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The gap between the practice and theory of Digital
Transformation
Whitepaper
Gerhard Gudergan
Paul Mugge
Hawaiian International
Conference of System Science
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Acknowledgements
We would first like to thank the organizers of HICSS 50 who allowed us the opportunity to
explore this important topic.
Next, we would like to thank Heather Yurko, CISCO Corporation, Yassi Moghaddam, ISSIP, and
Professor Terri Professor Terri L. Griffith, Ph.D. Associate Dean, Leavey School of Business,
Santa Clara University who helped us moderate the World Café. These people served as table
moderators for the World Café.
Lastly, we would like to thank the participants in the World Café who gave us their valuable
input and comments. The insights they provided are the basis for the research roadmap
outlined in this paper.
Names
Alexander Pflaun Fraunhofer SCS
Alexander Schmid Universität Lichtenstein
Andreas Reuschl Universität Bayreuth
Barbara Durkin Suny Oneonta
Bettina Horlach Universität Hamburg
Christoph Klötzer Universität Hamburg
Daniel Ehls Technische Universität Hamburg
Harburg
Don Kerr University of the Sunshine Coast
Ferry Nolte Universität Hannover
Gary Sterrenberg Department of Human
Services
Gerhard Gudergan Fir an der RWTH
Aachen
Günter Prockl CBS Department of
Operations Management
Heather Yurko Cisco
Joanda Svenheden Acando
Names
Kaisa Still VTT Technical Research Centre of
Finland
Leif Flak Universitetet i Agder
Manuel Holler Universität St.Gallen
Matthijs Verhulst Tilburg School of
Economics and Management
Michael Yousif AstraZeneca
Murray Turoffe New Jersey Institute of
Technology
Nigel Melville University of Michigan
Nila Windasari National Tsing Hua
University
Paul Mugge NC State University
Sanna Ketonen-Oksi Tampere University
of Technology
Sherah Kurnia University of Melbourne
Terri Griffith Leavey School of Business
Walter Fernandez UNSW Business School
Yassi Moghaddam ISSIP
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I. Background
Digital transformation is impacting entire segments of our society and industries of every type:
healthcare, medicine, agriculture, manufacturing, retail, etc. enabling new types of innovation,
creativity, and entirely new business models. We consider digital transformation to be a significant
change in the basic pattern of how organizations create value. In most instances digital transformation
represents a fundamental change in the organization’s underlying mindset, systems, and tools needed
to reposition parts of, or the entire business design.
For this reason the topic of digital transformation has gained a tremendous amount of attention in
consulting publications and management journals. This indicates that there is a profound interest, if not
an outright economical need, to better define and understand and manage this phenomena.
Unfortunately, the topic is not covered appropriately at scientific conferences and in academic
publications.
This paper describes the collaborative efforts underway at the Center of innovation Studies located at
the Poole College of Management, NC State University and FIR Institute for Industrial Management at
RWTH Aachen University, to understand the gap that exists between the practice of digital
transformation and the coverage of this phenomena in the literature. On January 5, 2017, at the
Hawaiian international Conference of System Science (HICSS50), the authors hosted a World Café
exercise as part of their workshop, titled Digital transformation: Research Challenges and Priorities for
the Future. In the World Café over 50 participants enthusiastically helped frame a multi-year, multi-
discipline, Digital Transformation Research Roadmap to help organize and guide studies into the many
facets of digital transformation. The road map along with the methodology we used to synthesize the
results of the World Café can be seen in section IV Results of the Expert Workshop
Singular disciplinary approaches are not sufficient. To be effective the scope of the research needs to be
holistic and span the many disciplines of systems science, i.e. advances in computational and
communications technologies, big data and advanced analytics, the internet of things (IoT), as well as
the social sciences of service management, and organization design. Indeed, we believe digital
transformation to be the latest instantiation of system science. Consequently, we offer this paper and its
findings to the organizers of HICSS for their consideration in shaping future conferences.
II. What exactly is Digital Transformation?
Before engaging participants in the World Café exercise it was necessary that everyone have a common
understanding of what digital transformation is, and what it is not. In fact, in the time allotted, it was
easier to describe what digital transformation is not in order to contrast it to other major change
initiatives, like the dot.com explosion of the early and middle 1990’s (and subsequent implosion in the
early 2000’s).
