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© Санкт-Петербургский государственный университет, 2020
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
https://doi.org/10.21638/spbu05.2020.204 243
UDC: 65.011.56
JEL: O33
e framework for assessing company’s digital
transformation readiness
O. V. Stoianova, T. A. Lezina, V. V. Ivanova
St. Petersburg State University,
7–9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation
For citation:
Stoianova
O. V., Lezina T. A., Ivanоva V. V. (2020).
e framework for assessing company’s
digital transformation readiness. St Petersburg University Journal of Economic Studies, vol. 36, iss. 2,
pp. 243–265. https://doi.org/10.21638/spbu05.2020.204
At present, the focus of discussions on digital transformation has shied from issues of its
necessity to problems of assessing a company’s readiness for digital transformation. e speci-
city of digital transformation in Russia requires new criteria of readiness and prioritization
of existing criteria. is study explores a combination of factors (prerequisites) that determine
the readiness of Russian companies for digital transformation. Our hypothesis is that it is pos-
sible to systematize and formalize these prerequisites, which can be presented as a framework
for assessing readiness. e purpose of the study is to design such a framework that takes
into account not only the current state of the company, but also its previous development.
e paper formulates the requirements for the readiness assessment system in the form of a
framework. It also proposes a method of desing a framework with these requirements. e
method combines analysis of practical cases and theoretical study of modern concepts and
best management practices. As a result of applying the proposed method a framework for
a company’s readiness for digital transformation assessment (DTRA) is created. e DTRA
framework includes criteria and characteristics of readiness grouped into domains. It is in-
tended for a qualitative evaluation of readiness and for understanding obstacles to success of
the digital transformation.
Keywords: digital transformation, the company’s readiness, framework, criteria of readiness,
readiness assessment.
Introduction
e digital transformation of the economy is connected with high expectations (new
quality of services, increasing competitiveness and productivity, unique experiences, etc.)
and concerns (new professions, job loses, threats to information security, high-cost risks)
[Sebastian et al., 2017]. Digital transformation is a complex phenomenon that aects all
areas in company organization and management and in the internal and external envi-
ronment [Khan, 2016]. Misunderstanding the essence of this transformation, mistakes
in determining initial projects, and too high expectations become severe obstacles to a
company’s success.
According to international cross-sectoral research on the impact of the digital trans-
formation on company activity, conducted by analytical agency Arthur D. Little [Opitz et
al., 2015], only 15 % of companies understand digital transformation strategies and allo-
cate resources for analyses of the implementation of strategies and improvements.
244 Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
Choosing a strategy for digital transformation has crucial importance for Russian
companies. e Institute of Statistical Studies and the Knowledge Economy identied the
digitalization index of Russian businesses as 28points (Finladn is ranked highest, at 50)
[Abdrakhmanova et al., 2019]. However, this indicator characterizes the level of technol-
ogy used in business, rather than a transition to new business models. Moreover, as stated
by A. Kudrin on August 19, 2019, the following problem has emerged: about 37 % of the
national project’s “Digital Economy” funds are blocked because they have not been re-
quested [Minak, 2019].
According to the analytic report of the Digital Transformation in Russia [KMDA,
2018], only 25 % of companies are in the process of implementing digital transformation,
and only 9 % have a strategy. ese are mainly in the banking sector, IT companies, and
telecommunications. 53.2% of the 700 respondents from dierent industries noted that
the main obstacle to digital transformation is the lack of a clear strategy.
One of the reasons for this failure is the incomplete methodological base of company
management in the digital economy, including in the eld of digital transformation man-
agement. Existing models of IT management cannot be used as the basement for manag-
ing digital transformation, because they do not take into account features of the process,
which involves changing all aspects, including company management, business models,
and business processes, and not just information systems and technologies.
Recommendations about digital transformation management, oered by the schol-
arly community and by analytical and consulting companies, are usually general. ey
lack formal methods and models of solving many management problems, particularly the
problem of choosing a digital transformation strategy. Successful practices of the digital
transformation of Russian companies are still few and not consolidated to universal ap-
proaches.
Critical parameters for choosing a digital transformation strategy result from assess-
ments of the current state of the company, or rather an assessment of the company’s readi-
ness for digital transformation. e analysis of published research in this area revealed a
problem in choosing measurable readiness criteria. Most existing approaches for evaluat-
ing companies and digital transformations consider the level of digital maturity, and not
readiness (in the sense of being prepared for implementing concrete activities). Another
circumstance that exacerbates this problem is the insucient consideration of the features
of the digital transformation of Russian companies.
e results of numerous studies conrm the specicity of digital transformation in
Russia. For example, according to the PWC survey, representatives of Russian companies
identify “inexible and slow processes” (70 % of respondents versus 42 % in other coun-
tries) and “lack of integration of new and existing technologies and data” (73 % versus
59 %) as the main obstacles to digital transformation [PWC, 2018]. ese data conrm
that for Russian companies, it is necessary to use specic prioritization of criteria for as-
sessing readiness for digital transformation. is requires developing an integrated assess-
ment system that includes interrelated indicators (metrics) of expectations and strategic
goals of the company, the quality of business processes, competencies and motivation of
employees, the maturity of technological environment of the company, manageability of
information support, and a number of other characteristics.
For companies that are just starting this transformation, key questions are: how to
start and what barriers are hindering the digital transformation. ese questions relate to
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 245
the company’s readiness for digital transformation. In this study, we consider the concept
of readiness through the prism of the company’s capabilities and internal barriers to digi-
tal transformation. e eld covered by this study relates to a combination of factors (pre-
requisites) that determine the availability of Russian companies for digital transformation.
e hypothesis of research can be formulated as follows: “ere is the possibility to sys-
tematize and present in a formalized form (in the form of a framework) the prerequisites
that determine the company’s readiness for digital transformation”. e purpose of the
study is to design a framework that allows evaluating readiness and identifying barriers to
digital transformation, taking into account not only the current state of the company but
also the previous development.
Related work
Digital business transformation is widely discussed both in business and academic
literature. e results of numerous studies represent that only the synergy of business
and digital management strategies lead to success. For example, MIT Sloan Management
and Capgemini Consulting conclude that digitally mature organizations are 26 % more
protable than their average industry competitors due to their ability to combine digital
and transformational management intensity [Westerman et al., 2017]. e need for busi-
ness and IT consistency is based on the idea that new technologies introduced into an
organization should comply with its business strategy and goals [Nissen, Termer, 2015].
