Computers in Industry 132 (2021) 103522
Contents lists available at ScienceDirect
Computers in Industry
journal homepage: www.elsevier.com/locate/compind
Digital transformation capability maturity model enabling the
assessment of industrial manufacturers
Ebru Gökalp ∗ , Veronica Martinez
Institute for Manufacturing, Department of Engineering, University of Cambridge, 17 Charles Babbage Road, Cambridge, CB3 0FS, United Kingdom
a r t i c l e
i n f o
Article history:
Received 29 December 2020
Received in revised form 25 June 2021
Accepted 8 July 2021
Available online 27 July 2021
Keywords:
Digital transformation
Maturity model
Digital transformation maturity
Process assessment
Smart manufacturing
a b s t r a c t
The utilization of on-premise technologies in the business environment is ushering in a new era known
as digital transformation (DX). Although organizations are aware of the potential advantages of DX, they
have faced problems creating a clear path to reshape their existing processes in line with on-premise technologies. Therefore, they need guidance from a holistic viewpoint. Maturity models (MMs) are developed
to guide organizations by providing an extensive roadmap for improvement. The digital transformation
capability maturity model (DX-CMM) is developed to assist organizations by providing current DX capability/maturity determination, derivation of a gap analysis, and the creation of a comprehensive roadmap
for improvement in a comprehensive, structured, objective, complete, and standardized way. The aim of
this study is to check the usability and applicability of the DX-CMM by performing a multiple case study,
including assessments of the DX maturity level and derivation of a roadmap for DX maturity improvement
to move one level further in two organizations in the chemical and machine manufacturing domains. The
case study results show that the DX-CMM is applicable for identifying the DX maturity level, and it is
capable of providing a roadmap for DX maturity improvement for moving one DX maturity level further,
as well as benchmarking organizations evaluated using the same approach.
© 2021 Elsevier B.V. All rights reserved.
1. Introduction
The exploitation and integration of new digital technologies
have been transforming almost all industries by reshaping and frequently disrupting existing business and operating models. This
transformation provides increasing innovations in value creation,
sales, productivity, and service quality by improving the intelligence of products, processes, services, and systems. Recently,
digital transformation (DX) has been attracting increasing interest from industry and academia. More than 80 % of CEOs reported
that they have digital business transformation programs in place;
and it is estimated that by 2030 > 70 % of new value creation in the
economy will depend on digital platforms (World Economic Forum,
2018).
Although DX has a significant disruptive impact on business
and society, and organizations are aware of its potential effect,
many do not have a clear roadmap to re-engineer the existing
processes in line with the emerging technologies (Beckert, 2014).
DX is a continuous and complicated undertaking that can substantially shape organizations’ operations. It is, therefore, essential to
∗ Corresponding author.
E-mail addresses: eg590@cam.ac.uk, vm338@cam.ac.uk (E. Gökalp).
https://doi.org/10.1016/j.compind.2021.103522
0166-3615/© 2021 Elsevier B.V. All rights reserved.
coordinate and manage the holistic business-to-technology scope
of this transformation. It is necessary to acquire a comprehensive viewpoint to lead this DX, which includes heterogeneous
and complex processes from different domains of strategy, human
resources, process management, information technologies, among
others (Neff et al., 2014). Correspondingly, there is a need for assistance and guidance to provide a clear path from a holistic viewpoint
for the DX journey. The aim of maturity models (MMs), consisting
of a sequence of discrete maturity levels, is to bridge over organizations by offering extensive guidance and providing a roadmap for
improvement. To this end, we have developed the digital transformation capability maturity model (DX-CMM) to assess the current
DX maturity level of the organizations and to offer a roadmap for
maturity level improvement in a structured way. The aim of the
DX-CMM is to satisfy four requirements to:
• evaluate DX processes in detail;
• provide guidance in identifying the current DX maturity level of
the organization;
• show opportunities for improvement to move to the next DX
maturity level;
• benchmark the organization against other organizations evaluated with the DX-CMM.
E. Gökalp and V. Martinez
Computers in Industry 132 (2021) 103522
The research objective of this study was to analyze how the DXCMM identifies organizations’ current DX maturity level and gaps,
and to provide roadmaps for DX maturity improvement. This this
research aims to apply the DX-CMM to check its usability and applicability through the utilization of a qualitative multiple case study
approach. The model was applied to two companies with different
sectors, sizes, countries, and DX adoption. As a result of semistructured interviews with DX process owners, and investigation
of DX-related documents, detailed assessment reports, including
DX gaps, successful practices observed, and improvement opportunities, were documented and presented to the DX stakeholders
in the organizations. After discussing the assessment results, the
participants were asked to fill in the questionnaire to evaluate the
applicability and usability of the DX-CMM.
The remainder of the paper is organized as follows: the related
research is provided, followed by the structure of the DX-CMM.
After this, the application of the DX-CMM is given, and the results
are discussed; lastly, the paper is finalized and a conclusion is
drawn.
processes, reducing expenses and inconsistencies, and increasing
employee productivity and involvement (Tarhan et al., 2016). These
models have been utilized by hundreds of organizations worldwide
because of their proven benefits.”
A software process improvement and capability determination
model (SPICE), also known as ISO/IEC 3300xx (ISO, 2015a, 2015b,
2015c), a revised version of ISO/IEC 15504 (ISO, 2012, 2004a, 2004b,
2003), provides a structured process assessment framework, facilitating a basis for process capability/maturity level improvement. It
assumes that a higher level of process capability or organizational
maturity is associated with better performance. Although SPICE
was developed for the software development domain, after observing its benefits, such as expense savings, increased involvement
of employees, predictable and improved quality and productivity, and constructing a consistency of process capture and use,
it has been customized to different domains, such as automotive
(Automotive, 2010), enterprise management (Ibrahim, 2008), IT
security ((Barafort et al., 2006), IT service management (Malzahn,
2007), and government (Gokalp and Demirors, 2016). It consists of a
set of technical standards documents for process improvement and
capability determination, it is a reference model for the maturity
models.
The DX-CMM was developed based on SPICE. The primary reasons for selecting SPICE, the family of standards ISO/IEC 3300xx
(ISO, 2015a, 2015b, 2015c), as a benchmark are its well-established
and widely recognized structure. It presents a process viewpoint of
process assessment, providing a clear set of requirements for the
process assessment process, and the resources required to implement it effectively. It consists of technical standards, including the
requirements for MM design (ISO, 2015b), process definition (ISO,
2015c), planning, and execution of process capability/maturity
assessments (ISO, 2015d), and the application of process improvement based on the process assessment (ISO, 2013).
2. Background research
A brief description of the DX and business process capability or
MMs as well as a review of MMs developed for DX, smart industry,
Industry 4.0, and smart service domains, is given in the following
subsections.
2.1. Digital transformation (DX)
DX is defined as a disruptive technological achievement
bringing new business and operating models across all sectors.
Organizations seek to reshape their processes in line with onpremise technologies such as digital twins (Annunziata and Biller,
2015), the Internet of things (IoT) and connected devices (Gilchrist,
2016), artificial intelligence (Schuh et al., 2017), cyber-physical systems, integration (Kagermann et al., 2013; Schuh et al., 2017), social
media and platforms, blockchain (Swan, 2015), everything-as-aservice (XaaS), robots and drones, data analytics (Gökalp et al.,
2021b; Gökalp et al., 2021c), and 3D printing (Schwab, 2017). For
example, collecting data via IoT devices and implementing analytical tools to make predictive analysis on product quality trends can
be defined as a DX project that will affect the existing production
process, or the way employees are doing production. Since it has
social, technical, technological, and managerial effects in the organization, it should be managed from a holistic perspective (De la
Boutetière et al., 2018; Gökalp et al., 2021a; Henriette et al., 2016;
Kagermann et al., 2013; Li, 2020; Verhoef et al., 2021)
2.3. Digital transformation capability/maturity assessment
models
A search on the Web of Science, Scopus, and Google Scholar
research platforms was conducted to identify existing MMs.