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It is not a bolt on strategy
Some organizations tend to treat digital transformation as a “bolt on strategy”, i.e. an appendage to the
prevailing business design. This is potentially a very dangerous stance. A recent cross-industry survey
conducted by Cisco Systems focused on the “digital disruption” caused by digital transformation. Cisco
defined “disruption” as the substantial change in the market share about to befall sector leaders.
Participants in the survey were asked: In your industry, how many companies will lose their place in the top
10 due to digital disruption (over the next five years)?
The results were startling. Respondents predicted that over “40% of market incumbents would be replaced --
in an average of just 3 years”. This level of turnover - across all industry sectors -is unprecedented and
certainly worthy of more than bolt on thinking and action.
It is not an IT initiative
Others relegate digital transformation to their IT departments and treat it as yet another in a series of IT
projects. While information technologies such as data analytics, cognitive computing, cloud, IoT, and
others span the solution space, proficiency in these tools is only part of the challenge. For these
organizations to reap the full benefits of digital transformation they need to change the very nature of
their work and the flow of information with customers, as well as with their business partners.
Digital transformation is not the purview of the IT Department, but rather the responsibility of all
business functions working together.
It is not something that can (or should) be ignored
A 2016 research study performed by the Poole College of Management’s Enterprise Risk Management
Initiative, in conjunction with Protiviti, Risk and Consulting Inc., bears this out. In the survey they asked
535 executives and board members of global organizations to identify their top strategic risks. The top
2 strategic risks were:
1. Rapid speed of disruptive innovation and/or new technologies may out pace our
organizations ability to compete without making substantial changes to our business model.
2. Social media, mobile applications, and other internet-based applications may significantly
impact our brand, customer relationships and how we do business.
The second risk is perhaps the most interesting. It first appeared as a strategic risk in the 2015 survey;
and by 2016 it had risen to number 2 on the list.
It is not mature, or broadly adopted
Despite the promise of creating new and productive business designs, designs that are able to profitably
leverage the literal explosion occurring in communications and computing technologies, many
organizations exhibit a ‘wait and see’ attitude to digital transformation. At best the digital
transformation activities of these organizations can be labeled ‘pilots’ or ‘proof of concepts’. Is this an
appropriate response? Or can the senior managers of these organizations foresee the substantial
change this presents to the present business model and prefer to let their successors deal with it?
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Digital transformation is the unique confluence of data, advanced analytics, and innovation
The definition of digital transformation we prefer is taken from the United States Government
Accountability Office’s 2016 report to Congress, entitled: Data and Analytics Innovation, Emerging
Opportunities and Challenges. In it they describe digital transformation as a cycle, or process, that
enables organizations – through better, more informed decision-making - to create value for themselves
and society.
We agree. The availability of massive amounts of machine readable data and the ubiquity of advanced
analytics software tools are what makes decision-making and subsequent value creation vastly
improved. Franky, we think is the main difference between this digital transformation and the e-
commerce craze of the 1990’s.
Figure 1 Essential Activities of Digital Transformation
This virtuous cycle of Data – Analytics – Innovation can create benefits at all levels of the enterprise. At
the Strategic level, customer preferences can be gleaned from social media platforms, major market
trends can be ascertained, and even predicted by monitoring the world’s news sites, eligible technical
partners can be found by mining the sites of major federal funding agencies, etc.
At the Operations level Predictive Analytics can be used to optimize inventory sizes and parts
management. Likewise, business processes can be streamlined and customer service enhanced. At the
Work Process level, Virtual Reality and Artificial Intelligence are already showing the ability to enhance
employee capabilities in complex work situations.
Working with the McKinsey Global Institute the GAO estimate the impact of the economic and social
benefits – generate created by this virtuous cycle of data, analytics and innovation, on the U.S. economy
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alone, to be substantial. The impact from using open source data sets, such as those found on the World
Wide Web, is projected to range between 3.2 and 5.4 trillion dollars by 2025. They expect another 2.7 to
6.2 trillion dollars of economic growth to occur as the result of analyzing and acting on the data
produced by “connected sensors” (Internet of Things).
