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An Approach for a Digital Maturity Model for SMEs Based on Their Requirements


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This study aimed to develop an approach for a digital maturity model (DMM) based on Small and Medium Enterprises’ (SMEs’) requirements. Our research is based on a systematic literature review in which we analyzed and compared existing approaches of DMMs with regard to their stakeholders. In addition, we conducted several interviews with SMEs for the InnoSÜD research project “Digitaler Reifegrad@Mittelstand.” Our findings show that DMMs are currently a significant topic for SMEs across various industry sectors, but there is no consensus on the required dimensions to examine when applying a DMM. The chapter offers an approach to the development of a DMM consisting of the following dimensions: digital strategy, partner interface, the company’s processes, employees and technologies, products and services, and customer interface. Moreover, the chapter offers recommendations for further research.
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An Approach for a Digital Maturity Model for SMEs
based on Their Requirements
Daniel Schallmo
University of Applied Sciences Neu-Ulm
Wileystrasse 1, 89231 Neu-Ulm, Germany
Klaus Lang
University of Applied Sciences Neu-Ulm
Wileystrasse 1, 89231 Neu-Ulm, Germany
Daniel Hasler
University of Applied Sciences Neu-Ulm
Wileystrasse 1, 89231 Neu-Ulm, Germany
Katharina Ehmig-Klassen*
University of Applied Sciences Neu-Ulm
Wileystrasse 1, 89231 Neu-Ulm, Germany
Christopher A. Williams
Johannes Kepler University
Altenbergerstraße 69, 4040 Linz
* Corresponding author
This paper was presented at The ISPIM Innovation ConferenceInnovating Our Common Future,
Berlin, Germany on 7-10 June 2020.
Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-335-467-8
Abstract: This study aimed to develop an approach for a digital maturity model
(DMM) based on Small & Medium Enterprises’ (SMEs’) requirements. Our
research is based on a systematic literature review in which we analyzed and
compared existing approaches of DMMs with regard to their stakeholders. In
addition, we conducted several interviews with SMEs for the InnoSÜD
research project “Digitaler Reifegrad@Mittelstand.” Our findings show that
DMMs are currently a significant topic for SMEs across various industry
sectors, but there is no consensus on the required dimensions to examine when
applying a DMM. The paper offers an approach to the development of a DMM
consisting of the following dimensions: digital strategy, partner interface, the
company’s processes, employees and technologies, products and services, and
customer interface. Moreover, the paper offers recommendations for further
Keywords: digital maturity models; maturity models; stakeholder
requirements; requirements for SMEs; digital transformation tools; SME; SLR;
deductive method
1 Introduction
Digitalization and digital transformation are currently some of the most used
buzzwords in consulting, economics, and management sciences. The media constantly
seems to report that Germany is at risk of losing touch with the latest trends, but,
according to the digital economy and society (DESI) index of the European Commission,
Germany is placed slightly above average with countries such as Finland, Sweden, the
Netherlands, and Denmark leading the field (European Commission 2019). Some might
speak of Digital Darwinism(Kreutzer and Land 2015), suggesting that technology and
society are changing faster than businesses can adjust.
The bigger the company, the higher their perception of digital maturity (Lichtblau et al.
2018; Brandt 2018). Taking a deeper look, it is particularly the German SMEs that will
have to adapt their current business models to new consumption patterns and disruptive
technologies or risk losing their competitive advantages in a globalized marketplace.
Only one in four companies uses digital marketing or sales concepts, reorganized
workflows to prepare for the digital age, or digitalized their products and services
(Zimmermann 2019).
A possible and efficient solution to correctly determine the status quo of a company’s
state of digitalization can be the use of a digital maturity model (DMM). Maturity models
are rather practical tools that have been present in different areas of actions, e.g., project
management (Cook-Davies 2002: 16–20), for quite some time but have become
extremely popular in recent years in the context of digital transformation (Hess 2019). In
our understanding, a DMM serves to clarify the current state of digitalization of a
company based on different questions and variables, sometimes compared to other
companies in the same sector or cross-sectoral, and recommends further actions to
improve the company’s state of digitalization.
Although the Internet is currently being flooded with practical tools provided by different
stakeholders, there is little theoretical consensus on what a DMM is. The problem here
lies within the lack of clarity of tools and literature as well as objectivity when it comes
to application, execution, and analysis of a DMM in practice. Therefore, we seek to
provide insight into what requirements SMEs have and how they can be integrated into
future DMMs.
2 Theoretical Background
A common opinion or standard procedure is not apparent regarding either maturity
models or the degree of DT.
