However, data application is a systematic and complex subject. How to effectively combine production planning, marketing strategy, financial strategy and business strategy is a great test of managers' knowledge and wisdom. However, some business owners simply ignore the correlation between statistical management, data analysis and operation marketing.
In today's economic environment that emphasizes competitive advantage, if we can't grasp the accurate professional competition, scientifically combine the various resources of enterprises according to various occupational probability indicators, and effectively use the resource allocation, the maximization of resource integration value will become a bubble, and it will become empty talk to implement digital management and cultivate the competitive advantage of enterprises.
First, make clear the basic requirements of data management.
1, managers attach importance to data management, which is the basic condition for implementing data management. Managers attach importance to data and human factors, establish an effective combination of people and data, make full use of the role or function of data, recognize and use the value of data, and mobilize people's enthusiasm and subjective initiative, thus building a data management platform and carrying out related work according to the requirements of data.
2. Understand the relationship between data and management. If enterprises don't pay attention to data management, they can't realize the relationship between data and management. Many managers often compare the reasons for the differences in management efficiency through data analysis. For example, in production management, if the personnel, equipment, materials, time and other factors of the two departments are exactly the same, but the production efficiency is different, I can analyze the data through data decomposition in the production process, and then I can confirm whether the staff morale, staff proficiency or management factors lead to the difference in production efficiency.
3. The collected data must be true and reliable. Data exists for people and comes from management activities. The method and management of data collection should be standardized in system and process, and we should not do whatever we want, let alone estimate and falsify data. The authenticity of data is very important to the analysis and decision-making of enterprises. On the one hand, its authenticity depends on people's moral behavior, on the other hand, it can not be separated from the guarantee of the system. Only under the double requirements can our data collection be guaranteed.
4. The data is continuous and systematic. In management activities, data collection cannot be interrupted. You can't just collect one aspect, otherwise it will affect the accuracy and integrity of the data. All business units or departments of an enterprise can collect data on all aspects of enterprise management and business on an annual, quarterly, monthly, weekly and daily basis, and conduct induction and statistics.
Second, expand the space of digital management on the basis of target management.
Data management is based on financial management and target management, and is carried out from the inside out. Under the guidance of strategic objectives, enterprises decompose the data determined by long-term business objectives into years, and the years are decomposed into quarters and months, forming a pyramid-shaped data chain. All functional departments of the enterprise design their own work plans around the core data of this period and determine their own quantitative goals. Such data indicators become the center of management and work. All work results are aimed at achieving quantitative goals.
From the perspective of target management, it is more financial quantitative indicators. Financial indicators are undoubtedly core data, but the completion of core data objectives is supported by other data. For example, employee satisfaction, customer satisfaction, sales terminal growth rate, the cost of new technology development invested by enterprises, the proportion of high-tech personnel to employees and many other quantitative indicators are all used to support the realization of financial data goals. Because a lot of work is based on these quantitative indicators for decomposition, analysis and summary, improvement and adjustment.
Therefore, in data management, each business unit must extend the data to every corner of enterprise management, so that it has a clear data quantitative footprint in management processes, standards and modules. In this way, we will work around the data, and the work efficiency and effect will be more guaranteed.
Third, the use of data management must be linked with institutionalization, process and charting.
In many of our enterprises, data management is mainly financial data, and other aspects seem to have nothing to do. In fact, without institutionalization and process, data management has no foundation and cannot be effectively managed.
Data management pays attention to systematic analysis and scientific evaluation.
Only by deeply understanding each link of the process and its characteristics, and determining the standards and processes, can scientific decision-making and management methods be formulated. For example, in production management, managers choose suitable and skilled workers to study working hours, actions and materials, accurately record the data used by workers in each action, each working procedure and each material in the testing process, thus obtaining the total time and total materials needed to complete the work, and accordingly determining a worker's "reasonable hourly, daily and monthly workload and material consumption". And write the procedures and standard operating procedures into written materials, and train employees according to this education.
Through institutionalized management requirements and long-term unremitting implementation, data can be connected with processes and standardization on the basis of institutionalization. There are basic guarantees. If all the factors in production are sorted into standardized forms at the same time, filled in according to the specifications, and the time of statistics, analysis and reporting is stipulated, this will form the basis of data management in production management. If this kind of management is persisted for a long time, constantly revised and improved, in the long run, it will accumulate into a set of rules and habits that regulate the operation of enterprises, and it can also constitute the unique core advantages of enterprises.
Fourth, it must be the design carrier of digital management.
Enterprises produce a lot of data every day, such as production data, inventory data, financial data, product data, sales data and so on. But it must have a suitable carrier to run, so that it can produce effective value, which requires us to design a carrier-professional charts (or tables) or professional management software. In this way, on the one hand, we can use charts and other tools to sort out and analyze, on the other hand, we can use computer information software technology to carry out effective and rapid management activities, but now many small and medium-sized enterprises can not apply computer software technology in the extensive management stage. Therefore, we briefly explain the application of drawing tools.
Form design can be said from a non-professional point of view, and consultants in consulting companies use more data analysis tools. Our managers use statistical tools more. This is also the reason why we design various forms from the aspects of financial management and statistical management. Summarize.
When designing management charts or tables, enterprises must design reasonable and perfect tables according to their own specific conditions. Such as: daily business forms, various expense forms, various business management forms, human resources-related management forms and other forms, and classify the data collected by the forms according to departments, levels, requirements, operations and time. Design number, category, grade, review, tabulation, cc and other related information. Fill in, review, analyze and manage this information according to the standard process to make the management activities more effective.
In particular, enterprises that integrate production, supply and marketing have complex management activities and many forms. Without the support of management software application, managers need to merge and screen some "gender tables", optimize "personality tables" and simplify table management as much as possible. Some complex and dispensable forms need to be sorted out in time to reduce the complexity of form management. When designing and managing forms and other tools, we regard computer operating system as the most basic tool, and many of its basic functions are tools that can realize and master data management.
Of course, if enterprise conditions permit, management software can also be introduced for application to improve management efficiency. Use charts or computers to accumulate data, analyze data, establish relevant modules, establish analysis methods, establish mathematical models, design application systems, and provide decision support. Using various methods to mine data application technology will further improve management efficiency.