Tool Development for Assessing the Strategic Development of Territorial Socio-Economic Systems for the Purposes of Energy Sector Digital Transformation

Abstract

This article addresses the issue of implementing and assessing the readiness of territorial and economic systems for digital innovations in the energy industry. To achieve the goal of this research, qualitative and quantitative methods were used, including systemic and comparative analyses, a balanced scorecard (BSC), and statistical data collection and processing methods. The study resulted in a list of indicators for monitoring the readiness of the energy sector for digitization, based on which a balanced scorecard reflecting the readiness of the energy industry in countries and regional industrial complexes (RICs) was developed. A strategic map for assessing the level of readiness of the power industry for digitisation in countries and RICs was constructed using the indicator pool. The uniqueness and novelty of this study lie in the adaptation of a balanced scorecard system, aligned with a country’s or RIC’s development strategy, to determine indicators for assessing the readiness level of the considered entity for digitising the power industry. The authors establish an approach to the overall assessment and subsequent monitoring of the energy industry’s readiness for digitisation in countries worldwide and RICs.

1. Introduction

In the context of the global trend towards digitisation, the question of digitalisation in the energy industry becomes highly relevant. Research in the field of information development for the energy complex is referred to as “smart energy”. Digital energy is considered a key part of the future digital economy [1]. Its essence lies in the creation and development of new products and economic relationships based on digital approaches and tools. The main goal of digital energy is to significantly reduce the growing integration costs of distributed energy and market transactions [2]. Digital transformation in the energy sector primarily involves creating new business models based on the capabilities of the digital economy [3] across all three sectors of the fuel and energy complex: the fuel industry, power generation, and fuel and product transportation, heat, and electricity. The main goal of digital transformation in the electricity sector is to increase power supply reliability, limit the growth of electricity prices, and develop new interaction formats (services) with consumers. The main objective is to create smart grids that enable the efficient and environmentally friendly distribution of electricity to consumers. Digital technologies offer new opportunities and benefits for the power industry, such as the increased stability of energy systems, prospects for expanding the use of distributed generation—including renewable energy sources—and improved monitoring and control systems for equipment and facilities to reduce accidents and annual electricity losses [4]. In today’s world, a global energy transition or global energy transformation is taking place. The introduction of new digital technologies and solutions, from “green” energy and next-generation nuclear reactors to intelligent smart grids and the use of Internet of Things (IoT) technologies as consumer services, is driving an increased investment in R&D in this industry and the need for various other developments [5].

Domestic and foreign studies have focused on various directions of energy development and the emergence of new technologies that contribute to the digitalisation of energy. Kholkin and Chausov [6] and Knyaginina [7] reported that, compared with the coal and oil industries, the electric power industry is the most flexible and capable of digital transition. They claimed that the development of the electric power industry is based on the theory of the Internet of Energy (IoE), an energy supply organisation that unites producers and consumers into one system for energy exchange.

The complete transformation of the electric power industry can be represented by the concept of the three Ds (decarbonisation, decentralisation, and digitalisation). Decarbonisation is the transformation of the energy industry manifested in the reduction of environmental damage due to carbon emissions into the environment. The development of decarbonisation is facilitated by an increase in the share of renewable energy sources in the energy balance and the use of electric transport. Decentralisation is the spread of distributed electric power with increases in the use of various generators and small distributed energy. The emergence of consumers producing and consuming electricity (prosumers, who both consume and produce) and the participation of active consumers who can afford to change their level of electricity consumption in the network contribute to the development of decentralisation. Digitalisation is the spread of the use of various digital devices connected to the internet during the entire process of electricity production, from generation to delivery to end users. This factor enables the control of entire power systems at the level of intelligence in the future [8].

Verma et al. [9] and Grabchak [10] described the main technologies listed in

Table 1. Comparison of energy digitalisation technologies.

