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An Exploration of Grassroots Statistical Work in Power Supply Enterprises under the New Situation

2018-05-04

　　Under the new circumstances, energy consumption patterns across various industries are gradually evolving. Consequently, conducting robust power-supply statistical analysis is of paramount importance for accurately gauging trends in national economic development and providing a solid decision-making foundation for power-supply enterprises. This paper focuses on several common issues in the current statistical practices of grassroots power-supply enterprises and offers feasible analytical recommendations, with the aim of enhancing the role of statistical work in supporting the development of these enterprises.

　　At present, pilot reforms on the retail side of electricity sales are being carried out by power supply enterprises across the country. Meanwhile, the report to the 19th National Congress of the Communist Party of China stated that socialism with Chinese characteristics has entered a new era and that the principal contradiction in Chinese society has evolved into one between the people’s ever-growing needs for a better life and unbalanced and inadequate development. Accordingly, power supply enterprises must promptly adjust their development strategies and proactively respond to changes in both the internal and external environments of the electricity market. In particular, it is of paramount importance to strengthen statistical analysis at power supply enterprises—especially at the grassroots level in counties and districts—in order to keep abreast of trends and patterns in the evolution of the electricity market. Such statistical work should be grounded in statistical principles, employ probability theory to construct mathematical models, and systematically investigate and implement methods for collecting, organizing, and analyzing data that reflect the overall characteristics of a phenomenon, while also making inferences and forecasts about those characteristics to provide a solid basis and valuable reference for relevant decision-making.

　　Statistical comprehensive analysis, in accordance with the objectives of the analytical study and based on statistical data, conducts a scientific analysis and integrated investigation of the current state of objective phenomena and their trends of development and change. It elucidates the causes of problems, reveals the essential nature and underlying patterns of these phenomena, and proposes solutions to resolve contradictions. Throughout the entire statistical process, statistical comprehensive analysis occupies a crucial final stage, as it determines whether statistics can fully fulfill its role and function in decision-making and scientific management.

Common Problems in Statistical Work at Grassroots Power Supply Enterprises

　　The level of attention paid to statistical work at the management level needs to be strengthened.

　　At present, some managers of grassroots power supply enterprises still fail to recognize the critical importance of statistical work in driving enterprise development. They view statistical work as merely a support function for higher-level authorities, believing that the core drivers of profitability and growth lie in operational and production activities—particularly financial management—and thus accord low priority to routine statistical tasks. Even worse, some regard statistical work as little more than filling out a few data forms, devoid of any substantive technical content. Consequently, when enterprises reorganize their specialized departments or reallocate staff positions, management tends to overlook the vital role of the statistics function, leading to haphazard staffing assignments for statistical duties—sometimes even assigning personnel from other functional areas to concurrently handle statistical responsibilities. Even where dedicated statistical positions are established, it is all too common for statisticians to hold concurrent roles in other business functions. Under such circumstances, the statistics function has effectively become a peripheral area that anyone can readily take on or replace at short notice. As a result, statisticians devote insufficient effort to deepening their expertise in statistical theory and methodology, thereby severely limiting the contribution that statistical work can make to the development of grassroots power supply enterprises.

　　The professional competence of statistical practitioners needs to be improved.

　　Due to the relatively low priority accorded to statistical work by some grassroots power-supply enterprises, a prominent problem has emerged: the professional competence of statistical personnel is highly uneven. In particular, there is a notable lack of foundational theoretical knowledge in statistics and insufficient capacity for comprehensive analytical thinking, which prevents them from delving deeply into the underlying patterns of development during the critical stage of analysis. Consequently, the full potential of the statistical profession remains untapped. These factors have led some statisticians, in their day-to-day work, to merely enter data haphazardly and submit it in a mechanical, rote manner. Coupled with a limited understanding of the meanings of cross-disciplinary data and the interrelationships among different types of data, this practice readily results in the submission of erroneous data, thereby severely undermining the validity of statistical findings. Furthermore, since statistical work involves coordinating with various specialized departments to conduct data sampling, this aspect places particular demands on statisticians’ ability to organize and coordinate across disciplines. When such coordination skills are weak, the collection of data from different departments can be impeded, making it difficult to obtain accurate data in a timely manner. As a result, statisticians may be forced to resort to “estimation-based statistics” when reporting data, which introduces substantial bias into the statistical outcomes and ultimately compromises the quality of decision-making within the enterprise.

　　The presentation of statistical analysis results is not sufficiently diverse.

