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Article

Application of Management Controlling in the Energy and Heating Sector: Diagnosis of Implementation Level and Identification of Development Barriers in the Context of Other Economic Sectors

by
Marta Kołodziej-Hajdo
1,*,
Artur Machno
2,*,
Janusz Nesterak
3 and
Michał Kowalski
4
1
Department of Finance and Accounting, Faculty of Management, AGH University of Krakow, al. A. Mickiewicza 30, 30-059 Krakow, Poland
2
Department of Applications of Mathematics in Economics, Faculty of Management, AGH University of Krakow, al. A. Mickiewicza 30, 30-059 Krakow, Poland
3
Department of Economics and Organization of Enterprises, Krakow University of Economics, Rakowicka St. 27, 31-510 Cracow, Poland
4
Department of Management Systems and Organizational Development, Wroclaw University of Science and Technology, ul. M. Smoluchowskiego 25, 50-372 Wroclaw, Poland
*
Authors to whom correspondence should be addressed.
Energies 2025, 18(17), 4458; https://doi.org/10.3390/en18174458 (registering DOI)
Submission received: 1 August 2025 / Revised: 12 August 2025 / Accepted: 15 August 2025 / Published: 22 August 2025

Abstract

The article examines the application of controlling in energy and heating (E&H) companies, with particular emphasis on diagnosing the extent to which reporting and management controlling are implemented, as well as identifying barriers that limit the development of their managerial functions. The aim of the study was to determine the extent to which management controlling is applied in the managerial practice of the E&H sector and how its use differs from practices observed in other sectors of the economy. The research employed a mixed methods approach, including a literature review, a case study of controlling implementation in a selected energy company, and a quantitative analysis based on the Managerial Controlling Index (MCI). The central research question addressed the impact of legal, market, and organisational conditions on the scope of controlling in the E&H sector. The findings indicate that E&H companies record lower MCI scores than companies in other industries, regardless of their size, age, or business profile. The article concludes with a set of managerial recommendations outlining directions for the development of management controlling as a tool for supporting decision-making and enhancing integration with the overall management system.

1. Introduction

Intensifying changes in the economic environment require companies to continuously adapt to market demands while simultaneously pursuing product innovations and improvements in management systems. Controlling serves as a key tool that enables economic entities to meet these challenges. Baldi [1] and Wijethilake et al. [2] argue that innovations in controlling constitute an important driver of development across individual sectors of the economy.
Controlling plays a particularly important role in companies operating in the energy and heating (E&H) sector. Organisations in this sector operate in an environment marked by dynamic regulatory and technological change, alongside rising stakeholder expectations in terms of efficiency, transparency, and sustainable development. These conditions place growing demands on companies to anticipate and adapt effectively to evolving circumstances. In both Poland and globally, the energy sector is marked by the absence of a uniform structure, encompassing companies engaged in various stages of the value chain—from production, through transmission and distribution, to the sale and delivery of energy to end users. The distinctive nature of this market, shaped by technological, regulatory, and infrastructural factors, sets it apart from both traditional commodity markets and the financial market [3,4]. Price risk management, optimisation of the energy mix, and emission control require modern controlling tools capable of integrating technical and economic data.
For Polish energy companies, a key challenge lies in meeting climate-related requirements while maintaining price competitiveness and minimising the burden of climate transition costs for end consumers. In the E&H sector, which faces increasingly stringent energy efficiency regulations, controlling supports cost allocation between licensed and market activities, tariff monitoring, and the calculation of unit costs for energy supply.
Within this context, the development of controlling systems—particularly reporting and management controlling—assumes critical importance as a set of solutions that enhance decision-making processes and ensure alignment with the strategic objectives of energy sector organisations. The implementation of reporting and management controlling also facilitates more effective resource allocation and project management, including projects involving the modernisation of energy sources, the deployment of cogeneration technologies, and the introduction of smart metering systems. By employing controlling to assess project profitability and evaluate investment risk, energy companies are able to make more informed strategic decisions grounded in reliable data and forecasts.
In the framework of sustainable development, controlling offers a means of integrating economic, environmental, and social objectives. E&H companies are increasingly adopting extended non-financial controlling measures, incorporating ESG indicators, carbon footprint assessments, and energy efficiency metrics. In business practice, the role of the controller as a strategic partner to the management board is expanding. There is a discernible shift from a passive role, limited to the provision of data, towards active engagement in strategic management processes, tariff policy formulation, demand–supply scenario modelling, and the evaluation of the profitability of renewable and low-carbon energy sources. In this way, controlling contributes to strengthening the resilience of energy sector entities against market shocks, such as rising resource prices or frequent regulatory changes.
The effective implementation of controlling in the E&H sector depends on the company having a technological infrastructure tailored to its specific needs. An important element is the use of advanced ERP systems and data warehouses that support automated reporting, enable simulations and integrate data from different areas of activity. It should also be noted that controlling in this sector must pay attention to the needs of external stakeholders, such as regulatory bodies, consumers, local authorities and investors. Transparent and clearly presented reports are important for these groups.
This study concerns the application of controlling in enterprises within the energy and heating sector (E&H). The primary objective is to assess the extent and effectiveness of reporting and management controlling in E&H companies. The research examines the relationship between the actual application of these forms of controlling and compares the results with those observed in entities operating in other sectors of the economy. It also seeks to formulate conclusions and recommendations on how to overcome barriers within E&H companies, enabling them to make greater use of management controlling.
The core scientific problem lies in identifying conclusions and developing recommendations that can support management in the process of implementing management controlling alongside existing reporting controlling, thereby ensuring their function as complementary components of an integrated management system.
The following main research question was posed in the study:
RQ 1: what are the main conditions (legal, market, organisational) influencing the current scope and nature of controlling (reporting and management) in the companies surveyed from the heating energy sector (E&H)?
The following specific research questions were also formulated:
RQ 1a: which internal conditions and organisational factors contributed to the unsuccessful implementation of management controlling in the examined energy and heating enterprise, despite formal completion of project assumptions and acceptance of proposed changes?
RQ 1b: is there a noticeable trend in the surveyed E&H companies that the size of the company (measured by size classes) is related to the scope of management controlling?
RQ 1c: what are the observed differences in the application of management controlling between the surveyed E&H companies, taking into account their ownership status (public and private companies)?
RQ 1d: are there any visible links between the type of activity (manufacturing/trade/services) and the scale of operations (e.g., large vs. smaller entities) or the level of maturity and the scope of management controlling in the surveyed E&H companies?
RQ 1e: is there a noticeable tendency in the surveyed E&H companies that the length of the company’s operation (measured by the length of time it has been on the market) is related to the scope of management controlling?
The considerations presented in this article are a response to an identified knowledge gap in research on the implementation of management controlling in Polish companies operating in the E&H sector.
The research presented in this article is discussed in five parts. After the introduction, Section 2 presents a review of the literature on the implementation of controlling and its role in business management, as well as a review of the existing scientific achievements in the field of research on the application of controlling in E&H companies. Section 3 presents a case study on the implementation of controlling in a selected energy company. Section 4 discusses the research procedure used, data sources, and research results. Finally, Section 5 presents a discussion and conclusions from the research.