Digital Transformation
Various definitions of DT have been presented (e.g., BMWi 2015; Bowersox et al. 2005;
Bouée and Schaible 2015; PwC 2013). In our understanding, DT can be seen as follows:
the networking of actors such as businesses and customers across all value-added
chain segments, and the application of new technologies. 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. In order to
increase the performance and reach of a company, DT involves companies, business
models, processes, relationships, products, etc. (Schallmo et al. 2017)
Maturity Models
Becker et al. (2009b: 23) state that many maturity models often deal with similar topics,
deriving from the field of business informatics or considering the use of information
technologies in companies or other organizations. For example, there have been around
30 different maturity models in the domain of project management(Cook-Davies 2002:
1620) and even 150 maturity models for IT service capability, strategic alignment,
innovation management, program management, enterprise architecture, or knowledge
management maturity(Bruin et al. 2005: 3).
The authors criticize that only in rare cases is it even disclosed how the development of a
new maturity model was motivated, in which steps it was developed, who was involved
in these steps, and whether and how it was evaluated that the new model fulfilled its
function (Becker et al. 2009b: 23).
Degree of Maturity
Basically, the degree of maturity of a research object deals with the fulfilment of certain
objectives, characteristics, or indicators (Becker et al. 2009a: 213). The characteristic
values or dimensions necessary to achieve a degree of maturity are generally predefined
This paper was presented at The ISPIM Innovation ConferenceInnovating Our Common Future,
Berlin, Germany on 7-10 June 2020.
Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-335-467-8
(CMMI Product Development Team 2011: 464); the point in time can be arbitrary
(Pfeifer-Silberbach 2005) but is usually the actual state of a company and its products,
services, business model, and processes considering the point in time of the
Digital Maturity Models
Considerable research has been done on maturity models focusing on digital capabilities
in the areas of IT management (Becker et al. 2009b) and business processes (Tarhan et al.
2016; Williams et al. 2019). Maturity models for digitization in companies must
summarize certain characteristics in particular dimensions at a specific time (Becker et al.
2009a; Pfeifer-Silberbach 2005; CMMI Product Development Team 2011: 464). They
serve to determine the current state and the degree of digital maturity in the context of DT
(e.g., regarding competence, performance, and level of experience) and allow
recommendations for future actions deriving from the current degree of maturity.
Small & Medium Enterprises (SMEs) and Their Requirements
According to the Institut für Mittelstandsforschung (2020), SMEs are companies that
employ fewer than 500 persons and have an annual turnover not exceeding 50 million
SMEs are also typically seen as long-term, stable, and independent (Bundesverband
der Deutschen Industrie e. V. 2015). Therefore, they have their own needs and
requirements, especially when it comes to new and radically changing issues like DT.
They do not rely much on theoretical approaches and prefer quick and easy, pragmatic
solutions. Their requirements must consist of practical facts and recommendations for
Furthermore, Arendt (2008: 93108) found that knowledge and skills were the biggest
barriers for the SMEs with regard to digital initiatives. Zimmermann (2019: 11) adds data
security and governance as well as Internet infrastructure.
3 Research Questions and Research Design
Research Questions
Based on the previous sections, we propose the following research questions:
What are their main requirements for the creation of a DMM to support SMEs?
What DMMs exist?
What does a suitable maturity model for SMEs look like?
Research Design
Our research design consists of three parts. First, we collected practical qualitative data
by interviewing SMEs for their requirements regarding DMMs. Second, we conducted a
systematic literature review (SLR) to gain insight into existing approaches for DMM. In
the last step, we compared theoretical and practical results to see how DMMs for SMEs
can be improved in the future.
For the qualitative data, we used action research as this method helps to “address
complex real-life problems and the immediate concern of practitioners” (Avison et al.
1999: 95), and we can test and refine a DMM approach for SMEs with the help of SMEs’
In the context of the InnoSÜD research project “Digitaler Reifegrad@Mittelstand” at
University of Applied Sciences Neu-Ulm, in various workshops and interviews with
regional SMEs, we are currently in the process of obtaining data and requirements for
developing and testing an SME-oriented DMM. The goal of the InnoSÜD university
network is to use innovative transfer formats to facilitate a sustainable and effective
exchange between science, business, and society. The focus is on topics that are
important for the region, such as transformation management. In this case, the transfer
refers to SMEs. With the support of the Institute for Digital Transformation of the
University of Applied Sciences Neu-Ulm, they should determine their digital maturity to
be able to derive a digitization strategy and implement it in their own company.
We interviewed five regional SMEs on the topics of digital maturity and DT in their
companies to determine necessary requirements for an SME-oriented DMM.
The central questions asked were:
What is the status quo of your company regarding the DT?
Where do you see the biggest problem field in your company regarding the DT?
Where do you see the greatest need for action regarding digitalization in your
What are your expectations for determining digital maturity?
Furthermore, we conducted an SLR to gain insight into existing approaches for DMMs as
[s]ystematic reviews are undertaken to clarify the state of existing research and the
implications that should be drawn from this(Feak and Swales 2009: 3). This formal and
methodical approach aims to reduce bias in choosing literature selectively and to increase
the reliability of the chosen literature (Tranfield, Denyer and Smart 2003).