　　Due to the relatively low level of statistical expertise among staff at some grassroots power-supply enterprises, the presentation of statistical analysis results tends to be rather monotonous, and statisticians seldom apply statistical theory to organize, process, and conduct in-depth analyses of the data they collect. Even when analytical work is undertaken, the findings often remain superficial, with little effort made to probe the underlying causes of data variations or to examine the interrelationships among variables. Under this prevailing situation—where emphasis is placed on mere data compilation while analysis is neglected—statistical personnel end up functioning merely as data transmitters for various specialized domains. Consequently, statistical analysis outputs are typically limited to simple tables and textual descriptions, with scant use of graphical or other visually intuitive representations. When statistical analysis lacks comprehensiveness and depth and fails to provide a clear, overarching framework, instead merely furnishing decision-makers at power-supply enterprises with a cluttered array of specialized data, it hinders management’s ability to efficiently interpret these results and make informed decisions.

　　The forward-looking nature of statistical analysis work needs to be strengthened.

　　Due to the poor analytical and presentation quality of statistical data from some grassroots power supply enterprises, the company’s decision-making level finds it difficult to accurately grasp the underlying patterns of change in these enterprises’ production and operational activities, and likewise struggles to promptly detect emerging trends in the electricity market. We are now entering a new era that both builds on the past and ushers in the future; the substitution of electric power for other energy sources will be a major trend in end-use energy substitution, quietly reshaping the energy consumption landscape across certain industries. Consequently, how to employ scientific statistical methods to capture these subtle shifts in energy substitution will pose a new challenge for the statistics profession. Since the issuance of the “Several Opinions of the CPC Central Committee and the State Council on Further Deepening the Reform of the Power System” (Document No. 9 of the CPC Central Committee, 2015), the National Development and Reform Commission has been steadily advancing pilot reforms on the retail side of power sales by power supply enterprises. What impacts will these retail-side reforms have on power supply enterprises? How should their production and operational activities be adjusted? And how can these reforms be leveraged to play a positive guiding role in the development of the electricity market? All of these questions underscore the need to strengthen statistical analysis.

　　Some Approaches to Addressing Issues in Statistical Work

　　Enhance management’s attention to statistical work; strengthen understanding of statistical practices; promote awareness of statistical laws and regulations; leverage the role of statistical professionals in data oversight across all business functions; concurrently address the issue of dual roles and overlapping responsibilities; ensure job stability for statistical personnel; and create a favorable environment for statistical analysis.

　　Enhance the professional competence of statistical personnel. It is essential to rigorously screen and certify individuals before they assume statistical positions, selecting only those with high overall qualifications to undertake statistical analysis work, thereby stabilizing the statistical workforce. At the same time, training efforts must be intensified to ensure that statisticians are thoroughly familiar with relevant expertise in economics, energy, and statistics as it pertains to power supply enterprises. Furthermore, the assessment of statistical expertise should be strengthened, the reward-and-punishment mechanism refined, and the sense of responsibility among statistical personnel reinforced, so as to comprehensively elevate the professional standards of statistical staff in power supply enterprises.

　　Enhance the presentation of statistical analysis results. By providing vertical guidance and fostering horizontal exchange, we will strengthen the comprehensive analytical capabilities of statistical professionals. The use of statistical analysis software such as SPSS (Statistical Product and Service Solutions) will help statisticians produce visually compelling data-analysis materials, moving beyond rudimentary, basic analysis methods. This will enrich both the content and the format of statistical analysis reports, improve the precision of analytical findings, and ensure that results are clear, vivid, and concrete—ultimately providing enterprise decision-makers with effective, actionable evidence for informed decision-making.

　　Statistical professionals must possess a forward-looking perspective. By applying principles of descriptive and inferential statistics, they conduct comprehensive analyses and syntheses of collected data, explore the intrinsic relationships among data points, discern subtle shifts in the evolution of various industries, identify patterns in industry electricity consumption, and perform inference and forecasting. In doing so, they provide decision-making support for corporate management, enabling power supply enterprises to timely adjust their strategic priorities, implement energy management in a scientifically sound manner, and steadily advance all reform initiatives.

　　As a foundational industry underpinning China’s socio-economic development, the power sector plays an irreplaceable role in national economic construction. Conducting statistical analysis of power production and operations serves as the prerequisite for macroeconomic regulation by the state; at the same time, it provides robust guidance for power supply enterprises in forecasting the electricity market, formulating grid planning, and adjusting corporate development strategies. Emphasizing the management of statistical work, enhancing the professional competence of statisticians, and gaining a thorough understanding of the underlying patterns of socio-economic development are all critical to effectively serving power supply enterprises and promoting their healthy, sustainable growth.