Technologies	The Possibility of Predictive Analytics	Cost Reduction	The Possibility of Training	The Possibility of Conducting Experiments
Big data	Yes	Yes	No	Yes
Augmented and virtual reality (AR/VR)	No	No	Yes	Yes
Digitisation of business processes	Yes	Yes	Yes	No
Cloud computing	Yes	Yes	No	No
Internet of Things (IoT)	Yes	Yes	No	No
Digital twins	Yes	Yes	Yes	Yes

, the introduction of which has contributed to the digitalisation of the electric power industry. A comparison of the main technologies according to four criteria is presented in the Table 1.

Innovative developments, according to the authors, provide an ‘impetus’ to companies engaged in energy generation and distribution, suppliers, and other entities that need electricity to create and test new models that, in faster lines, efficiently distribute, generate, and deliver electricity.

In Russia, the digital transformation of the electric power industry is carried out by the Ministry of Energy and the association ‘Digital Energy’. Owing to digitalisation, reduced power supply disruptions, improved technical conditions in main production facilities, and reduced accidents in electric power facilities are expected. Digitalisation opens up new opportunities for energy companies to increase their business efficiency (profitability), such as the development of new areas to increase revenue, reduce current operating costs, and increase productivity. The digitalisation of the electric power industry is quite an interesting and promising area of development. However, at the moment, no real and interesting examples of the use of innovative technologies exist. A monitoring system would help to keep a close watch on the effectiveness of innovative technologies being used at all stages of their life cycle.

Digitalisation revolutionises the energy sector, increasing the productivity, safety, accessibility, and overall sustainability of energy systems [11]. New, smarter ways of modelling, monitoring, analysing, and forecasting energy production and consumption contribute to the transition to sustainable energy [12]. Digitalisation implies structural transformation in many industries, including the energy sector [13]. It also allows new market players to enter the energy sector [14].

In discussions about developing and implementing digital technologies, the term digital readiness is often used. First, readiness indicates the ability of the system to undergo changes. As readiness is a rather complex (general) concept, it is necessary to identify the types (directions) of readiness for digitalisation in socio-economic systems (country, region, RIC, etc.). However, such a classification system has not been reported in previous scientific articles.

In this regard, we propose the following classifications of readiness for digitalisation:

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Technological (‘electricity generation’ projection);

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Functional (‘learning and innovation’ projection);

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Economic (‘finance’ projection);

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Institutional (‘regulation and provision of energy’ projection); and

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Socio-ecological (‘energy security and sustainability’ projection).

The readiness of countries to introduce and study digital technologies as a key factor of economic transformation is assessed by the Center for the Study of World Competitiveness of the International Institute for Management Development, which compiles annual ratings of digital competitiveness according to the World Digital Competitiveness Ranking [15]. This digital competitiveness rating is used to evaluate the ability of an economy to introduce and master digital technologies, which leads to the transformation of government practices, business models, and society as a whole. The rating methodology determines digital competitiveness through three main factors. One factor is knowledge, which includes indicators such as talent, training and education, and scientific potential. The second factor is technology, which includes the following sub-factors: regulatory framework, capital, and technological infrastructure. The third factor is readiness for the future, which includes sub-factors such as the integration of information technology, business flexibility, and adaptability to change.

The digital competitiveness rating takes into account a country’s readiness to introduce digital technologies, but not indicators related to the population and customers. In this article, researchers are advised to take into account the willingness of a population to use digital technologies. Moreover, in the considered rating, the economic part is represented by investments, and the economic development of a territory/region is not considered. However, the key difference in the research presented in this article is the focus on the energy industry, that is, on determining the readiness of the energy sector for digitalisation. We will consider the term digitalisation as the readiness to implement innovative systems and advanced digital practices. In the context of the ‘digital readiness of a country/region/industry/enterprise’ in relation to energy, we understand this as the ability to respond positively and benefit from the digitalisation of the energy system.