The search terms relevant to this literature review research
were defined as “Digital Transformation”, “Digitalization”, “Smart”,
“Industry 4.0”, “Industry Internet of Things” AND “Maturity Model”,
“Capability Model”, “Assessment Model”, “Readiness Assessment”, and
so on. The references of the articles were also reviewed. Consequently, it was determined that there are 18 MMs regarding the
development of MMs for the DX, smart manufacturing, and smart
services domains. During the search, it was observed that there has
been a research stream investigating the subject in recent years,
and the MMs that are published extensively use the “maturity” (83
% of all studies) and “Industry 4.0” (61 % of all studies) keywords.
Although there are no standard or published evaluation criteria for
the scope of DX, we utilized the MM evaluation criteria used in
(Özcan-Top and Demirors, 2019). Correspondingly, The 18 MMs,
given in Table A1 in the Appendix A, were evaluated based on three
criteria:
2.2. Business process Capability/Maturity models
Process capability/maturity models (PCMMs) are developed
to provide a guideline for the implementation of vital practices
for organizational processes. These models have process capability/maturity levels, referring to the level of progress from ad hoc
practices to established and measurable processes (Curtis et al.,
2009). PCMMs provide the application of the model-based process
assessment. As a consequence of the process assessment, the current capability/maturity level of the process is determined, and a
roadmap for the process capability/maturity level improvement
to the next level is achieved (Röglinger et al., 2012). There are
some criticisms about the concept of MMs oversimplifying reality and lacking an empirical foundation (Benbasat et al., 1984);
however, their benefits are demonstrated through several case
studies (Goldenson and Gibson, 2003; Isoherranen et al., 2015). The
MM approach demonstrated significant advantages in quality and
productivity issues. They improve the performance and quality of
• C1- The MM should be published as an academic paper, which is
an indicator of the academic approach.
• C2- The MM should include a detailed description of its components in order to provide a detailed analysis.
• C3- The MM should be applicable across all sectors instead of
being domain-specific.
Although the number of existing MMs in the DX, smart manufacturing, and smart services domains is not small, none in the
literature fully satisfied all of the evaluation criteria listed above.
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Computers in Industry 132 (2021) 103522
MM1, MM2, and MM6 are published as a White Paper and do not
fulfil C1. There is no detailed description of the components of the
MM, and a preliminary MM is given in MM8, MM11, and MM14.
There is no maturity level defined in MM4, MM15, and MM18. The
assessment method is not described in MM3, MM5, MM10, and
MM16. The measurement attributes are not defined in MM7 and
MM17. Thus, these models do not satisfy the second criterion. Since
MM9 was developed for the telecommunications sector, MM12
targets the supply chain sector, and MM13 targets Industry 4.0
strategy, these models do not satisfy the third criterion. Although
all value-adding DX processes must be taken into consideration
using a holistic and integrated approach in order to benefit fully
from DX, none of the existing MMs has a comprehensive and integrated approach. Moreover, none have been developed based on a
well-established PCMM, and they do not aim to improve DX processes. Additionally, none of them gives full details of the model
for the application or provides an action plan for enabling maturity
stage improvement. Taking all of these issues into account, it can
be said that there is a lack of research in this domain. Thus, we aim
to fill this research gap by developing an MM for the DX domain
by satisfying all criteria used for the evaluation of MMs. It is developed by applying a theoretically grounded development approach.
It is aimed to be applicable across all sectors and provide a detailed
description of its components. The details of the research method
are given in the next section.
tifying DX processes in the model. As a result of three consecutive
sessions, DX processes retrieved from the literature were discussed
in the first session; additional processes offered by the experts were
retrieved after some series of discussions in the second session,
and all of DX processes were considered through a systematic and
interactive meeting to resolve conflicts to reach a consensus on DX
processes and DX process groups in the last session. As a result
of the expert panel, all experts agreed on the DX processes and
DX process groups defined in the DX-CMM. After developing the
process definitions for the DX processes, and the measurement
framework for capability and maturity level determination, the
expert panel reviewed the developed DX-CMM and provided feedback. Consequently, the development of the DX-CMM was finalized.
The third phase covers the validation of the model, with a multiple
case study being conducted in two organizations operating in two
different industries in two countries with different DX adoption
levels. The decisions made when developing the DX-CMM are highlighted with grey boxes in Table 1. The DX-CMM needs to include
both management-oriented and technology-oriented constructs
and need to focus on both management and technology-oriented
processes.
4. The DX-CMM: the digital transformation capability
maturity model
The aim of the proposed MM, the DX-CMM, is to improve the
organization’s DX competencies in a structured way as a consequence of the existing capability/maturity level assessment, and
to provide a comprehensive roadmap for improvement. The DXCMM was developed by customizing SPICE (ISO, 2015a, 2015b,
2015c, 2012, 2004b, 2004a, 2003), which comprises two dimensions, process and capability. The process dimension in SPICE
includes software-development process definitions; and the capability dimension consists of process capability levels, which are,
in turn, composed of process attributes (PA), including base practices (BPs) for Level 1 and generic practices (GPs) covering Level
2 to Level 5. Organizational maturity is also defined based on the
process set for each maturity level. The capability levels defined
in the SPICE measurement framework from level zero to level five
have been developed to be appropriate universally to all processes
except for level-1 (performed) where the observable indicators are
different for each process, while all the PAs from level two to five
are common for all processes. In the scope of this study, the process
definition of 26 DX processes are developed, including level-1 process performance indicators as outcomes, base practices and work
products. Thus, the DX processes capability level can be assessed
based on SPICE owing to these developed process definitions.
The DX-CMM has two dimensions, as seen in Fig. 2. The process
dimension comprises process definitions for DX-related processes
instead of software-development processes, while the capability
dimension includes the same capability levels, PAs, BPs, and GPs
defined in SPICE (ISO, 2012). The literature provides that the capability dimension is applicable to all processes across all domains
(Automotive, 2010; Mc Caffery and Dorling, 2010; Mitasiunas and
Novickis, 2011). Organizational DX maturity is also defined based
on the DX process set for each maturity level. The requirements
defined in SPICE, the set of standards of ISO 3300xx, were followed
for the development of the DX-CMM. ISO/IEC 33004 (ISO, 2015c)
was used in the development of DX process definitions, as well as
the maturity levels of the DX-CMM; ISO/IEC 33003 (ISO, 2015e),
ISO/IEC 33020 (ISO, 2015c), and ISO/IEC 15504-5 (ISO, 2012) were
used for the capability dimension of the DX-CMM; ISO/IEC 33002
(ISO, 2015d) was utilized to perform process assessment; and
ISO/IEC 33014 (ISO, 2013) was used to generate a road-map for
process improvement.
3. Research method
The research method to develop an MM for the DX domain
consisted of three phases, as defined in Fig. 1. In the first phase,
the organizations’ need for a clear roadmap for their DX journey
was identified. As a result of the evaluation of the existing studies
related to this need, it was determined that none of the current
studies satisfies the requirements, and there is a research gap in
this field. To fulfill this necessity, a solution approach, the development of an MM for guiding organizations in their DX activities based
on a well-established PCMM, SPICE, was determined. The theoretical foundations of the development of the DX-CMM are detailed
explained in one of our previous studies (Gökalp and Martinez,
2021).
