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History of Digital Transformation

  • University of Applied Sciences Neu-Ulm

Abstract and Figures

In this section, the definition of digital and a brief history of digital transformation will be presented. Additionally, we explore the difference between digitization and digitalization. Finally, we will address the similarities and differences between Business Process Reengineering and digital transformation and look at the future of digital transformation.
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University of Applied Sciences Ulm
Prittwitzstrasse 10, 89075 Ulm, Germany
Ulm University, Helmholtzstraße 16
89081 Ulm, Germany
University of Applied Sciences Ulm
Prittwitzstrasse 10, 89075 Ulm, Germany
Published 30 November 2017
The purpose of this paper is to clarify the denition of digital transformation (DT) and to
introduce a structured approach with phases, activities and results. Our research is based on
a literature review which provides insight into the basic understanding of DT. Examples
complete the research and show the practical application of DT. The main ndings are that
although DT is a widely known concept, an approach for the structured DT of business
models is missing. The paper offers a clear denition of the DT of business models and
phases for the DT of business models. Moreover, the paper offers examples of enablers
and DT.
Keywords: Digital transformation; digitisation; business model; business model innova-
tion; enabler; best practices.
Corresponding author.
International Journal of Innovation Management
Vol. 21, No. 8 (December 2017) 1740014 (17 pages)
© World Scientic Publishing Europe Ltd.
DOI: 10.1142/S136391961740014X
What do vehicle makers like Rosenbauer, logistics company DB Schenker,
compressor manufacturers such as Bauer, elevator producers like ThyssenKrupp,
and Hagleitner, a hygiene goods corporation, have in common? They all use the
potential of digitisation to offer customers smarter and faster services and actively
shape their business models digital transformation (DT). DT affects all sectors of
society, in particular economies. At the same time, DT opens new networking
possibilities and enables cooperation between different actors, who, for example,
exchange data and thus initiate processes. In this context, the DT of business
models plays an essential role because business modelsindividual elements can
be digitally transformed.
DT has been discussed for many years but what is still unaccounted for is a
clear denition for the DT of business models, an approach for how to digitally
transform business models, which phases and instruments should be considered,
and examples of what enablers exist. In our research, we develop a framework for
the DT of business models by analysing the existing literature and studying
practical examples. We combine two relevant topics: DT and business model
(innovation). Our contribution is important for dening the DT of business
models within academia and providing a blueprint for how it can be applied in
Theoretical Background
History of DT
Although DT is a popular point of discussion at the moment, the ideas of digital
products, services, and mediums were already well-understood in the 1990s and
2000s (Auriga,2016). For example, in the retail industry, mass media advertising
campaigns were considered important digital channels with which to reach cus-
tomers in the 1990s and 2000s, even though purchases were still primarily made
inside brick-and-mortar stores, often with cash. From 2000 to 2015, the rise of
smart devices and social media platforms led to a drastic sea change in the
methods customers used to communicate with businesses, and also the expecta-
tions customers had with regards to response times and multi-channel availability.
Businesses started to see that they were now able to communicate digitally with
their customers on an individual basis, and often in real time. An ever-growing
selection of digital payment options such as PayPal also contributed to more and
more online commerce and opportunities for web-based points of sale. Nowadays,
there is a focus on mobile devices and on creating value for customers by
D. Schallmo, C. A. Williams & L. Boardman
leveraging the kinds of personalised customer data that mobile technologies can
generate on a massive scale. Businesses are taking advantage of this personalised
information and are able to better tailor their products, communications, and
interactions to t customersspecic needs.
Dening DT
There is currently no commonly accepted denition for the term DT. Moreover,
the terms digitalisation and the digitisation are often used interchangeably (BDI
and Roland Berger,2015). Selected denitions in the context of DT are shown in
Table 1.
Table 1. Current denitions.
Author Denition
BMWi (2015) Digitisation stands for the complete networking of all sectors of the
economy and society, as well as the ability to collect relevant
information, and to analyse and translate that information into
actions. The changes bring advantages and opportunities, but they
create completely new challenges.
Bowersox et al. (2005) Digital Business Transformation (DBT) is a process of reinventing a
business to digitise operations and formulate extended supply chain
relationships. The DBT leadership challenge is about reenergizing
businesses that may already be successful to capture the full
potential of information technology across the total supply chain
Westerman et al.
DT the use of technology to radically improve the performance or
reach of enterprises is becoming a hot topic for companies
across the globe. Executives in all industries are using digital
advances such as analytics, mobility, social media, and smart
embedded devices and improving their use of traditional
technologies such as ERP to change customer relationships,
internal processes, and value propositions.
Mazzone (2014)DT is the deliberate and ongoing digital evolution of a company,
business model, idea process, or methodology, both strategically
and tactically.
PwC (2013) DT describes the fundamental transformation of the entire business
world through the establishment of new technologies based on the
internet with a fundamental impact on society as a whole.