For the SLR, we used the keywords Digitalisierung,” digitalization,” Digitaler
Reifegrad,” digital maturity,” Reifegradmodell,” maturity model,” digital
assessment,” “digital readiness,” and digital fitto retrieve sources from the Internet as
well as Web of Science, SpringerLink, Ebsco, Emerald, ScienceDirect, and Wiley
This paper was presented at The ISPIM Innovation ConferenceInnovating Our Common Future,
Berlin, Germany on 7-10 June 2020.
Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-335-467-8
To refine the review, we applied the following exclusion criteria. First, we only kept
sources for analysis that were available in German or originated in Germany, Austria, or
Switzerland. We conducted our workshops and interviews in Southern Germany (Bavaria
and Baden-Wurttemberg), and our objective was to rely on available additional data with
a minimum of cultural-related bias as DT and maturity might be perceived differently in
other areas of the world.
Second, we focused on maturity models with the core topic of DT. As mentioned above,
maturity models are present in various areas of action, but our focus is on digitalization
and DT.
Third, sources had to be generally or at least cross-sectionally applicable. To achieve
transparency and possible comparison among the different SMEs interviewed, it was not
possible to rely only on industry specific DMMs.
Sources were further examined using the following criteria:
Group: Who designed the model?
Sector: What are the main target sectors of the maturity model?
Methodology: How was the survey conducted, and how were data collected?
Model structure: How is the model structured? How many questions, dimensions,
rating levels (degrees of maturity) does it consist of?
The results are summarized in Table 3 in the appendix of this paper. As a last step, we
present the following four DMMs and compare them to SME requirements from the
Digitaler Reifegrad of Schweizer KMU (Wyss 2017)
Quick Check Industrie 4.0 Reifegrad (Digital in NRW n.d.)
Industry 4.0 / Digital Operations Self-Assessment (Geissbauer et al. 2016)
Potentialanalyse Arbeit 4.0 (Offensive MittelstandGut für Deutschland 2018)
These were chosen because (1) the questions were simple, understandable, and minimally
complex so that they could be used in a workshop context; (2) each of them comes from a
different group; and (3) they all include recommendations for further actions and
therefore seem to have a good overall fit for an application to SMEs.
4 Findings
We analyzed four DMMs and examined how they meet requirements of SMEs deriving
from interviews and workshops of the InnoSÜD research project “Digitaler
Reifegrad@Mittelstand.” None of the existing models met all of the requirements.
Consequently, suggestions for improving future model constructs can be derived.
Requirements for SMEs based on “Digitaler Reifegrad@Mittelstand”
The results of the workshops are summarized in Table 1. We clustered the SMEs’
responses into various dimensions, such as (digital) strategy; the interaction with partners
and suppliers via a partner interface; the company’s processes, employees, and used
technologies; the interaction with customers via a customer interface; and the company’s
products and services.
The most important areas for improvement are internal processes, products, and services
and the overall digital strategy. Processes are often “highly analogue” and “still use a lot
of paper,” which “impedes the processing of important data” internally and towards
customers, partners, and suppliers. In this context, IT systems are very old or the IT
infrastructure is not harmonized.
Regarding products and services, the potential of new technologies, such as artificial
intelligence or mobile apps, to upgrade existing products and expand the service portfolio
have already been detected, but these initiatives progress slowly due to a lack of capacity
and knowledge of the company’s employees.
Table 1 Required dimensions for digital maturity models provided by SMEs
Requirements / Dimensions
Partner interface
Customer interface
Products & services
strong need for further actions (top priority)
need for further actions
(blank) no immediate need for further actions
This leads to the third core topic: digital strategy. The companies know that “something
has to be done” but often “do not know where to start.” Determining the digital maturity
This paper was presented at The ISPIM Innovation ConferenceInnovating Our Common Future,
Berlin, Germany on 7-10 June 2020.
Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-335-467-8
is seen as a good way to discover “potentials and recommendations for further actions” as
well as to create a “digitalization roadmap including priorities.”
Existing Approaches for Digital Maturity Models
Table 3 in the appendix of this paper summarizes the results of the SLR. In general, there
is a large number of maturity models, which are based on different dimensions and are
therefore neither generally comparable nor applicable. Studies differ in terms of the
industries and sectors, company sizes, and the number of participating companies.
A wide variety of methodologies have been applied from (online) questionnaires and
online self-checks (e.g., Hochschule Neu-Ulm (HNU), minnosphere GmbH 2017;
techconsult n.d.; Mittelstand 4.0 Kompetenzzentrum Kaiserslautern n.d.) over conceptual
modelling (Westerman et al. 2012) and literature reviews (Back et al. 2016, 2017)
towards more qualitative methods, such as interviews (Geissbauer et al. 2016), focus
groups, workshops (e.g., Acatech n.d.; H&D 2016) and assessments (fme AG n.d.).
We see the following main groups as creators of DMMs.
Consulting firms use DMMs as a practical supporting tool for providing information
and consultancy services to companies needing to improve their digital strategy.
Their objective is profit-orientated, like the companies they are consulting, operating
in one or various industry sectors.
