The digital transformation of enterprises refers to the enterprise-level transformation through the construction of digital operation system, including the upgrading of enterprise IT architecture and the reshaping of management system.
IT architecture upgrade refers to the upgrade and optimization of enterprise information system. The construction and upgrading of enterprise information system will generally go through three stages: electronization, informatization and digitalization. Electronization is the primary stage, that is, enterprises build information systems applied by a single department, migrate offline transactions to online, and operate data from scratch; Informatization is a stable transition stage, with the integration of information systems of various departments supporting the centralization, standardization and standardization of business, and the operation data is "from existence to communication"; Digitalization is an advanced stage, driven by enterprise data to accurately reshape the business, relying on technical support such as artificial intelligence, big data, and middle platform construction to help enterprises explore the best solutions for operation management, survival and development, and give play to the value of "data assets".
Remodeling the management system refers to the intellectualization of enterprise management. Build a management system based on "data communication and sharing", rely on appropriate IT architecture foundation, realize automatic acquisition and extensive link of enterprise operation data, understand business essence based on data, gain insight into value creation process, carry out business decision-making and agile actions, drive business innovation and lean management, and realize management "transformation".
Digital transformation relies on cutting-edge technologies such as cloud computing, big data and machine learning, and takes culture first, organizational empowerment, talent support and mechanism traction as boosting forces to help enterprises overcome internal and external development resistance and promote enterprise management improvement. Enterprises after digital transformation generally present four typical characteristics:
Enterprises can't achieve efficient management without systems and data. At present, most enterprises have realized "informatization" through the construction of internal information systems. These information systems are generally software packages, which take the process as the center, establish tightly coupled data models according to the predetermined process processing scenarios, standardize data acquisition, rule control and business processing, and finally form information output.
In the digital era of the Internet of Everything, there is a conflict between the demand of enterprises for efficient decision-making, lean value and flexible response, and the support ability of traditional information systems for modularization and process. At the same time, in the process of long-term operation and management, the information coordination obstacles caused by the inconsistency of data standards and caliber in cross-departmental systems have accumulated seriously.
The structural "dilemma" faced by enterprises is increasingly obvious, which is mainly reflected in the following aspects:
Digital transformation is just to break the game and meet the challenge, realize the integration and interaction between the real world and the digital world, simulate deduction in the digital world, promote the strategic landing and optimize business decisions. Scattered and unrelated data cannot be called assets. In order to release the value of data assets deeply, it is the only way to reconstruct enterprise-level data standards. Enterprise business departments and technical departments need * * * to build * * * enjoyment, by combing data logic, building data maps, defining data standards, opening data links, developing data insight and data applications. Taking enterprise data as the center, functional applications are serviced and componentized to support flexible business requirements. Build a value network based on data fusion, and create a space for value growth.
Enterprise data map
Digital transformation is enterprise-level integration and transformation. As the driving energy of transformation, if data only serves some functions, it is bound to fail to exert its full value. Data needs to be well-connected, and data standards must be common within the enterprise. Based on the business context, enterprises should comprehensively sort out business logic and data relations, optimize and transform existing processes, systems and systems, form a stable core of data relations, guide the optimization of system architecture, improve the efficiency of data use, enhance the value of data assets, and realize management empowerment by relying on rapid data output.
In the practice of enterprise-level data standard reconstruction, we can follow three steps, starting from the unified data standard, gradually improve the front-end business process transformation, produce data with unified semantics, clear logic, high standards and high quality from the source, and build a solid data asset foundation.
0 1. Establish enterprise-level data standards and form a cross-departmental "* * * same language"
Focusing on the main line of enterprise business, combing business scenarios, deconstructing and refining all kinds of information and form elements is the basis of building enterprise-level data standards. In the process of unifying data standards, we can start with financial information and trace back the corresponding business scenarios through a single financial record; Taking the product type and the whole process of product production as the meridian, the business logic is clear, and the economic business scene is deconstructed elementarily; Standardize the expression of data elements from three levels: management object, transaction record and business label, and form a clear data relationship.