2. Theoretical Framework

2.1. Overview of Research in the Field of Controlling Implementation

Research on controlling has a relatively long history; however, its large-scale implementation has only been examined in depth since the 1990s. Earlier studies primarily presented classifications of controlling functions, their relationship to management accounting, and their basic tools, such as cost accounting, budgeting, and variance analysis. Pioneering approaches—such as Anthony’s concept (1965)—treated controlling, then referred to as management control, in a narrow sense, as a process through which managers ensure the effective acquisition and efficient utilisation of resources to achieve an organisation’s objectives [5].
Since the beginning of the 21st century, there has been a discernible shift in research towards the strategic implementation of controlling and its role in generating value for organisations. Concepts such as the balanced scorecard [6] and various models of integrated management systems [7,8] have played a pivotal role in this shift. During this period, publications began to emerge that focused on the implementation of controlling in dynamic environments, under conditions of uncertainty, and in response to technological and regulatory changes [9,10].
Currently, researchers are increasingly addressing issues related to the digitisation of controlling, its integration with Business Intelligence (BI) tools, and the evolving role of the controller in hybrid organisations—such as those combining elements of project management, lean management, and agile decision-making structures [11]. Research also touches upon the role of the controller as a “business partner” rather than merely a cost guardian [12].
The literature on controlling identifies various approaches to its implementation, which can be classified according to criteria such as purpose, scope, time horizon, and the position of controlling within an entity’s organisational structure. Three approaches are particularly noteworthy: functional, process-based, and structural.
The first, functional (goal-oriented) approach conceptualises controlling as a management subsystem. A classic example is the framework proposed by Horváth [10], who defines controlling as a planning, steering, and control system that supports decision-making processes at both the operational and strategic levels. A similar perspective is presented by Weber and Schäffer [13], who identify the following key functions of controlling: coordination, information, motivation, and control.
The second, process-based (stage-oriented) approach views the implementation of controlling as an organisational project. An example is the model developed by Nowak [9], which presents the implementation of controlling as a process comprising five consecutive phases: diagnosis of the current situation; design of the controlling system; piloting and testing of tools; implementation and integration with other management systems; and ongoing improvement and adaptation. Nesterak [14] proposed a similar approach, but with explicit consideration of IT systems and tools supporting controlling. His model consists of four stages: analysing the initial conditions for implementation; defining the company’s objectives in the controlling implementation process; designing and implementing the controlling framework; and deploying IT systems to support controlling.
The third, systemic (structural) approach emphasises the interconnection between controlling and other organisational subsystems, such as finance, accounting, strategy, and human resources. This approach is reflected in publications by Anthony [5] and Simons [7], among others.
Contemporary models of controlling implementation cannot be considered in isolation from digital technologies. Increasingly, implementations are based on integration with ERP systems, Business Intelligence platforms, or AI-based tools [15,16,17]. Langman [18] highlights the advanced nature of such technology-driven implementations in the areas of reporting, planning, forecasting, data integration, and dashboard development. However, digital implementations require a different design methodology, including the application of agile methods, iterative development of functionalities, and collaborative teamwork between controlling, IT specialists, and management.
When discussing the implementation of controlling within an organisation, it is difficult to avoid addressing the relationship between reporting controlling and management controlling. Reporting controlling focuses on processing historical and operational data, generating consistent and timely reports, and supporting budget execution and variance measurement. In this context, the role of the controlling department is largely confined to developing an information system, with the controller’s competences being relatively limited [12,19,20]. Reichmann [21] defines reporting controlling as a reporting system that provides indicators forming the basis for management decisions. It assists managers in monitoring deviations, controlling budgets, and ensuring operational compliance, thereby serving as an important management tool in many organisations.
ERP and BI systems form the technological foundation of reporting controlling. As highlighted by Nesterak [14], reporting controlling makes use of data warehouses, OLAP technology, and reporting automation. Management controlling should be regarded as an extension and further development of the functions of traditional controlling. According to Nesterak [14] (p. 46), the fundamental premise of management controlling is “the comprehensive optimisation of economic processes within a company, resulting in improved economic and financial performance and aiming to enhance its competitive position in the market.” He further observes that management controlling requires a process-oriented approach and coordination of activities at their point of origin, thereby enabling the streamlining of business processes. This approach to controlling is concerned with supporting decision-making, strategic planning, and organisational management. It integrates financial, operational, and strategic dimensions in a holistic manner and relies on scenario analyses, forecasts, and models that inform the decision-making process. Reichmann [21] also underscores the role of Executive Information Systems (EIS) and Business Intelligence (BI), which support management by delivering data analysed by management controllers. Table 1 presents the key differences between management controlling and reporting controlling.
Management controlling focuses on supporting decision-making processes and implementing strategy, whereas reporting controlling primarily serves a reporting and analytical role, concentrating on the provision of historical data. The differences between them relate to the scope of activities, operational level, types of technology employed, and the nature of the data used. Management controlling relies on BI tools, forecasts, and scenario analyses, while reporting controlling utilises ERP systems and actual data. The differing roles of controllers—as business partners in the former case and report coordinators in the latter—are also noteworthy. Both types of controlling are complementary, and it is only through their integration that they can be effectively employed in organisations with diverse structures and varying levels of management maturity.
It should also be noted that there is an alternative view whereby management controlling and reporting controlling should not be treated as separate forms but rather as complementary components of an integrated management system. In Controlling Maturity Models, both dimensions are considered as stages of advancement in an organisation’s controlling function—ranging from the operational reporting phase to full integration with strategic planning [10,12].
The effective implementation of controlling depends on a variety of factors. Among the most frequently cited in the literature are strategic support from top management, a clearly defined controlling concept, effective integration with information systems, a broad range of competencies within the controlling team (including analytical, technical, and communication skills), as well as organisational flexibility and a culture based on collaboration and knowledge sharing [8,10,12,22]. Conversely, it is important to highlight the limitations and barriers that may significantly impede the implementation of controlling. These include, in particular: organisational resistance; poor data quality and lack of system integration; insufficient competencies and unclear responsibilities; excessive technocratisation; and a failure to adapt to the specific characteristics of the organisation [23,24,25].
Mykhaylychenko and Tokarev [26] emphasise that there is no single, universal approach to implementing controlling within an organisation, as each entity has its own distinctive development strategy, management vision, and stakeholder relationships. Furthermore, the technologies employed and the organisation’s position in the market can influence both its structure and its organisational mindset.
An increasing number of authors analyse the implementation of controlling as an integral element of organisational change management. Within this perspective, controlling is not an end in itself but a means of transforming decision-making, resource allocation, and knowledge management. According to Gleich [27], the implementation of controlling should be managed as a strategic project with clearly defined stakeholders, milestones, and success metrics.

