With the advent of the era of big data, big data technology can build a data center and discover the value of information hidden behind the data, thus providing useful help to the enterprise and bringing profits to the enterprise.
The "logistics + big data" model logistics industry is expected to achieve a large outbreak in the face of massive data, while logistics companies are increasing their investment in big data, and should not only view big data as an information technology for data mining and data analysis. Big data should be regarded as a strategic resource, give full play to the development advantages brought by big data to logistics enterprises, and make comprehensive deployment in strategic planning, business model and human capital.
The so-called big data of logistics, that is, data, information, etc. involved in logistics links such as transportation, warehousing, transportation and handling, packaging and distribution processing. Big data analysis can improve transportation and distribution efficiency, reduce logistics costs, and more effectively meet customer service requirements. The data of all goods circulation, logistics express company, supply and demand sides are effectively combined to form a huge instant information platform, thus achieving fast, efficient and economical logistics. The information platform does not simply provide management services for the logistics activities of enterprise customers. Instead, it provides a solution with meso-instructive significance by analyzing the entire system of the supply chain of the enterprise customers or the entire system of the industry logistics. Many companies specializing in logistics data information platforms have formed the logistics big data industry.
1. Big Data Industrial Policy and Development Policy Analysis 1.1 <br> <br> since 2012, the state has gradually introduced related to industrial planning and policies to promote the development of large data from different sides of the industry. However, policy planning specifically for big data development, especially logistics big data, has not yet been made.
At present, the logistics industry planning and policies related to big data issued by the state mainly include the “Guidelines for the Construction of Third-Party Logistics Information Service Platformsâ€, the “Special Action Plan for Trade and Logistics Standardizationâ€, and the Medium- and Long-Term Plan for the Development of Logistics Industry (2014-2020). Years), "Guiding Opinions on Promoting Logistics Informatization Work" and other policies, the big data and information processing methods are important guiding ideologies for the transformation and upgrading of the logistics industry.
The "Internet of Things" Twelfth Five-Year Development Plan, launched in November 2011, listed "Information Processing Technology" as one of four key technological innovation projects, including massive data storage, data mining, and intelligent analysis of image and video. The other three key technology innovation projects, including information-aware technology, information transmission technology, and information security technology, are also important components of the big data industry and closely related to the development of the big data industry.
The Guiding Opinions on Promoting the Healthy Development of the Logistics Industry in the Transportation Industry Released in June 2013 pointed out that the construction of the public information platform for transportation and logistics should be accelerated, the platform-based exchange network should be improved, and the effective inter-regional and cross-industry platforms could be effectively promoted. To achieve the interconnection of railway, highway, waterway and civil aviation information. Accelerate the improvement of information systems for railways, highways, waterways, civil aviation, postal and other industries, promote interconnection and enhance integrated service capabilities. Encourage enterprises to accelerate the construction of information technology.
The "Guidelines for the Construction of Third-Party Logistics Information Service Platforms" issued in February 2014 pointed out that the guiding ideology, basic principles, construction types, construction standards, safeguard measures and assessment requirements for the construction of third-party logistics information service platforms were specifically explained. And it also includes the construction of a third-party logistics information platform with relatively advanced domestic business model and good economic and social benefits.
In addition, the Ministry of Transport is preparing the “Thirteenth Five-Year Plan†for logistics development, which plans to plan the development of modern logistics, points out the need to develop smart logistics, timely research and develop the “Internet†cargo and logistics action plan, and further promote mobile Internet, big data, The application of new generation information technology such as cloud computing; strengthening the construction of public logistics information platform and improving platform service functions.
The life cycle of the logistics big data industry (data generation - data collection - data transmission - data storage - data processing - data analysis - data release, display and application - generate new data) is relatively long, generally in 5-8 years, early Data accumulation and precipitation are time consuming, labor intensive. At present, China's logistics big data industry is in its infancy, and it is expected to develop rapidly in the next two years, taking the lead in realizing big data appreciation.
1.2 Industry development status <br> <br> logistics is an important activity throughout the global economic development and social life. 2013 is called the first year of big data, and 2014 is the first year of mobile internet. In this context, it is necessary to analyze the application of big data technology in the field of logistics.
The research and application of logistics big data has just started, and it is still an emerging research field, and its development is relatively slow. From the perspective of market segments, pharmaceutical logistics, cold chain logistics, and e-commerce logistics are all trying to catch up with Big Data, a high-speed train. However, from the practical application point of view, e-commerce logistics has a certain priority with the Internet platform. The advantage of the development, the rookie network turned out to bring new hope to the e-commerce logistics big data industry, pointing out a new direction.