In the second phase the DX-CMM was developed by utilising the MM development framework proposed by De Bruin et al.
(2005) as the methodological foundation. The framework offers six
steps; namely, scope, design, populate, test, deploy, and maintain,
to develop an MM in a structured manner. At the scope phase, the
scope of the model was determined. At the design phase, the structure/architecture of the model was determined based on the criteria
of the target audience, the method of application, and the driver of
application, the respondents, and the application,which are defined
in the MM development framework proposed by De Bruin et al.
(2005) While the models’ dimensions and sub-dimensions, which
should be measured, were defined at the populate phase, the model
is validated in the test phase by indicating that the assessment
result of the model is exact and repeatable. The multiple case
study approach was utilized for validation of the MM. Following
validation, the MM is made available at the deploy phase for generalization and standardization of the MM. As a final step of the
maintain phase, the MM ensures its continued relevance through a
longitudinal study.
The DX-CMM was developed by identifying DX processes, developing the process definitions for the DX processes, and developing
the measurement framework for capability and maturity level
determination. An expert panel comprising five senior academicians, one senior DX leader, and one senior executive member
working in the DX domain was formed for the purpose of iden3
E. Gökalp and V. Martinez
Computers in Industry 132 (2021) 103522
Fig. 1. The Research Method.
4.1. The process dimension of the DX-CMM
DX initiatives should include gearing up and aligning the strategy,
culture, workforce, and process gathering to embrace this rapidly
changing environment. As a result of the expert panel described
in the research method section, the process dimension of the DXCMM consists of 26 DX processes defined under 4 process groups
of strategic governance, information and technology, digital process transformation, and workforce management, as seen in Fig. 3
(below). These DX processes are defined based on the requirements
outlined in ISO/IEC 33004 (ISO, 2015c), which states that a process
definition should include the process name, purpose, outcomes,
base practices, and output work products.
DX processes can be defined as a set of interrelated or interacting activities that transform inputs into outputs for the purpose of
enabling the DX of the organization. The literature review (De la
Boutetière et al., 2018; Kagermann et al., 2013) and survey results
(Koch et al., 2014; Leaders, 2018) show that the most critical dimensions of DX in organizations are organization strategy (Brynjolfsson
and Hitt, 2000; Tao et al., 2017), upskilling of the workforce (Autor
et al., 2003; Fu et al., 2011; Morrison et al., 2008), and digital process transformation. DX is not just about technology: successful
4
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Computers in Industry 132 (2021) 103522
Table 1
Decisions made when developing the DX-CMM (Adapted from the study of Mettler (Mettler, 2010, 2009).
4.1.1. Strategic governance
The DX strategy needs to be led from the top, with a strong, clear,
and inspiring vision of how emerging technologies can create a new
future with shared value (Tao et al., 2017). Organizations should
create their DX roadmap, which is generated based on their vision.
The portfolio should be designed based on the strategic objectives,
enterprise worth, and risk. The projects should be managed by
identifying, establishing, and controlling DX activities. Finding the
most appropriate supplier and maintaining the relationship is also
essential in the DX journey.
software, data, and business process layers; management of infrastructure such as as IoT devices, servers, and so on; collecting,
storing, analyzing, and distributing data; management of data
analytics; development of applications based on agile software
development principles; and IT security management. These processes are all fundamental to the DX journeys of organizations.
4.1.3. Digital process transformation
This includes digitalization of business processes through technology to cut costs and increase productivity; integration of
processes at different intra-company, and inter-company, levels,
as well as across the entire value chain; establishing and maintaining a quantitative management of processes; improvement of the
process performance; and data-driven decision-making, enabling
machines to autonomously adapt to the predicted status. These are
all essential dimensions in the DX journey of organizations.
4.1.2. Information and technology
An IT strategy should be developed that is aligned with the
organization’s DX strategy for migration to the desired future
environment. The IT requirements for each DX project should
be defined: the development, integration, and maintenance of
a standardized enterprise architecture (EA), including hardware,
Fig. 2. Dimensions of the DX-CMM.
5
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Computers in Industry 132 (2021) 103522
Fig. 3. DX Process Categories.
Fig. 4. Process Capability Levels (Adapted from SPICE).
4.1.4. Workforce management
Cultural change should be implemented before the process
transformation begins. Human resources (HR) skills development,
organizational structure management, sustainable learning management, and organizational change management are all essential
for the DX journey of organizations.
0: Incomplete, to Level 5: Innovating. The PAs at each capability
level are shown in Fig. 4 (below).
4.3. Organizational digital transformation maturity
Organizational DX maturity is the extent to which a firm consistently implements DX processes to achieve the desired level
of achievement of DX maturity, which is evaluated by assessing
achievement of the specified process capability levels for a defined
profile of processes, as set out in an MM. Organizational DX maturity is evaluated concerning process capability in a staged manner.
4.2. The capability dimension
The capability dimension, which is applicable to any process,
was adapted from SPICE (ISO, 2012). It includes six levels, from Level
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Computers in Industry 132 (2021) 103522
Fig. 5. The DX-CMM Maturity Levels.
It is fundamental to understand that successful DXs occur stepby-step. The DX-CMM provides a roadmap, including all related
dimensions, with a staged approach that relies upon a sequence of
capability levels, from the basic necessities to the continuous adaptation for DX. Each level builds on the previous one. Fig. 5 shows
that the model has six maturity levels, from Level 0 to Level 5.
Level 0: Incomplete – The DX initiative has not yet started.
Level 1: Performed – The DX initiative has been started. The
vision of DX exists, and the roadmap for the transition strategy
has been developed, but it has not been entirely implemented. The
portfolio consisting of the DX projects that have been identified,
evaluated, prioritized, and authorized is created. Additionally, a
department or group is assigned to carry out DX. Workforce skill
necessities are determined, and corresponding training starts to be
acquired in the company.
Level 2: Managed – DX is managed at this level, at which the
digital shadow of physical items begins to be created. This concept
is also known as Digital Twin, which serves as a bridge between
the physical world and the digital world (Qi and Tao, 2018; Tao
et al., 2018). This requires the performance of several complementary processes. Existing business processes are digitized through
technology; the IT department publishes an IT strategy to migrate
to the demanded future environment stated in the organization’s
DX strategy; DX-related projects are started; feasibility analysis of
the projects is performed, pilot studies are conducted, and requirements are defined for each project; the acquisition of IoT devices,
hardware, and software has begun, and the vendor relationship
is managed; the requirements and needs of the enterprise architecture (EA), consisting of the business process, information, data,
application, and technology architecture layers are identified, and
standards, guidelines, procedures are defined; and, finally, infrastructure, data governance, software development, and the security
of the information systems are managed.
Level 3: Established – DX is established robustly at this level.
Key processes are well defined and consistent with corresponding standardization. Vertical integration, including intra-company
integration of IoT devices, up to enterprise resource planning or
customer requirement management systems, has been achieved.
The developed EA is integrated, and organizational change is managed at this level.
Level 4: Predictable – The quantitative techniques begin to be
applied to the collected real-time data for products, services, or
processes. Horizontal integration, which is the integration across
networks at the business level, is established. Data analytics are
applied.