By any measure digital transformation represents an enormous opportunity for those organizations
capable of seizing it. We see opportunities for these firms to redefine their core competencies and
reposition themselves in the marketplace with entirely new value propositions. By making better, more
informed decisions - using carefully analyzed data - the resulting innovation can even generate strategic
imperatives for future success. As stated, digital transformation is a virtuous cycle, and as such should
be the core strategy for any company that wants to succeed in the digital era.
III. A step-wise approach in the capital goods sector (Case Study)
Digital transformation it is not confined to just internet-based firms, like Amazon, Google, Netflix and
others. It is a pervasive trend is taking place in industries of all types. To illustrate the impact digital
transformation is having on to traditional manufacturing industries, we provided workshop participants
with an actual case study from the agricultural equipment industry -- that of the CLAAS Group.
CLAAS Group is a manufacturer of advanced agricultural machinery for the very lucrative market of
‘precision farming’ equipment and services. Over a period of more than 10 years, CLAAS has transitioned
from a major producer of harvesting equipment, to a pioneer of a new, platform-based business – one
that holds great promise for the entire agricultural industry. During this period the company’s strategic
focus changed from 1) its initial focus on the quality and reliability of its machines, to 2) a focus on
availability management and its ability to offer contract-based services, to 3) today, with its focus on
data acquisition and integration and being an analytics- savvy partner in a new platform business. (See
Figure 2 CLAAS transitions to an Information Services business)
How this was possible
A well-known, and successful strategy industrial companies frequently use to differentiate themselves
from their competition is to offer value-added services. Over time this leads these organizations to shift
their focus away from purely product-based offerings, to integrated, value-added solutions offered
through favorable, long-term client contracts. The goal is to provide customers with unique services -
thus establishing long lasting relationships that more closely link customers to these producers.
IoT is a Key Enabler
Sensors and actuators are becoming more intelligent and fully integrated in industrial goods. The
Internet of Things (IoT) offers the potential to transfer a wide variety of data at unprecedented levels of
speed and volume. These data can be used to gain new insights into customer needs that can be used to
accurately define new products and services for these and other clients. As such, broad application of
IoT technologies is an important driver for innovation and a clear way to differentiate ones business
model.
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Figure 2 CLAAS GROUP Transitions to an Information Services Business
Over time these companies accumulate more and more knowledge about how a piece of equipment
behaves and the factors that determine equipment performance. CLAAS GROUP was no exception; they
become experts on equipment behavior and offer this knowledge to their customers. This presented
CLAAS with the opportunity for a new, services-led business model – one which differed significantly
from their past product-based model. Revenues, and brand identity, are no longer solely linked to the
production and sales of new products. Instead, they are driven by an intimate connection with their
customers and the in-depth knowledge of these customers equipment needs. (Refer to Figure 2 and the
intersection of Customer Integration and Equipment Services).
In the final phase of its digital transformation, CLAAS sought out partners who could provide
other data, such as weather, and other context related information that further enriched its
knowledge base. This final step established CLAAS as full partner in an agriculture information
service platform, 365 FarmNet (See Figure 3 for a complete description of the 365 FarmNet ecosystem).
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Figure 3 CLAAS GROUP as major platform player in 365 FarmNet
Exponential growth is a real possibility
Entering a platform-based model offers a unique opportunity for manufacturing companies to
reposition as an orchestrator or at least core player in an ecosystem and even actively design such an
ecosystem. The notation of a two-sided business model is the core concept of the platform-based
economy and states that a unique value is produced for two different customer groups, which are linked
through the platform. Direct network effects in each customer group and indirect network effects across
the two sides are in the core of the development strategy: it is intended to grow the numbers of
customers for both sides as fast as possible to generate exponential growth.
Figure 3 illustrates how a software defined information platform, such 365 FarmNet, brings together
many different players to form an agriculture ecosystem. Every player is part in the value network. The
common interest of all parties is to generate novel insights when linking data from the harvesting
process, weather forecasts, or geographic data to predict the effects of a particular fertilizer and seed
combination. Analyzing this data allows CLAAS to offer a variety of services such as area specific
cultivation or location specific fertilization protocols.
IV. Results of the Expert Workshop
World café methodology
The world café methodology builds upon a structured process of group discussion. Ideas related to a
particular topic are discussed first by one group and subsequently by the other groups. Each group
building upon the thoughts of the previous group(s) by their own perspectives and ideas. The objective
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is to gather the collective knowledge of all the people in the room. Facilitators of a world café formulate
hypotheses, or questions, related to a topic and write them down on a work table. Groups move from
table to table writing their ideas on the table cloth.