2.2. Implementation of Controlling in Companies in the Energy and Heating Sector

The E&H sector is characterised by high capital intensity, complex regulatory requirements, long investment cycles, and a strong emphasis on environmental and social responsibility. These features add to the complexity of decision-making processes and underscore the need for appropriate support tools, including advanced data analysis and reporting systems. The electricity sector is subject to constant fluctuations in raw material prices and CO2 emission allowance costs, as well as volatility in energy supplies. Heating companies, by contrast, face challenges arising from ageing technical infrastructure and the necessity to invest in modernisation and decarbonisation. Such activities should be systematically monitored and assessed from both financial and strategic perspectives. These factors create a clear need for the implementation of controlling, a system designed to support management at all organisational levels.
The issue of implementing controlling in E&H companies is addressed in research, but the number of studies is significantly lower than in the case of its application in other manufacturing and commercial enterprises. In classic activities, there is a clear separation between core activities (manufacturing products or providing services) and support activities (supporting core processes). In the case of energy companies, processes are more complex and often formalised, which is why model controlling solutions are significantly different. From the implementation of selected controlling tools [28] to comprehensive management support models [29,30].
Controlling tools can be divided into operational, financial and strategic tools. In Polish energy and heating companies, the following tools dominate: budgeting, KPIs (Key Performance Indicators), responsibility centres, cost analyses and investment analyses. In EU countries, controlling in this sector is gaining an additional technological dimension based on AI (artificial intelligence) and IoT (Internet of Things) or MPC (Model Predictive Control) systems [27,31]. At the strategic level, controlling is supported by regulatory KPIs, investment profitability analysis and long-term planning. Controlling functions in E&H companies are increasingly integrated with management systems such as EMS, ERP, and EAM.
Table 2 presents a summary of selected studies on the implementation of controlling in the E&H sector, with particular emphasis on research objectives, functional areas analysed and controlling tools used.
The literature describing the implementation of controlling in the E&H sector more often refers to traditional tools than to more advanced controlling instruments [40,41]. One of the most frequently mentioned ways of achieving its objective is budgeting. Other traditional tools are also mentioned, such as systematic cost accounting, the implementation of which is intended to help provide relevant and useful information on the costs of the company’s operations or unit costs [42].
Nesterak, Kołodziej-Hajdo, and Kowalski [39] indicate in their research that budgeting and reporting controlling are among the main controlling tools used in Polish companies in the E&H sector. They emphasise the need for greater use of management controlling to support managers in their decision-making.
The domestic and foreign literature emphasises the need for precise information on energy production and transmission costs and the growing share of indirect costs, which creates room for further development of controlling instruments. The main focus here is on the need to use specialised cost accounts, e.g., environmental cost accounts, quality cost accounts or activity-based costing (ABC) [37,43,44,45,46,47,48,49,50,51]. Research on the implementation of activity-based costing in the E&H sector has been conducted by, among others, Rof and Capusneanu [46]. The authors argue that the implementation of activity-based costing (ABC) in an energy company is feasible and beneficial, as it leads to better cost control and increased operational efficiency.
Despite the widespread use of the balanced scorecard (BSC) by companies in various industries [52], there is little research on its application in the energy sector, which means that this instrument is not very popular [34]. However, the authors point to the need to implement BSC in E&H entities, for example, by benchmarking against companies in other industries where BSC has been used successfully [53].
Some authors emphasise in their research the importance of using financial controlling tools and their impact on operational performance and efficiency of operations [29], as well as personnel controlling instruments [54]. In the area of project management, attention is drawn to the importance of project controlling [55] as an instrument that supports investment and modernisation processes in E&H sector.
The implementation of controlling in the E&H sector requires appropriate technological resources. As researchers emphasise, it is crucial to implement advanced ERP/BI systems and data warehouses that enable automated reporting, multidimensional simulations and data integration from different areas of activity [56,57]. The interoperability of production systems with financial systems is particularly important [38].
Today, more and more research are focused on the use of artificial intelligence (AI) in controlling. Ardebili et al. [58] identify five main areas of AI application for this purpose: process automation, prediction and forecasting, decision optimisation, data reporting and narrative support, and strategic support. As indicated in the literature, the specific nature of E&H companies predisposes them to use generative artificial intelligence in many areas [59,60]. In the context of sustainable development, controlling is a tool for integrating economic, environmental and social objectives. E&H companies are increasingly using extended non-financial controlling, including ESG indicators, carbon footprint and energy efficiency [35,61,62,63].
The implementation of various forms and tools of controlling in the E&H sector brings a whole range of benefits. The literature on the subject emphasises, among other things, improved operational and financial efficiency, better investment management, support for strategic decisions, compliance with regulatory requirements and ESG objectives, and technological development and digitisation of the sector. In a broader context, it also means reducing energy consumption and emissions to the environment.
The main barriers to the implementation of controlling include high implementation costs, the need to change the organisational culture, employee resistance and lack of analytical skills, integration difficulties (e.g., lack of data standards), and data security and compatibility of the IT systems used.
Controlling is now used effectively in all industries, including the E&H sector. A properly structured and tailored strategy can be the basis not only for planning but also for building a financial strategy and expanding the company. It helps both in the reporting process and in situations that require decision-making [64]. Controlling in the E&H sector is evolving from the use of operational controlling tools towards greater involvement of strategic controlling instruments, supported by digitalisation, AI and system integration. Energy companies in both Poland and abroad use controlling to improve efficiency, manage investments, and meet regulatory requirements.

3. Case Study—The Process of Implementing Controlling in an Energy Company

The purpose of this case study analysis is to identify practices in the implementation of controlling, examine the course of the implementation process, and evaluate the outcomes of the project. The authors aim to determine which implementation practices are employed and assess their impact on the execution of controlling tasks and objectives, with particular emphasis on achieving the aims of management controlling rather than focusing solely on reporting controlling.
The adoption of a case study as the research method enables the authors to identify specific methods and solutions applied by energy companies in their use of controlling. The practices identified through this analysis will subsequently be assessed within a broader research sample using quantitative methods. The conclusions drawn from this process will facilitate the development of general guidelines that may help overcome barriers limiting the application of management controlling.

3.1. Description of the Research Entity

The company under analysis supplies central hot water and heat to residents of a large urban agglomeration with a population exceeding 500,000. Its main areas of activity include:
The production and supply of steam, hot water, and air for air conditioning systems; the transmission and distribution of heat; and heat trading,
Construction work related to the erection of residential and non-residential buildings,
The installation of water supply and sewerage systems.
A key component of the company’s operations is the development of heating systems. The ongoing programmes focus on expanding networks to connect both newly constructed facilities and existing buildings. The company undertakes between 200 and 250 investment projects annually and operates a network of main, branch, and distribution heating pipelines with a total length of nearly 1000 km.
The organisational structure of the company is complex, reflecting both the scale of its operations and the specific characteristics of the energy sector. Several key organisational subunits can be identified, including management; technical departments responsible for heat production, heating networks, investments, maintenance, and repairs; commercial departments covering sales, customer service, and marketing; a finance department encompassing accounting, controlling, settlements, and risk management; and an administrative department responsible for human resources, legal affairs, and IT. In addition, an operational support department oversees logistics and other support functions. The company has an established controlling unit—the Planning and Controlling Department—embedded within the organisational structure in a line position, reporting directly to the Chief Financial and Project Management Officer. The department employs six staff members. Its principal activities include managing heat energy tariffs, coordinating capital investment projects, analysing the purchase, production, and sale of heat energy, and developing technical and economic indicators. The department also prepares materials for annual and long-term plans and conducts economic analyses, providing inputs to both the controlling and management accounting systems. In practice, its tasks are centred on preparing the annual budget, producing monthly budget implementation reports, and supporting external reporting, primarily to meet the requirements of energy market regulators.

3.2. Characteristics of the Implementation Project

The aim of the project was to improve controlling and management reporting systems focused on implementing the idea of management controlling. The objective of the project was to provide adequate management information that would reflect the complexity of business processes, the specific nature of the contracts and services provided, and the actual involvement of controlling services in supporting business management.
In the course of the analysis and evaluation of the controlling models, processes and tools used, the following problems and areas for improvement of the controlling function were identified:
Overly complex cost accounting rules, although reflecting the complexity of the business processes carried out,
Complicated and unclear accounting code rules, which are difficult to process further, have been modified many times and are inconsistent with the existing organisational structure,
Lack of an attribute database for accounting account segments, which significantly limited reporting capabilities, analysis and drilling down of data in cross-sections useful for management information,
Omission of profit centres,
Lack of a generic cost account, unformulated rules for the management grouping of generic accounts,
No management model for presenting financial results or margin/financial coverage accounts, resulting in a lack of comprehensive or cascading logic for presenting management information,
Lack of comments on results and deviations from budgets, which could provide information to a wider group of managers,
Limited use within the organisation of information prepared by the controlling department, lack of involvement of managers in the analysis and explanation of deviations from the budget,
No link between the remuneration systems for managers and the achievement of financial objectives or tasks resulting from the budget or the strategy management system,
Fragmented system of data supply from various incompatible systems: F-K programme, Ms Excel, investment record system, without the possibility of referring to source data and/or the need to make individual corrections to individual data,
An overly complicated and labour-intensive reporting system,
An overly complex planning system based on extensive procedures, which does not bring any added value, is centrally managed and does not take into account the needs of smaller organisational units,
Lack of forecasting and financial planning procedures, with reporting and management limited to a single, unchanging annual financial plan.

3.3. Results Achieved

The principal outcome of the nine-month project was the implementation of management reporting procedures based on a multi-block financial margin model, together with the development of an appropriate database-driven reporting system. The project’s objectives were achieved, specifically through detailed documentation of the rules for recording economic events and the codification used in accounting accounts; procedures for exporting data from the accounting system; a set of tools for decoding accounting data into a database; and attribute dictionaries for management dimensions. As part of the Proof of Concept, a complete database covering two reporting months was created. The results of the work undertaken were accepted and endorsed by the management board, leading to the decision to implement the developed system for operational management purposes.
In the subsequent stage, revised management reporting rules were introduced. The month-end closing process was supported by external service providers, enabling the controlling department to focus on management analyses and initiatives aimed at improving the company’s efficiency, rather than on data transformation. Operational managers were involved in the monthly analysis of the company’s results and the preparation of management commentaries. Work also commenced on revising the incentive systems.