Level 5: Innovating – The organization uses the collected data
for continuous improvement, innovative culture is established, and
dynamic cooperation and increasing transparency, by extending
operational visibility with automated and seamless information
exchange among the network, are enabled.
The relationships between organizational DX maturity level and
DX process capability level are illustrated in Fig. 6. To give an
example, at Organizational Maturity Level 1, the processes of SG1.
Digital Transformation Strategy Development, SG2. Portfolio Management, WM1. HR Skills Development, and WM2. Organizational
Structure Management are assessed. The capability level of these
processes should be Level 1: Performed to satisfy the requirement
of being Organizational DX Maturity Level 1. At Organizational
Maturity Level 2, the processes of DPT1. Business Process Digitalization, SG3. Project Management, SG4. Financial Resources and
Supplier Management, IT1. IT Strategy Management, IT2. Requirement Definition, IT3. Enterprise Architecture Development, IT4.
Infrastructure Management, IT5. Data Governance, IT6. Agile Software Development, and IT7. Security Management, as well as the
processes assessed at Maturity Level 1 (SG1, SG2, WM1, WM2), are
evaluated. The capability level of these processes should be Level
2: Managed, to satisfy the requirement of being at Organizational
DX Maturity Level 2. At Organizational Maturity Level 3, the processes of IT8. Enterprise Architecture Integration, DPT2. Business
Processes Vertical Integration, WM3. Organizational Change Management, and WM4. Sustainable Learning Management, as well as
the processes assessed at Maturity Level 2 (SG1, SG2, WM1, WM2,
DPT1, SG3, SG4, IT1, IT2, IT3, IT4, IT5, IT6, IT7), are assessed. The
capability level of these processes should be Level 3: Established,
to satisfy the requirement of being at Organizational DX Maturity
Level 3. At Organizational Maturity Level 4, the processes of DPT3.
Business Processes Horizontal Integration, DPT4. Data-Driven Deci7
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Computers in Industry 132 (2021) 103522
Fig. 6. The Relationships Between Maturity Levels and Capability Levels.
sion Management, DPT5. Quantitative Performance Management,
IT9. Data Analytics, and IT10. Enterprise Architecture Maintenance,
are assessed. The capability level of these processes should be at
Level 3: Established, to satisfy the requirement of being at Organizational DX Maturity Level 4: Predictable, and the previous processes
capability level should stay at Level 3. At Organizational Maturity
Level 5, the processes of DPT6. Self-Optimized Decision Management, DPT7. Business Process Integration Toward Life Cycle, and
DPT8. Quantitative Process Improvement are assessed. The capability level of these processes should be at Level 3. Established, and
the previous processes capability levels should stay at Level 3. to
satisfy the requirement of being Organizational DX Maturity Level
5: Innovating.
of the outputs, and so on, is produced and approved by the organization.
4.4.3. Step 3: assess current DX maturity level
The assessment is conducted by the assessment team, one of
whom is a competent SPICE assessor. The team follows ISO/IEC
33002 (ISO, 2015d) for process assessment procedures, including
data collection and data validation techniques. The team collects
data by conducting semi-structured interviews with process owners and investigating processes’ work products, such as documents,
tools, and mail, for example. After completing data collection, the
team analyzes and synthesizes them to rate BPs, GPs, and PAs,
and correspondingly to determine the current capability levels,
strengths, and weaknesses of the DX processes and DX maturity
level of the organization. Finally, the team documents the assessment report containing these results.
ISO/IEC 33003(ISO, 2015e), ISO/IEC 33020 (ISO, 2015c), and
ISO/IEC 15504-5 (ISO, 2012) are followed for rating and capability level determination. To perform a Level-1 assessment, PA 1.1.,
focusing on the performing process, is assessed by checking the BPs
described in the DX process definitions. To perform process assessments from Level 2 to Level 5, the GPs defined in SPICE are used.
The PAs are rated based on the ratings of the corresponding BPs and
GPs. The four-point rating scale is used for rating BPs, GPs, and PAs.
The rating shows the extent of the achievement: if the achievement
level is between 86 % and 100 %, it is rated as Fully Achieved (F.A.);
if it is between 51 % and 85 %, it is rated as Largely Achieved (L.A.);
if it is between 16 % and 50 %, it is rated as Partially Achieved (P.A.);
and if it is between 0 % and 15 % of achievement, the rating is Not
4.4. The DX maturity level assessment process
The DX maturity level improvement life cycle is shown in Fig. 7.
The details are as follows.
4.4.1. Step 1: examine the organization’s business goals
As a result of the examination of the organizational strategy, the
need to improve the DX maturity level of the organization is determined. Then, initiation of the DX maturity improvement project is
decided in the organization.
4.4.2. Step 2: initiate DX maturity improvement
The assessment team is constructed, and the assessment plan,
including the assessment team, interview schedules, delivery dates
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Computers in Industry 132 (2021) 103522
Fig. 7. DX Maturity Level Improvement Cycle.
Achieved (N.A.). The rating of PA is determined based on its BPs and
GPs ratings, and the capability level of the process is determined
based on its PA ratings: if all PAs below Level X are rated as F.A.,
and the PAs at Level X are rated as F.A. or L.A., the capability level of
the process will be determined as Level X, as defined in SPICE. For
instance, if the rating of PA 1.1 is identified as N.A., the capability
level of the process will be Level 0; if the rating of PA 1.1. is determined as L.A., the capability level of the process will be identified as
Level 1; if the rating of PA 1.1. is determined as FA, and PA 2.1 and
PA 2.2 are assessed as L.A., the capability level of the process will
be identified as Level 2. The DX maturity level of the organization
is determined based on the process capability levels, as defined in
the section on organizational DX maturity.
ops an action plan, including work packages, assigned people, and
schedules by considering their specific circumstances.
4.4.5. Step 5: improve the DX maturity level
This step, including implementation of the action plan, confirming and sustaining improvements is long-lasting. It often covers a
period of one year. As a consequence of completing this step, the
following improvement cycle can be initiated.
5. Implementation of the DX-CMM
A multiple case study was conducted following the protocol
template of Yin (2013).
4.4.4. Step 4: analyze results and derive an action plan
ISO/IEC 33014 (ISO, 2013) was used to generate a roadmap
for process improvement. As a consequence of process capability
level determination, process improvement opportunities are determined and prioritized for the establishment of an order of execution
of the action plan in the assessment report. The organization devel-
• The objective of the case study was to investigate if the DX-CMM
could be used for assessment of the current DX maturity level and
the derivation of a roadmap for improvement.
• The research questions (RQs), defined according to the above
objective, were:
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•
•
•
•
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o RQ How does the DX-CMM identify organizations’ current DX
maturity level and gaps and provide roadmaps for DX maturity
improvement?
The design type of the case study was multiple cases because it
was applied in two companies in two different industries in two
countries with different DX adoption levels to assess their 26 DX
processes.
The measures used in the research were the DX maturity level of
the organizations. To identify the DX maturity level, the capability
levels of the DX processes performed in the organizations had to
be determined.
Field procedure, data collection, and limitations were based on
SPICE. ISO/IEC 33002 (ISO, 2015d) was followed to ensure the performance of assessment, consisting of activities for assessment
planning, data collection, ratings, and reporting assessment, in a
standardized manner.