To assess the state of Digital Transformation research and to begin formulating an action plan to close
the gap between practice and theory, we choose three topics, or themes, to explore: 1. Transformation
Strategies, 2. Transformation Design, and 3. implementation (Gudergan, Buschmeyer 2014).
Transformation Strategies identifies the business strategies, which from our experience, are the
strategies organizations most frequently employ when beginning their digital transformation journey,
e.g. Digital Joint Venture, Digital Hub, Digital Ecosystem, etc.. Transformation Design addresses the
specific actions organizations take to deploy the strategy at a program and business unit level.
Transformation Design covers all aspects of defining the new business system, including its business
model and organizational structure. Implementation integrates the specifications created in
Transformation Design into the existing organization, creating the new systems and procedures needed
to operate the new model.
For each topic, we wrote three questions on the tablecloth to generate discussion:
1. What in your mind are the greatest opportunities for new research?
2. What do you see as the biggest barriers to progress?
3. What actions would you recommend be taken immediately?
We had 50 experts, learned research faculty from around the world, participate in the World Café. We
broke these people into 3 groups. As can be imagined the discussions were lively! We were impressed,
however, by the seriousness these faculty approached the task. At the end all participants were of the
same mind that a gap does indeed exist between the practice and theory of digital transformation and,
more importantly, they want to see it closed. Consequently they took the exercise seriously and
immediately engaged with the other participants in voicing ideas to close the gap. We were very
impressed by these people, they are wonderful representatives of their universities and academe
overall.
The raw results from the world café are captured in the following data tables. To see our analysis of
these inputs, please jump ahead to the three narratives labeled A. Transformation Strategies, B.
Transformation Design, and C. Implementation respectively.
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Data Tables
Research
Opportunities
Transformation
Strategies
Transformation Design
Implementation
Theoretical foundations
(Multi perspectives view
including social systems and
technology)
Shared understanding of
digital transformation as a
phenomenon
Embeddedness in corporate
strategy
Barriers and success factors
Value of data and data
analytics
Disruptive business models
Ecosystem design
Transformation patterns for
established companies
Integration of mature
workforce and change in
established mindsets
Interplay between culture,
technologies and processes
Impact on employment and
role definitions
Resources to do research
Design tools and
methodologies suited to the
development of digital
products (waterfall vs. scrum
…)
Creating new/green
meadows as research areas
Methods for agile value
creation
Methods for Ecosystem
design
Human Technology
interaction models
Cognitive Engineering
Methods to analyses paths
and patterns and
organizational development
Digital business innovation
Make use of popular
practical publication (blogs)
Interdisciplinary, domain
crossing approaches
Inertia and cultural
barriers
Skills transformation and
shift in peoples’ mindsets
Digital Leadership
Leadership roles in
implementation
Change in Culture and
mindset
Trust Building
Crises management
Managing complexity of
change in organizations
Table 1
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Barriers to
Research
Transformation
Strategies
Transformation Design
Implementation
Missing Definition and
concept of digital
transformation
Lack of Theory Building
Lack of understanding cause
and effects
Get access to real cases
Stimulate urgency at
business leadership level
Publication speed to slow
Single discipline focused
publications needs to be
changed towards
interdisciplinary perspective
Need to Position the term
“Digital Transformation”
Ecosystem Design
Descriptive domain models
Models for IT-Business
integration
Focus on quality research
not necessarily following old
publication paradigms
Review journal policies to
allow case based research
Increase speed of review
processes
Develop set of new and
acknowledged research
methods
Focus on Data based
perspective
IPR restrictions from
industrial side
Need to reduce
conceptual confusion and
to define the core
concept of digital
transformation
Need to rethink change
Management processes
and to handle emergent
phenomena
Specific needs regarding
social demographics
Missing knowledge about
human-technology
interaction
Missing knowledge about
success factors and
boundary conditions such
as employment modes
Need of new research
philosophy and
approaches
Table 2
Immediate
Actions
Transformation
Strategies
Transformation Design
Implementation
Help industry understand
value of academic research
Develop first taxonomy
Understand business needs
and industrial systems
Develop maturity models
Develop crowd platforms
Apply service design
approaches to start
Address topic at C-Level
Focus on case based
research approaches and
learn in cooperation with
industry
Change university curricula
Try to identify first theoretical
and conceptual foundations
Stronger partnership with
industry
Teach design thinking
Accept less rigorous but faster
methods
Reward & encourage
empirical research & analysis
Change university curricula
to focus on implementation
and change methods
Understand knowledge
creation
Develop interdisciplinary
research teams
Address C-Level
Table 3
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A. Transformation Strategies
1. Research Opportunities
Transformation Strategies are the actions taken by senior management to change the organization into
a new digital business. In general, great opportunities can be realized if transformation strategies are
made an integral part of corporate strategy and thus becomes a part of the strategic research agenda.