Bouée and Schaible
We understand DT as a consistent networking of all sectors of the
economy and adjustment of the players to the new realities of the
digital economy. Decisions in networked systems include data
exchange and analysis, calculation and evaluation of options, as
well as initiation of actions and the introduction of consequences.
Digital Transformation of Business Models
Based on the literature, we propose the following denition of DT for our
The DT framework includes the networking of actors such as
businesses and customers across all value-added chain segments
(BMWi,2015,p. 3; Bowersox et al.,2005,22ff.;Bou
ee and
Schaible,2015,p. 6), and the application of new technologies
(PwC,2013,p. 9; Westerman et al.,2011,p. 5). As such,DT
requires skills that involve the extraction and exchange of data as
well as the analysis and conversion of that data into actionable
information. This information should be used to calculate and
evaluate options, in order to enable decisions and/or initiate
activities (BMWi,2015,p. 3; Bou
ee and Schaible,2015,p. 6).In
order to increase the performance and reach of a company
(Westerman et al.,2011,p. 5), DT involves companies,business
models,processes,relationships,products,etc. (Bowersox et al.,
2005,22ff.;Mazzone,2014,p. 8).
Business process reengineering vs. DT
Some researchers and practitioners might see similarities between Business Pro-
cess Reengineering (BPR) and DT. In their oft-cited work, Hammer and Champy
(1993) provided a denition of BPR. The authors state that BPR is the rethinking
and reengineering of business-related processes in order to reduce costs and
improve products and services.
Although there are some similarities between BPR and DT, there are some
distinct differences between the two approaches as well. According to Proctor
(2017), BPRs focus is mainly on automating rule-based systems. Rule-based
systems are dened as sets of clearly assigned rule-based (algorithmic) processes
which are automated by technologies. Instead of focusing on rule-based processes
like BPR does, the main objectives of DT are obtaining new data and using this
data to reimagine these old, rule-based processes.
A more data-oriented approach allows for the opportunity to gain new
knowledge and in turn reimagine business models and operations. For example,
Airbnb turned its attention from processes to data. Airbnb does not own its own
physical assets (e.g., hotels). Here is an example of how old, rule-based processes
in the hotel industry can be completely reimagined in a data-driven world. The
part-time landlords and landladies who own properties in highly sought-after
locations and microlease them on Airbnb offer an alternative to hotels and create
unique value for guests (Bendor-Samuel,2017).
D. Schallmo, C. A. Williams & L. Boardman
How employees interpret newly acquired know-how and use it to improve
decision-making capabilities is what differentiates DT from other elds of study.
All of the new data sources create newly formed knowledge sources based on that
data. Instead of only making processes more efcient or quicker, which is the aim
of automation, DT requires individuals to rethink old processes and reimagine new
processes and decisions.
Denition of business model
One of our contributions to the eld of the DT of business models is the following
denition (Schallmo,2013):
A business model is the basic logic of a company that describes
what benets are provided to customers and partners. A business
model answers the question of how the provided benets ow
back into the company in the form of revenue. The created value
enables a differentiation from competitors,the consolidation of
customer relationships,and the achievement of a competitive
advantage. A business model involves the following dimensions
and elements:
.The customer dimension contains the customer segments,cus-
tomer channels,and customer relationships.
.The benet dimension includes products,services,and values.
.The value-added dimension includes the resources,skills,and
.The partner dimension includes the partner,partner channels,
and partner relations.
.The nancial dimension includes the revenues and expenses.
The objective is to combine the business model elements in such
a way that they mutually reinforce each other. This makes it
possible to achieve growth and makes imitation by competitors
Denition of the DT of business models
Based on the proposed denitions, we dene the DT of business models as follows
The DT of business models relates to individual business model
elements,the entire business model,value-added chains, as well
as the networking of different actors in a value-added network.
Digital Transformation of Business Models
The degree of the DT includes the incremental (marginal) as
well as the radical (fundamental) change of a business model. The
reference unit with regard to the level of novelty is primarily the
customer,but a DT can also affect its own business,partners,
industry,and competitors.
Within the DT of business models,enabler(s)and technologies
(e.g.,big data)are used to generate new applications or services
(e.g.,on-demand prediction). These enablers require skills that
enable data collection and exchange as well as the ability to
analyse,calculate,and evaluate options. The evaluated options
are used to initiate new processes within the business model. The
DT of business models is based on an approach with a sequence
of tasks and decisions that are related to one another in a logical
and temporal context. It affects four target dimensions:time,
nance,space,and quality.
Research Questions and Research Design
Research questions
In the previous section, a brief review of the literature established our theoretical
foundation for DT. To serve as a basis for our Roadmap, we have selected three
independent existing approaches to DT. Esser (2016)denes ve phases that lay
out a development plan for a DT strategy and its implementation. Pricewa-
terhouseCoopersframework denes six phases of DT (PwC,2013). Boueé and
Schaible (2015) describe a detailed plan for digital transformation that is specif-
ically designed to prepare for the digital future.