Moreover, some authors [Stucki, Wochner, 2019] consider the complementarity of tech-
nological and organizational capital as the key to the success of the digital transformation.
Typical barriers companies face in the transformation can be divided into two groups:
leadership and institutional [Ismail, Khater, Zaki, 2017]. Among problems of leadership is
the absence or uncertainty of a digital strategy, which turns out to be the most signicant
barrier, especially in the early stages of transformation [Kane et al., 2015]. Institutional
barriers include insucient organizational structure, lack of technical skills and invest-
ments, regulatory restrictions, the cultural gap between managers and employees, and
even psychological aspects, such as indierence to the need for transformation and fear of
change [EY, 2013; Von Leipzig et al., 2017]. ese problems are not only in the scale of the
novelty of digitalization, but rather in the company’s inability to function outside of the
familiar operating environment [Von Leipzig et al., 2017]. All these restrictions require
the company to deeply analyze its internal relations and operations, to understand the
company’s readiness for digital transformation.
Leading consulting companies Forrester, BCG, IDC, PWC, and KPMG began devel-
oping methods and models that allow assessing a company’s ability to implement digital
projects in the rst half of the current decade. As far back as 2008Forrester [Gill, Van-
Boskirk, 2017] proposed a methodology for evaluating e-business and digital marketing.
e modern version of the Forrester model is a two-level model of digital maturity fo-
cused on assessing eectiveness of implementing digital technology for realizing competi-
tive strategies. e readiness of companies for digital transformation as one indicator of
digital maturity is assessed in the areas of Vision and strategy, Talent, Culture, Technology,
and Structure (team organization). e model [BCG, 2016] allows one to evaluate a com-
pany’s orientation to changes, and to a lesser extent its current state, using such measure-
ments as digitally driven business strategies, creating new businesses and development
246 Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
directions, digitalizing customer relations, implementing digital capabilities, and trans-
forming technologies. e model [IDC, 2015] measures maturity by areas of Management
(leadership), Omni practice, labor force, operational model, and information. is model
allows companies to get a perception of the maturity level, to form a map of processes to
be optimized, and to recommend technologies. A similar approach is used by the com-
pany [PWC, 2016] to determine the level of digital maturity along six dimensions, such as
business model, processes, digital culture, compliance with laws and risks, IT architecture,
and relations with customers. e company [KPMG, 2016] evaluates the ability to use new
(digital) business, considering digital strategies, talents, exible models of infrastructure,
management, and digitalization of business processes. Notice, that all of the considered
models do not contain a comrehensive assessment of the management system: they place
emphasis on the automation/digitalization of business processes, but do not consider the
level of their connectivity and regulaition, the company’s digital culture is analyzed only
from the point of view of competencies, etc.
Not only consulting companies, but also IT industry leaders (for example, IBM), IT
communities (for example, the Open Group) and the academic community develop man-
agement and IT standarts. IT companies [Jan van Groningen, 2017] assess readiness for
transformation through the prism of technological readiness as a determining factor in
possible directions of changes (rethinking) of a business: developing competencies, using
technologies in standard activities, introducing new working methods (new quality of
customer service, exible customization to customer needs, integration with customers
based on open standards), and introducing new business models.
Using the methodology of enterprise architecture framework TOGAF, the Business
Transformation Readiness Assessment framework [e Open Group, 2018] oers a list
of readiness factors, which can be specied for any particular enterprise. A signicant
drawback of this framework is that it requires its inclusion in the general project of the
company architecture development, which is not always possible at the start of transfor-
mation projects.
e academic community, including that in Russia, also conducts active research
in assessing readiness for transformation and determining a company’s digital maturity.
Many authors emphasize the fact that existing standards provide recommendations for
changes, and are not focused on the digital nature of transformation; reference models,
including consulting models, are oen generalized [Wulf, Mettler, Brenner, 2017].
Proposed by the academic community, evaluation models are usually oriented to spe-
cic sectors or activities and contain only partly overlapping areas of readiness assessment.
However, their evaluation criteria are dierent. us, [Wulf, Mettler, Brenner, 2017] oers
to evaluate digital readiness according to seventeen criteria clustered into seven groups
(strategy, consumers, services/products, processes, management, information, technolo-
gies, and infrastructure). In turn, the DREAMY model (Digital Readiness Assessment
Maturity model) [De Carolis et al., 2017] evaluates company processes grouped in ve
areas (Design and Engineering, Production Management, Quality Management, Main-
tenance Management, Logistic, Management). Another framework [Sánchez, Zuntini,
2018], unlike others, evaluates not only internal but also external factors that determine
readiness for digital transformation: these include ecosystem collaboration, as determined
by the level of partnerships with stakeholders; the power of consumers, the force of sup-
pliers, digital products and services, industry boundaries that are changing due to new
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 247
digital capabilities, competitors (according Five Forces concept). Framework based on
Industry 4.0 concept [Schumacher, Erol, Sihn, 2016] was designed to assess the maturity
of an industrial company and contains nine dimensions: strategy, leadership, customers,
products, operations, culture, people, governance, technology.
In any case, diagnosing the state of a company to identify internal and external [Sán-
chez, Zuntini, 2018] constraints, as well as possible risks, should be a key starting point for
digital transformation. At the same time, as companies risk approaching transformation as
an IT project, a concept is needed to integrate business and IT strategy. is risk could be
overcome within the framework of the architectural approach [Dolganova, Deeva, 2019]
to building the current and target architecture of the company, dening a transformation
scenario, and ensuring smart management. Digital transformation is not recommended
to be implemented as a single project [Issa et al., 2018], so as not to lead the company to
a big failure, but to fulll it gradually, based on capability maturity, that is, alignment and
integration of business and technology.
As it is easy to see, the considered frameworks are oriented to a dierent level of
generalization. ey dier both in the object of evaluation— the eectiveness of digital
technologies in the company, readiness to change, readiness to create a new business, etc.,
and measurement/evaluation domains. Moreover, there is no consistent terminology in
the discussions on company readiness. Conducted analysis of existing solutions shows
that there are several concepts concerning company readiness for digital transformation
such as “readiness for digital transformation”, “digital readiness”, “digital maturity”, “digital
business aptitude”, and others. At the same time, the methodologies of the framework
development used by dierent authors have much in common.
e analysis and synthesis of methodologies for the development of models/frame-
works made it possible to distinguish the following stages (steps).