3.4. Summary of Project Results

Overall, it can be concluded that the project aimed at improving the controlling function and transforming it from a reporting-oriented to a management-oriented role ultimately ended in failure. After only five of the twelve planned months of pilot management reporting, a decision was made to terminate the initiative. The project ran for a total of 13 months, during which four of the eight planned stages intended to enhance controlling procedures were completed. Among the unimplemented measures were the simplification of budgeting procedures, the introduction of rolling budgets, the standardisation of rules for reporting on the implementation of investment tasks, and the adoption of indirect cost accounting systems to determine the full profitability of heat production plants and investment projects.

3.5. Evaluation of the Project and Conclusions

When assessing the project and the reasons for its failure, it is necessary to describe the implementation process itself and the results achieved in this context.
The project was implemented over 13 months out of the 20 planned.
The project budget was defined and approved before its inception. It should be noted that the project costs did not constitute a limitation in its implementation. The project was implemented according to the developed and approved schedule. The time allocated for the implementation of the project was not a constraint; the project was implemented according to the adopted plan, and there were no significant deviations from the adopted schedule. The project objectives were defined, and the strategic and operational tasks of the project were specified. The objectives were approved at the senior management level and communicated within the organisation. The concept of changes was approved by the controlling department. A series of training courses were conducted at all management levels as part of the project. Operational managers were involved in the implementation process. The implementation of the target solutions was preceded by a pilot project (Proof of Concept), the results of which were approved.
Despite the implementation of the project model, the expected results were not achieved. The controlling function did not evolve from reporting to management. The project management objectives were not achieved to the extent originally specified. The results of the project are used to a limited extent in the company, have not been made available to operational managers, and are not used in management decision-making. As a result, the control department tasks have returned almost 100% to the preparation of financial and material reports. Tasks related to commenting on the results achieved, optimising business processes, evaluating and proposing business solutions, and formulating strategies or initiatives for improving the company or its areas are practically non-existent. Controlling participates to a very limited extent in formulating company strategy and influencing management decisions.
To sum up the undertaken presentation, the following cultural limitations should be noted on the implementation and improvement of the controlling function:
Limited involvement in the project and its implementation on the part of senior management, changes in the composition of the management board, and the departure of the board member who initiated the project, resulting in a lack of further determination to implement it,
Strongly articulated dissatisfaction of the controlling department, which had to adapt to a new model of management reporting and new tasks,
An organisational culture characterised by resistance to change and limited awareness of the impact on the overall operations and functioning of the company.
The company’s deep roots in a complex network of regulations, rules and public management, which fundamentally hindered and limited agile management. In addition, the company’s extensive hierarchical organisational structure and highly formalised management culture also hampered the continuation of the project.
Lack of integration of the project with the company’s development strategy.

4. Empirical Framework

4.1. Data and Descriptive Statistics

The survey research, conducted under the scientific direction of Prof. Janusz Nesterak of the Krakow University of Economics, was carried out continuously from 2013 to 2015 as part of a broader research project devoted to controlling practices in enterprises. From the set of issues addressed in this research, those were selected that best meet the stated objectives of this research article. The empirical research focused on assessing the level of maturity of the implementation of controlling practices in companies operating in Poland, including in the energy and heating (E&H) sector. A purposive, non-random sampling approach was employed, allowing for the selection of E&H companies from business registry databases in a manner that maximised the representativeness of the sample. Invitations to participate were sent to organisations listed in official company registers. The primary respondents consisted of individuals in managerial roles, ranging from senior executives to operational managers and controllers who had a comprehensive understanding of the survey topics. This ensured a high level of relevance and reliability in the collected data. In instances where respondents were unable to address substantive questions, they opted to withdraw from participation. In several cases, responses were obtained from multiple individuals within the same organisation. This scenario occurred exclusively in large enterprises, predominantly those with majority state ownership and extensive controlling structures. These respondents represented distinct organisational units within the controlling department. Data were gathered using digital survey tools, namely the Archman Business Navigator system’s questionnaire module and Google Forms. Initially, the questionnaire was developed in a spreadsheet format and subsequently integrated into both the Archman Business Navigator and Google Survey platforms for distribution and completion.
A pilot version of the questionnaire was developed, revised, and subsequently distributed to a group of 911 people who had previously expressed interest in participating in the study. The pool of potential respondents was compiled based on initial interviews conducted with professionals holding managerial positions, as well as employees working in finance and controlling departments within companies operating in Poland. Of the total sample, 301 participants completed the questionnaire in full, representing 33.0% of all invited respondents. The remaining 610 individuals (67.0%) did not submit a completed survey. Among these, 198 respondents (21.7%) began filling out the questionnaire but discontinued before completion. Several of those who abandoned the survey provided feedback indicating that, after reviewing the detailed content, they felt unable to respond competently or accurately. They attributed this to insufficient familiarity with the subject matter covered in the research.
The questionnaire was structured around six thematic sections, each varying in length and scope. To gain a more comprehensive understanding of the background of the respondent, the survey also included a detailed profile section on both the individual who completed the survey and the organisation they represented.
In addition, the questionnaire incorporated open-ended questions, allowing participants to elaborate on selected topics in greater depth. These qualitative responses enriched the dataset by providing insightful perspectives and contextually valuable comments from practitioners, thus enhancing the interpretive dimension of the research findings.
This publication presents the results of research on the implementation of controlling in enterprises. The research tool, in the form of a questionnaire, consisted of 103 questions, the vast majority of which were closed-ended. The respondents also had the opportunity to supplement their responses with comments. This study presents selected results based on questions deemed particularly relevant during the data analysis phase, specifically those concerning the control processes implemented.
In the initial phase of the investigation, the empirical data collected were systematically examined. The main objective was to investigate the controlling practices adopted by companies in the energy and district heating (E&H) sector and to compare them with those implemented in companies of other industries. The analysis began with a presentation of the research sample.
The data set comprised 301 companies operating in Poland, of which 63 were classified within the E&H sector. Only valid and complete responses were included in the analysis; answers marked missing or “not knowing” were excluded to ensure the reliability of the results. The group of E&H companies was analysed compared to companies in other sectors (denoted “Other”) to identify sector-specific controlling approaches. Subsequently, the selected controlling dimensions were examined in more detail to identify the features and practices of the E&H industry.
To test the study’s research questions, we combined descriptive statistics with distribution-free and parametric inference. For categorical (binary) survey items we compared the proportions between energy and heating (E&H) firms and other firms using Pearson chi-square tests; when the expected cell count was <5 we used Fisher’s exact test (two-totes). For composite indices we report Welch unequal-variance t-tests and Mann–Whitney U tests (robust to non-normality). Effect sizes are communicated through raw mean gaps (percentage points for proportions, absolute differences for continuous indicators). To identify the most salient item-level differences, we rank gaps by absolute size and display the statistically significant ones (p < 0.05) together with direction.

Managerial Controlling Index (MCI)

(e.g., strategy monitoring “once a year” = 0, “continuous” = 1; budget update frequency “once a year” = 0, “four times” = 1; allocation of time to operational optimisation “not in scope” = 0, “>50%” = 1, etc.). The block scores were then averaged (requiring data on ≥70% of constituent blocks) to yield the firm-level MCI. This approach preserves interpretability: every 0.10 difference corresponds to a 10 percentage-point shift along the managerial maturity continuum across the included dimensions.
Among companies with usable data (N = 291), the E&H group has a lower MCI than other sectors: mean = 0.4456 (SD = 0.1974, N = 62) vs. 0.5008 (SD = 0.1658, N = 229). The difference is statistically significant (Welch t-test p = 0.0466; Mann–Whitney U p = 0.0174) and small-to-moderate in magnitude (Cohen’s d ≈ 0.32). Distributionally, E&H firms concentrate in the 0.25–0.45 range and are under-represented above 0.60, indicating a leftward shift of the entire distribution rather than a few outliers. As shown in Figure 1, the results support the thesis of the study that management controlling is weaker in E&H.