Although these approaches make valuable contributions, they do not
completely cover the DT of business models and do not specify the DTs appli-
cation. In our contribution, we initiate the DT of business models and develop a
Roadmap including several phases.
Based on the problem described and current understanding, we will answer the
following research questions:
.What does a structured approach to the DT of business models look like?
.What types of phases, activities, and results are relevant?
.Which enablers (e.g., sensors, big data, etc.) and which applications are
.What examples exist for the DT of business models and what are the best
practices in this eld?
D. Schallmo, C. A. Williams & L. Boardman
Research design
We applied case study methods to our literature review because this methodology
is desirable for describing and analysing relevant cases in which grounded-theory
can be developed (Benbasat et al.,1987;Eisenhardt,1989;Kromrey,2013;Stake,
We analysed existing denitions, approaches, and examples of the DT of
business models. We conducted the literature review to gain insight into current
research in DT and developed a Roadmap for the DT of business models,
including examples.
Approach to the DT of Business Models
A Roadmap is given here based on the presented approaches to DT and based on
existing theories about business model innovation (see Bucherer,2011;Rusnjak,
2014;Schallmo,2013,2014;Thomas,2014), the Roadmap for the DT of business
models is explained as follows:
.Digital Reality: In this phase, Digital Reality, the companys existing business
model is sketched along with a value-added analysis related to stakeholders and
a survey of customer requirements. This provides an understanding of the
Digital Reality for this company in different areas.
.Digital Ambition: Based on the Digital Reality, objectives with regards to DT
are dened. These objectives relate to time, nances, space, and quality. Digital
Ambition postulates which objectives should be considered for the business
model and its elements. Subsequently, objectives and business model dimen-
sions are prioritised.
.Digital Potential: Within this Digital Potential phase, best practices and
enablers for the DT are established. This serves as a starting point in terms of
Digital Potential and the design of a future digital business model. For this
purpose, different options are derived for each business model element and
combined logically.
.Digital Fit: The Digital Fit phase looks at options for the design of the digital
business model, which are evaluated to determine Digital Fit with the existing
business model. This ensures that one fulls customer requirements and
that business objectives are achieved. The evaluated combinations are then
.Digital Implementation: Digital Implementation includes the nalisation and
implementation of the digital business model. The various combinations of
Digital Transformation of Business Models
options are further pursued within a digital implementation framework. The
Digital Implementation also includes the design of a digital customer experience
and digital value-creation network that describe integration with partners. In
addition, resources and capabilities are also identied in this phase.
Figure 1represents the Roadmap to the DT of business models with the various
phases and activities. The phases are explained further below, each with its specic
objectives and questions. Subsequent activities along with each of their instru-
ments are also shown. Selected activities are illustrated by case studies.
Enablers serve to allow applications or services to be used for the DT of the
business model. Four categories for enablers and applications/services are detailed
.Digital Data: The collection, processing, and analysis of digitised data to fa-
cilitate and improve predictions and decisions.
.Automation: The combination of classical articial intelligence technologies
that enables autonomous work and self-organising systems. This reduces error
rates, increases speed, and makes it possible to reduce operating costs.
Fig. 1. Roadmap for DT (Schallmo,2016, p. 23).
D. Schallmo, C. A. Williams & L. Boardman
.Digital Customer Access: The mobile internet enables direct access to the client,
who are thus provided with high levels of transparency and new services.
.Networking: Mobile or wired networking of the entire value-added chain via
high speed broadband telecommunications allows for the synchronisation of
supply chains, which leads to a reduction in production times and innovation
Enablers are listed with their applications/services in a digital radar, which is
shown in Fig. 2.
The Digital radar can supplement more enablers and applications/services as
needed. The following is an example of the additive manufacturing of bionic
aircraft components. Additive manufacturing can be used analogously for the
printing of spare parts for engines (Knabel,2015;Flugrevue,2016). Airbus
installed a bionic-shaped bracket in an A350 test aircraft in July of 2014 and ight
tests were successful. It is a component which was printed(sintered) with ti-
tanium powder and it has the same specications regarding function and strength
as a conventional component. Advantages include:
.Less material and weight (30% lighter)
.Subsequent reduction of fuel consumption
.Increased inventory exibility, as Airbus can printspare parts on the spot
according to original specications without depending on large manufacturing
facilities or waiting on shipments.
Fig. 2. Digital radar with enablers and applications (Boueé and Schaible,2015).