1. Setting objectives for the model/framework. Characteristics and limitations. On this
stage, consulting companies monitor successful projects [KPMG, 2016] to conrm
the need to design a framework or develop previously existing evaluation models
Forrester [Gill, VanBoskirk, 2017]. In the research of the academic community,
the objective of developing a framework is formed based on a constant study of
transformation problems [Schumacher, Erol, Sihn, 2016], identifying the need for
a model by the business community [Dolganova, Deeva, 2019].
2. e study of related materials.Consulting companies rely, as a rule, on their own
projects [PWC, 2016; KPMG, 2016; Gill, VanBoskirk, 2017], interviews of part-
ners [BCG, 2016]. e academic researchers [Schumacher, Erol, Sihn, 2016;
Dolganova, Deeva, 2019; Sánchez, Zuntini, 2018; Issa et al., 2018] provide analysis
of articles, analytical reports of consulting companies and IT companies. Criteria
for selecting sources corresponding to a given goal are dened, general concepts
of a future model are marked.
3. Generalization of desired concepts: levels of models/frameworks, measurements.On
this stage, through the used methodologies, the general framework of the model is
determined [Schumacher, Erol, Sihn, 2016; Dolganova, Deeva, 2019; Bibby, Dehe,
2018; De Carolis et al., 2017].
4. Consistency assessment. is stage involves verication of the model with
government programs, adopted methodologies, and standards: TOGAF
[Dolganova, Deeva, 2019], CMMI, COBIT, CBOK [Isaev, Korovkina, Tabakova,
248 Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
2016; Issa et al., 2018]; with scientic articles and analytical reports, ocial
recommendations for the implementation of Industry 4.0[Schumacher, Erol, Sihn,
2016; Bibby, Dehe, 2018]; scientic works and experience of brieng seminars
[PWC, 2016; KPMG, 2016; BCG, 2016; IDC, 2015; Gill, VanBoskirk 2017].
5. Testing (verication) on companies. On this stage, a combination of methods is
used to test the models, including analysis of cases of successful companies
[Schumacher, Erol, Sihn, 2016; Sánchez, Zuntini, 2018; Dolganova, Deeva, 2019;
Wulf, Mettler, Brenner, 2017], semi-structured interview [De Carolis et al., 2017;
Bibby, Dehe, 2018; Gill, VanBoskirk 2017; BCG, 2016; IDC, 2015; Wulf, Mettler,
Brenner, 2017], questionnaires [KPMG, 2016; PWC, 2016; Isaev, Korovkina,
Tabakova, 2016], seminars and assessment of assumptions that are built into the
logic of the case study, testing on real projects [Schumacher, Erol, Sihn, 2016;
Wulf, Mettler, Brenner, 2017].
6. Updating the model/framework and presenting results.is stage is described in all
studies of the academic community and reports of consulting agencies. Changes
are presented and justied, evaluation algorithms are specied, recommendations
for application are oered. In some cases, new versions of the Forrester models
[Gill, VanBoskirk 2017] are formed.
e identied similarity of the approaches used to the development of frameworks
does not ensure the generality of the obtained results, including the dierent purposes of
the frameworks. On the whole set of proposed solutions for assessing the company’s abil-
ity to implement digital transformation projects, in terms of the evaluation results, two
approaches can be distinguished. e rst approach (Approach A) allows dening the
company’s level of digital readiness/maturity; the second approach (Approach B) allows
assessing specic aspects of the company’s readiness for digital transformation.
As examples of Approach A we can note models/frameworks from Forrester [Gill,
VanBoskirk, 2017], BCG [BCG, 2016], IDC [IDC, 2015], Maturity Model for Assessing
Industry 4.0Readiness [Schumacher, Erol, Sihn, 2016]. Forrester identied three levels of
digital maturity: digital beginner, digital intermediate, digital advanced. e BCG frame-
work describes four stages of digital transformation (levels of digital maturity): digital
passive, digital literate, digital performer, digital leader. IDC identies ve stages of digital
transformation: digital skeptic, digital experimenter, digital competitor, digital leader, and
digital disruptor. Despite the usefulness of these models/frameworks (as well as others are
implementing the same approach) for assessing the level of a company’s digital readiness/
maturity, they are not suitable for answering the questions:
•how to start, and does the company have the required capability to move to the
next level of digital transformation;
•what are internal transition barriers?
Partially, this drawback is eliminated by the models implementing Approach B, for
example, e Digital Business Aptitude mode [KPMG, 2016] etc., which helps compa-
nies to understand how prepared they are for adopting new digital technologies, as they
propose the specic characteristics, which correspond to the key success factors of digital
transformation.
e bottleneck of the models which implement approach B is the ambiguity of evalu-
ation criteria, characteristics, and metrics. Some of the above-mentioned models, as well
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 249
as other models/frameworks for assessing readiness, contain several universal character-
istics: the availability of company’s strategy, support for changes by the company’s man-
agement, digitalization of interaction with the client, the level of automation of the com-
pany’s processes, the level of IT infrastructure, sta development, digital culture, etc. But
the meaning of these characteristics varies in dierent models. Such characteristics as
calibrated risk management [KPMG, 2016], risky, innovative solutions (tolerance of in-
novative risk) [Gill, VanBoskirk,2017], etc. are presented only in particular frameworks/
models. Moreover, in the mentioned above models/frameworks, there is no justication
for choosing the characteristics of readiness and principle for grouping them.
e analysis conrms the relevance of developing a framework that includes crite-
ria and characteristics of companies’ readiness for digital transformation and allows to
identify opportunities and obstacles based on which the choice of digital transformation
strategy can be justied.