However, this requires developing the set of theoretical foundations and a shared understanding of
digital transformation as a phenomenon. Developing effective transformation strategies requires taking
multiple perspectives into account, such as new social systems and organization structures that facilitate
and encourage open communications between business functions.
Another suggested research opportunity is to study the effect specific success factors have on a
transformation strategy, to include the Interplay between culture, technologies and processes in
achieving the strategy. Yet others suggested we explore how a mature workforce, with established
mindsets, deal with change.
Participants generally were in agreement that the value of having access to massive amounts of real
time data and advanced data analytics tools needs to be better understood and models created to
quantify these values. As the report by the US General Accountability’s Office observes -- this is the main
difference between today’s digital transformation and the Dot.com explosion of the 1990’s. Participants
also agree that developing adequate transformation strategies requires a profound understanding of
disruptive business models and the function and design of digital ecosystems as well.
2. Barriers to Research
Participants cited several major barriers to research. They see digital transformation as missing any
theoretical basis. It lacks rigorous definition and in academic circles the subject is not connected to great
benefits it promises for society. There was almost universal agreement that there is an urgent need to
start building a solid theoretical foundation of digital transformation and launching research into its
domains.
Current research practices was cited as a chief barrier to doing studies in digital transformation. It is
often difficult for research faculty to get access to real cases – while they are occurring - and executives
at the business leadership level to sponsor their studies. In addition, the publication cycle of academic
journals is be too slow to meet the pace of digital transformation. By the time an article is published it
may be too late for organizations who bet their future on changing their business models. Lastly,
journals that focus on a single discipline, for example Computer Science, Business Management, or
Industrial Engineering, need to expand their scope and include interdisciplinary articles that deal with
the complexity and true nature of digital transformation.
3. Immediate Actions
In general, participants felt that academics need to get in much closer contact with companies to better
understand the needs of industry. There was general agreement that if some prominent institutions
were to initiate this practice - and be recognized for it - that others would soon follow. Others felt that if
institutions were to emphasize case-based research approaches - that foster “action learning” with their
industry counterparts - it would likely generate new insights faster. As a result the academic research
performed by their faculty would be viewed as being more timely and relevant.
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Participants generally support the development of a digital transformation taxonomy to help bridge the
gap that exists between industry and academia. They also recommend the development of a digital
transformation maturity model to help educate and guide organizations through their transformation
journeys. Making use of existing methodologies, such as FIR’s Innovation Blocks Methodology, or CIMS
Innovation Management Maturity Assessment (IMMA) tool (Mugge, Markham 2013), might make good
starting points for this initiative.
B. Transformation Design
1. Research Opportunities
Transformation design refers to the specific tasks required to form a new organization and culture, i.e.
defining its structure, governance system, core processes, tools, and key performance indicators.
Participants agreed there appears to be a great opportunity to create new research methods for the
design of a digital organization.
When it came to specific research recommendations there was no shortage of ideas. Participants
recommended several interesting topics such as: i) new methods for agile value creation, ii) methods
and tools for ecosystem design, iii) human-technology interaction models, iv) cognitive engineering
approaches, v) methods to analyze the paths and patterns and organizations take to become digital
businesses, etc.
Also participants told us that even see an opportunity to make use of popular practitioner publications,
such as blogs which typically cross domains and disciplines.
