supports the design task of intangible offerings and thus a foundation for solution design. We enhance the existing body of research in service engineering by proposing to apply the systematic approach of service engineering for solution design. An architecture for services design is introduced as an initial starting point to designing service based solutions. 1 INTRODUCTION Providing business related services more and more means to solve a customer problem and deliver an individualized solution that is able to substitute a customer internal process or function rather then just to deliver a single service in a single transaction. For example, the automotive industry requires pre-production services (such as design services and research and development), production-related services (such as maintenance and IT services), after-production services (transport and distribution services) and financial services and finally other business services such as accounting or legal services. In business to business settings of producing companies, these services are usually bundled into an integrated offering which is configured by different tangibles such as capital goods, spare parts and intangibles such as repair services, remote services, joint project management and others [15]. It has been well realized that this integration of high quality services, business related services in particular, is crucial for the competitiveness of existing and future economies. Thus, producing companies increasingly link products, parts, after sales services and valued added services such as training, business consulting and engineering services into a integrated solution system to successfully differentiate from worldwide competition [12]. The underlying strategy in industrial markets is to substitute the subsequent and single offerings by integrated value adding solutions which lead to lasting relationships to closely link providers and customers. These often are characterized by collaborative engineering efforts and even link providers and customers on an emotional level. Belz has first introduced the term solution system to describe the integrative character of the solution delivered [2]. Companies in the future have to develop and establish solution systems to generate superior value to the customer [14]. The corresponding concept is illustrated in the following picture.
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This paper presents an overview of the current state of the art in multiple testing in genomics data from a user's perspective. We describe methods for familywise error control, false discovery rate control and false discovery proportion estimation and confidence, both conceptually and practically, and explain when to use which type of error rate. We elaborate on the assumptions underlying the methods and discuss pitfalls in the interpretation of results. In our discussion, we take into account the exploratory nature of genomics experiments, looking at selection of genes before or after testing, and at the role of validation experiments. Copyright © 2014 John Wiley & Sons, Ltd.
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