Analysis of applicability of existing solutions for
readiness assessment by Russian companies
To understand whether the Russian specics impose additional restrictions on the
usage of existing frameworks for assessing readiness for digital transformation in domes-
tic companies, a survey of representatives of Russian companies holding senior and mid-
dle-level managers was conducted. Approximately half of the respondents were IT manag-
ers and specialists with managerial authority. e purpose of the survey was to identify
conformity between the respondents’ assessment of the company’s readiness for transfor-
mation in terms of various aspects (business processes, personnel, etc.), and evaluations
of characteristics of these aspects, according to the same respondents. A questionnaire
included questions that correlated with readiness criteria considered in the majority of ex-
isting frameworks. Questions were grouped into sections in accordance with the assessed
aspect. In each section, there was added direct question about the respondent’s assessment
of the level of preparedness of the relevant aspect [Lezina et al., 2019]. As a result, exciting
ndings were obtained. For example, among those who rated the company’s data manage-
ment level as high, about 50 % noted the absence of data architecture in the company.
Moreover, within the survey, the task was to nd out how the current level of use of
digital technologies in companies is linked with digital transformation by company rep-
resentatives. e survey results showed that among companies with a high demand for
digital transformation and a high current level of digital technology usage, only 33.33 %
consider the level of readiness for digital transformation as high, 50 % as a medium, and
11.11 % as low. 6 % of respondents could not answer the question.
e results of the survey allowed us to formulate the following conclusions.
e existing frameworks use many concepts and terms that are dierent and not al-
ways unambiguously interpreted by representatives of Russian companies. is signi-
cantly complicates the use of these frameworks and reduces the reliability of readiness
estimates obtained with their help.
e least understandable criteria and readiness characteristics are in the area of enter-
prise architecture and data management. e main reason is the dierences in the devel-
opment of company management systems in Russia and the countries— digital leaders.
250 Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
e indicated limitations of the frameworks for assessing digital readiness, along with
previously mentioned factors, such as a large number of dierent criteria and characteris-
tics of readiness, as well as the lack of justication of choosing these criteria and character-
istics, determine the relevance of developing a new framework. e business requirements
for such a framework are:
•taking into account the characteristics of Russian companies as objects of digital
transformation;
•understandability and reasonableness of the criteria and characteristics of
readiness;
•transparency of the framework structure.
Implementing these requirements will make the framework a convenient tool for in-
dependent (without the involvement of consultants) assessment of readiness for digital
transformation by Russian companies.
General description of the framework
e basis of any assessment system is evaluation criteria. Moreover, for assessment to
be reliable, criteria must satisfy the requirement of completeness, i. e., take into account all
aspects of the object, process, or phenomenon under consideration. Moreover, the more
complicated the concept, being the objects of assessment, the more dicult it is to ensure
completeness of the criteria. is is the case for readiness assessment, since the concept of
readness is vague.
To simplify the task of ensuring criteria completeness, one should resort to grouping
criteria according to some features (the basement of the grouping). e concept of a do-
main can be used to denote the idea of a group. In dierent areas of knowledge, the term
Domain is considered an area, a set, group of objects, entities, characteristics, actions,
similar in some sense. In frameworks and models, domains are used to dene the struc-
ture, ordering characteristics, or variables to make the framework/model more comfort-
able for analysis. In a well-organized framework, the domain structure should be balanced
in terms of the number of criteria for each Domain.
Another important requirement, in addition to the completeness of the criteria and
the balance of their distribution across domains, is the relevance of criteria. In the case of
a high rate of change of the object of assessment and external conditions, ensuring the rel-
evance of criteria becomes the key requirement. Relevance can be maintained in various
ways, the most obvious being the modication of the system by eliminating some criteria
and adding new ones. e main disadvantage of this method is the diculty of comparing
evaluation results in a time perspective. A gentler option is to set criteria signicance lev-
els and modify them in accordance with changing conditions. e main disadvantage of
this option is the diculty of objectively assessing signicance levels. An alternative is to
use dierent readiness characteristics within each parameter. Changing the set of charac-
teristics makes it possible to ensure the relevance of criteria system without changing the
structure. e second method is preferable since, in the framework under development, it
is planned to use readiness criteria evaluations as indicators of problems or barries.
To assess characteristics, we propose using so-called metrics— objective quantitative
estimates. For example, for the characteristic “personnel qualications”, such metrics as
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 251
“average score based on certication results”, “number of errors due to the fault of employ-
ees”, etc. can be used. However, obtaining metrics for a number of characteristics is not
always possible, due to the lack of initial data, poor data quality, etc. In such a situation,
evidence can be used— facts conrming a particular value of a given characteristic. For
example, for the same characteristic “personnel qualications”, evidence in favor of the
values “high” or “above average” is the certicate “the presence of training and develop-
ment programs for personnel in the company”.
e alignment of evidence and metrics in accordance with the characteristics that
underlie criteria grouped into domains determines the structure of the framework for
assessing company’s readiness for digital transformation (further, the Digital Transforma-
tion Readiness Assessment (DTRA) framework), which is shown in Figure1.
It is important to emphasize that the structure of the framework does not imply a
unied integral indicator of a company’s readiness for digital transformation. Its purpose
is a qualitative assessment of readiness according to the most signicant universal criteria.
Such evaluation aims to help managers understand what might prevent the success of that
transformation.
e universality of the criterion is autonomy from the type and scope of the company,
size, organizational form, and other factors.
Fig 1. e structure of the DTRA framework
252 Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
Design of the study
e framework development methodology should provide compliance with the fol-
lowing system requirements discussed above:
requirement 1. Completeness of the criteria system;
requirement 2. A balanced distribution of criteria across domains;
requirement 3. e relevance of the criteria.
e requirement of relevance can be conrmed only by analysis of practical cases of
companies that successfully implement digital transformation projects. Because there are
not a large number of successful cases among Russian companies, the case research meth-
odology does not guarantee the completeness of criteria. To conrm it, the study should
also include a theoretical analysis of modern concepts and best management practices.
Based on these prerequisites, the authors’ research method was developed; those steps are
described in Table 1.
Table 1. Research stages
Stage 1 Formulating hypotheses about framework domains
Research method Case study
Goal
To identify general trends of changes in companies before implementing the digital
transformation projects, and to formulate hypotheses about the domains of the
framework for assessing companies’ readiness for digital transformation
e subject of
research
Changes of the previous periods in the companies which implement successful
complex large-scale digital transformation projects
Information base Ocial websites of companies, press releases, publications in professional journals
and open reporting
Tasks
1. To analyze the activity incompanies for the last 5–10years.
2. To identify key areas of change for each company.
3. To identify common areas of change for all the companies and formulate
hypotheses about the framework domains.