Associations are representations of a sum of companies with the intention to inform
and strengthen the industry sector in which the respective companies are operating.
Digital maturity should help create benchmarks and comparison for the members.
Universities and research institutes, in this context, have the goal to inform, educate,
and support the public, e.g., companies, citizens, etc., on actual topics like
digitalization, DT, and digital maturity.
Big companies, e.g., Deutsche Telekom (Techconsult n.d.), sometimes create their
own DMM to improve their status quo with regard to DT and to collect market data.
We also encountered various combinations of the groups, e.g., an association contracting
a research institute for conducting a survey on digital maturity (e.g., IMPULS-Stiftung
2015), a university partnering with a company for transforming research results into a
product or service (e.g., Universität St. Gallen & Crosswalk AG 2016, 2017), or a
company using their knowledge for their own consulting branch (e.g., Rockwell
Automation 2014).
Moreover, the model structures differ largely in the number of dimensions, questions, and
rating levels. While some DMMs only deal with three (Rockwell Automation 2014),
others consist of up to nine different dimensions (e.g., Frauenhofer Austria Research
GmbH 2017) while the majority presents five central fields of action. The number of
questions range from 15 (Digital in NRW n.d.) to 166 (Offensive Mittelstand Gut für
Deutschland 2018). The number of different degrees of maturity is usually in between
three and six rating levels. Only one DMM (Industrie- und Handelskammer (IHK)
München & Oberbayern n.d.) offers 11 different maturity degrees.
Furthermore, not all information on dimensions, questions, and rating levels have been
publicly available, which complicates detailed comparison of existing approaches.
Comparing SME Requirements to Existing Approaches
As Table 2 shows, none of the four analysed DMMs fully considers every dimension of
digitalization mentioned by the interviewed SMEs during the InnoSÜD research project
“Digitaler Reifegrad@Mittelstand.” The four existing models, however, all consider to
some extent the aspects of the company (processes, employees, and technologies) as well
as the overall digital strategy. The latter as well as the internal processes have been
detected as the most important areas of improvement by the interviewees as well. The
partner interface and sometimes the customer interface are neglected in some of the
analysed existing approaches.
Nevertheless, an approach for a DMM for SMEs should consist of all of the requirements
mentioned in Tables 1 and 2. For the upcoming data collection process, the questionnaire
has to include questions to determine the digital maturity of all aspects of digitalization.
Table 2 Existing digital maturity models vs. SME requirements
Requirements /
Industrie 4.0-
Reifegrad von
Schweizer KMU
analyse 4.0
Partner interface
Products &
included in the model
partly included in the model
(blank) not included in the model
This paper was presented at The ISPIM Innovation ConferenceInnovating Our Common Future,
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Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-335-467-8
5 Contributions
This study aims to determine the requirements that are currently lacking in DMMs for
companies through analysis and a deductive method. The results give readers a deeper
look into requirements of SMEs in relation to DMMs. These results and the indication
that requirements are lacking in current DMMs can be used in the development of future
6 Practical Implications
First of all, practitioners will get an overview of and deeper insights into existing DMMs.
In addition, they will find the analysis of the requirements of SMEs for DMMs and first
approaches to build a model that meets the requirements of SMEs.
7 Limitations
This paper aimed to report our current research-in-progress regarding the necessary
requirements for standardized DMMs to meet stakeholder interests. We see the following
limitations to this paper. Due our focus on the German-speaking area, the results may not
be generalizable on a global level.
Furthermore, it is debatable whether companies are willing to publish their data on digital
maturity for a common goal. Although it would be helpful to create more transparency in
the context of benchmarking, they could interpret this as an exposure of their own
shortcomings, endangering their market position.
8 Recommendations for Further Research
Practitioners should be even more included into further research as the model could
intensively be tested and more company data would be available for comparison. It would
be interesting to create an overall accessible and anonymized database to be able to
strengthen which dimensions are truly necessary for a DMM. This database would allow
researchers to get insights from different industries, regions, or countries; practitioners
would get a reliable benchmarking tool providing recommendations for further actions
inside their companies.
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Berlin, Germany on 7-10 June 2020.
Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-335-467-8
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Berlin, Germany on 7-10 June 2020.
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This paper was presented at The ISPIM Innovation ConferenceInnovating Our Common Future,
Berlin, Germany on 7-10 June 2020.