The objectivity of the judgment: To overcome the effects of subjectivity and reduce uncertainty in the results, the DX-CMM had
explicit indicators and a hierarchical bottom-up approach for rating. As a first step, as defined in the section on the DX maturity
level assessment process, BPs and GPs were rated as Not Achieved
(N.A.), Partially Achieved (P.A.), Largely Achieved (L.A.), and Fully
Achieved (F.A.). Then, based on these ratings, corresponding process attributes (PAs) were rated as N.A., P.A., L.A., and F.A., After
that, process capability levels were determined based on the ratings of PAs, and lastly, the DX maturity level was determined
based on the capability levels of the processes assigned to each
maturity level. Moreover, the necessity to prepare an assessment
report, including pieces of evidence, reduced subjectivity.
is used to describe the company in this study, for the purpose of
confidentiality.
Case-2: The chemical company produces beauty care and laundry and home care products, employing around 53,000 people
worldwide. The data was collected from three different people: the
DX specialist, the IT manager, and the data scientist. The total duration of the interviews was three hours. The term “The Chemical
Company” is used to describe the company in this study.
5.2.1. Step 1: examine the organization’s business goals
These include the organizational strategy documents, including DX maturity improvement; the top management supports this
improvement in the two companies. Thus, the initiation of the DX
maturity improvement project was decided in each of the organizations. We checked the company reports, and additional information
was requested from the interviewees.
5.2.2. Step 2: initiate DX maturity improvement
The assessment team was constructed, and the assessment
plan, including the assessment team members, interview schedules, delivery dates of the outputs, and so on, was produced and
approved by the organizations.
5.2.3. Step 3: assess current DX maturity level
The meetings with each organization occurred over two
separate days to conduct the DX maturity level assessment. Semistructured interviews, as well as investigating direct evidence, were
used for data collection. The collected data was analyzed to determine the DX maturity level of the organization. The findings were
documented in the assessment reports.
The interviews were recorded during the meeting, then transcribed and mapped onto each BP and GP in the model for rating.
The Level-1 assessment was executed by checking if the BPs given
in the process definitions were performed. The ratings were done
based on evidence gathered as follows: F.A., L.A., P.A., and N.A as
defined in the section on the DX maturity level assessment process.
As an example, the rating in Level 1 of the digital transformation
strategy development process in The Machine Company is given in
Table A2. in the Appendix A. As is illustrated, PA 1.1 was rated as
L.A. (Largely Achieved) based on the BPs ratings. For the assessment
of PAs from PA 2.1 to PA 5.2, the GPs provided by SPICE were used
and rated, as defined in (ISO, 2015c, 2012, 2004a). These capability level assessments were carried out for 26 DX processes in each
organization. Detailed information about the evaluations was given
in the assessment reports (University of Cambridge, Institute for
Manufacturing, 2019; University of Cambridge, 2020).
5.1. Design of the case study
The multiple case study was designed to cover the following
activities:
(a) Preparation: Development of the data collection templates,
preparing semi-structured interview questions, and the postassessment survey questions to be used for collecting feedback.
(b) Case Selection and Planning: Selecting organizations to be able
to observe all patterns in DX processes and DX maturity levels.
Managing the interactions with case organizations about the
assessment plan, including assessment schedules and participants.
(c) Assessments and Data Collection: DX maturity level assessment,
and collecting data via semi-structured interviews and investigating direct shreds of evidence, such as documents, records, IT
strategy, plans, tools used, and metrics collected. To triangulate
data in each case, conducting interviews with at least three people from different roles, such as the head of the DX department,
IT manager, process quality manager, DX project manager, and
HR manager.
(d) Analysis: Transcribing the voice records of the interviews, investigating the direct evidence, and analyzing the data to develop
the assessment reports.
(e) Validation of the Findings: Sharing the assessment results and
discussing with interviewees to obtain their feedback and
determine if any revision was necessary on the reports.
6. Results and discussions
A process capability level is determined as Level X if the ratings
of all PAs below Level X are F.A., and the ratings of PA(s) at Level
X are rated as F.A. or L.A., as defined before. Process capability levels were determined for The Machine Company and The Chemical
Company, as shown in Tables A3 and A4 in the Appendix A. For
example, the capability level of the digital transformation strategy
development process is Level 3 in The Chemical Company, since PA
1.1., PA 2.1, and PA 2.2. are rated as F.A. and PA 3.1 and PA 3.2 are
rated as L.A. Still, the software development process is performed
by the sub-contractors; the assessment of this process is assessed as
Not Applicable, since the company outsources it. The improvement
opportunities related to this process are also given in the assessment report (University of Cambridge, Institute for Manufacturing,
2019, 2020).
5.2. Case study conduct
The DX-CMM was applied in two organizations.
Case-1: The machine production company has 255 employees
and is located in the UK. Interviews were conducted with three
people: the head of the DX department, the IT manager, and the
quality manager. The duration of the interviews for each person
was approximately one hour. The term “The Machine Company”
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6.1. Organizational DX maturity level assessment
After performing the DX Maturity Level-1 assessment, as can
be seen below, the requirements of being at DX Maturity Level 1,
being at a process capability level of Level 1 for the processes of Digital Transformation Strategy Development, Portfolio Management,
HR Skills Development, and Organizational Structure Management,
are satisfied in both companies. Therefore, a Level-2 assessment
could be continued for both of them. They developed a DX strategy
and roadmap by conducting value-mapping workshops and gap
analysis, created a portfolio for DX projects, had an organizational
unit for DX management, and provided some DX-related training
to improve their HR skills (Fig. 8).
When we continued to assess Maturity Level 2, it was evident
that, although the requirements of being at DX Maturity Level 2
are not satisfied in The Machine Company, they are satisfied in The
Chemical Company, as seen in Fig. 9. Thus, the DX maturity level
of The Machine Company was determined as being Level 1, and
the capability level of the processes, rated below Level 2, should be
improved to at least Level 2 to improve the DX maturity level of the
organization from Level 1 to Level 2. The gap analysis to move to
Maturity Level 2 is shown in Fig. 12. Meanwhile, an assessment for
the next maturity level could be done for The Chemical Company.
Fig. 8. Organizational Maturity Assessment – Level 1.
A DX Maturity Level 3 assessment was performed, and it was
observed that the requirements of being at DX Maturity Level 3 are
satisfied in The Chemical Company, as seen in Fig. 10. Thus, a DX
Maturity Level 4 assessment could be conducted.
Fig. 9. Organizational Maturity Assessment – Level 2.
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Fig. 10. Organizational Maturity Assessment – Level 3.
To achieve Maturity Level 4, all processes assigned to Maturity Levels 1, 2, 3, and 4 will achieve Process Capability Level
3 or higher. As seen in Fig. 11 (below), the requirements for
Organizational Maturity Level 4 are not satisfied in The Chemical Company. To fulfill this, the business processes horizontal
integration process should be improved from Level 1 to Level
3, and quantitative performance management and EA maintenance processes should be improved from Level 2 to Level 3. After
completing these four process improvements, the organizational
maturity level of the organization will be at Level 4. Thus, the DX
maturity level of The Chemical Company is determined as being
Level 3.
For The Machine Company, the DX maturity level was determined as being Level 1. The gap analysis to move to Maturity Level
2 is shown in Fig. 12. All processes seen in the figure should be
improved to Level 2.
For The Chemical Company, the DX maturity level was determined as being Level 3. To achieve the highest DX maturity level
of Level 5, The Chemical Company should first satisfy the requirement of being at Maturity Level 4, and then improve the capability
level of the processes of self-optimized decision management and
business process integration toward product life cycle from Level
0: Incomplete to Level 3 (Fig. 13).