4.2. Differences Within the Sector in MCI Between E&H Firms

We examined whether the distribution of MCI varies within the Energy and Heating (E&H) sample across four firm characteristics: size (number of employees), age (years of operation), primary activity, and ownership.
Number of employees. No statistically significant heterogeneity (Kruskal–Wallis H = 2.57, df = 3, p = 0.4621). The medians are tightly clustered for 10 to 100 and 101 to 500 employees (≈0.39), while >1000 employees show a somewhat higher median (0.50) and mean (0.4900), but this difference is not significant. With n = 2 in the group of 501–1000, inference for this band remains underpowered.
Firm age. No significant differences (H = 1.87, df = 2, p = 0.3919). The 1–5-year group has the highest mean (0.5400) but is very small (n = 4). The group >15 years (n = 41) has a median of 0.4583, close to the general E&H median, while the 6–15-year group shows a somewhat lower median (0.3050). Overall, MCI appears broadly stable across age bands in E&H.
Primary activity (manufacturing/services/trade). No significant differences (H = 1.91, df = 2, p = 0.3853). Services show the lowest median (0.3400), and trade the highest (0.4727), but dispersion overlaps and sample sizes per cell are modest (trade n = 12, Services n = 20).
Ownership (private vs public). The omnibus test is borderline (H = 5.64, df = 2, p = 0.0598), driven by a higher MCI in public (mean 0.5190, median 0.5000, n = 25) than in private (mean 0.3965, median 0.3625, n = 36). A stray code (“0.4”, n = 1) is between categories and should be treated as data artefact; it is recommended to collapse ownership to private vs public and apply a Mann–Whitney U (excluding that single case) as the main test for this factor In terms of direction, public E&H firms score higher on MCI than private ones.
Within E&H, MCI is fairly homogeneous by size, age, and activity. The clearest internal split is ownership: public entities tend to show stronger management controlling than private E&H firms. This complements the finding between the sectors by indicating that the energy-sector shortfall is not concentrated in a specific size/age/activity niche but may be less pronounced among public E&H companies.

4.3. Item-Level Contrasts Between Management Controlling Components

To understand which specific practices drive the sectoral gap in the Managerial Controlling Index (MCI), we decompose the index and compare the answer-option frequencies between E&H firms and other sectors for each underlying question block. For each option, we report the percentage-point difference (Energy − Other) and a p-value of a χ2 test (Fisher’s exact when the expected counts are <5). The figures display horizontal bars: values to the right indicate options more common in E&H, values to the left indicate options less common in E&H. This item-level view pinpoints whether the disadvantage of E&H stems from strategy monitoring cadence, monitoring ownership, budget revision practices, reporting adequacy, or the allocation of controlling time (financial vs operational), thereby clarifying which levers most strongly characterise the E&H profile.
Figure 2 illustrates monitoringof execution of the strategy. Energy firms select “once a year” far more often (+16.4 pp, p = 0.0028) and “quarterly” more often (+9.1 pp, p = 0.0004), while “continuous” monitoring is less common (−10.1 pp, p = 0.0785). This indicates a less frequent and more episodic monitoring cadence in the energy sector.
Who monitors strategy execution? As shown in Figure 3, energy firms are less likely to have directors (−18.3 pp, p = 0.0127) or managers (−18.5 pp, p = 0.0031) directly monitor the strategy and rarely indicate “other departments” (−9.2 pp, p = 0.0061). A strategy/development department is somewhat cited more often (+9.3 pp, p = 0.0849). In general, monitoring appears less owned by line management, aligning with a more centralised or staff-driven model.
The budget helps the company achieve better results. Figure 4 shows that energy firms answer “rather no” (+14.7 pp, p = 0.0018) and “definitely no” (+14.6 pp, p < 0.001) more often, with a corresponding drop in “rather yes” (−13.8 pp, p = 0.0516). This reflects a greater scepticism about the usefulness of the budget for performance improvement.
Budget update frequency (per year). As presented in Figure 5, energy firms report updates “at most once” more frequently (11.5 pp, p = 0.0442), without significant increase at higher update frequencies. This points to a slower budget revision cycle.
Reporting adequacy for decision-making. Figure 6 indicates that energy firms more often indicate “rather no” (+13.2 pp, p = 0.0022) regarding reporting adequacy, while “the responses “don’t know” are lower (−9.0 pp, p = 0.0630). This suggests perceived shortfalls in reporting support for decisions.
Percent of controlling time, financial tasks. As shown in Figure 7, energy firms are much more likely to allocate >50% of controlling time to financial tasks (+24.0 pp, p = 0.0007), with a borderline rise in 25–50% (+12.4 pp, p = 0.0515). That is, financial controlling dominates.
Percent of controlling time, operational/process. Figure 8 demonstrates that energy firms often mark much more often “0% (not in scope)” for operational/process controlling (+26.7 pp, p < 0.001) and are less likely to report >50% time (−7.6 pp, p = 0.0172). This reflects a relative de-emphasis of operational/process improvement activities.
Taken together, the evidence for the per questions shows that energy utilities practice management controlling less intensively: they monitor the strategy less frequently, assign less monitoring responsibility to the line managers, review budgets less frequently, and perceive both budgets and reporting as weaker support for performance. At the same time, their controlling effort is pulled toward financial tasks and away from operational/process tasks. These patterns are fully consistent with the lower Managerial Controlling Index (MCI) observed for energy firms and support the research question that managerial (decision-support) controlling is comparatively weaker in the energy sector.

5. Discussion and Conclusions

Based on the analysis of the empirical data collected, a synthetic measure was developed in the form of a one-dimensional, interpretable Managerial Controlling Index (MCI), scaled from 0 to 1. This index integrates seven thematic blocks of the survey into a unified scale of management controlling maturity. The MCI enables a transparent assessment of how “managerial” the controlling practices of a firm are, considering dimensions such as the frequency and ownership of strategy monitoring, budget review procedures, reporting adequacy and allocation of controlling department time.
The application of this index revealed that companies in the energy and heating (E&H) sector consistently achieve lower MCI scores compared to companies operating in other sectors of the economy. These findings indicate a relatively underdeveloped state of management controlling functions in the E&H sector, which can limit the ability of these organisations’ to effectively support decision-making and adapt to dynamic market and regulatory environments.
A decomposition of the MCI into its constituent components helps clarify the sources of this deficit. Energy firms tend to monitor strategy less frequently, relying more heavily on annual reviews and less on continuous or monthly follow-up mechanisms. Line managers and directors are less often the owners of strategy execution, with a greater role assigned to separate strategy units and a relatively smaller role played by the controlling department. Budgeting practices reveal infrequent updates throughout the year and a higher degree of scepticism about the actual impact of the budget on performance results. Reporting is less frequently perceived as sufficient to support managerial decision-making. Finally, controlling time allocation is predominantly focused on financial tasks, with relatively little attention devoted to operational or process optimisation.
In short, the sector’s strengths lie in financial control, while the management, forward-looking dimension—encompassing timely monitoring, management ownership, adaptive budgeting, and decision-ready reporting—remains underdeveloped.
The results of the study indicate significant differences in the level of management controlling development between the energy and heating sector (E&H) and other industries. The use of the synthetic MCI (Managerial Controlling Index) indicator enabled an objective assessment of the maturity of management controlling in the surveyed companies and the identification of areas requiring improvement.
Contrary to initial assumptions, variables such as company size, age, type of activity, and scale of operations did not have a significant impact on the level of maturity of management controlling. Only the form of ownership (public vs. private) was found to be a factor of marginal importance, which may suggest that institutional and regulatory factors play a greater role than structural factors.
Identified deficits in strategy monitoring, budget flexibility, reporting adequacy, and time allocation of controlling departments indicate the dominance of a reporting approach, with simultaneous underdevelopment of functions supporting operational, tactical, and strategic management. This state of affairs may limit the organisation’s ability to respond effectively to changes in the market and regulatory environment. Regulatory and technology-intensity moderators were not measured in the survey; their role is considered for future research.
Key conclusions:
Based on the analysis, the following key conclusions were drawn:
Uniformity of practices in the E&H sector. Management controlling practices are relatively homogeneous, regardless of the size, age, or business profile of the company. This may indicate the existence of a common organisational model that does not favour differentiation in the level of management maturity.
Marginal impact of ownership form. Public companies show a slightly higher level of management controlling maturity than private companies, which may result from a greater emphasis on process formalisation and compliance with regulations. However, these differences are minor and do not determine the quality of the controlling.
Deficits in strategy monitoring and ownership. Strategy monitoring is mainly carried out on an annual basis, and the responsibility for its implementation rarely rests with line managers. This limits the operational anchoring of strategic objectives and hinders their effective implementation.
Low budget flexibility. Rare budget updates during the year and limited belief in its impact on results indicate a static approach to planning, which may be insufficient in a volatile environment.
Insufficient reporting for decision-making purposes. Controlling reports are often considered insufficient for management decision-making, which limits their value as a tool supporting effective management.
Focus on controlling financial tasks. Controlling departments in the E&H sector focus mainly on financial tasks, with limited involvement in process optimisation and operational decision support.
Significance of the results and practical implications:
The results of the study are important for both the development of controlling theory and management practice. They show that the development of management controlling in the E&H sector requires not only structural changes, but, above all, a cultural and competence transformation. It is crucial to shift the focus from reporting to supporting decision-making and achieving strategic goals.
In practical terms, the results obtained can form the basis for developing specific recommendations for management staff to support the development of management controlling as an integral part of the management system.
Recommendations for managers of companies in the E&H sector
Based on research and analysis of the MCI indicator, the following recommendations have been formulated:
Strengthening the management controlling function. The expansion of the controller’s role from a reporting function to active decision-making and strategic support, as well as the integration of controlling with the processes of planning, monitoring, and evaluating the achievement of objectives.
Increase the frequency of strategy monitoring. Implement quarterly or continuous reviews of the implementation of the strategy and link the monitoring to the KPI system and the budget cycle.
Decentralise the responsibility for strategy monitoring. Involve line managers in the process of monitoring and reporting on the achievement of objectives and strengthen cooperation between the controlling department and operational units.
Modernisation of the budgeting process. Increasing the flexibility and frequency of budget updates (e.g., rolling forecasts) and linking them to measurable strategic and operational objectives.
Improving the quality of management reports. Systematic review and optimisation of the structure of the report in terms of its usefulness for decision-making and the implementation of Business Intelligence (BI) tools enabling interactive data analysis.
Balancing the allocation of the controlling department’s working time. Reducing excessive focus on financial tasks in favour of operational and process activities, including performance analysis, innovation support, and operational optimisation.
Development of management controlling competencies. Training for controllers and managers in strategic controlling, data analysis and communication, and promotion of a culture of cooperation and knowledge sharing.
Benchmarking and exchange of good practices. Comparison of your own practices with companies outside the E&H sector that achieve higher MCI values and participation in industry initiatives, conferences, and development projects.