Stage 2 Clarication of framework domains
Research method Analysis of management standards, bodies of knowledge, best practices
Goal To clarify and create rationale of the domains of the DTRA framework
e subject of
research
e content of management methodologies corresponding to each area of change
distinguished on stage 1
Information base Management standards, bodies of knowledge, etc.
Tasks
1. To analyze management methodologies corresponding to each area of change.
2. To match the changes with management tools, which can be used to guide them.
3. To create a nal list of key domains of the framework for assessing companies’
readiness for digital transformation.
Stage 3 Identication of criteria and characteristics of readiness
Research method Systematic analysis of management standards and practices
Goal To identify characteristics of the company’s readiness for digital transformation
corresponding to each domain
e subject of
research
Features of transformation management discussed in the standards corresponding
to eachdomain
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 253
Stage 3 Identication of criteria and characteristics of readiness
Information base Management standards, bodies of knowledge, etc.
Tasks
1. To analyze management standards, bodies of knowledge to distinguish best
management practices on the basis of domains
2. To create a list of typical features of transformation management by matching
them with changes of previous periods in companies identied in stage 1and to
formulate hypotheses about characteristics of readiness
Stage 4 Verication of readiness criteria and characteristics
Research method Case study
Goal To verify characteristics obtained on the previous stage
e subject of
research
Changes of previous periods in engineering companies implementing successful
digital transformation projects(a set of companies diers from the set of
companies used on stage 1)
Information base Ocial company websites, press releases, publications in professional journals, and
open reporting
Tasks
1. To match distinguished on previous stage characteristics of readinesswith
changes in the companies over the last 5–10years.
2. To identifytypical characteristics presented in most cases and create a veried
list of readiness characteristics.
Stages 1and 4use case studies of successful companies that are implementing com-
plex, large-scale projects of digital transformation. Companies embarking on similar proj-
ects have demonstrated their readiness for digital transformation and have gone through
digital reinvention.
e study was conducted under the following limitations:
•digital leaders (banks) and IT companies were excluded from consideration, as
their high readiness for digital transformation can be explained by the specics of
their activities;
•the research doesn’t regard the aspect of readiness concerning the company’s
hardware and soware assets, because the experience of Russian companies shows
that this kind of gap is not a barrier to digital transformation.
Several examples explain the last limitation. In 2015, the company Russian Post had
the following problems [Russian Post, 2019]: old technologies, a “patchwork” automa-
tion of business processes, absence of systems for planning and optimizing logistics ows,
sales support systems, customer databases, etc. In 2017, Russian Post received the CNEW
AWARDS in the digital transformation category. e company implemented the following
projects of digital transformation: deploying a unied automated system of post oces,
launching centralized accounting systems based on Data lake methodology, and imple-
menting a computerized information system in more than 1050regional sorting units.
Several successful digital transformation projects in industries with intense technological
weakness (e.g., mechanical engineering) conrm that the low quality of hardware and
soware assets is not a key barrier for digital transformation. It is important to note that
the purchase of hardware and soware does not guarantee digital transformation success:
there are examples of failures of digital transformation, despite signicant investments in
technology.
254 Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
Results
Results ofstage 1. Formation of a hypothesis about the framework domains
Case study 1was conducted to formulate a hypothesis about the DTRA framework
domains. e objects of research in Case study 1are industrial companies— digital lead-
ers:
•NPO Energomash JSO (mechanical engineering);
•Cherkizovo Group PJSC (food industry);
•Gazpromne PJSC (fuel and energy);
•Sportmaster LLC (textile&retail);
•Russian helicopters (mechanical engineering);
•FSUE Russian Post.
e companies belong to dierent industries, and some of them, such as Russian
Post, had a strong technological backlog at the beginning of the digital transformation.
e subject of study is the changes in companies that preceded successful digital
transformation projects.
e results of the analysis allow identifying common areas of changes, preceding the
implementation of the digital transformation projects such as management system, busi-
ness processes, human resources, and technologies. To illustrate the results, Table 2pro-
vides a comparison of the presented cases. It contains the practices (projects) of digital
transformation and key changes preceding the digital transformation in each company
grouped according to the distinguished areas.
e distribution of changes by distinguished areas (as a percentage of the total num-
ber of changes), calculated on case-study data, is shown in Figure 2.
23,4
18,8
15,6
40,3
1,9
Management system
Business processes
Human resources
Technologies
Other
A percentage of changes by areas in the total number of changes, %
Fig.2. Distribution of changes by areas
Note the asymmetry of the obtained structure, in which the technology eld includes
a signicantly higher number of changes compared to all the others. is circumstance,
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 255
Table 2. Key changes preceding digital transformation
Management system Business processes Human resources Technologies
NPO Energomash JSO [NPO Energomash JSO, 2019]. Project: “Ensuring digitalization of complex
multi-stage production of the enterprise”
— e research and
technical council has
been established;
— a unied risk
management policy
has been introduced;
— to coordinate
production load,
cooperation
between the holding
companies has been
organized;
— a quality assurance
policy has been
documented.
— Business processes
have been organized
according to common
standards at all
enterprises of the
holding;
— more than
700business
processes at one of
the enterprises have
been automated.
— Support programs for
young professionals
have been
implemented;
— “School Personnel
reserve”, the
“Schoolmaster”, etc.,
have been established;
— the Centre of Dual
Education started
functioning.
— ERP for management
integration is being
implemented;
— the system of
navigation control of
the equipment has
been developed;
— the corporate portal
has been created;
— digitization of
design and technical
documentation has
begun;
— PLM system
modules have been
implemented.
Cherkizovo Group PJSC [Cherkizovo Group PJSC, 2019]. Projects: robotic plant for producing smoked
sausages, data processing center
— A vertically
integrated system
of four business
segments has been
implemented;
— the company follows
the approach of
cascading strategic
(measurable) goals.
— Business processes
in all companies of
the group have been
unied;
— all lifecycle processes
have been automated;
— the sales network,
supervisors and
merchandisers have
been automated.
— A study of employee
engagement has been
conducted;
— the model
of corporate
management
competencies has
been created;
— a social platform
based on SFA
exchange between
employees of all levels
has been launched.
— Unied corporate
service helpdesk has
been implemented;
— a robotic plant for
producing smoked
sausage (Industry 4.0)
has been launched;
— a geographically
distributed data stor-
age system has been
implemented.