The application of big data in logistics enterprises runs through all aspects of the entire logistics enterprise. Mainly in the process of logistics decision-making, logistics enterprise administration, logistics customer management and logistics intelligence early warning.
(1) Big Data applications in the Logistics Decision <br> <br> in the Logistics Decision, big data technology involves the analysis and decision of the competitive environment, logistics, supply and demand matching, optimization of logistics resources and configuration.
In the competitive environment analysis, in order to maximize the benefits, it is necessary to cooperate with appropriate logistics or e-commerce companies to conduct a comprehensive analysis of competitors, predict their behavior and trends, and thus understand in a certain area or in a certain Special period, the partner that should be chosen.
In terms of logistics supply and demand matching, it is necessary to analyze the logistics supply and demand situation in a specific period and a specific region, so as to carry out reasonable distribution management. Supply and demand also requires the use of big data technology, from a large number of semi-structured network data, or the company's existing structured data, that is, two-dimensional table type data.
The allocation and optimization of logistics resources mainly involves transportation resources and storage resources. The logistics market has strong dynamics and randomness. It needs to analyze the market changes in real time, extract current logistics demand information from massive data, and optimize the resources that have been configured and will be configured to achieve reasonable logistics resources. use.
(2) big data in the logistics business administration application <br> <br> in business administration also can be used in big data technologies. For example, in terms of human resources, when recruiting talents, it is necessary to select appropriate talents, conduct personality analysis, behavior analysis, and job matching analysis for talents; and also analyze the loyalty and job satisfaction for the incumbents.
Application (3) big data applications <br> <br> large customer data management in logistics in the logistics customer management mainly in the customer satisfaction analysis for logistics services, old customer loyalty analysis, customer needs analysis , prospect analysis, customer evaluation and feedback analysis.
(4) Big Data applications <br> <br> logistics business logistics intelligence warning has a sudden, random, imbalance and other characteristics, through big data analysis can effectively understand consumer preferences, consumer anticipation The consumption may be, the preparation of goods in advance, the rational planning of logistics routes, etc., so as to improve the logistics efficiency of logistics during peak periods.
The "logistics + big data" model logistics industry is expected to achieve a large outbreak in the face of massive data, while logistics companies are increasing their investment in big data, and should not only view big data as an information technology for data mining and data analysis. Big data should be regarded as a strategic resource, give full play to the development advantages brought by big data to logistics enterprises, and make comprehensive deployment in strategic planning, business model and human capital.
The so-called big data of logistics, that is, data, information, etc. involved in logistics links such as transportation, warehousing, transportation and handling, packaging and distribution processing. Big data analysis can improve transportation and distribution efficiency, reduce logistics costs, and more effectively meet customer service requirements. The data of all goods circulation, logistics express company, supply and demand sides are effectively combined to form a huge instant information platform, thus achieving fast, efficient and economical logistics. The information platform does not simply provide management services for the logistics activities of enterprise customers. Instead, it provides a solution with meso-instructive significance by analyzing the entire system of the supply chain of the enterprise customers or the entire system of the industry logistics. Many companies specializing in logistics data information platforms have formed the logistics big data industry.
1. Big Data Industrial Policy and Development Policy Analysis 1.1 <br> <br> since 2012, the state has gradually introduced related to industrial planning and policies to promote the development of large data from different sides of the industry. However, policy planning specifically for big data development, especially logistics big data, has not yet been made.
At present, the logistics industry planning and policies related to big data issued by the state mainly include the “Guidelines for the Construction of Third-Party Logistics Information Service Platformsâ€, the “Special Action Plan for Trade and Logistics Standardizationâ€, and the Medium- and Long-Term Plan for the Development of Logistics Industry (2014-2020). Years), "Guiding Opinions on Promoting Logistics Informatization Work" and other policies, the big data and information processing methods are important guiding ideologies for the transformation and upgrading of the logistics industry.
The "Internet of Things" Twelfth Five-Year Development Plan, launched in November 2011, listed "Information Processing Technology" as one of four key technological innovation projects, including massive data storage, data mining, and intelligent analysis of image and video. The other three key technology innovation projects, including information-aware technology, information transmission technology, and information security technology, are also important components of the big data industry and closely related to the development of the big data industry.