Author Contributions

Conceptualisation, J.N. and M.K.; methodology, J.N. and M.K.; software, A.M.; validation, J.N. and M.K.; formal analysis, J.N. and M.K.-H.; investigation, A.M.; resources, J.N. and M.K.; data curation, M.K. and A.M.; writing—original draft preparation, J.N.; writing—review and editing, J.N. and M.K.-H.; visualisation, A.M. and M.K.-H.; supervision, J.N.; project administration, M.K.-H.; funding acquisition, M.K.-H. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the AGH University of Krakow through funds allocated for the development of research capacity at the Faculty of Management, as part of the ‘Excellence Initiative—Research University’ programme.

Data Availability Statement

The original contributions presented in this study are included in the article material. Further enquiries can be directed to the author.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References

  1. Baldi, N. Management of innovations in public governance: Quality management system, management controlling and internal auditing appropriation. Mark. Manag. Innov. 2020, 2, 95–107. [Google Scholar] [CrossRef]
  2. Wijethilake, C.; Munir, R.; Appuhami, R. Environmental innovation strategy and organisational performance: Enabling and controlling uses of management control systems. J. Bus. Ethics 2018, 151, 1139–1160. [Google Scholar] [CrossRef]
  3. Matusiak, B.E. Modele Biznesowe Na Zintegrowanym Rynku Energii; Wydawnictwo Uniwersytetu Łódzkiego: Łódź, Polska, 2014; ISBN 978-83-7969-151-7. [Google Scholar] [CrossRef]
  4. Weron, A.; Weron, R. Giełda Energii: Strategie Zarządzania Ryzykiem; CIRE: Wrocław, Polska, 2000; ISBN 8391386406. [Google Scholar]
  5. Anthony, R.N.; Govindarajan, V. Management Control System, 12th ed.; McGraw-Hill Education: Boston, MA, USA, 2007; ISBN 978-0073100890. [Google Scholar]
  6. Kaplan, R.S.; Norton, D.P. The Strategy Focused Organisation: How Balanced Scorecard Companies Thrive in the New Business Environment; Harvard Business School Publishing Corporation: Boston, MA, USA, 2001; ISBN 1-57851-250-6. [Google Scholar]
  7. Simons, R. Levers of Control; Harvard Business School Press: Boston, MA, USA, 1995. [Google Scholar]
  8. Ferreira, A.; Otley, D. The design and use of performance management systems: An extended framework for analysis. Manag. Account. Res. 2009, 20, 263–282. [Google Scholar] [CrossRef]
  9. Nowak, E. (Ed.) Controlling W Działalności Przedsiębiorstwa; PWE: Warszawa, Polska, 2010; ISBN 9788320819090. [Google Scholar]
  10. Horváth, P.; Gleich, R.; Seiter, M. Controlling; Vahlen: München, Germany, 2015; ISBN 978-3800649549. [Google Scholar]
  11. Zangemeister, A. Entwicklungsorientiertes Controlling im Total Quality Management. Konzeption und Instrumentelle Umsetzung; Springer Fachmedien: Wiesbaden, Germany, 1999; ISBN 978-3-8244-6994-9. [Google Scholar]
  12. Becker, W.; Ulrich, P. Handbuch Controlling; SpringerGabler: Wiesbaden, Germany, 2022; ISBN 978-3658264307. [Google Scholar]
  13. Weber, J.; Schäffer, U. Introduction to Controlling; Schäffer-Poeschel: Stuttgard, Germany, 2008; ISBN 978-3791027593. [Google Scholar]
  14. Nesterak, J. Controlling Zarządczy; Wolters Kluwer: Warszawa, Polska, 2015; ISBN 978-83-264-8536-7. [Google Scholar]
  15. Schallmo, D.R.A.; Rusnjak, A.; Anzengruber, J.; Werani, T.; Lang, K. Digitale Transformation von Geschäftsmodellen. Grundlagen, Instrumente und Best Practices; SpringerGabler: Wiesbaden, Germany, 2021; ISBN 978-3-658-12387-1. [Google Scholar]
  16. Schäffer, U.; Weber, J. Die Digitalisierung wird das Controlling radikal verändern. Control. Manag. Rev. 2016, 60, 6–17. [Google Scholar] [CrossRef]
  17. Friedl, G. Künstliche Intelligenz im Controlling. Controlling 2019, 31, 35–38. [Google Scholar] [CrossRef]
  18. Langman, C.H. Digitalisierung im Controlling; SpringerGabler: Wiesbaden, Germany, 2019; ISBN 978-3658250164. [Google Scholar]
  19. Lichtarski, J.M.; Nowosielski, K. Metodyka pomiaru stanu zaawansowania controllingu w małych i średnich przedsiębiorstwach. In Prace Naukowe Akademii Ekonomicznej we Wrocławiu; Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu: Wrocław, Poland, 2006; Volume 1101, pp. 139–152. [Google Scholar]
  20. Łapińska, A.; Dynowska, J. Zakres zadań i oznaczenia stanowiska controllera w przedsiębiorstwie w świetle badań ankietowych. In Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu; Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu: Wrocław, Poland, 2010; Volume 123, pp. 318–327. [Google Scholar]
  21. Reichman, T. Controlling: Concepts of Management Control, Controllership and Ratios; Springer: Dortmund, Germany, 1997; ISBN 978-3-642-64546-4. [Google Scholar]
  22. Weber, J.; Schäffer, U. Is ensuring management rationality a controlling task? In Behavioral Controlling; Schäffer, U., Ed.; Springer Gabler: Wiesbaden, Germany, 2019; pp. 87–111. [Google Scholar] [CrossRef]
  23. Nesterak, J. Bariery procesu wdrażania controllingu w przedsiębiorstwach działających w Polsce w świetle prowadzonych badań. Misc. Oeconomicae 2014, 1, 237–248. [Google Scholar]
  24. Dynowska, J. Czynniki ograniczające wdrażanie controllingu w świetle badań ankietowych. Pr. Nauk. Uniw. Ekon. We Wrocławiu 2015, 399, 168–175. [Google Scholar] [CrossRef]
  25. Jánská, M.; Celer, Č.; Žambochová, M. Application of corporate controlling in the Czech Republic. Sci. Pap. Univ. Pardubic. Ser. D 2017, 40, 61–70. [Google Scholar]
  26. Mykhaylychenko, N.; Tokarev, A.; Pro Mykhaylychenko, N.; Tokareva, A. Problems and prospects of implementation controlling as a modern enterprise management tool. Экoнoмический вестник Дoнбасса 2016, 4, 75–78. [Google Scholar]
  27. Gleich, R. Data Driven Controlling. Data Analytics und KI Kennen und Nutzen; Haufe Lexware GmbH: Schäffer-Poeschel, Germany, 2023; ISBN 978-3648173879. [Google Scholar]
  28. Mihăilăa, M. Managerial accounting and decision making, in energy industry. Procedia—Social. Behav. Sci. 2014, 109, 1199–1202. [Google Scholar] [CrossRef]
  29. Kes, Z.; Kubalańca, L. Controlling w zakładach energetycznych. In Prace Naukowe Akademii Ekonomicznej we Wrocławiu; Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu: Wrocław, Poland, 2001; Volume 902, pp. 212–218. [Google Scholar]
  30. Tworek, K.; Bieńkowska, A.; Zabłocka-Kluczka, A. Coexistence of business continuity management and controlling: Controlling use as a moderator of relation between BCM maturity and organisational results. Int. J. Ind. Eng. Manag. 2019, 10, 57–68. [Google Scholar] [CrossRef]
  31. Stochastic Model Predictive Control, Energy Efficient Building Control, Smart Grid. Available online: https://cordis.europa.eu/article/id/188555-predictive-models-aid-energy-efficient-management/pl (accessed on 10 July 2025).
  32. Kapustka, K. System wskaźników KPI jako fundament systemu controllingu dokonań w elektroenergetyce. In Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu; Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu: Wrocław, Poland, 2010; Volume 122, pp. 204–212. [Google Scholar]
  33. Bek-Gaik, B.; Surowiec, A. Controlling finansowy w przedsiębiorstwie energetycznym. In Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu; Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu: Wrocław, Poland, 2011; Volume 181, pp. 13–22. [Google Scholar]
  34. Borowiec, L. Zbilansowana karta dokonań jako instrument controllingu w przedsiębiorstwie energetyki cieplnej. Rynek Energii 2011, 5, 80–86. [Google Scholar]
  35. Soni, V.; Dash, A.P.; Singh, S.P.; Banwet, D.K. Life Cycle Costing Analysis of Energy Options: In Search of Better Decisions towards Sustainability in Indian Power &Energy Sector. Glob. J. Manag. Bus. Res. 2014, 14, 43–54. [Google Scholar]
  36. Kowalewski, M. Umiejscowienie controllingu oraz zasady wyodrębniania ośrodków odpowiedzialności za koszty w Miejskim Przedsiębiorstwie Energetyki Cieplnej. Finanse. Rynk. Finans. Ubezpieczenia 2017, 4, 457–468. [Google Scholar] [CrossRef]
  37. Topor, D.I.; Căpușneanu, S.; Constantin, D.M.; Barbu, C.M.; Rakos, I.S. ABB-ABC-ABE-ABM Approach for Implementation in the Economic Entities from Energy Industry. Bus. Manag. Horiz. 2017, 5, 36–48. [Google Scholar] [CrossRef]
  38. Möller, K.; Schäffer, U. Digitalization in management accounting and control: An editorial. J. Manag. Control. 2020, 31, 1–8. [Google Scholar] [CrossRef]
  39. Nesterak, J.; Kołodziej-Hajdo, M.; Kowalski, M. Controlling in the Process of Development of the Energy and Heating Sector Based on Research of Enterprises Operating in Poland. Energies 2023, 16, 773. [Google Scholar] [CrossRef]
  40. Rubik, J. Ewolucja controllingu w Energetyce Kaliskiej S.A. In Prace Naukowe Akademii Ekonomicznej we Wrocławiu; Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu: Wrocław, Poland, 2005; Volume 1080, pp. 366–374. [Google Scholar]
  41. Konsek-Ciechońska, J. Operational and strategic controlling tools in microenterprises—Case study. Manag. Syst. Prod. Eng. 2017, 25, 278–282. [Google Scholar] [CrossRef]
  42. Rubik, J. Model Controllingu kosztów i jego Zastosowanie w Zakładach Energetycznych; Wydawnictwo AGH: Kraków, Poland, 2006. [Google Scholar]
  43. Szyszłowski, R. Wykorzystanie narzędzi rachunkowości zarządczej w przedsiębiorstwach energetyki cieplnej. Rynek Energii 2004, 4, 52–54. [Google Scholar]
  44. Mesjasz-Lech, A. Rachunek Kosztów Ekologistyki w Ocenie Proekologicznej Działalności Elektrowni Cieplnych; Wydawnictwo AGH: Kraków, Poland, 2006; pp. 183–194. [Google Scholar]