2. Barriers to Research
One major barrier seems that the term “Digital Transformation” is not yet positioned in academic
research. The term needs to be positioned to pave the ground for further research. There is specific
need to start with ecosystem design and descriptive domain models including business-IT interaction to
in order to advance future research. As mentioned, current research practices act barriers to research in
Transformation Design as well. Research institutions should be open to the immediate problems of
industry. Case-based research should be fostered and the speed in publication practice should be
increased. Again this will require a significant change in paradigm for existing journal publishers and
vetted articles that could take as long as 2 years to publish.
3. Immediate Actions
There is an immediate need to adjust university curriculums to address the skills organizations require to
survive and prosper in this era of disruptive innovation and change. All students, regardless of discipline,
must possess an entrepreneurial mindset and be proficient in the use of advanced analytics software
tools.
Strong partnerships with industry should be established immediately to help guide the definition of
these curricula. If established journals do not want to change their present practice a new outlet must
be found for the faculties’ publications. In addition to quality, these outlets must put an equal emphasis
on speed in keeping with the needs of a new audience – those organizations engaged in a digital
transformation.
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C. Implementation
1. Research Opportunities
The greatest research opportunity associated with implementing a digital business is how to overcome
inertia and cultural barriers that keep companies locked into their current business designs. These
aspects are complicated by the fact that implementation represents a fundamental change to the
organization and is heavily dependent on transforming skills and shifting peoples’ mindsets. Participants
see an opportunity for research aimed at developing “digital leaders”. These leaders must be versant in
the principles of new technologies, such as IoT, machine learning, etc. Most importantly, they must be
able to assess the organizations appetite for risk and be able to align employees behind the
organization’s transformation plan. Some participants were even more specific and suggested that a
comprehensive curriculum be researched and developed for digital leaders to include new methods for
managing crises and how to build and maintain trust throughout the transformation process.
2. Barriers to Research
There was a strong desire on the part of most participants to reduce the conceptual confusion
associated with digital transformation. As already established, emergent phenomena like it are not
covered sufficiently by the academic literature. This confusion in terms and definitions is itself a barrier
to research. Participants see a strong need for a new research philosophy, and approach, for advancing
the knowledge about implementing a digital transformation strategy. Some participants thought that
the whole topic of human-technology interaction needs revisiting – this may likely be a critical success
factor. Again, the barriers to research cited were manifold and consistent with those already discussed.
3. Immediate Actions
There was a general consensus that in order to advance research in digital transformation
implementation, faculty need to petition their universities to change existing the curricula of degree
programs that may no longer be relevant. Participants also recommend these institutions develop
interdisciplinary faculty research teams and foster a close collaboration with industry.
VI. Recommendations
From our analyses, we generated a set of policy recommendations which from our perspective might
advance academic research activities in the area of digital transformation. These recommendations are
intended to begin closing the gap which exists between industry and academe on this important topic.
1. Universities should initiate cross-College research teams to investigate what needs to be done
to investigate Digital Transformation in their institutions. In all likelihood, this will lead to new,
cross-discipline curricula, a must for learning how to apply digital transformation methods and
tools.
2. University's need to put an emphasis on industry collaboration. A good first step would be to
form an Industry Advisory Council at the Chancellor/President level. This body could act as a
steering committee for the initiative, and faculty, described in 1. above.
3. Journal editors need to provide an outlet for clinical / applied research articles. University's need
to recognize the merit of these publications and reward faculty for these works.
4. Researchers need to build the conceptual foundation for research in digital transformation.
Profound research in digital transformation needs a common understanding of the terminology
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and research domain. This could start with a HICSS-sanctioned Taxonomy of Digital
Transformation.
5. Researchers need to develop new tools and methods to shape the future digital system. The
design and research of enterprises is currently still done with tools and methods which have
been developed for the pre-digital economy. More efforts need to be invested to provide
organization designers and researchers with a set of tools which are suited to model the specific
aspects of a digital enterprise.
Final Thoughts
As for CIMS and FIR we have initiated a large scale, international study on the key aspects of digital
transformation. This study is targeted to research the implications of digital transformation from an
industry perspective. A best practice benchmarking platform is under development by CIMS and FIR.
This will provide these companies - and ourselves - further insights into how companies are
transforming themselves.
Likewise, we intend to develop a “living” Ontology of Digital Transformation using the machine learning
capability of IBM Watson. At HICSS51 we plan to find and classify all the research publications and major
conference proceedings on the subject. (See proposal we made for a workshop at HICCS51).