Based on the selected projections, we can formulate our own definition of readiness for digitalisation in the energy sector. Readiness for digitalisation in the energy sector is the level of the current state of territorial socio-economic systems in five areas of development: technological, functional, economic, institutional, and socio-ecological in the context of the introduction of digital technologies to the energy complex. Technological readiness indicates the current level of technology development and the possibility of switching to environmentally friendly types of generation. Functional readiness indicates the current level of staff qualification and innovation activity, as well as the possibility of obtaining additional effects from the introduction of digital technologies to the industry. Economic readiness is associated with the current level of economic development and the possibility of obtaining additional effects from the introduction of digital technologies, including a reduction in the energy intensity of a country’s economy/production and an increase investment attractiveness. Institutional readiness reflects the current level of development in institutions and their regulatory framework, as well as the availability of state support measures, including those that increase the availability of electricity. Socio-ecological readiness reflects the current state of a system, in which there is a need and opportunity to improve the environmental sustainability, reliability, and quality of its energy supply. Thus, if a country/RIC is ready for digitalisation in the energy sector, improving the efficiency of electric power complex enterprises and improving the quality of services will contribute to the effective functioning of socio-economic systems, reducing energy costs, and reducing environmental damage to the environment.

A country’s readiness for the digitalisation of energy can be determined by assessing the country’s readiness for an energy transition itself and by demonstrating the dependence and influence of energy digitalisation indicators on the indicators of enterprises and industries. It is impossible to ignore the impact of industry indicators on a country’s indicators and vice versa.

To assess the transition of a country’s energy industry to a new level, the following market and technological trends should be considered:

• The emergence of an increasing number of advanced consumers who actively participate in the production of goods that they, themselves, consume. (In Russia, electricity consumers are allowed to sell up to 15 kW of electricity to a common network.)
• The emergence of smart contracts involving new financial technologies that allow for direct settlements between electricity generators and consumers (which occurred in Russia at the end of 2019).
• A trend towards the decentralisation of the electricity supply (reductions in the energy component of the cost of production) due to the ease of maintenance of SDE (small distributed energy based on natural gas and renewable energy sources (RES)) facilities and the annual growth of tariffs outpacing the rate of inflation for consumers.
• The development and distribution of digital intelligent control systems for the active energy complex, which automatically solve all operational and technical management tasks and manage energy regimes.

In the context of global energy trends and a dynamically changing environment, it is important to understand and clearly identify the readiness of each country (a specific territorial entity (city or urban agglomeration or locality)) for large-scale ‘digital’ transformations, especially in the energy sector. Therefore, the purpose of this study was to develop a system of indicators for assessing the level of readiness of countries for the potential digitalisation of the energy industry. The developed system of indicators will allow for not only the assessment of a country’s readiness for digitalisation but also the tracking of progress and the monitoring of the implementation of the national project ‘Digital Economy’ in the field of energy.

Instead of considering regions, industries, and enterprises separately, in this study, we propose paying attention to the country as a macro-level system and its regional industrial complex (RIC) as a meso-level system. By studying the RIC, we can understand the totality of the economic entities of various branches of production as independently conducting their activities within a certain territory and as an integral part of the regional socio-economic system, producing means of labour and consumer goods and having a single system and management mechanism [16]. In this article, indicators of the readiness of an RIC for the digitalisation of energy reflect both the readiness of a certain territorial system and its industries. The indicators show possible directions for increasing a country’s readiness for the digitalisation of the energy sector at these levels.

Digital technologies increase the efficiency and reliability of energy systems and, as a result, affect the economy. Therefore, it is necessary to develop a system of indicators that can best assess the readiness of a country and its RIC for the digitalisation of energy. Therefore, it is relevant and necessary to systematise all available indicators for further research to assess the readiness of a certain country and its RIC for digitalisation, which was the purpose of this work.

