Internet, big data and cloud computing are constantly subverting the traditional industrial structure, and can not seize new opportunities for development are likely to be eliminated by the industry.Industry big data for agricultural machinery enterprises to obtain more profound and comprehensive insight provides an unprecedented space and Potential, with big data and related technologies, can circumvent information silos, data chimneys, develop targeted and competitive strategies and implement personalized, precision marketing.
At present, the agricultural machinery industry is in the depth of market adjustment, industrial innovation and transformation, the key stage of product upgrading, revitalize the stock, accelerating the pace of incremental optimization. Industry as a barometer of changes in the industry has become an important part of information technology The industry will judge, plan and make decisions based on this, so that agricultural enterprises will formulate strategies, optimize resources and enhance their capabilities accordingly, and users will make more decisions on purchasing time, purchasing targets, homework and big data. It can be said that the industry basically reached a consensus on the importance of big data.At the same time, due to the existence of big data industries, the corresponding information barriers between units, data obstruction, different units, different enterprises such as the widespread data blockade, large Part of the data is difficult to achieve an orderly fusion, collaborative advancement, increasing the difficulty of data acquisition, integration.
Recently, at a trade exchange meeting, many experts hope that all parties attach importance to the construction of big data, call for norms, strengthen the production and marketing of agricultural machinery industry, agronomy and other data, get the appropriate response and support .Agricultural machinery industry has been the lack of big data platform. Better production and marketing data has a variety of caliber, with the backbone of enterprises, some enterprises, pre-judged data sources such as large differences to large and medium-sized tractors, for example, some experts determine the industry sales of nearly 500,000 units, and some Industry data show that about 300000. Lack of comprehensive and accurate data support, agricultural machinery enterprises is difficult to grasp the real market conditions, easily lead to 'market prosperity' or 'market downturn' misjudgment.In the strategic decision-making, and some agricultural machinery Enterprises that the industry downturn is only a temporary phenomenon, firmly believe that 'carry the past is the spring', and did not choose to shrink the front line to reduce operational risk, but to adhere to the original extensive growth strategy, the full pursuit of 'performance waterfall' and some companies think The industry has reached the critical stage of industrial restructuring, and has entered the new normal of upgrading and slowing growth, actively optimizing the corresponding input of resources and reducing the economic growth Goal, stock control, incremental optimization, speed up industrial restructuring, to find and grasp new opportunities.
Objectively speaking, the industry is in the early stages of big data construction, began to have a certain reference value. Comprehensive view of the development of the industry big data, there are still some difficulties encountered in the development of data sources. Agricultural machinery, agricultural technology, agricultural resources and customer relations Such as missing large data content, it is difficult to give the industry units to make specific information decision support, far less than scientific, comprehensive, accurate and timely information delivery requirements.
First, the industry big data to be the system.Industry big data the most basic requirement is to be able to show the whole picture of the industry, can not appear 'there can only refer to, without injury' phenomenon.Industry big data statistics show a phenomenon of more than six, More agricultural machinery data, less agronomic data, more power machinery, fewer supporting tools, more traditional enterprises, fewer emerging enterprises, more middle and low-end products and less high-end products; less total data, less subdivision data, more model data, It is worth mentioning that the lack of data more reflect the systematic nature of the data. The lack of relevant systems and standards, some departments are reluctant to open up, some companies are reluctant to share their own data.
Second, the industry big data needs to be comprehensive.Agricultural and agro-agricultural data in the region are mostly at a weak stage, and it is difficult to effectively support the improvement of traditional products and the development of new products, restricting the development of full-mechanized products and making it difficult to sustain the entire crop life cycle Equipment operation conditions monitoring. National subsidy data as part of regional policies on the low-end, saturated and other products are not subsidized, the overall industry information is difficult to fully reflect the industry association data mainly lack of emerging business data, regional sales and other data support. In recent years, there has been an increase in newly emerging enterprises in agricultural machinery, and in particular the sales of leading products of tractors in the third and fourth tier brands have become an important part of the power section of over 100 horsepower.It is hard to find the hidden young tiger in the market jungle without the product changes of the emerging enterprises Industrial upgrading, the pace of the industry to speed up the reshuffle, the number of emerging enterprises has been propped up half the market, is expected to obtain new industrial advantages.Customer relations, the lack of appropriate construction of most enterprises, the lack of coherence and systematic data.Among them, the regional demand Quantity, models can better demonstrate the market development, the rules of user needs, Is the most research value data foundation.