Digital Transformation of Business Models
Best Practices for the DT of Business Models
ThyssenKrupp is a German industrial group with different divisions. The Elevator
Technology division produces passenger and freight elevators as well as escalators
for ofce buildings, residential buildings, hotels, airports, shopping centres, and
other facilities. In addition to the sale and installation of elevators and escalators,
maintenance, repair, and modernisation services are also offered (ThyssenKrupp,
Initial situation & problem denition
ThyssenKrupps old business model mainly focused on the manufacturing of
elevators, installing them, and carrying out maintenance as needed. An increasing
number of tall buildings in major cities led to an increased demand for high-
performance elevators. Furthermore, customers and users demanded superior el-
evator reliability. In addition, several already-installed elevators posed a risk to
users due to maintenance backlogs (ThyssenKrupp,2016b;Wetzel,2014).
Additionally, ThyssenKrupps competitors began to offer elevator maintenance
service packages, which is a high-margin offering compared to product sales
(Dispan, 2007: 22; Odermatt and Kressbach,2011).
Objective & solution approach
The objective of ThyssenKrupps elevator business was to reduce the duration of
their elevatorsoutages by identifying causes of potential failure in a predictive
manner. This would ultimately allow for faster maintenance and shorter repair
times. To address this concern, they created the MAX, Elevator Monitoring
The timely identication of potential causes of outages requires a real-time ow
of information which provides key insights into an elevators current status. To
accomplish this, they outtted ThyssenKrupp elevator components, such as drive
motors, elevator doors, and elevator shafts, with sensors. These sensors collect
information such as the cabin speed and motor temperature. The information
obtained is then evaluated with the help of predictive analytics and provided to
employees, who are responsible for maintenance and technology. These
employees now receive warning alerts as well as maintenance guidance and
These changes allowed ThyssenKrupp to proactively carry out maintenance
work and with foresight, thus reducing elevator downtime. In addition, costs,
resources, and maintenance planning were improved (CGI,2016).
D. Schallmo, C. A. Williams & L. Boardman
ThyssenKrupps MAX Elevator Monitoring System is an example of a mainte-
nance-oriented digitisation initiative. MAX collects relevant technical and me-
chanical information through sensors to reduce maintenance backlogs and improve
ThyssenKrupps overall maintenance services. Put simply, information that was
being ignored before is now being collected and utilised to provide value to
customers and create prot for ThyssenKrupp a textbook example of the DT of
a business model.
DT is a continual process. One could also imagine other opportunities for DT
which ThyssenKrupp could implement. For example, an interactive screen/bill-
board could be offered in select models of elevators. These touch screens could
add value to a wide swath of stakeholders. The interactive elevator billboard could
be used by ThyssenKrupp to collect customer satisfaction feedback or the inter-
active elevator billboard space could be leased or sold outright to end users or
third-party advertising agencies. End users could leverage the interactive elevator
billboard space to increase company awareness or collect employee feedback on
certain company events or decisions, while third party advertisers could use the
screen to serve highly-targeted ads to a captive audience.
ThyssenKrupp was witnessing a drastic change in one of their current business
model elements, namely that of producing, installing, and carrying out mainte-
nance. The customer maintenance requirements were changing and ThyssenKrupp
needed to come up with a solution. The sole purpose of MAX is to gather and take
advantage of data and utilise modern predictive analytics to better evaluate and
predict maintenance issues.
The proposed interactive elevator billboard space could address another
opportunity to add value; namely workplace communication and a chance to
introduce a new media channel and marketing platform into an otherwise barren
environment. Effective maintenance services are an obvious priority add-on for a
major elevator manufacturer like ThyssenKrupp but an in-elevator touch screen
digitisation initiative could also be valuable. The idle-time spent riding in an
elevator could be seen as a golden opportunity to broadcast information to or
collect information from elevator riders.
ThyssenKrupps Max system increased protability by offering a premium
maintenance add-on service which promises to decrease maintenance backlogs.
The proposed interactive elevator billboard space could provide an additional
revenue stream via one-time sales or third party leasing agreements. Alternatively,
advertising revenue from the screens could be used to subsidise the initial list price
of the elevator for builders and contractors, allowing ThyssenKrupp to position its
Digital Transformation of Business Models
products at more competitive price points while maintaining healthy margins vis-
à-vis their competitors.
ThyssenKruppsnal decision to prioritise the MAX system probably stemmed
from the realisation that their in-house maintenance know-how was not being
fully utilised. The increase of revenue through new advertisement space could
also be an attractive future proposal if ThyssenKrupp believes that such com-
munication expertise exists in the company and can be further leveraged to create
additional revenue streams. Comparing the two examples, ThyssenKrupps MAX
maintenance system could be seen as the more pressing need, given their core
Application to digital reality
ThyssenKrupp digitally transformed their business model by developing an in-
novative maintenance management system. ThyssenKrupps MAX system created
a data-driven maintenance system which created new benets for their customers
and in turn generated a new revenue stream. The following sections will apply our
Digital Reality analysis to ThyssenKrupps MAX system and compare it to a
theoretical, potential alternative which they could pursue but until now have not
an in-elevator touchscreen billboard.