  45. Rof, L.M.; Farcane, N. Current State and Evolution Perspectives for Management Accounting in the Energy Sector by Implementing the ABC Method; Annals of Faculty of Economics, University of Oradea, Faculty of Economics: Oradea, Romania, 2011; Volume 1, pp. 653–660. Available online: http://anale.steconomiceuoradea.ro/volume/2011/n1/063.pdf (accessed on 2 July 2025).
  46. Rof, L.M.; Capusneanu, S. Increase the Performance of Companies in the Energy Sector by Implementing the Activity-Based Costing. Int. J. Acad. Res. Accounting. Financ. Manag. Sci. 2015, 5, 139–148. [Google Scholar] [CrossRef] [PubMed]
  47. Ferens, A. Systematyka kosztów środowiskowych w przedsiębiorstwie branży energetycznej do celów decyzyjnych. Zeszyty Teoretyczne Rachunkowości 2016, 86, 11–34. [Google Scholar] [CrossRef]
  48. Sadkowski, W. Rachunek Kosztów Jakości jako Narzędzie Efektywnego Zarządzania Kosztami Jakości w Sektorze Energetycznym; Fundacja na rzecz Czystej Energii: Warszawa, Poland, 2018; pp. 305–401. [Google Scholar]
  49. Szadziewska, A.; Majchrzak, I.; Remlein, M.; Szychta, A. Rachunkowość Zarządcza a Zrównoważony Rozwój Przedsiębiorstwa; Wydawnictwo IUS Publicum: Katowice, Polska, 2021; ISBN 978-83-66922-06-8. [Google Scholar]
  50. Potkány, M.; Hašková, S.; Lesníková, P.; Schmidtov, J. Perception of the essence of controlling and its use in manufacturing enterprises in times of crisis: Does controlling fulfil its essence? J. Bus. Econ. Manag. 2022, 23, 957–976. [Google Scholar] [CrossRef]
  51. Lositska, T.; Bieliaieva, N.; Lagutin, V.; Melnyk, T. Controlling of trade enterprises in the context of the international dimension. Financ. Credit. Act. Probl. Theory Pract. 2022, 1, 92–98. [Google Scholar]
  52. Kumar, S.; Lim, W.M.; Sureka, R.; Jabbour, C.J.C.; Bamel, U. Balanced scorecard: Trends, developments, and future directions. Rev. Manag. Sci. 2024, 18, 2397–2439. [Google Scholar] [CrossRef]
  53. Haapasalo, H.; Ingalsuo, K.; Lenkkeri, T. Linking strategy into operational management—A survey of BSC implementation in Finnish energy sector. Benchmarking. Int. J. 2006, 13, 701–717. [Google Scholar] [CrossRef]
  54. Stańczyk, I.; Stuss, M.M. Personnel Controlling—Human Capital Management. Results of a Selected Company Listed on the Warsaw Stock Exchange. Int. J. Contemp. Manag. 2018, 17, 241–260. [Google Scholar] [CrossRef]
  55. Nesterak, J.; Głodziński, E.; Kowalski, M. Controlling Projektu w Praktyce Przedsiębiorstw Działających w Polsce; Krakowska Szkoła Controllingu: Kraków, Polska, 2018; ISBN 978-83-946066-2-6. [Google Scholar]
  56. Bousdekis, D.; Mentzas, G. Enterprise Integration and Interoperability for Big Data-Driven Processes in the Frame of Industry 4.0. Front. Big Data 2021, 4, 1–18. [Google Scholar] [CrossRef] [PubMed]
  57. Ogundipe, T.; Ewim, S.E.; Sam-Bulya, N.J. Enhancing financial reporting and management efficiency through enterprise resource planning (ERP) systems: A theoretical review for large-scale energy operations. Int. J. Manag. Entrep. Res. 2024, 6, 3415–3458. [Google Scholar] [CrossRef]
  58. Ardebili, A.A.; Zappatore, M.; Ramadan, A.I.H.A.; Longo, A.; Ficarella, A. Digital Twins of smart energy systems: A systematic literature review on enablers, design, management and computational challenges. Energy Inform. 2024, 7, 94. [Google Scholar] [CrossRef]
  59. Dena analysis: Using Artificial Intelligense in the Energy Industry. Available online: https://www.globema.com/dena-analysis-ai-in-energy-sector/ (accessed on 4 July 2025).
  60. Morkisz, P.; Wiącek, M.; Wochlik, I. Wykorzystanie metod obliczeniowych i sztucznej Inteligencji w bezpieczeństwie energetycznym. Wiedza Obronna 2023, 283, 2. [Google Scholar] [CrossRef]
  61. Stuss, M.M.; Makieła, Z.J.; Herdan, A.; Kuźniarska, G. The Corporate Social Responsibility of Polish Energy Companies. Energies 2021, 14, 3815. [Google Scholar] [CrossRef]
  62. Canova, A.; Profumo, F.; Tartaglia, M. LCC design criteria in electrical plants oriented to energy saving. IEEE Trans. Ind. Appl. 2003, 39, 53–58. [Google Scholar] [CrossRef]
  63. PGE Energia Ciepła, S.A. Raport Zrównoważonego Rozwoju. 2023. Available online: https://pgeenergiaciepla.pl/ (accessed on 2 July 2025).
  64. Bartoszewska, P. Dylematy planowania finansowego w przedsiębiorstwie ciepłowniczym. Nowa Energia 2023, 5–6, 50–52. [Google Scholar]
Figure 1. Distribution of the Managerial Controlling Index (MCI) by sector. The bars show within-group proportions (E&H sector vs. other). The brown color indicates overlap of the two levels.
Figure 1. Distribution of the Managerial Controlling Index (MCI) by sector. The bars show within-group proportions (E&H sector vs. other). The brown color indicates overlap of the two levels.
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Figure 2. Strategy execution monitoring—frequency.
Figure 2. Strategy execution monitoring—frequency.
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Figure 3. Who monitors strategy execution?
Figure 3. Who monitors strategy execution?
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Figure 4. The budget helps the company achieve better results.
Figure 4. The budget helps the company achieve better results.
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Figure 5. Budget update frequency (per year).
Figure 5. Budget update frequency (per year).
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Figure 6. Reporting adequacy for decision-making.
Figure 6. Reporting adequacy for decision-making.
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Figure 7. Percent of controlling time, financial tasks.
Figure 7. Percent of controlling time, financial tasks.
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Figure 8. Percent of controlling time, operational/process tasks.
Figure 8. Percent of controlling time, operational/process tasks.
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Table 1. Comparative analysis of management and reporting controlling.
Table 1. Comparative analysis of management and reporting controlling.
CriteriaManagement ControllingReporting Controlling
ObjectiveSupport for managerial decision-making and implementation of strategies.Processing and delivery of information.
ScopePlanning, analysis, forecasting, and risk management.Budgeting, variance analysis, and reporting.
Management LevelStrategic, tactical, and operational.Operational.
TechnologyBI, AI, machine learning, predictive analytics, interactive dashboards.ERP, spreadsheets, and reporting systems.
Interaction with ManagersConsultations and participation.Information and instruction.
Role of the ControllerBusiness partner and strategic analyst.Data expert and report coordinator.
Type of DataAggregated, scenario-based, and predictive.Historical, actual, and standard.
Type of OrganszationCorporations, project-based organisations, and innovative companies.Public institutions, SMEs, and hierarchically structured units.
Source: author’s own work.
Table 2. Review of selected scientific publications on the application of controlling in the E&H sector.
Table 2. Review of selected scientific publications on the application of controlling in the E&H sector.
AuthorResearch ObjectiveTools/Research Areas
Kapustka, K. (2010) [32]Presentation of the KPI system concept as the foundation for performance controlling in the power industry.KPI indicators: performance, availability, and environmental.
Bek-Gaik, B.; Surowiec, A. (2011) [33]Presentation of the scope of financial controlling in the energy sector in the context of market conditions and regulatory requirements.Financial ratio analysis, budgeting and variance analysis, BSC.
Borowiec, L. (2011) [34]Study of the applicability of the balanced scorecard (BSC) as a modern controlling tool in district heating companies.BSC, strategy map, KPIs.
Soni, V.; Dash, A.P.; Singh, S.P.; Banwet, D.K. (2014) [35]Life Cycle Cost (LCC) analysis of different energy generation options in the context of sustainable development in the energy sector.Life Cycle Costing as a tool of strategic controlling.
Kowalewski, M. (2017) [36]Placement of controlling within the organisational structure of a district heating company and the principles of defining cost responsibility centres.Cost responsibility centres, Quality Management System (QMS), process mapping and cost classification, and budgeting and cost analysis by departments.
Topor, D. I.; Căpușneanu, S.; Constantin, D. M.; Barbu, C. M.; Rakos, I. S. (2017) [37]Study of the impact of an integrated activity-based approach on decision-making processes and improvement of cost and environmental efficiency in the energy sector.Integrated controlling approach: ABB (activity-based budgeting), ABC (activity-based costing), ABM (activity-based management), ABE (activity-based emissions).
Möller, K.; Schäffer, U. (2020) [38]Presentation of the impact of digitalisation on the implementation of controlling in enterprises in the E&H sector.Strategic controlling, financial planning and analysis, reporting, and organisational structures of the enterprise.
Nesterak, J.; Kołodziej-Hajdo, M.; Kowalski, M. (2023) [39]Study of the level of use of basic controlling tools and forms in enterprises in the E&H sector.Controlling of budgeting and reporting.
Source: [32,33,34,35,36,37,38,39].
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MDPI and ACS Style