2. Literature Review

Currently, much attention has been paid to the identification and study of indicators that can be used to assess the readiness of an object for digitalisation in the energy sector. Foreign and domestic researchers have identified various indicators that can contribute to the assessment of readiness for digitalisation in the field of energy based on the experience, research, and opinions of experts worldwide and conducted their own research and development. Approaches to assessing digital maturity have been considered in different scientific publications at the enterprise level (micro-level) [17,18], the country level (macro-level) [19,20,21], and the region or industry level (meso-level) [22]. Grover B. and Damle M. [23] considered the assessment of digital maturity (readiness) at the enterprise level. The study includes a comparison of various models of digital maturity (Forrestor’s Digital Maturity Model 4.0, the Capgemini Digital Maturity Model, the PWC Digital Maturity Model, and the Deloitte Digital Maturity Model) to form an idea of the models used to assess the level of digital maturity in an organisation. The digital transformation index developed by the analytical agency Arthur D. Little should also be noted. Arthur D. Little has considered the digital maturity of more than 100 European companies from seven industries in detail and systematically assessed them. The Arthur D. Little Digital Transformation Index (DTI) shows that few firms can be considered “digital oriented” or “digital centric”. Only about 20 percent of companies know how to make digitisation active, and the rest are simply trying to respond to digital developments—without a conclusive overall concept [24]. A study by M. Braglia attempted to develop several key performance indicators that allow for tracking the impact of I4.0 technologies on the main processes of energy industry enterprises in eight areas: production operations management, physical operations, management, production asset performance management, technical data management, quality data and additive manufacturing management, smart safety, smart training, and cyber security [25]. Himang presented a system of indicators for evaluating the implementation of the Industry 4.0 concept and the introduction of innovations to the enterprise at three stages: pre-adoption, adoption, and post-adoption. The resulting indicators were filtered for relevance, redundancy, description, and thorough focus discussions. Finally, they were categorised by their stage of adoption. From 469 innovation adoption indicators found in the literature, their work identified a total of 62 indicators relevant for Industry 4.0 adoption, in which 11, 14, and 37 of them comprised the three stages, respectively [26].

Tripathi developed a comprehensive model for assessing the readiness of a country’s economy for digitalisation based on the analysis of several global indices and scientific research on Industry 4.0. A holistic approach was taken, with the author considering overall socioeconomic development along with industrial innovation and seven readiness dimensions: enabling environment, human resource, infrastructure, ecological sustainability, innovation capability, cybersecurity, and consumers. The formulated model was used to evaluate the Industry 4.0 readiness of 126 economies that account for 98.25% of the world’s gross national income [27]. According to Karanina and Bortnikov [28], it is necessary to use the following seven groups of indicators, each of which has its own quantitative indicators, to assess the readiness of a country to move to a new level in the electric power industry: human capital, reliability and quality of electricity supply, availability of electric energy, operational and investment efficiency, environmental sustainability, electric power system structure, and political determination and transparency. Next, the authors chose the methodology for setting threshold values of indicators and assessing the readiness of a country for digital transition in the electric power industry. For their results, they presented a rating of the first eight countries in each zone of readiness for digital transition in the electric power industry [28].

To understand the state and readiness of a country to introduce innovations in the energy sector, R. Bocca introduced the energy transition index (ETI). The ETI is a tool for energy decision makers that strives to be a comprehensive, global index that tracks the performance of energy systems at the country level. It also incorporates macroeconomic, institutional, social, and geopolitical considerations that provide enabling conditions for an effective energy transition. In this way, the ETI enables a better understanding of the past and present states of energy transition around the world, leading to more informed energy transition policies and investment decisions. The author argued that the speed of a country’s transition to a new level in the energy field is determined by the presence of a reliable, favourable environment, which includes a strong political organisation, a flexible regulatory structure, motivation for investment, the development of innovative projects, and awareness of the population about the emergence and introduction of new technologies, as well as many other factors [29].

The need to develop a system of indicators has been confirmed by modern studies. Dudnik et al. [30] examined the impact of the use of open innovation (OI) in the energy sector on readiness for the introduction of artificial intelligence (AI) technologies and their effectiveness. An empirical method was proposed to determine the level of readiness in companies participating in OI for the introduction of AI technologies by comparing Russian and French energy companies. The authors’ research confirmed that, at the moment, it is necessary to prepare a basis for the introduction of innovations to the country’s energy sector. In addition, the authors separately highlighted the need to convey to the population the positive prospects of digitalisation. The verification of readiness for digitalisation is a form of assessment and control of companies, industries, and, ultimately, the country that determines their possible directions of development, taking into account the identified weaknesses [31]. The scientific community has widely discussed the necessity of forming a set of recommendations for the effective implementation of indicators of intellectual readiness to increase the comparability of these indicators between buildings, companies, and industries by defining benchmarks and integrating them with other measurable key indicators [32], especially those related to energy flexibility and efficiency. In this study, we propose focusing on two levels, the country level and the level of the regional industrial complex, which reflect both regional and sectoral aspects.