6.1.1. Step 4: analyze results and derive an action plan
The strong and weak points of the DX processes of the organizations were identified depending on the assessment findings in
this step. Improvement opportunities were identified based on the
identified weak points of the DX processes for each case. The aim
was to achieve FA in the BPs and GPs to improve their capability
levels to the next levels.
For The Machine Company, the DX maturity level of the organization was determined as being Level 1. The transformation
was then initiated in the company. There was a DX roadmap
for the short term (one year). The portfolio consists of eight DX
projects that provide good results in a short amount of time with
a low budget. Moreover, a DX department was established in the
organization, although the number of employees working in the
department was only three. Lastly, there was a process management culture in the organization; thus, the DX-related projects
can be easily defined and established. On the other hand, there
was a long DX journey facing the company to achieve the highest DX maturity level. As a starting point, the organization should
focus on the DX processes defined at Level 2. For example, development of the DX strategy document for the long-term vision,
the acquisition of DX-related training, the development of plans
for DX projects, and development of the IT strategy, including the
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Fig. 11. Organizational Maturity Assessment – Level 4.
operational environment, enterprise architecture (business, information, data, applications, and technology domains), enterprise
culture, and current challenges can be taken into consideration
as beginning steps. A total of 122 improvement opportunities for
DX maturity improvement from Level 1 to Level 2 were defined
in the assessment report (University of Cambridge, Institute for
Manufacturing, 2019). Example Assessment Results for Two Processes in the Machine Company is given in Table A5 in the Appendix
A.
The initiatives highlighted in red suggest high priority, which
means they should be done as a first step to improve the relative
process. The blue ones, having medium priority, should be done as
a second step, and the grey ones, having low priority, should be
done after completing the previous ones.
The overall DX maturity was scored at Level 3 in The Chemical
Company. This means that DX is robust at this level. Key processes
are well defined and consistent with corresponding standardization. Vertical integration, including intra-company integration of
IoT devices, up to enterprise resource planning, customer requirement management, or supply chain management systems, has been
achieved. Developed EA is integrated, and organizational change is
managed at this level. The quantitative techniques are starting to
be applied to the collected real-time product–service or process-
specific data. The data analytics tools currently in use are showing
improvements on the overall productivity and service quality.
On the other hand, horizontal integration, including integration
across networks at the business level, has not yet been achieved,
and the functionalities of whole enterprises have not been integrated either. Additionally, self-optimized decision-making of the
machines has not yet been performed. The guideline, including 84
DX process improvement opportunities prepared mainly for the
company, will help to enable dynamic cooperation and increasing
transparency by extending operational visibility across the supply
chain with automated and seamless information exchange within
the network. Example improvement opportunities are given in
Table A6 in the Appendix A.
6.1.2. Step 5: improve the DX maturity level
Performing activities stated as improvement opportunities in
the assessment reports, sustaining these improvements, and monitoring them is a long-lasting step. Following confirmation of the
sustainability of the improvements, the current improvement iteration will be finished, and a new cycle of DX maturity assessment
can be started.
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Fig. 12. DX Maturity Level Gap Analysis for The Machine Company.
Fig. 13. DX Maturity Level Gap Analysis for The Chemical Company.
6.2. Analysis of the model’s applicability (RQ)
explained. They declared that the main benefit of the assessment
was understanding the necessity for the assessment and improvement of DX maturity; they also reported that they will focus on
following the guideline for DX maturity improvement and on utilizing the same approach for future process improvement cycles.
To investigate the usefulness and adequacy of the DX-CMM, we
conducted a post-assessment survey with all of the participants
The DX maturity level assessment results were shared in a meeting with the DX stakeholders in the organizations. The ratings for
each BP, GP, PA, process capability level, and organization DX maturity level, and also evidence for the evaluations, were described.
The developed roadmap for DX maturity improvement was also
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Fig. 14. DX Maturity Comparison of The Machine Company and The Chemical Company.
following the meetings. The open-ended structured questionnaire
was used for the interviews, which lasted approximately ten minutes.
Q1. Are measuring DX maturity level and achieving a guideline
for DX maturity level improvement useful? (5-point Likert-type
scale): Response is 4 in the median.
Q2. Do you think that the application of these suggestions
will improve the DX maturity level? (5-point Likert-type scale):
Response is 4 in the median.
Q3. Is there any information you want to add to the DX-CMM?
Please write, if any. (Open-ended): “No”
Q4. Is there any missing item in the guideline for DX maturity
improvement? Please write, if any. (Open-ended): “The suggested
actions are useful in the identification of ‘what’ to improve [in
order] to increase the maturity level. Future work might seek to
develop/expand on the ‘how’ to achieve these improvements.”
essential, but commitment drives the budget. At the moment, in
The Machine Company, there is an attempt to transition to DX: the
vision of DX exists but it is not fully implemented. They are struggling with people’s commitment levels, and they do not consider
training to be essential. They can also face organizational change
management problems during the implementation of DX projects.
There is a long DX journey facing the company to achieve the highest DX maturity level.
6.4. Mitigation of threats to validity
The qualitative data, used in the multiple case study approach,
might create some validity concerns. In order to mitigate threats
that might have an effect on the internal, construct, and external
validity and reliability, the following activities were performed.
6.4.1. Internal validity
Detailed question sets at different granularity levels for each DX
process were developed, the data was collected from at least three
people in order to triangulate it, and different sources for direct
evidence were used to overcome the threats to internal validity.
Moreover, the utilization of a multiple case study approach was
critical to mitigating this threat. A logical chain of data collection
was designed and implemented, the detailed collected data was
stated in the assessment reports, as well as being validated by the
stakeholders in the organizations.
6.3. Cross-case comparison
One of the logical bases for selecting the cases was to be able to
observe a rating for each DX process capability level and DX maturity level of the organizations. The two industrial manufacturers’ DX
journeys are quite different, and their ambitions regarding DX are
different. They experienced different DX journeys, reflecting different maturity levels. The DX maturity comparison of The Machine
Company and The Chemical Company is shown in Fig. 14. It was
observed that, although the DX initiative started just three years
ago, with four employees working in the DX department in The
Chemical Company, they made a significant achievement in this
limited amount of time. The reasons behind this achievement are
commitment, HR skills development, and financial resource allocation. There is a particular unit for upskilling, they perform the
training process in a well-established way, and they manage organizational change by training and empowering people. Budget is
6.4.2. Construct validity
To overcome this threat, related to the objectivity of the constructs, the data collection was performed with different people
and different sources; the interviews were recorded and transcribed; BPs, GPs, and PAs were rated objectively using the
four-point ordinal scale of SPICE, including N.A., P.A., L.A., and F.A.;
and the results were evaluated objectively.
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6.4.3. External validity
The cases were selected from different sectors, with different
sizes, and from different countries in order to increase the generalizability of the results. As the DX-CMM has been designed
independently of the sector, it is intended to observe its applicability in different circumstances. The assessment team did not observe
any difficulty or difference during the application. The model was
first applied to The Machine Company; and subsequently the replication material was applied to The Chemical Company. It was
ensured that the replication logic was executed consistently and
resulted in similar findings and conclusions in the same or different
organizations.
and capability. The process dimension consists of 26 DX processes
defined under 4 process groups: strategic governance, digital process transformation, workforce management, and information and
technology management. The capability dimension, adapted from
SPICE, has six capability and six maturity levels.