ThyssenKrupps customer dimension
ThyssenKrupps maintenance-oriented customer dimension in their business
model was digitally transformed by their MAX system. ThyssenKrupps customer
requirements were becoming more demanding and with the MAX system, cus-
tomers were willing to pay more for the increased value to the customer segment
element. The MAX system provided clear communication with regards to main-
tenance repairs and improved their customer relations.
The MAX system introduced an innovative data-driven digital initiative that
spoke directly to their customersand ThyssenKrupps maintenance departments.
Although the MAX system included additional costs for their customers, the
improved long-term operation, shorter downtimes, and increased elevator reli-
ability more than returned value.
The interactive elevator billboard takes advantage of an underutilised space in
the elevators and creates a new customer channel. This form of advertisement
could create a unique customer relations platform and reach customers who would
be shown commercials and notices, and who could then provide invaluable
insights through their interaction with the media displayed on the screen.
D. Schallmo, C. A. Williams & L. Boardman
ThyssenKrupps benet dimension
The enhanced transparency with regards to the maintenance requirements provided
benets for all stakeholders. ThyssenKrupp recognised it was essential to create a
new digitally driven process but the real benet for both ThyssenKrupp and their
customers was the access to data allowing for real-time maintenance alerts.
With regards to a touch panel, elevator riders are presented with an opportunity
to provide personal feedback. The touchscreen itself is a relatively uncomplicated
technology and its development and installation should deliver the benetof
revenue generating advertising or gathering personal feedback.
ThyssenKrupps value-creation dimension
The data and capabilities (i.e., resources) for such real-time maintenance alerts
were always available but there were not any processes within ThyssenKrupps
business model that specically took advantage of these resources. Once Thys-
senKrupp realised the importance and value of such a maintenance system, it was
clear that the development of the MAX system would be able to full this value
proposition. The data gathered and simultaneous delivered to both the internal and
external stakeholders created tremendous value.
ThyssenKrupp would probably possess the internal capabilities to develop their
own interactive elevator billboard space but the development could also be handed
over to other external stakeholders. Once the space is created, the process of
creating content could be handed off to marketing departments.
ThyssenKrupps partner dimension
ThyssenKrupps partners are an important part of the business model and to better
integrate the partners into their business model, the value of ThyssenKrupps
maintenance services needed to be communicated. The MAX system was able
to deliver this communication, which in turn improved the relations between
ThyssenKrupp and their partners.
The partnersinvolved in the development of an interactive elevator billboard
space would depend on who delivers the actual content. Again, ThyssenKrupp
could use this space to obtain feedback about the overall elevator experience but
third-party companies could use the space to communicate to their own demo-
graphics. The initial development of the touch screen platform would probably
also benet from external software development and consulting.
ThyssenKruppsnancial dimension
The decision to develop either a data-driven maintenance system like the MAX
system or an interactive screen/billboard ultimately depends on the potential
Digital Transformation of Business Models
revenue and expenses. The MAX system could potentially have a better long-term
outlook with regards to revenue. The importance of an innovative maintenance
system might outweigh the potential additional revenue stream of an interactive
screen/billboard. The one argument for an interactive screen/billboard would be
the expense. The MAX system involved considerable nancial investment but an
interactive screen/billboard would probably require a smaller investment, con-
sidering that the underlying technologies are ubiquitous, the software architecture
is relatively simple, and additional sensors/sensor networking is not required.
An interactive elevator billboard space would have a positive effect on the
nancial dimension inasmuch as it would provide an additional revenue stream
either to ThyssenKrupp or their partners. For example, ThyssenKrupp could re-
quire a rental fee for the space or simply include a surcharge in the purchase price
of the elevator.
The contribution of this research is to initiate the discussion of the DT of business
models by providing a concise denition, examples, and enablers. Based on this,
an integrated, ve-phase approach for how to successfully execute a DT was
presented. This addresses an existing research gap regarding the DT of business
models, which is linked to innovation management in general.
Practical Implications
Senior managers and business developers will gain from our ndings by acquiring
a clear denition, examples, and enablers of the DT of business models. The ve-
step Roadmap enables companies to take advantage of DTs potential (e.g., sen-
sors, big data) and reimagine their business model. By applying the Roadmap,
companies are able to optimise their current business model and create a distinct
competitive advantage.
The aim of this paper is to report our research results on the DT of business
models. The reader should bear in mind that due to practical constraints, the results
may not be fully generalisable. Furthermore, some aspects (e.g., the broad ap-
plication of our approach in several industries) need to be further investigated.
Therefore, we recommend interviews with practitioners and longitudinal studies in
other circumstances in order to establish a greater understanding of DT.
D. Schallmo, C. A. Williams & L. Boardman
Recommendations for Further Research
Further research regarding the impact of the DT of business models would be
worthwhile. For example, it would be interesting to create a knowledge building
community where researchers and practitioners can compare experiences gained
from our approach in different industries and company sizes. Another possible area
of future research would be to investigate the role of DT within innovation
management, particularly in the eld of business model innovation. Lastly, future
studies need to establish the quantiable benets of DT.