At the level of management objects, the management objects of single specialty and cross-specialty are uniquely identified. For a single professional management object, around the whole scene of enterprise economic matters, the granularity and business attribute description requirements of the smallest unit in each professional perspective are unified, and the management object can be freely combined to support multi-perspective integration. For cross-disciplinary management objects, for enterprise organizations, customers, assets and equipment, projects, business partners, etc., describe requirements around cross-disciplinary management objects and business attributes, sort out data information, and establish a unified and universal data standard.
Accurately express data elements from the management object level.
At the transaction record level, standardize the process and path of transaction information transmission. According to the business value chain, we will sort out the transaction record rules, standardize the information fields of various documents, establish the process management norms that cross-disciplines follow, and solidify the data connection relationship around business transactions. For example, establish the homologous linkage of contract, order and invoice information in the enterprise, establish a complete collection source, deploy clear data entry standards, and strongly control the integrity of various documents. On this basis, the business operation and online recording rules are clarified, and the data source is dynamically updated to realize the standardized transmission of all kinds of data information. Finally, the management object can be accurately matched, and the business management process can be accurately reproduced digitally with a complete document chain and information chain.
At the business label level, establish a standardized and unified label system. The purpose of constructing business labels is to unify the cross-disciplinary description of similar business attributes and realize the unification of management caliber. Four principles can be followed when building enterprise business labels:
Relying on clear and complete data elements and data relationships, the enterprise management data map is constructed to realize real-time automatic recording of data accompanying business activities, clarify the transformation from business to value, visually display the company's operation process, and accurately identify the needs of digital construction.
Example of data standard establishment method
02. Carry out business process transformation to achieve end-to-end data connectivity.
In the digital transformation based on enterprise finance, combing the industry and finance links is an important "bridge" to realize data empowerment management. Through the data sorting and process transformation of finance and business, the rules of the generation and circulation process of each data item from the business source to the financial end are clearly described, the actual business occurrence process is reproduced by using the inheritance relationship between data, and the data of various links are aggregated to each management object. In this process, enterprises need to focus on three aspects:
03. Enrich data application scenarios to flexibly output empowerment management.
Through data insight, we will build multi-scenario application practice, focus on incremental benefits, and realize business innovation and management change with business actions. Dig deep into the meaning and value of data with flexible output mode, and form multi-level, multi-field and multi-scenario business practice in the process of data accumulation and verification. Drive management behavior change with value signal, and guide value creation from four aspects: efficiency, benefit, innovation and * * *.
Accurately describe the operation of the enterprise and flexibly process the data according to the information needs of different scenarios. Multi-channel reports and application scenarios are used as media to analyze and compare all kinds of basic data and dynamic data, provide quantitative evaluation, intelligently optimize information output, and serve management and business decisions. Focusing on the business development, asset management, customer service, organizational incentives and other management fields, through the aggregate analysis of value data and business data, we can provide efficient and transparent data services for the company's management and various sectors, realize accurate evaluation, investment and incentives from the business motivation, and enhance the keen insight and efficient decision-making ability of enterprise management.
Building an application scenario generally follows the following five steps:
1. Define the scenario requirements: determine the departments and personnel that the application scenario needs to serve, and define the business requirements and the expected results of the scenario application;
2. Set the application theme: define the objectives and main contents of the application scenario, and identify the key points and points of the application scenario for construction or service;
3. Clarify the data source: sort out the business processes involved in the application scenario, and clarify the data types, calculation methods, data source systems and corresponding business logic relationships required by the scenario;
4. Determine the output mode: define the online or offline output and display form of the application scenario results, and formulate the future implementation specifications and iteration rules of the scenario;
5. Establishing data service: combing data link information according to the requirements of application scenarios, calling and analyzing relevant data through platforms or systems, and establishing scenario service capabilities.
In the process of data standard reconstruction, enterprises can realize "three transformations". One is the transformation from "data" to "information", decoding the management information behind the data to form a more complete description of the status quo; The second is the transformation from "information" to "insight", excavating the promotion value behind information and carrying out more scientific prediction and analysis; The third is the transformation from "insight" to "action", empowering decision-making with data value, providing smarter decision-making suggestions for enterprises and helping to improve business management.