The application and usability of the DX-CMM were verified by
the multiple case study in this study. The DX-CMM and the method
for conducting DX maturity assessment were explained, and the
results of a multiple case study analysis based on two different
organizations were given. The results of the analysis show that
the DX-CMM is capable of identifying DX maturity improvement
opportunities at different organizational DX maturity levels and
is successful at providing a guideline for moving the DX maturity
level one step further. The post-assessment survey results show
that the approach to assessment of DX maturity level and achievement of a roadmap for improvement is useful, and all suggestions
for DX maturity improvement given in the assessment reports will
improve the DX performance of the organizations. To this end, it can
be asserted that the DX-CMM proposes a baseline for starting and
sustaining a continuous improvement life cycle for DX processes in
a well-structured way. It provides an evaluation of the current state
of DX maturity in detail, and the generation of a feasible improvement guideline for moving one DX maturity level further, as well as
benchmarking organizations evaluated using the same approach.
The Machine Company has realized the importance of HR skills
improvement, while initiating DX in the company; and The Chemical Company has understood that DX is a never-ending cycle that
seeks to maintain continuous improvement.
One of the limitations of this research is generalizability, because
of the limited number of case studies. Additional case studies with
different sectors, countries, and DX adoption levels are needed to
increase generalizability. Future studies would include additional
case studies and the development of a self-assessment tool for use
by employees or organizations to evaluate themselves, observing
any weaknesses and improving DX maturity on their own.
6.4.4. Reliability
Reliability problems are related to ensuring that other people
can conduct the same study utilizing the methodology. In order to
prevent these problems, the case study protocol by Yin (Yin, 2013)
was followed to identify the objectives, RQs, design, and data collection of the case study in a structured way, and the assessment
methodology defined in the DX-CMM in detail was also followed.
Moreover, the replication material of the case study was prepared
and executed in different organizations. It was determined that
consistent outputs were produced through multiple implementations.
7. Conclusion
In this study, it was determined that none of the existing MMs
within the DX domain fully satisfied the defined criteria: publishing as an academic paper, including a detailed description of
its components, and being applicable across all sectors. None of
the existing MMs has a comprehensive and integrated approach
applicable across all sectors. Additionally, they are not developed
based on a well-established process capability maturity model,
they do not aim to improve the DX processes, and do not determine
the DX maturity level of the organization based on the capability
level of the processes. Moreover, none of them gives full details
of the model for the application or provides an action plan for
enabling maturity stage improvement. To fulfill these requirements, the DX-CMM, having a holistic and integrated approach
applicable across all sectors, was developed based on a wellestablished process capability maturity model, SPICE, by applying
the MM development framework proposed by De Bruin et al. (2005)
to assist organizations by providing current capability/maturity
determination, derivation of a gap analysis, and creation of a comprehensive roadmap. The DX-CMM, has two dimensions of process
Author statement
Ebru Gökalp: Conceptualization, Methodology, Validation, Formal analysis, Writing - Original Draft, Visualization
Veronica Martinez: Conceptualization, Writing - Review & Editing, Supervision
Appendix A
Table A7
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Table A1
The Existing MMs in DX/Smart Production/Smart Service Domain.
MM#
The MM
Dimensions
Levels
MM1
The connected enterprise maturity model
(Automation, 2014)
–
1 Assessment
2 Secure and upgraded
network and controls
3 Defined and organized
working data capital
4 Analytics
5 Collaboration
MM2
The digital maturity model 4.0 (Gill and
VanBoskirk, 2016)
- -Culture
- -Organization
- -Technology Insights
1
2
3
4
Skeptics
Adopters
Collaborators
Differentiators
MM3
IMPULS – Industrie 4.0 readiness (Lichtblau
et al., 2015)
- -Strategy and organization
-Smart factory -Smart
operations -Smart products
- -Data-driven services
- -Employees
1
2
3
4
5
6
Outsider
Beginner
Intermediate
Experienced
Expert
Top performer
MM4
A maturity model Industry 4.0 readiness
(Schumacher et al., 2016)
-
–
MM5
System integration maturity model Industry
4.0 – SIMMI 4.0 (Leyh et al., 2017, 2016)
- -Vertical Integration
- -Horizontal Integration
- -Digital Product
Development
- -Cross-Sectional Technology
Criteria
2 Basic Digitization
3 Cross-Departmental
Digitization
4 Horizontal and Vertical
Digitization
5 Full Digitization
6 Optimized Full Digitization
MM6
Industrie 4.0 maturity index – Acatech (Schuh
et al., 2017)
-
-Resources
-Information systems
-Organizational structure
-Culture
1
2
3
4
5
6
Computerization
Connectivity
Visibility
Transparency
Predictive capability
Adaptability
MM7
DREAMY – Digital readiness assessment
maturity model (De Carolis et al., 2017a, b)
-
-Process,
-Monitoring and Control,
-Technology
-Organization
1
2
3
4
5
Initial
Managed
Defined
Integrated and Interoperable
Digital-oriented
MM8
Three-stage maturity model in SMEs toward
Industry 4.0 (Ganzarain and Errasti, 2016)
- -Vision
- -Roadmap
- -Projects
1
2
3
4
5
Initial
Managed
Defined
Transform
Detailed BM
MM9
A digital maturity model for
telecommunications service providers
(Valdez-de-Leon, 2016)
-
-Strategy
-Organization
-Customer
-Technology
-Operations
-Ecosystem
-Innovation
1
2
3
4
5
6
Not started
Initiating
Enabling
Integrating
Optimizing
Pioneering
MM10
Industry 4.0 – MM (Gökalp et al., 2017; Şener
et al., 2019)
-
-Asset Management,
-Data Governance,
-Application Management,
-Process Transformation,
-Organizational Alignment
Level 0 Incomplete
Level 1 Performed
Level 2 Managed
Level 3 Established
Level 4 Predictable
Level 5 Optimizing
17
-Product
-Customers
-Operations
-Technology
-Strategy
-Leadership
-Governance
-Culture
-People
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Table A1 (Continued)
MM#
The MM
Dimensions
Levels
MM11
A smart manufacturing maturity model for
SMEs (SM3E) (Mittal et al., 2018)
-
1
2
3
4
5
MM12
DPMM 4.0 – Industry 4.0 maturity model for
the delivery process in supply chains (Asdecker
and Felch, 2018)
- -Order processing
- -Warehousing
- -Shipping
Based on SIMMI 4.0
MM13
Maturity and readiness model for Industry 4.0
strategy (Akdil et al., 2018)
-
Absence
Existence
Survival
Maturity
MM14
A preliminary maturity model for leveraging
digitalization in manufacturing (Sjödin et al.,
2018)
- -People
- -Process
- -Technology
1
2
3
4
5
6
Connected technologies
Structured data
gathering and sharing
Real-time process
analytics and optimization
Smart, predictable
manufacturing
MM15
A model for assessing the maturity of Industry
4.0 in the banking sector (Bandara et al., 2019)
-
-Products and services
-Technology and Resources
-Strategy and organisation
-Operations
-Customers
-Governance
-Employees
1
2
3
4
5
Initial
Managed
Defined
Established
Digital Oriented
MM16
IMA – Infrastructure maturity assessment
(Williams et al., 2019)
-
-Transport
-Collaboration
-Security
-Mobility
-Data Center
1
2
3
4
5
6
7
8
Administrative
Tactical
Fixed
Mobile
Externalized
Integrated
Contextualized
Orchestrated
MM17
A maturity assessment approach for
conceiving context-specific roadmaps in the
Industry 4.0 era (Colli et al., 2019, 2018)
-
-Governance
-Technology
-Connectivity
-Value creation
-Competences
1 None
2 Basic 2.Transparent 3.Aware
4.Autonomous 5.Integrated
MM18
Roadmapping toward industrial digitalization
based on an Industry 4.0 maturity model for
manufacturing enterprises (Schumacher et al.,
2019)
-
-Finance
-People
-Strategy
-Process
-Product
-Smart products and services
-Smart business processes
-Strategy
-Organization
-Technology -Products
-Customers and Partners
-Value Creation Processes
-Data & Information
-Corporate Standards
- -Employees Strategy and
Leadership
Novice
Beginner
Learner
Intermediate
Expert
–
Table A2
Capability Level 1 Assessment of Digital Transformation Strategy Development Process in The Machine Company.