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Digital Transformation of Business Models
... The notion of digital transformation is not a recent phenomenon, whereas the ideas of digital products, services and channels have been discussed by authors in the 1990s-2000s (Auriga, 2016. Prominent examples of this shift towards digital arethe use of social media for increasing awareness of fashion shops during the 1990s-2000s; followed by the usage of mobile phones and social media as mediums for customers to communicate with brands in 2000s-2015s; and later the use of PayPal as a direct payment option for businesses (Schallmo et al., 2018). The attention on digital transformation became even more prominent in 2016 during the Davos Forum, where digital technology were more constructively discussed (Min & Kim, 2021). ...
The present article examines the essence of digital transformation and the opportunities and changes associated with the application of technologies in small and medium-sized enterprises (SME’s). An overview is provided to the existing digital tools and technology, like social, mobile, big data, analytics and cloud, that SMEs are adopting in the process of transforming their business operations. The paper explores the building blocks of a digital transformation journey and overlooks the planning and implantation stages of digital technology. A literature review was carried out to gain more extensive understanding of the essence of digital transformation and its impact on SMEs. In fact, the article pays special attention to the digital transformation process in SMEs.
... Zadnji dve desetletji poteka digitalna transformacija podjetijvsi podatki, procesi in organizacija podatkov so prešli iz analogne oblike v digitalno. Oskrbovalne verige so se optimizirale skozi višjo preglednost podatkov, z lažjim ravnanjem s temi podatki in razmerij med njimi (Williams & Schallmo, 2018). ...
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Seznam kriterijev, ki jih podjetje mora izpolnjevati, da bi se jim implementacije tehnologije verižnih blokov v oskrbovalno verigo splačala.
... The goal is to achieve value proposition, beyond technology (Grajek, 2020;Kane et al., 2015;Orellana et al., 2019), a strategic manner to impact the society adding value to stakeholders (Berman, 2012;CISCO, n.d.), transforming in a strategic way (I-SCOOP, n.d.-b). Schallmo and Williams (2018) reviewed digital transformation definitions used in literature and, regardless of the different terms used, we can define digital transformation in a few words as the process of creating a new strategic business model for the organization, using the latest digital technologies, adding high value for all stakeholders. ...
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Higher Education Institutions (HEIs) are involved in an evolution to a new model of university called digital university. This model implies not only adopting new technologies but also developing an organizational strategic transformation which includes information, processes, human aspects, and more. Because an organization’s digital maturity correlates with the scope of its digital transformation efforts, this study aims to identify digital transformation initiatives (DTI) taken by HEIs, defining the new processes and technologies used to implement them. The main motivation is to have a real and clear vision of how universities are transforming themselves, discovering the most relevant DTI that they have applied and if they are doing it through an integrated plan aligned with a digital strategy, as recommended by experts. We conducted a Multivocal Literature Review, as methodology research, to include both academic and grey literature in the analysis. Main results show that the DTI implemented are primarily focused on providing a quality and competitive education (24% of 184 DTI from 39 different universities analyzed). Emerging technologies most frequently used are advanced analytics (23%), cloud (20%) and artificial intelligence (16% of total DTI). We conclude that HEIs are in the first steps to digital maturity as only 1 in 4 have a digital strategy and 56% have launched isolated DTI that are not integrated in a plan and do not have a high strategic return value to the organization.
Although digital transformation is currently a much-mentioned term in the business context, this construct is still an emerging topic for academia. At the same time, organizations are already experiencing extraordinary challenges, not only because of the COVID-19 pandemic but also because of rapid environmental changes and the quick adoption of digital processes. These two features stress the organizations and the people within them.
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Se enfoca en los pilares esenciales de la transformación digital y provee conceptos, buenas prácticas y lecciones aprendidas, dirigido a satisfacer un amplio grupo de lectores que van desde los profesionales de las TIC hasta los decisores en todos los sectores, pues la transformación digital es un proceso que impacta a todas las esferas de actuación humana. Hilvanado desde una caracterización conceptual de la transformación digital que nos lleva a reflexionar por qué necesitamos asumirla, el libro se adentra en las arquitecturas e infraestructuras claves para su desarrollo, con foco en la interoperabilidad y la ciberseguridad, como bloques fundamentales para soportar su implementación. Especial atención merecen los capítulos que describen el estado y los desafíos del gobierno digital en Cuba, junto al papel que desempeña el Observatorio de Gobierno Digital, para seguir el progreso de sus principales indicadores y las plataformas digitales, para incentivar los servicios de cara a la ciudadanía.
