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How to use big data thinking to boost the transformation of coal enterprises?
Release time:
2018-02-26
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With the advent of the era of big data economy, how to transform coal mining enterprises? Yi Mining Technology provides you with five focus points for reference only. 1. use big data thinking to predict trends and look for the general direction of coal enterprise development strategy. Using big data record prediction, big data statistical prediction and big data model prediction, the new trend of China's energy structure adjustment and change is predicted. Coal enterprises can use big data analysis methods and big data thinking to seek the strategic direction of their future development from the trend, clarify what coal enterprises want to do and what they can do in the future, and study and formulate their long-term development strategy accordingly. 2. with large numbers
With the advent of the era of big data economy, how to transform coal mining enterprises? Yi Mining Technology provides you with five focus points for reference only.
1. use big data thinking to predict trends and look for the general direction of coal enterprise development strategy.
Using big data record prediction, big data statistical prediction and big data model prediction, the new trend of China's energy structure adjustment and change is predicted. Coal enterprises can use big data analysis methods and big data thinking to seek the strategic direction of their future development from the trend, clarify what coal enterprises want to do and what they can do in the future, and study and formulate their long-term development strategy accordingly.
2. use big data thinking to guide innovation and find new value for coal enterprises.
The real value of big data lies in innovation and creation. In the era when data is king, coal enterprises classify the coal resources they occupy according to the quality properties of coking coal, anthracite, fat coal, lean coal and other coal types, with the goal of maximizing value, and carry out washing, matching and deep processing according to the element structure of different coal varieties. This is the behavior of using big data value thinking to lay out, innovate and excavate coal value.
3. use the big data thinking correlation analysis method to find new business opportunities for coal enterprises.
Change the traditional method of causality analysis and thinking, use the correlation thinking mode to analyze the trend of the supply and demand relationship of the coal market, comprehensively analyze the change information of coal, oil, natural gas and other fossil energy, nuclear energy, wind energy, solar energy, hydropower, biomass energy and other emerging energy structure, and judge the variable trend of each kind of energy, especially to judge the living space change of coal market demand, looking for new business opportunities for the transformation and upgrading of coal in the future.
4. use the big data efficiency thinking method to find a new way to enhance competitiveness.
In the past, people always had to organize personnel to conduct a large number of field surveys and data collection before studying and making decisions on certain things, which was not only time-consuming and laborious, but also inefficient. In the era of big data, you can use correlation thinking to analyze probability, analyze possibilities, and make quick decisions, move quickly, and seize opportunities.
5. use big data to customize product thinking and find a new path for coal enterprises to order production.
In the past, the products of coal enterprises were sold more through promotion or by intermediate agents. In the era of the Internet and big data, in order to understand the needs of users, enterprises should make use of the e-commerce of Internet big data and sales mode to sell products directly to users, eliminating the circulation link of middlemen, so that products can be sold at ex-factory prices and benefit consumers. Big data has changed the marketing mode and competition mode of enterprises, and further strengthened the direct relationship between coal enterprises and market end users.
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