Kołodziej-Hajdo, M.; Machno, A.; Nesterak, J.; Kowalski, M. Application of Management Controlling in the Energy and Heating Sector: Diagnosis of Implementation Level and Identification of Development Barriers in the Context of Other Economic Sectors. Energies 2025, 18, 4458. https://doi.org/10.3390/en18174458

AMA Style

Kołodziej-Hajdo M, Machno A, Nesterak J, Kowalski M. Application of Management Controlling in the Energy and Heating Sector: Diagnosis of Implementation Level and Identification of Development Barriers in the Context of Other Economic Sectors. Energies. 2025; 18(17):4458. https://doi.org/10.3390/en18174458

Chicago/Turabian Style

Kołodziej-Hajdo, Marta, Artur Machno, Janusz Nesterak, and Michał Kowalski. 2025. "Application of Management Controlling in the Energy and Heating Sector: Diagnosis of Implementation Level and Identification of Development Barriers in the Context of Other Economic Sectors" Energies 18, no. 17: 4458. https://doi.org/10.3390/en18174458

APA Style

Kołodziej-Hajdo, M., Machno, A., Nesterak, J., & Kowalski, M. (2025). Application of Management Controlling in the Energy and Heating Sector: Diagnosis of Implementation Level and Identification of Development Barriers in the Context of Other Economic Sectors. Energies, 18(17), 4458. https://doi.org/10.3390/en18174458

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