Gazprom Ne PJSC [Gazprom Ne PJSC, 2019]. Projects: soware and hardware complex
“Digital substation”, data management system
— A vertically
integrated company
management system
has been formed;
— the Directorate
for digital
transformation has
been created;
— digital technology
centers have been
created.
— Process chain
management system
based on real-
time data has been
implemented;
— business processes of
branches have been
automated;
— coordination of
business processes
using cloud
technologies has been
implemented.
— “Corporate
University” is
functioning
— competence centers
have been created;
— the system of training
of students of leading
universities is
functioning;
— a system of
scholarships for
students has been
implemented.
— A data management
system based on
the Lake data
methodology is being
formed;
— ERP system has been
implemented;
— digital tools for col-
lective process de-
velopment and data
analysis are being
implemented.
256 Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
namely the violation of the systemic requirement of a balanced distribution of criteria by
domains (requirement 2), indicates the need for additional research to clarify the possibil-
ity of using these areas as domains of the readiness assessment framework.
Sportmaster LLC [Sportmaster LLC, 2019]. Projects: “Cross-docking at entry points”; “Strategic Omni-
channel Communications Planning”
— e company’s
management system
based on strategic
goals has been
implemented;
— functional analysis
and formation
of electronic
sales channel
management
system has been
implemented.
— Optimization and
automation of
business processes of
return logistics has
been carried out;
— business processes in
the budgeting system
has been optimized;
— the system for
complex automation
and control of
business processes’
eciency has been
implemented.
— e company’s
“Distance Education”
project was
mentioned among
the top 3in the
nomination of “Best
e-learning project in
the company”;
— the transformation
of the “Distance
education” system
into a knowledge
management system;
— an online tool for
planning training has
been implemented.
— e Oracle data
backup complex
(Zero data
loss recovery
appliance) has been
implemented;
— the project “Return
logistics” on the
automation of return
logistics processes in
the retail chains of the
group was started;
— the data center
certied by
international
standards has been
launched.
Russian helicopters [Russian helicopters, 2019]. Project: a unied information platform for all enterprises
of the holding, a concept for the development of “digital production”
— A policy to improve
business eciency
has been developed;
— the product life
cycle management
system has been
implemented;
— production planning
and monitoring
systems have been
deployed.
— Automation of
paperless production
processes has been
launched.
— automation of
design processes,
technological
preparation of
production,
manufacturing of
products have been
implemented.
— e corporate
university began
functioning;
— the system of training
of students of leading
universities is
functioning.
— e ERP system has
been implemented;
— end-to-end use of
“digital” data in the
entire process chain
(from develop-
ing a 3D model to
controlling nished
products) has been
introduced.
Russian post [Russian Post, 2019]. Projects: unied automated system of post oces, centralized
accounting systems, integrated data processing center
— e centralization
of accounting and
management work
took place;
— a new organizational
structure has been
implemented;
— a unied IT service
management system
has been created.
— Internal business
processeshave been
transformed;
— subscription online
agency serving
1000publishing
houses without
intermediaries has
been launched.
— e human resource
management
system has been
implemented;
— professional skill
competitions are
held.
— Two projects for the
integrated automa-
tization of nancial
and business activi-
ties have been imple-
mented;
— a unied corporate
data transmission
network has been
created.
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 257
Results of stage 2. Clarication of the framework domains
To characterize the areas of change and create rationale of the framework domains,
analysis of management standards, bodies of knowledge, best practice, etc. (further, stan-
dards & practices), corresponding to each distinguished area of change, was carried out.
e procedure of analysis included the following four steps.
1. Choosing standards & practices corresponding to areas of change.
2. Analysis of standards & practices and choice of recommendations to manage
changes in each area.
3. Identication of standards & practices to be included in the analysis, in case there
are groups of changes that do not correspond to any item from the set, created in
the rst step. Analysis of these standards & practices.
4. Creation of the list of domains by clarication, narrowing, splitting areas of
changes based on the results of analysis of standards & practices.
e procedure and results of clarifying the framework domains are illustrated in Fig-
ure 3.
Fig. 3. Transition from the areas of changes to the domains of the DTRA framework
e area “Management System” was narrowed to the “Systematic management” do-
main, as the systematic factor was dominant in all the observed changes.
e changes in business processes that cover standardization, unication, and opti-
mization were grouped into the “Business processes” area, while changes related to im-
plementing complex automation progects associated with the eld “Technologies” (see
Table2). Such allocation is ambiguous becouse these progects oen aim to the optimiza-
tion of businessprocesses through automation. In the readiness assessment framework, a
domain “ Maturity of business processes” is allocated to avoid such ambiguity. It includes,
among others, the “automation of business processes” criteerion. is solution is proved
by management standards & practices [BPM CBOK, 2013; SEI, 2010], which consider
automation as one of the aspects of business processes maturity.
e area “Human Resources” was transformed into the “Corporate culture” domain,
as the analysis of standards and best practices in the sphere of human resource manage-
ment [TMI-ETMS, 2017; Deloitte, 2019] allowed classifying signicant changes as ele-
ments of the corporate culture.
258 Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
23,8
24,5
15,9
14,6
21,2
Management
system
Business
processes
Human resources
Using of data
Enterprise
architecture
A percentage of changes by domains in the total number of changes, %
Fig.4. Distribution of changes by domains
e “Technologies” area turned out to be heterogeneous: it includes changes related
to both purely technological innovations and IT management elds.
Analysis of management standards related to these elds (standards and bodies of
knowledge of IT management [TSO, 2011; ISACA, 2012; e Open Group, 2016], enter-
prise architecture management [e Open Group, 2018], and data management [Earley,
2017;Gwen, 2006] allowed distinguishing the domains “Using of data” and “Enterprise
architecture” from the “Technologies” area. e distribution of changes (analyzed in the
case-study) by these domains is shown in Figure 4.
e results presented in Figure 4allow to conclude that the proposed domain sys-
tem ensures the fulllment of requirement 2: a balanced distribution of criteria across
domains.