In-depth insight into the "three transformations" of data realization enables enterprises to effectively cope with the difficulties faced by data acquisition, data fusion and data empowerment, and realize the digital transformation from "business speaks its own words" to "unified data language", from "data patchwork collection" to "high data integration" and from "management of business data" to "data empowerment management".
0 1. Deepen digital inclusion and build cultural identity
At any time, the transformation of any enterprise needs to be based on cultural identity. Only when the whole organization adopts an inclusive attitude towards the concept of change and deeply integrates the concept of digitalization into the cultural blood of enterprise development can it change from "passive" to "active" and promote the transformation and sustainable development with endogenous power. Enterprises should make in-depth deployment of digital transformation as a part of their development strategy, formulate appropriate and clear strategies, top-level designs and road maps, publicize them among units, business departments and employees at all levels, enhance the sense of participation of enterprise personnel in digital construction, strengthen the experience of transformation effectiveness, and guide talent teams to create breakthroughs in digital skills.
02. Standardize data management and strengthen data information.
Some enterprises have some problems, such as low degree of digitalization, low quality of data sources, offline fragmentation of historical data, and poor database management paradigm. These problems have become bottlenecks in data acquisition and management, limiting higher-level and higher-quality data applications of enterprises. For the digital transformation of these enterprises, we can establish a unified data management organization, strengthen the data foundation, standardize data standards, comprehensively carry out standardized management of historical data, reduce human intervention in basic data and performance indicators, and ensure the smooth implementation of digital transformation.
03. Promote business integration, based on the overall perspective.
Some enterprises with large and complex organizational structures may have some problems, such as difficult communication and coordination among departments, complicated data sharing process, limited content, and low degree of integration between digitalization and business. Enterprises need to take "strengthening integration and cooperation between businesses" as the focus of digital transformation, promote horizontal and vertical integration within organizations, break down barriers between professions, and build a management system that is integrated, shared, coordinated and efficient. Through business integration, we can weaken the resistance of internal and external resource flow, break professional barriers internally, expand career boundaries externally, and form a global and industry-wide perspective.
04. Strengthen digital application and lay out sensitive operation.
Under the situation that the traditional growth mode of value creation of production factors tends to be stable, fully tapping the huge development potential of knowledge and data elements and expanding the dimension of value creation has become a breakthrough for management improvement. Enterprises can consider establishing an in-depth, three-dimensional and perfect data management application system, constantly iteratively improving data calculation and analysis methods, digging deep and expanding various scenario applications, and promoting quality and efficiency improvement and management improvement. Gradually, the value creation ability of data assets will be extended to the whole value chain and industrial chain, which will help enterprises to use the core competence of digital ecological network.
05. Deepen talent management and forge professional teams.
At present, the talent bottleneck problem in the digital transformation of some enterprises is still outstanding. There are few talents with professional skills in big data analysis and data statistical analysis in enterprises, and the source channels are insufficient. In view of this situation, enterprises should implement the skills training and talent strategy of sustainable development, actively introduce digital talents, deepen the reconstruction of the ability of enterprise staff and cadres, strengthen the training of talents in key professional fields and optimize the talent structure of the staff. In addition to paying attention to internal personnel training, enterprises can also introduce external professional service forces, quickly learn and apply industry-leading concepts, technologies and management practices, and take both internal and external courses, so as to forge a team of professionals capable of digital transformation.
Digital transformation will be an important direction of management reform in the next 5- 10 years, and opportunities and challenges coexist for enterprises. On the one hand, digital-driven innovation provides an opportunity for enterprises to overcome their internal development resistance and promote management improvement; On the other hand, the transformation cannot be achieved overnight, and its long-term and complexity require enterprises to make all-round adjustments in organization, technology, culture and management. In the process of deepening digitalization, how to explore the path to adapt to the development of enterprises, how to realize the effective aggregation of data and information, and how to meet the demands of digital management for the improvement of employees' level, technical ability and operational ability in the organization need constant exploration and practice. "God knows it, but there is only one person." In the wave of transformation, the enterprise's belief in change, persistence and rapid progress of technology will surely make generate full of vitality and embark on a unique and innovative digital road.
This article is written for the purpose of providing general information, and is not intended to be a reliable accounting, tax, legal or other professional opinion. Please ask your consultant for specific advice.