To assess the effectiveness of a digital transition in the electric power industry, it is necessary to take into account the quantitative and qualitative indicators that consider the reliability and safety of the power system, the reduction of costs in the production process before consumption, the improved usage of the required amount of generating capacity via the improved regulation of consumption cycles, and the reduction of environmental damage during electricity production [33]. Growth in the readiness of the electric power industry for digitalisation can be considered on three levels: the country (macro level), the industry (meso level), and economic entities (micro level) [34]. At the country level, it is most appropriate to consider indicators that take into account the following effects of digitalisation in the electric power industry: reduction in environmental damage, growth in a country’s economy as a whole, and the emergence of new markets. At the industry level, the most important indicators are those that can assess the levels of reliability, efficiency, and safety of a power system [35]. The assurance of an uninterrupted supply and generation of electricity for consumers and a reduction in the number of accidents in electric power facilities are the main indicators of reliability in a power system. Safety should be understood as the provision of the necessary amount of electricity to consumers through the use of new technologies and modern equipment. The efficiency of a power system is estimated using the maximum reduction in their consumption of various resources for the production of 1 kWh [36].

Thus, on the basis of the studies and articles analysed above, we can conclude that the availability of indicators and the indicators of readiness for digitalisation in the energy sector is a prerequisite for setting targets and assessing energy development, which, in turn, contributes to the optimisation and improvement of all functions of the energy system: electricity production, transmission, and generation [37]. In addition, indicators can be useful in finding the best solutions for a faster and more efficient transition from energy to digitalisation.

In this study, we propose focusing on two levels: the country and the RIC, which reflect both regional and sectoral aspects. Previous studies have focused on ratings; that is, they have ranked countries according to the criteria under consideration. Indicators at these two levels and their relationships have not been considered. Therefore, it appears necessary to take into account the gaps in existing studies and form a system of indicators for each level, whose interrelations represent a conceptual model of the development of territorial systems at the different levels (countries and the RIC).

3. Materials and Methods

The methodological basis of this study is the system of balanced indicators proposed by Kaplan and Norton [38], which was the basis for the development of a set of indicators of readiness for digitalisation in the energy sector. The balanced scorecard (BSC) is an integrated approach that allows for, with appropriate adaptation, the exploration of issues related to the development and implementation of strategies for the development of economic systems at different levels: country, region, municipality, enterprise, and industry, among others. The main advantage of the proposed approach is that it allows for the linking of the digitalisation strategies of individual enterprises, industries, regions, or other economic systems of a country to a general strategy to increase the readiness for digitalisation in the country’s energy system. It then translates each strategy into a specific sequence of actions based on the ‘bottom-up’ principle to achieve the goals at all management levels. At the same time, the BSC cascading method enables the formation of an interconnected set of indicators of readiness for digitalisation in an energy system. The indicators can be used for economic systems at different levels and for assessing results of the implementation of a common strategy to increase a country’s readiness for digitalisation in the energy sector.

Cascading is a tool for breaking down strategic goals into individual elements in a hierarchy. That is, the targets are broken down from the whole into separate levels, which in this case, goes from the country to the RIC level. Ultimately, the developed indicators are transformed into specific indicators, which are implemented at the lower level by local authorities and directly affect the higher levels. The cascading method allows for the formation of a transparent structure for the implementation of a development strategy in a separate territory [39].

The indicators identified during the formation of the BSC allow researchers to assess the achievement of a strategy and can be further used for modelling various relationships in a country that are related to digitalisation in the energy sector; that is, they can be the basis for building econometric models that assess the relationship between various elements of the BSC at various management levels. Indicators can be used to study the dynamics of a country’s development in the field of the digitalisation of energy, including in economic systems at different levels.