Third, the release of the industry big data to be agile.Most industry information release can not yet be done on a monthly basis unit release, the demand unit is difficult to obtain a steady stream of accurate, real-time data. And subsidy information time are different, with the same caliber industry data information is difficult to display in time.At the same time, the subsidy product information caused by the market overdraft factor lags behind and the real competition status in the dynamic market is difficult to be concretely reflected.Agricultural machinery and tools lack the corresponding industry statistics resources and platform, although Industry associations are able to release individual product information, most of which are still in the stage of "to be sorted out" and the overall industry data is hard to be released in time. Agronomy and agricultural resources are subject to planting patterns, seasonal demand and statistical resources, comprehensive quality of statisticians and heavy workload Various effects, it is difficult to be timely finishing and release.
Under the background of further industrial transformation and market depth adjustment, the periodic, structural and phased development of agricultural machinery market will be superposed on each other to promote and remind the industry to earnestly strengthen the construction of big data. In the face of potential risks and opportunities, early identification and early Early warning, early detection, early disposal, take precautions, take preventive measures. Industry big data construction must be continued to promote, strengthen and improve, not like clouds like fog and wind.
First, optimize the management of big data resources, integrate and optimize related resources and guide the healthy development of big data.At present, agricultural enterprises generally do not have the resources to establish relevant big data to break the 'islands of information' and 'chimney' and change the fragmentation of data The phenomenon requires the support and guidance from relevant government departments and trade associations, formulating or improving corresponding laws and regulations, rules and regulations, using market information to improve market supervision, discovering and resolving problems in the development of big data in time, and forming an online and offline integration Regulate the pattern.Use the methods of administrative collection, web search, voluntarily providing, paid purchase, etc. to guide enterprises, trade associations, research institutes and social organizations to take the initiative to participate in the study and formulate measures for the implementation of data opening up and regulate the data with laws and regulations Content, use of ways.
The second is to improve the quality of data staff.Because of the rise of big data, is in its infancy, while the basic work of the big data of the agricultural machinery industry is correspondingly weak, we need to give more resources to promote personnel training, talent introduction, etc. Integration of enterprises, institutions, etc. Social resources, promote strategic cooperation, build a reciprocal relationship, and build a long-term mechanism for education and training of professionals in big data industry.Complete talent incentive policies to attract high-level talent, to establish a flexible mechanism to attract talent, to create big data innovation support system, talent Highlands.
The third is to innovate the method of big data construction, with emphasis on data processing services in agricultural machinery, agronomy, agricultural materials and e-commerce, and to create a 'big data + industry model.' To promote the in-depth integration of big data with agriculture, economic operation and customer management, The orderly, safe and controllable flow of data should be used by customers who are in need, and employers in the industry should make use of big data analysis to obtain market research, product development, production and sales synergy, machine fusion, precision marketing and after-sales service etc. Product lifecycle management of cloud services and cloud applications, improve decision support, operational efficiency, promote industrial manufacturing to industrial intelligence, industry to create change and development.
Although the pearl is beautiful, it needs to be linked.Industry big data construction is a systematic project, to achieve the smooth flow of information requirements, standardize the development is still facing many difficulties, all parties need to cohesion, synergistic to promote the establishment of long-term development mechanism .Industry should be customer-oriented , Strengthen the construction and use of big data, take the initiative to study changes in the market, accumulate more energy for industrial development, and strive to create a "new business card" for the development of big data in the industry.