Redefine the production relationship with the blockchain, redefine productivity with cloud amount, quantity, mobile index, Internet of Things index, data application and open capabilities, and realize the modernization of the five-management management work of mobile enterprises, data production, and analysis visualization , Management cloudization, business socialization. I think this is what the digital transformation of the business to be done, it is summed up: a platform, two core skills, three stages, four strategic content, five of the building, that the digital transformation of enterprise 12345.

Specifically, a platform is, has a large variety of components and artificial intelligence data cloud computing platform;

The two core skills refer to the rapid IT capability of the business and the ability of data science. The three stages refer to: one: business dataization; two: data businessization; three: business functionalization; four strategies refer to: management The five constructions of strategy, operation strategy, analysis strategy, and tool strategy refer to : work mobility, data production, analysis visualization, management cloudization, and business socialization.

Through this 12345 strategy, enterprises use a new generation of information technology to build a closed loop of business data collection, transmission, storage, processing, analysis, visualization of results and feedback, playing different systems, different technologies, different departments, even different companies, and different industries. Data barriers, improve the overall operating efficiency of enterprises, industries, and industry ecology, and build a new digital economic system. This is the methodology of digital transformation implementation that I understand .

Let's come together.

n A cloud platform, in the process of a new round of digital transformation featuring digitalization, networking and intelligence , the cloud platform plays an important role as an "operating system". Because we can work together on a single platform, operation and maintenance of IT systems, agile development platform, cloud-based big work, cloud-based platform for innovation, cloud-based data exchange, before most of our systems chimneys, built ERP, CRM, OA , supply chain , finance or corporate website or corporate e-commerce platform are provided by many different system vendors. Each system has its own technical architecture, the database is not connected, workflow synergy between the cross-system can not, so what, run their own data in each system inside. A data chimney has been formed . By building a unified cloud platform, we can allow our technology integration , data integration , and business integration . The establishment of a cloud platform is very helpful for the sharing and circulation of data. Therefore, the construction of the home by the various systems will become a unified platform before Dazhong cloud-unified. Today the cloud platform provides a lot of services, storage, computing, network, balance, business, and the entire quickly customized management PaaS platform. Including the last enterprise SaaS of various application systems . Including the DaaS that the data spit out from the SaaS system can provide data services for business departments . From I aaS, PaaS, SaaS to DaaS .

Cloud platform provides the necessary IT resources, but also require data services, big data and artificial intelligence, here is to analyze some large data mining algorithms, and text analysis, voice analysis, video analysis, personalized recommendations. , Neural networks, various machine learning algorithms, etc. This is a core cloud platform of our current enterprise digital transformation, plus components of big data and artificial intelligence to help enterprises achieve digital transformation , including Amazon , Alibaba, IBM, Oracle, Some large foreign IT Internet companies such as Microsoft , Facebook, and Google .

n Two core capabilities , one is the ability to grasp the trend of the business, one is the ability of data science. The ability to grasp the business is actually a comprehensive ability for deep insight, foresight, preparation, layout, investment, operation management , and use of tools for the development trend of the industry where the company is located . The communication between internal staff and external business customers, internal business partners, suppliers, competitors. That work together to be able to faster and more efficient ah, security stability adapt to market development, especially our D T from IT to change this process, the enterprise business to get on the cloud.

Above this figure and share, mainly I wish to say, I T is a single, stable process, a number of process-driven system, such as C RM, E RP, O A , H Rc these are electronic processes, relatively stable.

I T deal with these , before you can be regarded as a cost center. Basically it is behind the business, because IT will do whatever system the business needs . Basically, it solves offline stable business problems.

D T mainly dealing with diverse, this real-time online system, such as user portrait, online user behavior analysis, personalized recommendation system, real-time search, tag management systems, including big data.

D T is a profit center, it solves a real-time online business. So from these two perspectives , IT is actually a cost center and a backward business. D T with the establishment of these systems is a profit center platform, is the leading business.

Why is IT lagging behind business and DT leads the business ? I have worked for IT for eight years before , and I have worked for DT for eight years . This is something I really understand . Because IT, we do what the customer wants the system is basically what we do, the client needs to put forward the project ground to basically take three to five months, is this short; if a bit longer take one to two years Even longer. So after the business is proposed, when IT is done, the business has actually changed.