To develop a system of indicators, it was first necessary to take into account strategic goals, priority areas of development, and tasks in areas that contribute to the implementation of a strategy to increase a country’s readiness for digitalisation in the energy sector. The next step in this study was the creation of a strategic map to increase a country’s readiness for digitalisation in the energy sector [40]. To develop this strategic map, the classic BSC was adapted, and the following BSC projections for assessing a country’s and RIC’s readiness for the digitalisation of their energy systems were identified: finance, regulation and provision of the electric power industry, safety and sustainability of the electric power industry, generation of the electric power industry, and science and innovation (Figure 1).

In this case, all four classic projections were adapted according to the concept of ‘readiness of the energy industry for digitalisation’ and the features of the selected objects (countries). The electric power industry was chosen for this study because it is the basic industry as a result of electricity provisions in the remaining ones. Thus, the following adapted BSC projections were utilised in accordance with the chosen research concept:

• The finance projection is aimed at analysing and evaluating the operational and investment efficiency of a country.
• The ‘safety and sustainability of the electric power industry’ projection reflects the following areas: environmental sustainability and the reliability and quality of an energy supply.
• The ‘electricity generation’ projection characterises the structure of an electric power system.
• The ‘learning and innovation’ projection is aimed at analysing and evaluating human capital and innovation activity.
• The ‘regulation and provision of the electric power industry’ characterises the availability of electric energy and institutional support in the field of energy.

For the next step, a strategic map was created to increase an RIC’s readiness for digitalisation in the energy sector. To develop this strategic map, the classic BSC was adapted, and the following projections from the BSC’s assessment of an RIC’s readiness for the digitalisation of energy were determined: regulation and provision of the electric power industry, safety and sustainability of the electric power industry, generation of the electric power industry, training, and innovation.

Thus, the following adapted BSC projections were utilised in accordance with the chosen research concept:

• The finance projection is aimed at analysing and evaluating the operational and investment efficiency of an RIC.
• The ‘safety and sustainability of the electric power industry’ projection reflects the following areas: environmental sustainability and the reliability and quality of an energy supply.
• The ‘generation and transportation of electricity’ projection characterises the structure of an electric power system.
• The ‘learning and innovation’ projection is aimed at analysing and evaluating human capital and innovation activity.
• The ‘regulation and provision of the electric power industry’ projection characterises the availability of electric energy and institutional support in the field of energy.

Further, the adapted BSC will be disclosed in more detail through goals, sub-goals and indicators.

4. Results

This adaptation enabled the creation of a strategic map for the implementation of a strategy to increase a country’s readiness for digitalisation in the electric power industry (Figure 2).

This map contains a general description of the strategy and illustrates the strategic objectives. On the basis of the literature analysis, expert opinions, statistics, the Strategy of Scientific and Technological Development of the Russian Federation, and the national programme ‘Digital Economy of the Russian Federation’, we identified strategic goals and objectives and indicators that they had been achieved for each BSC projection, which reflect the state of a country’s readiness for the digitalisation of energy (

Table 2. Objectives and corresponding indicators of the directions of the strategic map blocks [28,29].