Base Practices (BPs)
Rate of BP
Rate of PA 1.1
SG.SD.BP.01. Evaluate the business and market
SG.SD.BP.02. Analyze the current situation of the company
SG.SD.BP.03. Define the target situation of the company (i.e., value mapping, business model innovation)
SG.SD.BP.04. Conduct a gap analysis
SG.SD.BP.05. Define company-specific DX strategy and roadmap
SG.SD.BP.06. Communicate the DX strategy and direction with all related parties
SG.SD.BP.07. Publish the vision and strategy document
L.A.
F.A.
F.A.
L.A.
L.A.
F.A.
F.A.
L.A. (Largely Achieved)
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Table A3
Capability Level Assessments of DX Processes in The Machine Company.
Process
Digital Transformation Strategy Development
Portfolio Management
Project Management
Financial Resources and Supplier Management
IT Strategy Management
Requirement Definition
Enterprise Architecture Development
Infrastructure Management
Data Governance
Agile Software Development
Enterprise Architecture Integration
Data Analytics
Enterprise Architecture Maintenance
Security Management
Business Process Digitalization
Business Processes Vertical Integration
Business Processes Horizontal Integration
Quantitative Performance Management
Data-Driven Decision Management
Quantitative Process Improvement
Self-Optimized Decision Management
Business Process Integration Toward Product Life Cycle
HR Skills Development
Organizational Structure Management
Sustainable Learning Management
Organizational Change Management
Level 1
Level 2
PA 1.1
PA 2.1
PA 2.2
Level 3
PA 3.1
PA 3.2
L.A.
L.A.
P.A.
P.A.
P.A.
P.A.
L.A.
L.A.
L.A.
N.A.
N.A.
P.A.
N.A.
L.A.
P.A.
L.A.
P.A.
P.A.
N.A.
N.A.
N.A.
N.A.
L.A.
F.A.
P.A.
L.A.
L.A.
L.A.
–
–
–
–
–
L.A.
L.A.
–
–
–
–
L.A.
–
L.A.
–
–
–
–
–
–
L.A.
L.A.
–
L.A.
L.A.
L.A.
–
–
–
–
–
L.A.
L.A.
–
–
–
–
L.A.
–
L.A.
–
–
–
–
–
–
L.A.
L.A.
–
L.A.
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
−.
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
Process Capability
Level
Level 1
Level 1
Level 0
Level 0
Level 0
Level 0
Level 1
Level 1
Level 1
Level 0
Level 0
Level 0
Level 0
Level 1
Level 0
Level 1
Level 0
Level 0
Level 0
Level 0
Level 0
Level 0
Level 1
Level 2
Level 0
Level 1
Table A4
Capability Level Assessments of DX Processes in The Chemical Company.
Process
Digital Transformation Strategy Development
Portfolio Management
Project Management
Financial Resources and Supplier Management
IT Strategy Management
Requirement Definition
Enterprise Architecture Development
Infrastructure Management
Data Governance
Agile Software Development
Enterprise Architecture Integration
Data Analytics
Enterprise Architecture Maintenance
Security Management
Business Process Digitalization
Business Processes Vertical Integration
Business Processes Horizontal Integration
Quantitative Performance Management
Data-Driven Decision Management
Quantitative Process Improvement
Self-Optimized Decision Management
Business Process Integration Toward Product Life Cycle
HR Skills Development
Organizational Structure Management
Sustainable Learning Management
Organizational Change Management
Level 1
Level 2
PA 1.1
PA 2.1
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
Not Applicable
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
L.A.
F.A.
F.A.
F.A.
F.A.
F.A.
L.A.
P.A.
–
P.A.
–
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
Level 3
Level 4
PA 2.2
PA 3.1
PA 3.2
PA 4.1
PA 4.2
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
F.A.
L.A.
L.A.
L.A.
L.A.
L.A.
L.A.
L.A.
F.A.
F.A.
L.A.
L.A.
L.A.
L.A.
L.A.
L.A.
L.A.
F.A.
F.A.
–
–
–
–
–
–
–
P.A.
P.A.
–
–
–
–
–
–
–
P.A.
N.A.
F.A.
FA
L.A.
F.A.
F.A.
F.A.
P.A.
F.A.
F.A.
L.A.
–
–
F.A.
F.A.
F.A.
F.A.
L.A.
L.A.
L.A.
L.A.
L.A.
F.A.
–
L.A.
L.A.
–
–
–
F.A.
F.A.
F.A.
L.A.
L.A.
L.A.
L.A.
L.A.
L.A.
L.A.
–
L.A.
L.A.
–
–
–
L.A.
F.A.
F.A.
L.A.
–
–
–
–
–
–
–
–
–
–
–
–
–
L.A.
L.A.
–
–
–
–
–
–
–
–
–
–
–
–
–
–
P.A.
P.A.
–
19
Process Capability
Level
Level 3
Level 3
Level 3
Level 3
Level 3
Level 3
Level 3
Level 3
Level 3
Not Applicable
Level 3
Level 3
Level 2
Level 3
Level 3
Level 3
Level 1
Level 3
Level 3
Level 2
Level 0
Level 0
Level 3
Level 3
Level 3
Level 3
E. Gökalp and V. Martinez
Computers in Industry 132 (2021) 103522
Table A5
Example Assessment Results for Two Processes in the Machine Company.
20
E. Gökalp and V. Martinez
Computers in Industry 132 (2021) 103522
Table A6
Example Assessment Results for Two Processes in The Chemical Company.
Table A7
Abbreviations.
Abbreviation
Definition
BP
CMMI
DX
DX-CMM
Base Practice: the specific functional activities of the process
Capability Maturity Model Integration: a process level improvement training and appraisal program.
Digital Transformation: the disruptive technological achievement bringing new business and operating models.
Digital Transformation Capability Maturity Model: a model developed based on a well-established process capability
maturity model of SPICE by applying a methodological maturity model development framework to guide
organizations that wish to adopt digital transformation by providing a comprehensive, objective, consistent, and
standardized approach.
Fully Achieved: There is evidence of a complete and systematic approach to, and full achievement of, the defined
process attribute in the assessed process.
Maturity Model: a conceptual model consisting of a sequence of discrete maturity levels for a class of processes and
represents a desired evolutionary path for these processes
Largely Achieved: There is evidence of a systematic approach to, and significant achievement of, the defined process
attribute in the assessed process.
Not Achieved: There is little or no evidence of achievement of the defined process attribute in the assessed process.
Partially Achieved: There is some evidence of an approach to, and some achievement of, the defined process attribute
in the assessed process.
Process Attribute: a measurable property of process capability
Software Process Improvement and Capability dEtermination: a set of technical standards documents for the computer
software development process and related business management functions
F.A.
MM
L.A.
N.A.
P.A.
PA
SPICE also known as ISO/IEC 3300xx
21
E. Gökalp and V. Martinez
Computers in Industry 132 (2021) 103522
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