Event Proceedings: LUT Scientific and Expertise Publications: ISBN 978-952-335-467-8
Table 3 Digital maturity models
Maturity model
Industry 4.0
Maturity Model
Frauenhofer Austria
Research GmbH (2017)
University /
questionnaire, software
supported calculation,
visualization and report
in a roadmap
9 dimensions
62 questions
5 rating levels
The Connected
Maturity Model
Rockwell Automation
five steps: assessment,
secure and updated
network and controls,
defined and organized
working data capital,
analytics, collaborations
3 dimensions
? questions
5 rating levels
Industry 4.0 /
Digital Operations
Self-Assessment of PwC*
Geissbauer et al. (2016)
interviews and surveys
7 dimensions
? questions
4 rating levels
The Digital Advantage of
MIT Center for digital
Business and Capgemini
Westerman et al. (2012)
conceptual model but
refers to data (no
references) with MNCs
? dimensions
? questions
4 rating levels
Digital Maturity &
Transformation Study of
the university St Gallen
and Crosswalk AG
Back et al. (2016, 2017)
University /
literature review, expert
interviews, focus groups
9 dimensions
64 questions
5 rating levels
Digitales Reifegrad-
Hochschule Neu-Ulm
(HNU), minnosphere
GmbH (2017)
University /
online self-assessment,
based on answering 10
core questions on the
current status and the
planned status in 3 years
5 dimensions
50 questions
5 rating levels
Deutsche Telekom
Techconsult (n.d.)
(selection at the
online self-check to
determine your own
degree of digitalization
5 dimensions
71 questions
5 rating levels
Industrie 4.0-
Readiness-Modell IdW
Köln for VDMA*
IMPULS-Stiftung (2015)
University /
with focus on
online self-check to
determine the individual
industry 4.0 maturity
6 dimensions
27 questions
6 rating levels
Readiness Check
Mittelstand 4.0
Kaiserslautern (n.d.)
online self-check
5 dimensions
25 questions
5 rating levels
Leitfaden Industrie 4.0
Industrie- und Handels-
kammer (IHK) München
& Oberbayern (n.d.)
with focus on
online self-check for
digital maturity level
with a total of 19 main
4 dimensions
19 questions
11 rating levels
Quick Check Industrie
4.0 Reifegrad
Digital in NRW (n.d.)
University /
with focus on
online questionnaire with
five possible answers to
each question for self-
9 dimensions
15 questions
5 rating levels
Industrie 4.0-Readiness-
H&D (2016)
with focus on
cooperative maturity
analysis in cooperation
with the respective
5 dimensions
? questions
? rating levels
Industrie 4.0-
Acatech (n.d.)
University /
identification of status
quo of industry 4.0 in
companies via
4 dimensions
? questions
6 rating levels
Digitaler Reifegrad von
Schweizer KMU*
Wyss (2017)
University /
with focus on
study / survey
7 dimensions
54 questions
5 rating levels
Digital Maturity and
Value Assessment
McKinsey & Company,
Inc. (n.d.)
public sector
survey - representative
sample of authorities /
4 dimensions
76 questions
3 rating levels
Digital Maturity Model
tmforum (2020)
online presentation with
different implementation
5 dimensions
110 questions
? rating levels
fme Reifegradmodell für
die dig. Transformation
fme AG (n.d.)
5 dimensions
25 questions
5 rating levels
Potentialanalyse 4.0*
Offensive Mittelstand
Gut für Deutschland
with focus on
self-check with
implementation support
6 dimensions
166 questions
3 rating levels
*Models marked with the asterisk are analyzed more closely in chapter 4.
... Apart from these, it is also seen that factors such as internal communication, understanding the value of mistakes, and information sharing are also included in the evaluations made by large consultancy firms. In recent studies, the importance of quality [57,62,65,77] and innovative features [27,42,66,68] has also been emphasized. In addition, the use of renewable energy has been evaluated [62]. ...
... Therefore, it is necessary to determine the current situation of businesses and initiate the necessary improvements and changes within the business. Thus, it will be possible for businesses to develop a roadmap that they can follow for the digital transformation process [77]. ...
Full-text available
Changing market expectations and the increasing prevalence of the new technological trend in the world force businesses for digital transformation. However, the late realization of transformation opportunities may have devastating effects on businesses. As the first step of digital transformation, it is necessary to determine the status and deficiencies of businesses. Therefore, businesses need to make a comprehensive assessment with the digital maturity model. This study was conducted to provide businesses with an idea about the relevant digital transformation processes, to direct them toward the processes, and to support these activities when they are initiated. In the study, seven scales were developed, and the dimensions of the digital maturity model were formed. The dimensions of model were determined as strategy, customers, employees, process management, technology and data management, organizational culture, and innovation. This study aimed to examine the reliability and validity of the dimensions of the digital maturity model developed. In this context, the developed scales were applied to businesses in Turkey, and explanatory factor analysis (EFA) and validity analysis were performed. The scales were updated according to the analysis results. Moreover, the analysis results of the study were also used to specify the criteria of the model. The findings indicated that the developed scales were usable. It was purposed to provide researchers and businesses with significant opportunities since the model had a wide area of application and included environmental elements.
... DMMs' approach can cover specific capabilities that the firms are concerned with or all capabilities (multi-dimensions) they need to advance to digital enterprises [53]. There are four primary sources of DMMs creation [49]: Consultancy, Associations, Scientific, Big companies, where 70% of models are developed by Practitioners [8]. The popular components used to construct DMMs compose maturity level, dimension, capabilities, scale items, and requirements. ...