And why say DT is an advanced business? Because DT is more to use big data technology to make predictions and perform rapid update iterations of the system. When in-line, such as a supermarket, we have to do is put merchandise, recommended, we are the day after the supermarket complete account, we do an adjustment working in the sector, such as the Dragon Boat Festival the next day, we The dumplings are placed in the most prominent position. When the business is online, for example in JD.com, it is going to be a holiday tomorrow. Consumers should choose some commodities that are needed for the holiday online. If IT is used to collect consumer needs, then the system will be improved. Consumers are about to run away with a mouse , so it is too late. In fact, you want multiple heterogeneous , real-time online according to the consumer's label, preferences will immediately recommend him one. So, on the establishment of a platform for big data D T, real-time analysis of end-user behavior, this can lead the business, knows what he wants, what he wants to do, we can do what the commodity process improvement, can Always meet the needs of consumers and improve his user experience. So this forecasting ability, the ability to grasp the trend of consumer demand is the number of businesses, our words and deeds, every move is quickly transformed into big data, and then into the insight and decision-making power of businesses. Big data will drive the innovation of all business processes , experience and efficiency industries as the most important means of production . Therefore , in addition to the understanding of the market 's thinking , the construction of business trend grasping ability is actually that we can go from offline to online. from IT to D T, the establishment of a platform based on big data, can always respond to changes in business, and even lead to business.

One of the two core capabilities is data science. Why is data science not popularized in many industries today, and now it has been popularized in Go. We have produced some excellent artificial intelligence robots such as Alpha Go to play Go . So why there is no Alpha Cat , Alpha Doctor , Alpha playing mahjong , that is because people who know data science do not play mahjong , and people who play mahjong are not good at data science. So when our business in the digital transformation, there is a class of people is very important that not only understands the business and understand the data and scientific talent, can the business effectively to describe the data of science, to achieve its efficient processing speed. Business use of all walks of life sciences data can be run more high intelligence, wisdom, health, wisdom transportation, urban brain, wisdom, travel, wisdom, customs, taxation wisdom, wisdom **, is to take advantage of the wisdom of the scientific data.

n Three stages :

The first stage is the dataization of the business. So far, many enterprises have not digitized all of their business. This dataization is actually a closed loop in the entire business of the enterprise. Find customers from the enterprise, follow up with customers after finding customers, and follow up with customers to do some customization or product design; after getting the order, we must form a service, produce products, and then need to transport, Collection. In the end, customers will give an evaluation of this product, feedback whether the product is doing well, and then go to the next wave of customers that affect the company.

This is from a socialized customer to a sales lead to an opportunity to an order to a service to a review, and then to a customer that affects your socialization. Such a closed-loop marketing, has the company digitized it? If it is said to be digital, then the first stage of the construction of the digital economy --- the digitalization of business is completed. At this stage, many excellent and well-known enterprises in the country, including some governments and institutions, have now realized the business data. From this collection of data, to data management to data modeling and analysis to visualization. Basically, these companies have screens for visual analysis, which means that they have basically finished this part of business data. Of course, there are many companies do not realize this logical process, many aspects of the data or written down on paper or in an excel sheet, and it did not go well in the system which records, statistics and analysis. In the course of business data, data quality management is very important, if the activity is not enough data, data quality, and data granularity, data dimensions, data correlation is not enough, the data collected will also affect business.

After completing the first stage, the enterprise entered the second stage called data commercialization. The data analyzed by the business can guide the business practice. For example, we found that he often watches some football news through online user cookies. He has also commented on a lot of football- related activities, and he is also very concerned about the recent World Cup. So when we go to the shopping site, can we recommend him some products related to the World Cup or football to meet his needs. This is the commercialization of data, and the results of data analysis are used to value and generate revenue. Many companies have not achieved this step. Internet companies may do a better job in data collection, processing, analysis, and guidance, but many of our traditional companies, such as manufacturing companies, have collected the defect rate of products, and he cannot pass This data is used as a guide, because changing the production line may cost a lot of money, and changing personal behavior requires many management methods. Therefore, the commercialization of data, in fact, I think is very challenging for traditional enterprises, completely using data to manage, let the data speak, data management, data decision-making, in fact, many companies can not do it now. This stage is a relatively long process. This process may continue for another 20 to 30 years in traditional enterprises . For example , the transformation of factory buildings , organizational structure challenges, and changes in government management systems will all affect data guidance business. What must be said here is whether all enterprises make decisions based on this data. Whether it is decision management or business, there are scientific and artistic elements in it. The recent World Cup said that the German team used the SAP system to do sports for players, guidance for coaches, and very good data analysis for the entire game. It is good to line up, but the German team still lost . Some people said that the German team lost proved that this matter is very scientific, but lack of the belief in winning, the key shooting and other artistic behaviors, and ultimately can not win.

