Heavyweight_The path for enterprises to implement big data

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There are four main aspects to the implementation of big data in enterprises:

First, enterprises should establish a data culture, and enterprises should use data to make decisions.

Second, companies need to establish a data strategy.

Third, the company's ability to organize a data management team under a data strategy.

Fourth, the technical ability of enterprises to implement big data.



There are two specific construction paths for enterprises to implement big data, one is bottom-up, and the other is top-down.



The top-

down approach is to firstly establish a decision-making culture for data at the management level in an orderly manner, build awareness of the use of data at the corporate culture level, and then establish a corresponding organizational structure, corresponding departments and teams, and determine What kind of people need to be recruited, how many people are needed, how to divide the specific responsibilities, and finally establish the corresponding technology platform. Bottom-up



The first is to let employees learn and master relevant technical skills, which can be through internal training or external recruitment.

Second, there must be a planned design, and there must be a long-term plan for how the system will go and how to do it in the future. Third, there must be clear performance appraisal indicators, data management, quality control, and how to ensure benefits. Fourth, keep an open attitude in thinking. Big data in the Internet era is still in the early stage of development. It is generally believed that the application of big data in enterprises is still in the kindergarten stage. At this time, there are still many things to learn. Mindset, continuous learning, can really do things well.



(1) Establishing an enterprise's data culture

Culture is a measure of how an enterprise views things and implements actions. The establishment of a data culture is to establish a value and institutional system at the entire enterprise level with objective data as the basis for decision-making and measurement, providing a foundation for enterprises to truly use big data to generate value. Without this foundation, even if an enterprise has the best technology and resources, it cannot make good use of them to serve the enterprise.



What is an enterprise data culture? It includes six aspects.



First, data culture is mainly reflected in data-driven decision-making, and decision-making is mainly spoken through data.



Second, the analysis of enterprise operation efficiency. On the one hand, through in-depth analysis of the data, one can understand the operation of all aspects of the enterprise like a telescope; on the other hand, the data can be used like a microscope to observe the details of the operation of the enterprise and find places for optimization.



Third, analyze the gains and losses of marketing planning through data. Usually, when a company does promotional activities, it is considered a success when the sales volume increases, but the promotion has a cost, and when the sales volume increases, does it really bring benefits?



Fourth, in the people-oriented era, companies are more and more responsible for the personal safety and health of their employees. If we can pay attention to the working environment and comfort of employees through objective and measurable data, it will play a very important role in ensuring a good and healthy working environment and improving employee satisfaction.



Fifth, employee performance must have a quantitative indicator.



Sixth, data management in the value chain. Through the sharing and exchange of data in the vertical supply chain, the upstream and downstream enterprises in the supply chain can better understand the demand, inventory and supply of the entire supply chain, so as to optimize the inventory on the chain, actively initiate the preparation of supply, and more Quickly respond to market changes. In the horizontal ecological chain, by sharing and exchanging data, users can be analyzed in all-round life scenarios, so as to create a one-stop service that meets the wider needs of users, which can not only tap more business opportunities, but also enhance user stickiness.





(2) Establish an enterprise data strategy
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