Full-text available
The growth speed of top trending for global firms, the digital transformation (DT), has become steadier than ever by the advancement of digital technologies as well as the COVID-19 pandemic. In order to implement a digital evolutional path appropriately, the Digital Maturity Model (DMM) has been seen as a handy tool since they help companies evaluate their initial states and plan development road maps. So far, several DMMs have been developed for both cross-industry and/or specific sectors, including manufacturing. However, none of them is developed for the Electronics Industry (EI) firms despite the vital importance of the EI sector, especially in developing countries like Vietnam. These companies contribute a significant proportion of Vietnam's GDP, up to 40% in 2021. Moreover, none of them guide EI firms to embrace the Servitization model. This article presents a new DMM to digitally transform EI companies to align with the Servitization model by applying both the Product Service System (PPS) and Service Design approach. The DMM is developed with on the design science research methodology and uses its strategy of combining related models to form a new one to gain high quality. Experts from a joint-venture telecom equipment company under VNPT, the biggest telecommunication service provider in Vietnam, were chosen to join the DMM pre-evaluation phase of the development process. For further research, the authors expected that the newly developed DMM should be transferred and evaluated by more EI incumbent firms and then become a standardized DMM for the EI sector.
Full-text available
A cikk a vállalati digitalizáció, KKV-digitalizáció és ezek mérése kapcsán elvégzett irodalomkutatás eredményein alapul.Egy kétrészes cikksorozat első darabja, a KKV-digitalizációt kutató Digiméter kutatássorozat tág értelemben vett elméleti megalapozása. A KKV-k kapcsán az egyik leggyakrabban vizsgált témának számít a digitalizáció, a digitális fejlettség és az érettség mérése. Ugyanakkor a KKV-digitalizáció kutatása számos kihívással küzd. Egyrészt a digitalizáció a vállalatok működésének egészét érinti, másrészt a KKV-k a nagyobb cégekhez képest inkább élhetik meg nehézségként ezt a folyamatot. A cikk bemutatja, hogy mennyire sokszínű a vállalati digitalizáció területe, aminek következtében nem létezik egyetlen átfogó, általánosan elfogadott definíciója. Emiatt nem egyértelmű a KKV-digitalizáció mérése sem a szakirodalom, sem a gyakorlat alapján. A beazonosított mérések között több az eltérés, mint a hasonlóság, nem létezik bevett módszertan a KKV-érettség vagy fejlettség mérésére.
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A szerzők tanulmányukban egy olyan, az Európai Bizottság Digitális gazdaság és társadalom fejlettségét mérő mutatója (DESI) által inspirált vállalati digitális fejlettségi indexet mutatnak be, amelyet egy 2500 cégre kiterjedő, reprezentatív vállalati felmérés alapján, entrópiaalapú objektív súlyozási módszerrel alakítottak ki. A mutató öt fő dimenzióból áll, melyek együttesen jól jellemzik a vállalatok által használt digitális alkalmazásokat, illetve a digitális eszközökhöz, infrastruktúrához való hozzáférést és a kapcsolódó készségeket (Eszközök és hálózati használat; IKT-képességek és ismeretek; Általános jellegű, külső alkalmazások; Speciális jellegű, belső alkalmazások; Közszolgáltatásokhoz kapcsolódás, alkalmazások). A fő dimenziók, illetve az ezeket alkotó aldimenziók, illetve ezek entrópiaalapú súlyainak bemutatása mellett a vállalatméret és a digitális dimenziók közötti összefüggéseket is feltárják, melyhez az ANOVA-módszert használják fel. Eredményeik alapján a vállalatméret hatása az IKT-képességek és az általános, külső, illetve a speciális, belső alkalmazások esetében lesz szignifikáns.
To survive and thrive in highly competitive environments, micro‐enterprises, like all businesses, need to adapt to changing market conditions. In today's digital age, digital transformation can help micro‐enterprises improve their efficiency, customer experience, and decision‐making to remain competitive and meet consumer demands. Therefore, this study seeks to establish a micro enterprise‐specific digital transformation maturity model based on prior literature and interviews with 12 micro enterprise business owners. The resulting model has four dimensions: strategy, process, technology, and people. Each dimension consists of four maturity levels comprised of significant, specific characteristics. Five specialists from diverse fields reviewed and modified the proposed model. For model evaluation, we performed data analytics using the K‐means clustering algorithm on online questionnaire data. The final maturity model fits well with the needs of the micro‐enterprises under investigation and can be used as a guide by other micro and small businesses in developing countries.