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The role of Digital Human Resources Management (DHRM) in the era of globalization, especially in the COVID-19 pandemic, has made a major contribution to sustainable business performance. This is interesting to study considering that the DHRM work process will take place through mobile, electronic media, social media via the internet, and also with the help of IT (information technology). This research aims to analyze the role of Digital Human Resource Management (DHRM) in contributing to the improvement of sustainable business performance in companies in DKI Jakarta. The importance of the role of DHRM is investigated because DHRM is able to do human work through software and several applications, which are supported by the internet network. Digitalization in HRM will enable companies to operate more efficiently and relevantly in the future. This type of research is qualitative which involved managers working in oil companies and transportation companies in DKI Jakarta who used DHRM in the companies where they worked. This study analyzed the data using the triangulation method through documentation, interviews and direct observation in the field with case studies. The results of the study explain that several digital HRM practices have been carried out in several companies, but other practical activities have not been carried out optimally. This is because the support from the system and the digitization of business processes that are included in HR practices are not yet optimal. However, the company realizes that DHRM is able to improve business performance in a sustainable manner.
Conference Paper
The research aims to discover various concepts and issues in the retail industry while implementing digital transformation programs. The use of technology in the business world, more so in the Indian retail sector, increases daily; thus, companies have to adapt to the new means of making the customers satisfied using technological tools and resources. Hence, the study concentrates on finding out various challenges Indian retailers face in incorporating the digital transformation process. Equally, the paper investigates the impacts of recruiting talented, skilled, and expert individuals for utilizing various digital tools used by retail companies in the digital transformation process. Moreover, this study employed a descriptive research design, gathering information from multiple participants and then analyzing and presenting the data. The study used a questionnaire and personal interviews as the primary methods of data collection. The study found that most retail companies consider hiring and retaining talented and experienced individuals for the successful running of the technological tools used in the digital transformation, aiming to meet the consumers' expectations and increase competitive advantage. Furthermore, most retail companies consider various technical mechanisms to eliminate the challenges arising from the high rates of expansion in the customers' preference and offer whatever customers need at the right place and time. The research provides a solution for various retailers dealing with multiple challenges experienced in the industry while incorporating digital transformations in their operations to meet consumer expectations. Notably, the research faces some limitations, such as assessing the respondent companies' financial trends to analyze the pattern of revenues concerning the digital transformation.
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Purpose Exploring criteria for digital transformation in agribusiness (DTA) and analyzing their potential importance (weight) and priorities (ranking) for future DTA projects. Originality/value Digital transformation (DT) has become increasingly central in agribusiness, fostering a rapid process of dependence on digital technologies for operational processes. However, the lack of consistent criteria for DTA may hinder progress towards project development and industrial applications, as well as obstruct further research due to potential conceptual, technical, and theoretical shortcomings. Design/methodology/approach A manual review of literature coupled with automatic text clustering tools was employed to elicit criteria and subcriteria. To analyze weights and rankings, two methods were used in tandem: fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarities to ideal solution (Topsis) in order to aggregate responses from DTA specialists. Findings The criteria extracted from the literature were: knowledge management (analysis, monitoring, decision-making), automation (planting and harvesting, processing and manufacturing, maintenance, technology, machinery and tools), efficiency (costs, work and personnel, processes), and continuity (quality and food safety, environmental sustainability). The results point to a set of criteria anchored in the transition of operations to digital technologies yet bound by the physical limitations of a traditional non-digital business. This paper contributes to the development of the literature by providing a set of criteria for DTA projects and analyzing their possible importance according to a panel of specialists. Practical implications include a definition of areas and their potential relative importance for future implementations. Keywords: digital transformation; agribusiness; multicriteria decision analysis; strategic management; project management
In diesem Kapitel werden relevante Definitionen im Kontext der Digitalen Transformation von Geschäftsmodellen aufgezeigt. Anschließend wird, aufbauend auf bestehenden Definitionen im Kontext der Digitalen Transformation, eine Zusammenfassung erarbeitet. Ferner wird der Begriff des Geschäftsmodells erläutert.
Das Buch stellt eine Methode zur Geschäftsmodell-Innovation vor, mit deren Hilfe Anwender ein einzigartiges Unternehmensprofil schaffen. Gerade in Zeiten der Digitalisierung sind Unternehmen ständig gezwungen, sich gegenüber ihren Wettbewerbern zu differenzieren, da neben steigendem Preisdruck eine zunehmende Homogenität und Transparenz von Produkten und Dienstleistungen zu verzeichnen sind. Der Vorteil der Geschäftsmodell-Innovation gegenüber klassischen Differenzierungsmöglichkeiten – Produkt-, Dienstleistungs- und Prozess-Innovation – besteht darin, dass sie kaum nachahmbar ist und überdies durch ihre Orientierung an Kundenbedürfnissen eine starke Kundenbindung ermöglicht. Das Buch entwickelt auf der Basis theoretischer und praktischer erspektiven eine mehrteilige Methode der Geschäftsmodell-Innovation. Der Fokus liegt auf Techniken und Vorgehensweisen, mit denen die Vorgaben des Modells umgesetzt werden können. Aufgaben, Kontrollfragen und Templates erleichtern den Lern- und Umsetzungsprozess für Unternehmer und Führungsverantwortliche sowie für Studierende, die in der Lehre für Unternehmensherausforderungen hinsichtlich Innovations- und Wandlungshergängen sensibilisiert und zum proaktiven Handeln befähigt werden. Der Autor Dr. Daniel R. A. Schallmo ist Ökonom, Unternehmensberater und Autor zahlreicher Publikationen. Er ist Professor an der Hochschule Ulm, leitet das privatwirtschaftliche Institut für Business Model Innovation und ist Mitglied am Institut für Digitale Transformation. Er ist ebenso Gründer und Gesellschafter der Dr. Schallmo & Team GmbH.