Goal	Subgoal	Indicator	Dimension
Finance
Rational use of resources	GDP growth relative to electricity consumed	The ratio of GDP to the amount of electricity consumed	PPP $/MWh
	Development of the use of small distributed energy facilities (SDE)	The share of investments in SDE (including RES without hydropower) from the total investment in electricity production	%
Increasing investment attractiveness	Increasing the potential of the economy	Investment freedom index	-
		Access to loans
Safety and sustainability of the electric power industry
Environmental sustainability	Reducing the environmental burden on the atmosphere	CO2 emissions per capita	t/person
		CO2 emissions for total electricity consumption	t/MWh
Reliability and quality of power supply	Reduction of the number of power outages in the system	SAIFI (index of average frequency of system outages)	-
	Reducing the duration of outages from power supply through the system	SAIDI (index of average duration of system outages)
Electricity generation
Structure of the electric power system	Increase in the use of small distributed energy facilities for electricity production	The share of electricity produced at small distributed energy facilities (including RES without hydropower) from the total volume of EE	%
	Reducing the use of coal for electricity generation	The share of electricity produced by coal-fired generation from the total volume of electricity	% %
	Decrease in gas use and increase in water use for electricity generation	The share of electricity produced by gas generation and hydroelectric power plants from the total volume of electricity
Learning and innovation
Human capital	Improving the level of education in the field of electric power and electrical engineering	The total number of educational institutions according to the source	pieces
	Productivity growth in the field of SDE	The share of jobs in the SDE segment (including renewable energy with hydropower) of the total workforce	%
Innovative activity	Increasing the level of innovation activity in the industry	Number of registered patents	pieces
Regulation and maintenance of electric power industry
Political determination and transparency	Growth of sustainable development in the field of renewable energy	Regulatory indicator for sustainable development in the field of renewable energy	-
	Reducing corruption	Corruption Perception Index	-
	The increasing importance of the law	Rule of Law Index	-
Availability of electrical energy	Increase in the average wage in the country (net) relative to the increase in the price of electricity for the population	The ratio of the average wage in the country (net) to the price of electricity for the population	$/kWh
	Reduction of electricity prices for industries (net)	Price of electricity for industry (net)	$/kWh
	Increase in the level of saturation of the country’s electricity in various spheres	Level of electrification of the country	%

).

The adapted BSC enabled the creation of a strategic map for the implementation of a strategy to increase an RIC’s readiness for digitalisation in the electric power industry (Figure 3). Indicators for assessing an RIC’s readiness for digitalisation in the electric power industry are presented below (

Table 3. Indicators for assessing an RIC’s readiness for digitalisation in the electric power industry.

Goal	Subgoal	Indicator	Dimension
Finance
Operational and investment efficiency	Improving operational efficiency	Profit (loss) from the main operating activities of the industry enterprises	million rubles
	Improving the efficiency of entering new facilities	Reduction of average capital costs for the construction of energy facilities	million rubles/MW
Availability of electrical energy	The state of the electric power complex	The share of installed capacity of power plants included in integrated production management systems	%
		The share of the length of overhead power transmission lines included in integrated power transmission control systems	%
		The share of the length of thermal and steam networks included in integrated heat transmission control systems	%
	Reducing the cost of electricity supply	The cost of digital solutions to optimise the mode and volume of electricity consumption	rubles
Safety and sustainability
Environmental sustainability	Reducing the environmental burden on the atmosphere	The amount of environmental emissions per unit of generated electricity	kg/kWh
		The amount of gross greenhouse gas emissions in CO2 equivalent	tons
Reliability and quality of power supply	Improving energy efficiency	Energy efficiency of the industry	tonnes of conventional fuel × kilowatt-hour
		Total costs of measures to improve the energy efficiency of activities	rubles
	Improving the quality of energy supply	Average KIUM (installed capacity utilisation factor) for power plants	%
		Risk of interruptions in power supply	%
Generation and transportation of electricity
Structure of the electric power system	Growth in the use of SDE facilities in the total share of consumed electricity	The share of electricity produced at SDE facilities (including RES without hydropower) from the total volume of electricity used	%
	Reducing the use of coal for the production of electricity	The share of electricity produced at coal generation from the total volume of electricity used	%
Learning and innovation
Human capital	Increasing patent activity	Number of registered patents	pieces
	Development of professional competencies of staff	Percentage of employees who have received additional professional education in the field of digital professions	%
Implementation of innovations	Increasing the number of innovative solutions being implemented	The amount of innovation costs	rubles
Regulation and management
The level of support for the industry from the state	Tax benefits	The amount of preferential loans received	rubles

).

The relationships between indicators at different levels are shown in Figure 4. This figure reflects the relationships between the blocks of the strategic map. Each goal is displayed in a different colour. For example, red indicates environmental sustainability, blue indicates the reliability and quality of a power supply, and green indicates operational and investment efficiency.