Moreover, the commercialization of data must have the consciousness of the company executives, enterprise operation managers and other specific executives to be able to process and operate the data. In addition to consciousness, of course, there are also excellent technologies. Some business opportunities, such capabilities and technologies, as well as methods, are actually found in this stage. It is a very important part of enterprise construction at this stage.

The third stage is the intelligence of the business. We have reached a conclusion through system analysis, and then we can use the conclusion to adjust the system or optimize management and guide the work of the person. Then this is to write all of these into algorithms. , Let it execute intelligently, reducing human intervention.

For example, if an operator wants to call a group of customers, the call is automatically dialed out every time. When broadcasting, he may choose 10,000 phone numbers. People with different personality preferences choose different operators to communicate. After the exchange, the 10,000 telephone numbers may be answered for the first time, 5,000, and 3,000 in-depth communication after the answer. Finally, I have negotiated with you. There may be 2,000 purchase intentions, and finally, There are a thousand people who really have a business relationship with you. This is the data generated by an automated outbound call. Then the next time the company uses this data to make a call, there should be an automated scheduling. The person who has made this call before should not let him call again. This customer may not like him or there is a problem with his communication method; or if you have already purchased this product before, please do n’t allocate it; before a grumpy you can put a sweeter and gentle girl to communicate with her . Therefore, the entire process of the previous business is turned into an intelligent process, and he is continuously optimized. Of course, this is just a metaphor, that is, how to make the business intelligent.

Of course, in addition to this aspect of intelligence, we can also intelligently explore some sales leads, track some sales opportunities, make some order production, and even intelligently do some after-sales service, such as many chat robots now, we can do Intelligent product feedback and research, automatically go to the market to collect some of the shortcomings and advantages of our products, as well as some information about the natural language of consumers, and then use this information to improve our products and innovate and improve our marketing Methods and strategies.

Business data, data business, and business intelligence are roughly these three stages. We now often do some consulting and training projects. When we reach the customer, we basically know what he is like after talking with the customer. At different stages, the digital transformation of our enterprise that he needs is different. If you have n’t collected your data, it ’s very difficult to achieve intelligence. You do n’t have good business guidance data, guiding business ideas and specific people and scenarios to achieve it. You want to say whether this thing can Help me do it spontaneously, these are unrealistic ideas, we are doing this consultation with the company. By these three stages, we will immediately know what kind of solutions we want to provide to the enterprise through communication. Of course, these three stages are not absolute, and may be a mixture. It is also possible for enterprises to carry out these three stages according to their own business priorities. At different stages of development , the supply and marketing of the company ’s human resources, properties, and sales information systems and demand for D T system, the urgency is not the same.

n Next talk about the four aspects of the digital transformation strategy:

The first is the industry ’s data strategy consulting. What are the industry ’s changing trends? His policies, regulations, national investment, and industry development trends are crucial for an enterprise. In fact, it is equivalent to a large environment. When the environment is good, the company will be rewarded for investing in this area. When the environment is not good, the enterprise will make relatively little investment in this area.

The second one is operations , which is the index structure system of operations. We need to understand the industry. At present, leading companies have their advantages in operations, because each company will eventually form its own core management advantages during the establishment process. The advantages of these companies are What is the role of reference for our enterprise transformation, we need to know this.

The third is data analysis , because different analysis levels actually require different algorithms and models. We have a lot of excellent algorithms and the efficiency will be higher. We have a lot of excellent talents who can accelerate the enterprise ’s Speed growth and construction, so at the level of enterprise analysis, we need excellent algorithms and talents.

The fourth is tools . If you want to do the right thing, you must first sharpen your weapon. We need to implement our strategy, achieve better operating time and better business analysis. We need good tools, whether you choose Microsoft , Oracle , IBM , Alibaba , Tencent , Baidu, which big data platform , tool , SaaS, PaaS ... you will make some personalized choices based on your actual economic capabilities , personnel level , and business scenarios.

n Fifth is the construction of five

The first one is business mobility, because today it can be said that mobile phones account for eighty-ninety percent of the total time spent on the system , so the first five enterprises must be mobile, that is, the system should meet as much as possible Current user scenarios, mobile office, mobile business, and mobile needs.

The second is data productization, because data is easier to release its value through the product, you can turn your data, business of the enterprise into a data product, and your customers, employees, and leaders then explore the data to determine the data At the time, it can be obtained more conveniently and safer, so this productization of data is already a very important direction.

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