1. Definition of data strategy
Data strategy is an indispensable foundation for enterprise refined data management. Only by effectively implementing data strategy can we improve the quality of enterprise data, realize the sublimation of enterprise data value, and lay the foundation for enterprise digital transformation.
Data strategy is the primary task of the entire data governance system and the first thing that enterprises should consider when carrying out data governance work. Data strategy is a data management plan strategy. It is a plan to improve data quality and ensure data integrity, security, and availability. It is the overall goal and development roadmap of enterprise data asset management, and guides enterprises at various stages according to the roadmap. The work focuses on data governance and operations.
2. Data strategic vision and goals
The vision is the starting point for formulating corporate strategy. The realization of the vision is the long-term strategy of the company. The goals are the clear tasks that the company must achieve in the short term. The realization of the goals is the short-term goal of the company.
Enterprises must first establish the goals of data strategic planning, maintain and follow the data management strategy, and then maintain the data management strategy throughout the entire data governance process for all business areas. Then based on the business value of the data and data management goals, stakeholders are identified and the priorities of various data management tasks are analyzed. Finally, develop, monitor and evaluate follow-up plans to guide the implementation of the data management plan.
The strategic goals of an enterprise can be roughly divided into three stages:
The first stage - short-term goals.
The short-term goals are to meet basic management decisions and business collaboration. By solving various problems in data management of the group, it can meet the needs of decision-making analysis and business collaboration. The main goal of this stage is to solve the group's most basic, most urgent needs, and the most pressing problems that hit the company's pain points. For example, establish a unified data platform, unify data standards, break data barriers, improve data quality, accumulate data assets, and assist decision-making analysis.
The second stage - medium-term goal
The medium-term goal is innovation and transformation. Realize enterprise management upgrades and business innovation based on data, expand new businesses, build new business formats, and explore new models through data.
Use data governance to strengthen corporate organizational management and control, improve operation and management efficiency, reduce production costs and increase efficiency, and reduce safety risks; realize supply chain collaboration and optimization based on data; and realize innovative product design based on market predictions. Use big data to explore new service models, expand service horizons, and achieve horizontal expansion of model fields and vertical extension of service accuracy.
The third stage - long-term goal
The long-term goal is to define the role and status of the enterprise in the digital competitive ecosystem. With the change of technology, the business form and competition model of enterprises will change accordingly. In the future digital competition, the deployment and successful implementation of enterprise data strategy will determine whether the enterprise is the leader and challenges in the future competition and digital ecology. The winner is still the one being eliminated. Enterprises must integrate their data strategic vision into their corporate action policies and core values to outline their blueprint for the future.
3. Basic principles of data strategy
1. Data strategy is consistent with the group’s business strategy.
The enterprise’s business strategy affects the direction and design of the data strategy. Data strategy goals should be consistent with business goals and higher-level governance goals.
2. Leaders at all levels of the group attach great importance to
the data strategy. Leaders at all levels of the enterprise should attach great importance to the data strategy to ensure that the data strategy can be implemented smoothly. It is necessary to hold regular working meetings to keep abreast of project progress and participate in project review and evaluation according to implementation stages.
3. Full cooperation of business departments.
Business management departments should actively cooperate with project implementation. Data strategic planning should not simply be considered as a technical implementation of the information department, but should be considered as an innovation in business management. The business management department should jointly form a project team with the information department. The business management department personnel will make suggestions from the perspective of future business development and department operation management, and assist the implementation team in conducting business needs analysis. The business management department should be deeply involved in the detailed data strategy process sorting and optimization work, so that the optimized process can meet the business execution requirements of the business management department.
4. Strengthen the management of standards and regulations.
The planning of data strategy should achieve unified leadership, clear responsibilities, standardized systems, and optimized processes. The enterprise's data governance work should be carried out in strict compliance with the enterprise's unified data strategic plan. In terms of system construction and process optimization, the corporate headquarters formulates unified management systems and process specifications, and subordinate units implement them. The corporate headquarters regularly assesses the implementation of the data strategy.
4. Data strategy implementation steps
1. Step one: Analysis and prediction of corporate strategic environment
Analyze the internal and external environments that affect corporate data strategy. The internal environment includes: the enterprise's business strategy, relevant policies, the current status and future development direction of the business department; the maturity of the group's data governance, and the extent to which the current data governance supports the business. It is necessary to identify gaps and clarify improvements and improvements. direction. The external environment includes: changes that may occur now or in the future in various fields such as society, economy, politics, culture, technology, etc. The data strategy should only include various relevant factors of the internal and external environment, making the data strategy an integral and important part of the corporate strategy.
2. Step 2: Identify data strategy.
Enterprises must identify data strategy based on the requirements of their own business development strategy and information strategy. Data strategy comes from business and serves business. Enterprises need to formulate data strategies based on their own business development requirements.
3. Step 3: Formulate data strategic goals.
Data are resources and assets jointly owned by all units and departments of the enterprise. Data cannot be "privatized". Data assets should be managed centrally, governed uniformly, and used on demand, so that the data assets can be used as needed. Maximize utility. Only when the data goal is business application and data management is the means, can we achieve standardized management of data while improving the efficiency of data application and ensuring the compliant use of data.
4. Step 4: Prepare a data strategy implementation outline and plan.
Enterprises must prepare an implementation outline and implementation plan, listing the specific actions and measures to be taken to achieve each sub-goal, as well as the corresponding responsibilities. The formulation of the implementation plan must be combined with the actual situation of the enterprise and must be executable, quantifiable, and evaluable.
The data strategy implementation outline mainly includes:
1) The current situation and basis for the implementation of the data strategy outline
2) Guiding ideology and basic principles
3) Overall goals and stage goals
4) Main tasks
5) Supporting mechanisms and safeguards
The implementation plan mainly includes:
1) Decompose and refine the data strategic goals by department, and formulate implementation points and detailed implementation plans for each detailed goal.
2) Determine the start and end time of each implementation plan, responsible departments/positions/roles/personnel, and clear inputs. /Output results.
3) Clarify the phased short-term goals.
5. Step 5: Implement the measures to implement the strategy.
The measures to implement the strategy are mainly relevant safeguards established to achieve the data strategy, mainly including data management and control and technical tool systems. The management and control system includes data governance system, data standard specification system, data management process, data management system, etc.
6. Step Six: Review and Assessment
Qualitatively and quantitatively measure and score the data governance of relevant departments, and publish the assessment results. Promote the effective development of data governance work through performance assessment, verify data strategic goals, discover problems and deficiencies, and implement improvement measures in a timely manner, thereby continuously improving and optimizing data strategic goals.