Results of stage 3. Identication of criteria and characteristics of readiness
e goal of research on this stage is to identify the criteria and characteristics of the
company’s readiness for digital transformation related to each domain.
e study is based on the assumption that changes implemented in companies in
the period preceding digital transformation are the prerequisites for the success of digital
transformation, as they have led to improvements in the quality of management in dier-
ent areas, so “characteristics of management quality in the context of each domain can be
considered as characteristics of companies’ readiness for digital transformation”.
e results obtained on this stage are key criteria and characteristics of “high-quality
management” through the prism of domains, and a list of criteria and characteristics nar-
rowed by the generalized typical changes identied in the case study 1.
For example, an analysis of BPM, CBOK and ITIL as standards & practices related to
the “Maturity of business processes” domain, in particular the subject of Business Process
Eciency Management, Process Design, Process Transformation, Building a Process-Ori-
ented Organization, BPMS use, allows identifying the following key criteria and charac-
teristics of “high quality management”:
•BPMS is implemented; a signicant part of the activity is carried out in the BPM
operating environment using BPMS;
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 259
•inherited and acquired/leased information systems are integrated with BPMS;
•IT can create a exible performance measurement system;
•process eciency is measured: 1)close to real-time for operational management;
and 2)for the needs of business intelligence;
•a system of metrics is described: what to measure, how to measure, whether it is
normative and responsible;
•the coverage of measurement segments is dened: Operational eciency, Finance,
Legislation, Problem identication, and Consumer experience;
•the processes are decomposed into sub-processes and divided into actions and
workows concerning the company’s divisions;
•organizational rules are established; processes are planned; process descriptions
are approved;
•formal cross-functional process models are used;
•a system of indicators of cross-functional processes is built.
All listed aspects can be integrated into the following proposed readiness criteria:
•business processes standardization;
•business processes integration;
•automation of business processes;
•control of business processes.
e results of standards & practices analysis allow the DTRA framework to provide
the requirement “e completeness of the criteria system” (requirement 1).
Results of stage 4. Verication of readiness criteria and characteristics
e objects of the research in case study 2are engineering companies (C1–C9) that
are currently implementing successful digital transformation projects. As it was men-
tioned above, mechanical engineering companies conrm the possibility of successful
digital transformation in spite of strong technological gap.
С1. KAMAZ PJSC: one single production base incorporates the overall truck manu-
facturing cycle, beginning from design, manufacture, vehicle and component assembly,
and ending up with the sales of nished products and service backup (https://kamaz.ru/).
С2. UEC-Saturn PJSC: engine-building company, specialized in research and devel-
opment, production, marketing and sales, aer-sale services of gas-turbine engines (and
power plants/units) for aviation, power-generating and gas-pumping plants, ships, on-
shore, and o-shore industrial facilities (http://www.npo-saturn.ru).
С3.Novocherkassk Electric Locomotive Plant: the largest Russian manufacturer elec-
tric locomotives (https://www.nevz.com/).
С4. United shipbuilding Corporation: the largest shipbuilding company in Russia
(https://www.aoosk.ru/).
С5. Moscow Machine-Building Plant “Vpered”: production of tail rotor blades and
rotor blades for helicopters of Mi series (http://mmz-vpered.ru/).
С6. Machine-Building Factory of Podolsk JSC: designs, engineers and fabricates
steam and hot-water boilers of various types for thermal power plants (http://www.po-
dolskmash.ru/).
260 Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
С7. PSJC “Sukhoi Company”: development, production, training of ight personnel,
aer-sales service for combat and civil aircras (https://www.sukhoi.org).
С8. Shvabe: development and serial production of optical and laser systems and com-
plexes, modern optical materials and technologies, high technology medical equipment,
aerospace monitoring and remote sensing systems of the Earth, scientic research instru-
ments, energy-saving lighting equipment, nanomechanics (http://shvabe.com).
С9. KEMP JSC: production of machines and equipment for civil application: multi-
functional frontal loaders, trailed and truck-mounted liers, hydrostatic transmissions,
and hydraulic platforms (http://www.kemz.org/).
e subject of research is the changes implemented in companies in the period
preceding digital transformation. e aim of the analysis is to determine whether these
changes conrm the selected at the previous stage criteria and characteristics.
e nal list of criteria of a company’s digital transformation readiness as the result
of the verication and aggregation of initial list of readiness criteria obtained on the stage
3(for each domain) is presented in Table3. Example of characteristic of Systematic man-
agement domain is shown in Table4.
Table 3. Criteria of the company’s readiness for digital transformation
Domain Criteria
Systematic management
Management coherence
High quality feedback in management system
Change management eectiveness
Enterprise architecture Involvement of CIOs, CDOs in strategic management
Eciency of IT within the company
Using of data Understanding the value of data
Implementation of the data management system
Maturity of business processes
Business processes standardization
Business processes integration
Automation of business processes
Control ofbusiness processes
Corporate culture
Personnel motivation for changes
Support for initiatives and development of employees
Employees’ ability to learn
Table 4. Characteristics of the company’s readiness for digital transformation
Criteria Characteristic
Management coherence
— Vertical consistency of goals, objectives, plans, and actions
(from strategic to operational level)
— Horizontal consistency of goals, objectives, plans, and
actions (between functional areas, departments)
High-quality feedback in the
management system
— Quality of feedback within the company
— Quality of feedback with partners and customers
Change management eectiveness
— Speed of implementation of various (not only digital)
changes in the company
— Completeness of changes
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 261
1,50
14,00
3,00
9,00
7,50
4,00
4,00
11,00
7,00
8,50
11,25
12,25
7,00
Business process standartization
Automation of business processes
Business process integration
Implementation of data management system
Understanding the value of data
Management coherence
Change management effectiveness
High quality feedback in management system
Involvment of CIO, CDO in strategic management
Efficiency of IT within the company
Personall motivation for changes
Support for the initiative and development of
employees
Employee ability to learn
Maturity of
business processess
Using of
data
Systematic
management
Enterprise
rchitecture Corporate culture
A percentage of pieces of evidence by criterion, %
Fig. 5. e distribution of evidence by criterion
Figure 5presents the distribution of pieces of evidence from the cases C1–C9exam-
ined for all proposed readiness criteria. ese results conrm the relevance of the selected
criteria for assessing readiness. In all the cases examined, there is evidence of the proposed
criteria. erefore, the framework satises the system requirement “e relevance of the
criteria” (requirement 3).