To monitor the results, the indicators included in the BSC were presented, which allowed us to assess the degree of readiness for digitalisation in the energy industries of various countries and the identification of factors that must be influenced to increase the positive effects of digitalisation in the energy sector. For example, interruptions in the energy supply of enterprises affect energy efficiency at the RIC level, and the SAIFI indicator at the RIC level, in turn, affects the indicator at the country level.

Thus, relationships between all levels is shown; that is, the indicators at the lower levels affect those at the upper levels. Accordingly, these strategic maps can be used to track the level of readiness for the digitalisation of energy in individual economic systems.

5. Discussion

The literature analysis showed that, despite a large number of studies dedicated to digitalisation in the energy sector, there is currently no unified, universal system of indicators or unified theoretical and methodological approach for assessing a country’s and industrial complex’s readiness for digitalisation in the energy sector [41]. Existing research has focused on rankings [17,18,19], primarily ranking countries based on the considered criteria, without considering indicators at the level of industrial complexes and their interrelationships [15]. Therefore, it is necessary to address the gaps in the existing research and develop interconnected indicator systems for both the country and the industrial complex levels. Additionally, this article contributes by adapting the Balanced Scorecard (BSC) methodology by Norton and Kaplan [38,40] to the regional and country levels in the context of digitalisation.

The approach discussed in this article opens up opportunities for further discussions on increasing the readiness of a country/RIC for the digitalisation of the electric power industry. It is possible to use the results of this article to adjust strategies for the digital transformation of energy both at the country level and the RIC. Future research could utilise statistical information and expert surveys to classify regions and industrial complexes into groups based on their readiness for digitalisation, which would help identify key issues and growth areas and prioritize specific projects in those territories. Furthermore, regions with the lowest level of digitalisation in the energy sector could be identified, and special development programs could be created for them.

Within the framework of this study, the BSC was selected and adapted to build a system of indicators that reflect the relationships between the activities of a country and its RIC. On the basis of an adapted system of balanced indicators, and in accordance with the country’s and the RIC’s development strategies, indicators for assessing the level of readiness for digitalisation in the subjects under consideration were determined. Namely, the components of the BSC were adapted, and corresponding strategic maps were formed. Within this framework, indicators for assessing the readiness of the subjects under consideration for digitalisation were proposed for each strategic goal. Using the developed sets of indicators for the readiness of the subjects under consideration for digitalisation, it is possible to regularly monitor the strategic alternatives being implemented in this area and to exert regulatory influences to increase the readiness of an industry, region, and country. Depending on how the indicators in the system change, it will be possible to assess a country’s development trends in this area and identify factors that contribute to or hinder the country’s readiness to digitalise energy. This will help state authorities and other decision-makers determine the priorities for improving the country’s or RIC’s readiness for digitalisation and choose the best tools to achieve this goal. The indicators identified in the process of forming the BSC will allow for assessing the achievement of the strategy under consideration and can be used further for modelling various relationships at the country or RIC level, including the impact of the activities of the electric power industry on the development of the region and country.

6. Conclusions

In this article, a definition of readiness for digitalisation in the energy sector was formulated. The BSCs presented reflect a country’s or RIC’s readiness for digitalisation in the energy sector from various sides, taking into account technological, functional, economic, institutional, and socio-environmental factors. The practical significance of this integrated approach is that it allows for monitoring the effectiveness of measures to digitalise the energy sector, taking into account the impact on the development of the country/RIC. By using the cascading method, the BSC enabled the formation of an interconnected set of indicators of readiness for the digitalisation of energy systems at various levels, which can be used to assess the results of the implementation of the overall strategy to increase the country’s readiness for digitalisation in the energy sector. On the basis of the limitations of the article and the lack of necessary empirical data in open sources, the proposed system of indicators is based mainly on theoretical conclusions. To implement this approach and effectively use the adapted BSCs in practice, it will be necessary to introduce these indicators into a statistical accounting system. After which, it will be possible to continue the study and confirm (or refute) the alleged relationships between the selected indicators on the basis of empirical data.