Understanding of digital transformation

Digitization transforms the atomic world and analog data into binary information represented by 0 and 1, and the physical world is represented by bit information. This process is digitalization. There is also a concept called data twins, which can also be used as another alias for digitalization.

With the development of computer and network, digitalization is rapidly changing the operation mode of many traditional industries, and even giving birth to new industries. The digital transformation of Internet companies is also guiding the digital transformation of many other industries.

In practice, Taobao and JD.COM have changed the retail industry through e-commerce, Alipay and Tenpay have changed the business model of the financial industry, Didi taxi has changed the business model of people's transportation, and the news media industry has changed beyond recognition after digital transformation. These changes have even changed people's way of life. The people who bow their heads in the subway, the ubiquitous payment code, and the couriers walking on the street are all products of this change. Both "internet plus" and digital transformation are becoming the trend of the whole industry. Maybe one day the world will be like the scene described in The Matrix, and the physical world and the data world will really merge.

In recent years, "digitalization" is quietly replacing "informatization", and the concept of informatization is no stranger. The traditional informationization moves the information inside the enterprise from word paper to computer, from person to computer and from computer to computer through the network, which improves the efficiency of information transmission and processing. Furthermore, information transformation generally needs to optimize the business process (BPM) of enterprises, and solidify and automate it through information systems, so as to reduce the cost of process control and provide business decision support. Enterprise information transformation represented by OA, ERP and CRM systems has actually existed for many years and has been widely used. Generally speaking, there will also be an information department in an enterprise, and CIO has become an important position in many enterprises.

Many so-called "digital" transformations are actually old wine in new bottles, which are not essentially different from the previous "information" contents, including system integration, data integration, data analysis and decision-making, and information access between upstream and downstream. These are not unique to digital transformation. However, there are some differences in the new concept. According to the definition, informatization can be regarded as the basis of digitalization, and the scope of digitalization is wider. And with the help of the latest technology, the change of IT infrastructure will also give birth to some new value propositions and business models.

Digital transformation is to integrate digital technology into all areas of business, and fundamentally change the way you operate and deliver value to customers. This is also a cultural change, which requires organizations to constantly challenge the status quo, conduct experiments and accept failure.

Digital transformation is to integrate digital technology and apply it to all business areas of the organization, thus fundamentally changing the operation mode and how to deliver value to customers. At the same time, digital transformation is also a cultural change, which requires organizations to constantly challenge the current state and experience and face possible failures calmly.

Another explanation is that "digital transformation is the use of digital technology to promote the transformation of business models, organizational structure, corporate culture and other reform measures." Digital transformation aims to use a series of new technologies such as mobile, Web, social network, big data, machine learning, artificial intelligence, Internet of Things, cloud computing, blockchain, etc. to conceive and deliver new differentiated values for enterprises. Enterprises adopting digital transformation will generally pursue new sources of income, new products and services and new business models. Therefore, digital transformation is the deep integration of technology and business model, and the final result of digital transformation is the change of business model. "

The government's definition of digital transformation is still there, that is, deepening the digital transformation of the government and speeding up the construction of digital government, which is a government governance revolution with inward edge. It is an all-round, systematic and remoulding reform of governance concepts, processes, methods and tools by using digital technology based on the four-in-one framework of "government concept innovation+information technology innovation+government process innovation+governance model innovation".

The definition given by the Global Digital Business Transformation Center (founded by Cisco and Lausanne International Institute for Management Development * * *, hereinafter referred to as DBT) is that digitalization is a variety of technological innovations realized through connectivity. Digital business transformation is to use all-digital technology to build a new business model, realize organizational change, and then improve business performance.

What is digital transformation? Briefly summarize your understanding:

In addition, I saw two statements and quoted them:

"Full service data, full data service" is a phrase that many Internet companies often talk about. I looked up some information about this popular word and found two explanations that I agree with.

Refers to the process of achieving business goals for customers, which is being digitized. In fact, business digitalization has long started, or it was called informationization before. The advantage of business dataization is that business can be described by mathematics to a greater extent, thus achieving more detailed operations.

In fact, it takes two steps to complete business digitization, namely simple digitization and process digitization (as shown in figure 1).

The general view in the industry is that data commercialization refers to finding out the rules in the data through secondary processing of the data deposited in the business system, making the data better understand the business, driving the development of various businesses with data, infiltrating the data into the operation of various businesses, making the data feed back the business, and finally releasing the data value to complete the closed-loop operation of the data value. The above definition focuses on explaining the business of data from the operational point of view, emphasizing the understanding, penetration and feedback of data to the business. However, this definition does not reveal how data drives business operations, nor does it explain its principle and process.

The author believes that the focus of data commercialization is the word "business", which is ostensibly to make data into business. In the final analysis, data commercialization should belong to the category of products or businesses, and should be defined from the perspective of data productization and commercialization. Based on this, the author redefines the data service. The author believes that the so-called data commercialization refers to: on the basis of data integration, the data is packaged into products, upgraded to new business segments, and commercialized and operated by professional teams in a productized way. From this definition, we can see that the essence of data commercialization is the productization, commercialization and value of data. As shown in the following figure, data commercialization actually emphasizes productization, new business and specialized operation, that is, data products are made with data as the main content and production raw materials, and commercialized according to the routine of product definition, research and development, pricing, packaging and promotion, thus turning data products into emerging businesses that can generate income for enterprises.

Data operationalization is a natural extension of business dataization, and it can also be said to be a sublimation, that is, the collected data is used for business or products themselves. There are mainly two levels here, one is data intelligence and the other is data innovation. The former mainly uses big data technology to enhance product experience, such as recommendation system and credit rating. The latter mainly uses the accumulated data to develop new business.

Turn data into suggestive signals and become the content to achieve business goals for customers. Therefore, analysts do operational funnel analysis, propose optimization schemes, and promote product iteration. This is not data commercialization. Because it is not facing customers, but facing enterprises. However, a website that packages and sells users' data to customers cannot be called data commercialization, because the data is not converted into content for customers to use and achieve commercial purposes, and at best it is called data reselling. Netease cloud music, according to the records of my previous listening to songs, judges my preferences through algorithms and pushes the song list to me. This is the data service. Business dataization belongs to the field of operation. Data commercialization is a product category.