Introduction. The article examines the problem of digital transformation of modern society and education in the context of the general logic of present and future technological revolutions, called Industries 4.0 and 5.0. The purpose of the article is to identify the characteristic features of the modern understanding of digital maturity in education and the specifics of its evaluation methods (metrics). Materials and Methods. The methodology for solving the problem is based on the general research methods (synthesis and generalization of international and Russian publications focused on the stated problem). Results. The authors have analyzed and clarified the modern understanding of the concept of digital maturity in general and digital maturity of education in particular. It is noted that the currently emerging theoretical concept of digital maturity plays an essential role in determining key guidelines in the process of searching for appropriate strategies for digital transformation of education. The paper presents a comprehensive analysis of international and Russian evaluation inventories (metrics) of digital maturity, including education, aimed exclusively at the processes of collection and processing of quantitative indicators of evaluated industries at the micro-level. The existing methods of assessing digital maturity of education are supplemented by the approach developed by the authors which works at the macro level and expands the heuristic potential of existing assessment methods. Conclusions. The authors summarize the peculiarities of the modern understanding of digital maturity in education as an integral characteristic feature of introduction and implementation of end-to-end technologies within main educational processes.
Conference Paper
Digital technologies foster organizations to rethink their business models and socio-technical structures. Thus, digital transformation (DT) has become a compelling priority on organizations’ agendas. To meet the new environment, well-considered actions must be initiated and monitored at the operational and strategic levels. Therefore, it requires an understanding of fields of action and possible trajectories of DT within different organizational dimensions. For this purpose, practitioners and academics have designed numerous digital maturity models to keep track of DT progress. Still, most models reveal an incomplete picture of the holistic and socio-technical nature of DT and organizations. This motivates us to answer: Which set of organizational dimensions and characteristics maps the holistic and socio-technical nature of DT in organizations? With a systematic literature review and a Delphi study, our paper aims to identify and validate relevant DT-related dimensions and characteristics. The result is a socio-technical framework that serves as a pattern for (re)designing digital maturity models.
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As a result of increasing globalization, manufacturing companies are confronted with rising costs and time pressure. A possibility to counter these challenges is Industry 4.0, which focuses on optimizing industrial processes and is characterized by the digitalization and networking of all value chain participants. This paper elaborates the one-to-one interrelation between relevant Industry 4.0 technologies using the Delphi study method and interdependency matrices. Based on this, an Industry 4.0 implementation sequence for manufacturing companies is derived and validated by experts. The contribution shall serve as an essential basis for companies to implement Industry 4.0 in their production.
Conference Paper
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The aim of this paper is to present a systematic literature review on digital maturity models for SMEs. Our investigation is based on previous models in which we analyzed and compared existing approaches on SME digital maturity models. We also propose using a conceptual research design to gain insights to help validate our model. Our findings show that digital maturity model is currently a relevant topic across several industries but is still limited by the lack of validation and suitable digital maturity models for SMEs. The paper provides an initial digital maturity model which consists of six dimensions: strategy, products/services, technology, people/culture, management, and processes. Within our proposed research design, we offer valuable insights into how to provide further contributions to the maturity model field.
Full-text available
The purpose of this paper is to clarify the definition 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 findings 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 definition of the DT of business models and phases for the DT of business models. Moreover, the paper offers examples of enablers and DT.
Full-text available
Context: The number of maturity models proposed in the area of Business Process Management (BPM) has increased considerably in the last decade. However, there are a number of challenges, such as the limited empirical studies on their validation and a limited extent of actionable properties of these models in guiding their application. These challenges hinder the widespread usage of the maturity models in the BPM field. Objective: In order to better understand the state of the research on business process maturity models (BPMMs) and identify opportunities for future research, we conducted a systematic literature review. Method: We searched the studies between the years 1990 and 2014 in established digital libraries to identify empirical studies of BPMMs by focusing on their development, validation, and application. We targeted studies on generic models proposed for business process maturity, business process management or orientation maturity, and selected 61 studies out of 2899 retrieved initially. Results: We found that despite that many BPMMs were proposed in the last decade, the level of empirical evidence that reveals the validity and usefulness of these models is scarce. Conclusion: The current state of research on BPM maturity is in its early phases, and academic literature lacks methodical applications of many mainstream BPMMs that have been proposed. Future research should be directed towards: (1) reconciling existing models with a strong emphasis on prescriptive properties, (2) conducting empirical studies to demonstrate the validity and usefulness of BPMMs, and (3) separating the assessment method used to evaluate the maturity level from the maturity model which acts as the reference framework for the assessment.