VII. References and Bibliography
BRYNJOLFSSON; MCAFEE (2011): RACE AGAINST THE MACHINE - HOW THE DIGITAL REVOLUTION IS
ACCELERATING INNOVATION. Digital Frontier Press.
GAO-16-659SP (2016): DATA ANALYTICS AND INNOVATION Emerging Opportunities and Challenges.
GUDERGAN, G; BUSCHMEYER A. (2015): KEY ASPECTS OF STRATEGY AND LEADERSHIP FOR BUSINESS
TRANSFORMATION. In: 360° – the Business Transformation Journal No. 11 | August 2014.
ISMAIL, SALIM; MICHAEL S. MALONE (2014): EXPONENTIAL ORGANIZATIONS: WHY NEW
ORGANIZATIONS ARE TEN TIMES BETTER, FASTER, CHEAPER THAN YOURS (AND WHAT TO DO ABOUT
IT). Diversion Publishing.
MUGGE, PAUL; MARKHAM STEPHEN K. (2013): AN INNOVATION MANAGEMENT FRAMEWORK, the
PDMA Handbook of New Product Development: 35-50.
ROGERS (2016): DIGITAL TRANSFORMATION PLAYBOOK: RETHINK YOUR BUSINESS FOR THE DIGITAL
AGE. Columbia Business School Publishing
UHL; GOLLENIA (2012): A HANDBOOK OF BUSINESS TRANSFORMATION MANAGEMENT METHODOLOGY.
Springer.
WESTERMANN (2014): LEADING DIGITAL: TURNING TECHNOLOGY INTO BUSINESS TRANSFORMATION.
Harvard Business Review Press
Brief biographies of the authors
Dr. Gerhard Gudergan is Head of the Unit Research and Head of Department Business Transformation
both. For eight years, he used to be the head of the department “Service Management” at FIR with its
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main research groups on service engineering, service performance management and community
management. Dr. Gerhard Gudergan is director of the Center Smart Services on the RWTH Aachen
Campus and founder of the Service Science Innovation Lab at RWTH Aachen Campus. He is senior
lecturer at RWTH Aachen University for “Service Design and Engineering” and responsible for the
module of “Business Model Innovation and Services” and the Track of “Digital Transformation” as part of
the Executive EMBA of RWTH Aachen University and Fraunhofer Academy. Dr. Gerhard Gudergan has a
Ph.D. in Mechanical Engineering from RWTH Aachen University and a Masters in Mechanical Engineering
from RWTH Aachen University. He is member in different expert groups on service science and service
innovation and standardization. He is full member of the Working Group 5.7 of APMS within IFIP where
he is responsible for the SIG on “Service Systems”. His research interest is focusing on digital
transformation and innovation in services.
Paul Mugge is Executive Director, Center for Innovation Management Studies (CIMS) and Innovation
Professor, Poole College of Management, NC State University. After working in IBM R&D for over 35
years, Mr. Mugge was selected to lead the Center for Innovation Management Studies (CIMS) at NC
State University. CIMS was founded by the NSF in 1984 and is one of the few research centers in the
United States devoted to the science and art of innovation.
At IBM, Mr. Mugge served on the design team that pioneered IBM’s first self-diagnosing, self-healing
computing system. Additionally, he led the IBM task force that conceived the popular IBM ThinkPad. Mr.
Mugge received the IBM Innovation Achievement Award for the overall design and program
management of the company’s first rack-mounted, “supermini-mainframe,” the IBM 9370 and was also
awarded IBM Chairman’s Award for leading re-engineering of its hardware and software businesses.
At CIMS, Mr. Mugge teaches two masters-level programs, Masters of Global Innovation Management
and a unique MBA program called the Value Creation Practicum. Mr. Mugge is a noted author and
speaker. He and co-author Professor Stephen Markham recently published a book titled, Traversing the
Valley of Death: a guide to corporate innovation leaders. In addition Mr. Mugge authored the CIMS
Innovation Management Framework and the Innovation Management Maturity Assessment (presented
at HICSS 49). In addition Mr. Mugge was Co-PI, of the NSF Partnership for Innovation grant: National
Partnership for Managing Upstream Innovation: The Case of Nanoscience and Technology and a
contributing author, to CIMS Newsletter, Technology Management Report.
