The present and future life of big data of electric business

Data, is a relatively abstract noun, the use of data and research has a long history, processed data can be used as an important reference for people's behavior, small to day-to-day consumption to business operations, national decision-making, economic areas of data use is more comprehensive and in-depth, the model derived from the data in various decision-making plays an important role, As one of the fastest growing business models, the use of electronic commerce in data is still in its infancy.

With the rise of the Internet, the concept of data has undergone a fundamental change in the early 20th century, mathematics, physics and other natural science has been the most widely used in the field of data, and then gradually extended to the economics, enterprise operations management, the development of the Internet to provide a large number of data processing, complex operations, In turn, the extension of the data, 2010 years later, "cloud data" concept broke the data time, space constraints, the Big Data era door is open. Consumer E-business is essentially a retail model, compared with the offline it has more easily access to consumer data, commodity data characteristics, the domestic number of large electric dealers have more than tens other active users, Jingdong daily average turnover of more than 100 million, order volume of more than 500,000, the enterprise has a complex operating process, These should be the links where data can play a major role, and the full use of data can play an important role in efficiency and cost savings. In fact, the value of the enterprise's data is precisely the opposite, mass data is used by enterprises to do subtraction method, ratio, trend, absolute value is the most frequently used way, the data is divided into pieces, abstraction, limitations have not been breakthrough; There are many reasons for this result, which may be different It could be a shortage of human resources, whatever the reason, wasting such an important resource is a major loss for the enterprise, and data innovation needs to be improved, and in 2011 McKinsey's report said that only 21% of the entire retail industry was using big data and 21% of companies were planning to start; the arrival of the big data age, It provides new ideas for the change of managers ' ideas and the innovation of data utilization methods. The use of data will be better integrated with enterprise operation development and specific, its manifestation includes the following aspects:

One is the change of "object and object Order", that is, the operation driven data into data-driven operations, large data not only refers to a huge amount of data, but also contains data subdivision, the enterprise almost all the links will be in the form of data to be displayed, such as the time node of each business link derived from the efficiency optimization, Amazon has developed a lot in this area, every day there will be a large number of operational reports and data processing, operational strategy, marketing strategy changes are mainly to look at the data, its own definition of automatic replenishment model is based on the time series and the principle of extreme value formed, effectively solve the total reliance on artificial orders, replenishment mode, Improve the efficiency of inventory management.

Second, the relevance is richer, the biggest disadvantage of data utilization lies in the lack of relevance, once the data isolation considerations, the most core factors may be omitted or can not be accurate, comprehensive expression, e-commerce internal information flow can be transformed into data, based on operational data correlation will become the basis of data analysis, Multidimensional, multi-angle use of data, through a core dimension to expand the scope of the data, the cause of a behavior and rationality through more than 10 or more data standards to show, make it more accurate and highlight the focus, such as sales data can be the core of sales, the product sales of regional, cyclical, After-sales of return and replacement, customer complaint rate, the periodicity of orders, customers loyalty and other indicators of comprehensive analysis. Third, the user experience guidance, the most fundamental thing is to do the user experience, in particular, there are many viewpoints on consumer behavior, such as the theory of trans-period consumption, behavior theory, stochastic theory, etc., but these are basically macro-level, and there are a lot of data of consumer's buying behavior in the electronic business. , in-depth research in the microscopic field will be the main direction, can even be specific to a certain user, including regional purchasing power, commodity regionalization, customer stratification, shopping cycle, shopping bias, the cause of complaints and many other data indicators of the integration of enterprises to implement differentiated strategy and precision marketing to provide an important basis, "Blue Ocean Strategy" A book has talked about the differentiation of a method of identification-strategic layout, electricity through data analysis can effectively identify with the competitor differences, create a new blue sea and provide consumers with a more appropriate shopping experience.

Four is "visualization", the data is a relatively abstract concept, especially in the face of massive data when it is easy to touch the mind, the traditional sense of data analysis is more in the form of simple charts or PPT to show, not intuitive, 2010 after the rise of data information map, Provides a very good visual effect and understanding of data analysis and result output, he used a simple graphic combination to transform a single chart into richer connotations, which greatly stimulated the sensory nerves of people and made the boring data vivid, and the data information graph was only a manifestation of the further development of the data visualization, The big Data age will spawn many similar approaches.

The balance between modelling and basic analysis, the so-called basic analysis is mainly based on the simple data processing, the growth, trends, Jambi and other indicators of the summary analysis, does not involve too many complex processing methods, easy to understand, and the massive data or need to make long-term forecasts, the relevance of the impact of data processing, Basic analysis is hard to achieve, for example, the time series analysis of sales need to use methods such as seasonal adjustment, which requires the use of a suitable data model, the data model is formed on the basis of a series of hypothetical conditions, many hypothetical conditions in reality is not tenable, so the model has its own limitations, His more role is to provide a trend of reference and data processing methods, the use of the internal data is still in the basic analysis stage, the specialized modeling personnel appear very insufficient, and the whole industry is in the growth period, the regularity and predictability of the data is not obvious, the use of the model will have a great limit; in terms of time, The basic analysis is mainly based on historical data and real data, the model can provide long-term prediction data and evaluate the rationality of realistic data, which complement each other, and can provide more accurate reference for business development. With the stability and maturity of the business model, the use of the model will gradually increase, Especially in consumer research, sales forecasting, inventory management, simple or complex methods are necessary, the role of the two are different, in the construction of large data platform, the electrical business needs to better balance the relationship between the, so that it play a corresponding effect.

Six is sharing, the electricity quotient data is now difficult to obtain, the partial public data, such as Eric, Analysys published the report its accuracy is doubtful, the data is limited to internal use, including the competitor's analysis is also based on the not objective basis, which limits the entire industry to the reasonable use of data, because the appliance business is different, The business Operation model is also different, data can provide the basis for business model rationality, can effectively bring efficiency and cost savings, although a large number of people in the industry to promote the sharing of data, can be slow progress; the establishment of large data concept, improve the value of the enterprise to the data, the enterprise part of the function is also changing, Data-generated services are emerging, such as Amoy nets, Taobao, such as the regular release of Internal price index, category Sales report, is to share the internal data a good beginning, many enterprises will be combined with their own and industry open data on the field of electrical business to carry out a professional research, Provide deep service for the development of new entrants or industries; in the internet age, data sharing is an inevitable trend.

The extension of the

Large data concept and its impact on the electric business enterprise is a gradual and in-depth process, and will continue to be enriched and perfected in the practice of enterprise management, whether the method of data utilization or the results of the formation of a lot of uncertainty, but there is a point, as a new driving force, The status of large data is irreplaceable and necessary, can use large data platform to guide the business development of the electric business enterprise will be preemptive, external and internal occupy the opportunity.