Digitalisierung und digitale Transformation sind nicht nur ein Thema der Medien, sondern finden auch real in den Unternehmen statt. Der digitale Wandel tangiert die unterschiedlichsten Felder, von der Beschaffung bis zum Vertrieb und von der Organisation bis zur Strategie­entwicklung. Diese Aufgabe erfordert das Engagement jeder Unternehmensleitung und lässt sich nicht einfach delegieren. Dieses Buch will Managern und Unternehmern helfen, in ihrer Organisation Strukturen aufzusetzen, die es erlauben, die digitale Transformation systematisch anzugehen. Das Themen­spektrum reicht dabei von der Konfiguration von Digita­lisierungsstrategien über neue Managementrollen wie die eines Chief Digital Officers bis hin zur Bedeutung von IT-Infrastrukturen, dem HR-Mana­ge­ment und der Unternehmenskultur als „Enabler“ des digitalen Wandels. Als Orientierungsrahmen dient ein einfaches Framework, das die Manage­mentaufgaben strukturiert und die verschiedenen Konzepte und Instrumente übersichtlich zusammenfasst. „Prof. Thomas Hess gibt einen konkreten Überblick über viele wichtige Aspekte, die bei der digitalen Transformation von Unternehmen zu beachten sind. Klar lesenswert.“ Stefan Winners, Vorstand Digital bei Hubert Burda Media „Beyond the buzzword - Endlich schafft es jemand, das Chaos um die digitale Transformation systematisch zu entwirren. Thomas Hess stellt mit seinem Buch wahrlich die Leitplanken für das Management digitaler Transformationsprojekte auf. Während andere viel versprechen und wenig halten, gibt Thomas Hess dem Leser vielmehr einen Gestaltungsrahmen als ein Patentrezept mit.“ Dr. Christoph Steiger, ehem. Vorstandsmitglied und CDO der Hoffmann Group „Deutlich mehr als ein weiteres Buch zum Thema digitale Transformation! Mit spannenden Einblicken aus Wissenschaft und Praxis liefert Thomas Hess einen Werkzeugkasten für die digitale Transformation. Relevant für die Wirtschaft und relevante Forscher.“ Prof. em. Dr. Dr. h.c. Hubert Österle, Universität St. Gallen Der Autor Prof. Dr. Thomas Hess ist Direktor des Instituts für Wirtschaftsinformatik und Neue Medien der LMU München. Er beschäftigt sich seit über 20 Jahren mit dem digitalen Wandel von Unternehmen. Dazu hat er eine in Europa führende Forschungsgruppe aufgebaut, die über das Internet Business Cluster München, den Münchner Kreis und die Netvolution GmbH als Spin-off des Instituts stark mit der unternehmerischen Praxis verbunden ist.
Digital Darwinism is a key challenge for all companies and brands. Not all companies and managers are aware of the challenges lying ahead. This book helps to identify the need for change and adaption based on a framework of findings and additional tools to position you and your company in the digital rat race.
Maturity models are valuable instruments for IT managers because they allow the assessment of the current situation of a company as well as the identification of reasonable improvement measures. Over the last few years, more than a hundred maturity models have been developed to support IT management. They address a broad range of different application areas, comprising holistic assessments of IT management as well as appraisals of specific subareas (e. g. Business Process Management, Business Intelligence). The evergrowing number of maturity models indicates a certain degree of arbitrariness concerning their development processes. Especially, this is highlighted by incomplete documentation of methodologies applied for maturity model development. In this paper, we will try to work against this trend by proposing requirements concerning the development of maturity models. A selection of the few well-documented maturity models is compared to these requirements. The results lead us to a generic and consolidated procedure model for the design of maturity models. It provides a manual for the theoretically founded development and evaluation of maturity models. Finally, we will apply this procedure model to the development of the IT Performance Measurement Maturity Model (ITPM3).
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 – The purpose of this paper is to report findings of a study conducted on micro and small enterprises (SMEs) from selected regions of Spain, Portugal and Poland, and to compare them with the results of a similar survey carried out in California (USA). The European and US research studies focus on issues regarding the use of information and communication technology (ICT) solutions by SMEs and digital divide phenomena which exist between SMEs and large corporations. Design/methodology/approach – The data collected during face-to-face interviews with SMEs' owner–managers and employees from Spain, Portugal, Poland and the USA were used for making a comparative analysis based on descriptive statistical methods. Analyzing the barriers that discourage SMEs from using information and communication technology (ICT) and e-Business solutions in their business processes made it possible to identify the reasons for SMEs being on the “wrong side” of the digital divide. Findings – The paper argues that the main barrier to better utilization of ICT and e-Business, and thus the main reason why SMEs face a digital divide, is not so much the lack of access to information technology (“material access” barrier) as the lack of proper knowledge, education and skilled owner-managers and employees within the enterprise (“skills access” barrier). As long as European SMEs do not realize this fact, so long will the scale of the digital divide in Europe continue to grow. Research limitations/implications – The main limitation of the approach presented in this paper is related to the sample differences between Spain, Portugal, Poland and the USA. This made it impossible to carry out precise comparative statistical analysis of the results. Despite these methodological imperfections, it was possible to put forward certain recommendations on the directions of activities focusing on enhancing e-Business adoption in SMEs. The main conclusion is that the actions aimed at bridging the digital divide in SMEs should concentrate on overcoming the “skills access” and “usage access” barriers within SMEs, not the material ones. Originality/value – The comparison of the way these problems are perceived by European and US owner-managers is an added value of the paper, which brings new content to the existing discussion on barriers to the implementation of ICTs in SMEs. This approach is a step forward in analyzing the determinants and the mechanism of the digital divide within SMEs and has the potential to diminish the scale of this problem.