The Guiding Opinions on Promoting the Healthy Development of the Logistics Industry in the Transportation Industry Released in June 2013 pointed out that the construction of the public information platform for transportation and logistics should be accelerated, the platform-based exchange network should be improved, and the effective inter-regional and cross-industry platforms could be effectively promoted. To achieve the interconnection of railway, highway, waterway and civil aviation information. Accelerate the improvement of information systems for railways, highways, waterways, civil aviation, postal and other industries, promote interconnection and enhance integrated service capabilities. Encourage enterprises to accelerate the construction of information technology.
The "Guidelines for the Construction of Third-Party Logistics Information Service Platforms" issued in February 2014 pointed out that the guiding ideology, basic principles, construction types, construction standards, safeguard measures and assessment requirements for the construction of third-party logistics information service platforms were specifically explained. And it also includes the construction of a third-party logistics information platform with relatively advanced domestic business model and good economic and social benefits.
In addition, the Ministry of Transport is preparing the “Thirteenth Five-Year Plan†for logistics development, which plans to plan the development of modern logistics, points out the need to develop smart logistics, timely research and develop the “Internet†cargo and logistics action plan, and further promote mobile Internet, big data, The application of new generation information technology such as cloud computing; strengthening the construction of public logistics information platform and improving platform service functions.
The life cycle of the logistics big data industry (data generation - data collection - data transmission - data storage - data processing - data analysis - data release, display and application - generate new data) is relatively long, generally in 5-8 years, early Data accumulation and precipitation are time consuming, labor intensive. At present, China's logistics big data industry is in its infancy, and it is expected to develop rapidly in the next two years, taking the lead in realizing big data appreciation.
1.2 Industry development status <br> <br> logistics is an important activity throughout the global economic development and social life. 2013 is called the first year of big data, and 2014 is the first year of mobile internet. In this context, it is necessary to analyze the application of big data technology in the field of logistics.
The research and application of logistics big data has just started, and it is still an emerging research field, and its development is relatively slow. From the perspective of market segments, pharmaceutical logistics, cold chain logistics, and e-commerce logistics are all trying to catch up with Big Data, a high-speed train. However, from the practical application point of view, e-commerce logistics has a certain priority with the Internet platform. The advantage of the development, the rookie network turned out to bring new hope to the e-commerce logistics big data industry, pointing out a new direction.
The application of big data in logistics enterprises runs through all aspects of the entire logistics enterprise. Mainly in the process of logistics decision-making, logistics enterprise administration, logistics customer management and logistics intelligence early warning.
(1) Big Data applications in the Logistics Decision <br> <br> in the Logistics Decision, big data technology involves the analysis and decision of the competitive environment, logistics, supply and demand matching, optimization of logistics resources and configuration.
In the competitive environment analysis, in order to maximize the benefits, it is necessary to cooperate with appropriate logistics or e-commerce companies to conduct a comprehensive analysis of competitors, predict their behavior and trends, and thus understand in a certain area or in a certain Special period, the partner that should be chosen.
In terms of logistics supply and demand matching, it is necessary to analyze the logistics supply and demand situation in a specific period and a specific region, so as to carry out reasonable distribution management. Supply and demand also requires the use of big data technology, from a large number of semi-structured network data, or the company's existing structured data, that is, two-dimensional table type data.
The allocation and optimization of logistics resources mainly involves transportation resources and storage resources. The logistics market has strong dynamics and randomness. It needs to analyze the market changes in real time, extract current logistics demand information from massive data, and optimize the resources that have been configured and will be configured to achieve reasonable logistics resources. use.
(2) big data in the logistics business administration application <br> <br> in business administration also can be used in big data technologies. For example, in terms of human resources, when recruiting talents, it is necessary to select appropriate talents, conduct personality analysis, behavior analysis, and job matching analysis for talents; and also analyze the loyalty and job satisfaction for the incumbents.
Application (3) big data applications <br> <br> large customer data management in logistics in the logistics customer management mainly in the customer satisfaction analysis for logistics services, old customer loyalty analysis, customer needs analysis , prospect analysis, customer evaluation and feedback analysis.
(4) Big Data applications <br> <br> logistics business logistics intelligence warning has a sudden, random, imbalance and other characteristics, through big data analysis can effectively understand consumer preferences, consumer anticipation The consumption may be, the preparation of goods in advance, the rational planning of logistics routes, etc., so as to improve the logistics efficiency of logistics during peak periods.
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