It should be noted that changes implemented in the company can lead to improving
the characteristics related to dierent domains. is signicantly complicates the struc-
ture of the framework for assessing companies’ digital transformation readiness.
Conclusion
e key questions for companies that have only started transformations are how
to start and what barriers prevent digital transformation. ese questions concern the
company’s readiness for digital transformation, focusing on its capabilities and internal
barriers.
e analysis of existing solutions for assessing readiness for digital transformation,
proposed by consulting companies and the academic community, revealed an absence of
consensus on criteria and characteristics of readiness, as well as justications for proposed
criteria and characteristics in most reviewed works. e lack of clarity creates a problem
262 Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2
in choosing a readiness assessment tool that most closely matches needs. As a result, this
slows down or prevents the formation of a digital transformation strategy. Moreover, as
demonstrated by the survey, some considered criteria in existing frameworks are not al-
ways denitely interpreted by representatives of Russian companies. is complicates the
use of these frameworks and reduces condence in the results of an assessment.
ese reasons have resulted in the development of a new readiness assessment frame-
work that meets the following business requirements:
•taking into account characteristics of Russian companies as objects of digital
transformation;
•understandability and validity of criteria and characteristics of readiness;
•transparency of the framework structure.
Implementation of these requirements permits positioning the framework as a con-
venient and understandable tool for digital transformation readiness self-assessment by
Russian companies.
In addition to business requirements during the research process, the following sys-
tem requirements were formulated for the framework as a tool that ensures the reliability
of the obtained estimates:
•completeness of criteria;
•a balanced distribution of criteria by domains;
•the relevance of the criteria.
In support of compliance with these requirements, an author’s method of designing a
framework was proposed. e method combines the analysis of practical cases of compa-
nies that successfully implement digital transformation projects and theoretical study of
modern concepts and best management practices.
As a result of this method, the DTRA framework for assessing company readiness for
digital transformation was developed, which includes criteria and characteristics grouped
into the domains “Systematic management”, “Enterprise architecture”, “Using data”, “Ma-
turity of business processes”, and “Corporate culture”. e criteria are universal, they do
not depend on the type and scope of the company, its size, etc. However, industry pecu-
liarities can be taken into account. For each enterprise, there are critical resources and
success factors, which relate to specic domains. Such domains need to be investigated
more deeply, by specifying, and decomposing characteristics.
e framework is intended for a qualitative assessment of readiness and the develop-
ment of the company’s management understanding of what may hinder the success of the
digital transformation.
To enhance the validity of the ndings, further research could include a broader case
sample. To improve the applicability and practical contributions of this study, new re-
search will focus on selecting metrics for readiness characteristics and developing evalu-
ation algorithms. Another question that requires additional research is whether the pro-
posed framework can be applied to companies in advanced economies— the leaders of
digital transformation.
is paper is an initial step towards creating a sophisticated model for assessing a
company’s digital transformation readiness, which includes criteria, characteristics, met-
rics, and evaluating algorithms.
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 263
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Received: 01.12.2019
Accepted: 20.02.2020
Au th or s’ i nf or ma ti on:
Olga V. Stoianova— Dr. Sci. in Technics, Associate Professor; o.stoyanova@spbu.ru
Tatiana A. Lezina— PhD in Physics and Mathematics, Associate Professor; t.lezina@spbu.ru
Victoriia V. Ivanova— PhD in Economics, Associate Professor; v.ivanova@spbu.ru
Вестник СПбГУ. Экономика. 2020. Т. 36. Вып. 2 265
Фреймворк для оценки готовности компании кцифровой трансформации
О. В. Стоянова, Т. А. Лёзина, В. В. Иванова
Санкт-Петербургский государственный университет,
Российская Федерация, 199034, Санкт-Петербург, Университетская наб., 7–9
Для цитирования: Stoianova O. V., Lezina T. A., Ivanоva V. V. (2020). e framework for assessing
company’s digital transformation readiness.
Вестник Санкт-Петербургского университета. Эко
номи-
ка. Т.36. Вып. 2. С. 243–265. https://doi.org/10.21638/spbu05.2020.204
В настоящее время акцент вдискуссиях оцифровой трансформации сместился соб-
суждения ее необходимости на проблемы оценки готовности компаний кцифровым
преобразованиям. Для российских компаний, ввиду специфики цифровой трансфор-
мации вРоссии, необходима разработка новых иприоритезация существующих кри-
териев готовности. Это требует создания комплексной системы оценивания, включа-
ющей множество взаимосвязанных показателей, характеризующих ожидания истра-
тегические цели компании, качество бизнес-процессов, компетенции и мотивацию
сотрудников, зрелость технологической среды компании, управление информацион-
ным обеспечением идр. Область, охватываемая данным исследованием, касается сово-
купности факторов (предпосылок), определяющих готовность российских компаний
кцифровой трансформации. Согласно гипотезе исследования, эти предпосылки могут
быть систематизированы ввиде фреймворка для оценки готовности компании кциф-
ровой трансформации. Цель исследования— спроектировать фреймворк, позволяю-
щий оценить готовность компании, учитывая не только текущее состояние компании,
ноиее предыдущее развитие. Вработе сформулированы требования ксистеме оцен-
ке готовности, представленной ввиде фреймворка, ипредложен авторский метод его
проектирования в соответствии с требованиями, сочетающий анализ практических
кейсов компаний и теоретический анализ современных концепций и лучших прак-
тик менеджмента. Врезультате применения предложенного метода создан фреймворк
Digital Transformation Readiness Assessment для оценки готовности компании кцифро-
вой трансформации. Он включает критерии ихарактеристики готовности, сгруппи-
рованные в домены. Фреймворк предназначен для качественной оценки готовности
иформирования уменеджмента компании понимания того, что может препятствовать
успеху цифровой трансформации.
Ключевые слова: цифровая трансформация, готовность компании, фреймворк, крите-
рии готовности, оценка готовности.
Статья поступила вредакцию: 01.12.2019
Статья рекомендована впечать: 20.02.2020
Контактная информация:
Стоянова Ольга Владимировна— д-р техн. наук, доц.; o.stoyanova@spbu.ru
Лёзина Татьяна Андреевна— канд. физ.-мат. наук, доц.; t.lezina@spbu.ru
Иванова Виктория Валерьевна— канд. экон. наук, доц.; v.ivanova@spbu.ru