Der nachfolgende Beitrag beinhaltet die Darstellung des Vorgehensmodells der Geschäftsmodell-Innovation für die Entwicklung radikaler Geschäftsmodelle; somit wird das Vorgehen mit entsprechenden Ergebnissen im Großen (Was wird getan?) dargestellt. Der Beitrag zeigt zunächst bestehende Vorgehensmodelle der Geschäftsmodell-Innovation auf, die anschließend in einen Überblick einfließen. Anschließend werden die sechs Phasen jeweils mit der Zielsetzung, Aktivitäten, dem Input und dem Output erläutert.
- This paper describes the process of inducting theory using case studies from specifying the research questions to reaching closure. Some features of the process, such as problem definition and construct validation, are similar to hypothesis-testing research. Others, such as within-case analysis and replication logic, are unique to the inductive, case-oriented process. Overall, the process described here is highly iterative and tightly linked to data. This research approach is especially appropriate in new topic areas. The resultant theory is often novel, testable, and empirically valid. Finally, framebreaking insights, the tests of good theory (e.g., parsimony, logical coherence), and convincing grounding in the evidence are the key criteria for evaluating this type of research.
Mit Blick auf Alfred Chandlers Aussage "Structure follows strategy" (vgl. [Chan62], [Mint+98]) widmet sich dieser Abschnitt ergänzend zum Abschnitt 2.2 der Frage: "Was kommt zuerst, das Business Model oder die Strategie?" Zu beobachten ist, dass diese Frage sowohl in der wissenschaftlichen Literatur als auch in der Praxis nicht eindeutig geklärt ist. Einigkeit herrscht dabei jedoch darüber, dass Geschäftsmodelle primär die Kernlogik eines Unternehmens beschreiben, wohingegen sich Strategien überwiegend auf die Erfolgs- und Wettbewerbssituation eines Unternehmens beziehen ([SeLe03], [Haak+04]).
True supply chain excellence will only come from making a digital business transformation. It's a transformation that exploits all that technology has to offer, facilitates supply chain collaboration, and leads to new levels of operational excellence. More than a one-time project, the transformation is a journey—and the time to start that journey is now. The model for creating business value has changed. Companies today participate in extended supply chains, where real operational efficiency and revenue enhancement come from greater visibility, integration, and synchronization among connected partners. In short, collaboration among the partners in the extended supply chain—collaboration beyond the physical walls of the enterprise—is the new arena for value creation. Collaboration occurs when companies work together for mutual benefit. It happens when supply chain partners leverage each other's operational capabilities so that in combination they perform better than they could possibly do alone. Collaboration can occur at all points along the supply chain—from design through procurement to final distribution. When done effectively, it enables companies to share information that can dramatically shorten processing time, eliminate value-depleting activities, and improve quality, accuracy, and asset productivity—all of which are fundamental to long-term success.
Purpose According to IBM research, companies seeking opportunities in an era of constant customer connectivity focus on two complementary activities: reshaping customer value propositions and transforming their operations using digital technologies for greater customer interaction and collaboration. This paper aims to address this issue. Design/methodology/approach The paper explains that businesses aiming to generate new customer value propositions or transform their operating models need to develop a new portfolio of capabilities for flexibility and responsiveness to fast‐changing customer requirements. Findings The paper finds that engaging with customers at every point where value is created is what differentiates a customer‐centered business from one that simply targets customers well. Customer interaction in these areas often leads to open collaboration that accelerates innovation using online communities. Practical implications Companies focused on fully reshaping the operating model optimize all elements of the value chain around points of customer engagement. Originality/value The article explains how companies with a cohesive plan for integrating the digital and physical components of operations can successfully transform their business models.
This article defines and discusses one of these qualitative methods--the case research strat- egy. Suggestions are provided for researchers who wish to undertake research employing this approach. Criteria for the evaluation of case research are established and several characteristics useful for categorizing the studies are identified. A sample of papers drawn from information systems journals is reviewed. The paper concludes with examples of research areas that are particularly well- suited to investigation using the case research approach.