How do enterprises carry out digital transformation?

In the process of digital transformation, enterprises should put strategic planning at the top of the transformation path. Senior managers of enterprises should understand that digital transformation is a system-level project to reshape the business, technology and management of enterprises, and it needs to be upgraded with the help of digital technology, business information system and business intelligence BI. Without the strict implementation of strategic planning, the transformation task cannot be completed.

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In addition, business leaders should also form a team that can be fully responsible for the strategic planning of digital transformation. This team should have sufficient authority, digital technicians, BI data analysts and digital transformation experts. Through this team, enterprises can establish a top-down pace to promote digital transformation, add data to KPI assessment indicators, and establish a reward and punishment system.

Digital service development

Enterprises need to carry out information construction, integrate the business of each department into the business information system, and standardize, streamline and standardize the offline business process with the help of the online unified integration platform. Users, business and management personnel can remotely handle, submit, review and approve the business, which simplifies the operation process and stores the data generated by the business in the database through the system, laying a good data foundation for digital transformation.

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After the information infrastructure is completed, enterprises can deploy business intelligence BI, process the data in various departments' databases through ETL and data model, and store them in the data warehouse. Analysts will analyze the data through graphical means, make data visualization reports, track the effect of business execution, and make repeated predictions to provide information support for managers and assist decision-making.

Digital R&D and production

Using BI data analysis of business intelligence, enterprises can confirm the product demand put forward by users and the market through user portraits and market data. User-centered, starting from product planning, every step relies on BI data analysis of business intelligence, and studies the functions and modules in time to fully ensure the competitiveness of products in the market, which will be loved by users after mass production.

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At the same time, digital R&D and production also represent the application of automation. Enterprises automate the data interface and manipulator port of R&D and production through business information system, business intelligence BI and other information and digital technologies, which not only improves the accuracy, but also reduces the waste of manpower, so that R&D and production plants can run for a longer time and complete their tasks with good quality and quantity.

Digital management

In the traditional enterprise management mode, employees are divided into strict grades, and the management and promotion of employees depend more on managers' understanding of employees, which is prone to the phenomenon of cliques, leading to management problems and forced brain drain. Through BI, senior managers of enterprises can establish different business indicators, set up perfect assessment tasks, and view employees' performance data, the completion of business indicators and the analysis of growth potential in real time on data visualization reports, so as to better manage personnel.

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In addition, through digital applications such as business intelligence BI, senior managers can establish different digital platforms inside and outside the enterprise. Internally, we can integrate the business information system, build our own APP or integrate the business management content into other platforms, and manage it in the background of the big platform based on data to improve efficiency and accuracy. Externally, enterprises can establish a digital platform of industrial chain through business intelligence BI, display relevant data such as production, supply, raw materials, spare parts and logistics through data visualization, and "connect different enterprises in the industrial chain into a network" for unified management.

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