The digital growth with unlimited imagination space, why is it stagflation and has not been realized? Because the company fails to solve a key problem of external customers and suppliers simultaneously: the full-cycle perceived value. To solve this problem, we can adopt the “pre-experience virtual reality” strategy. This strategy not only has theoretical support, but also has been on the road of practice. It can pass the “Digital Innovation Scene Lab” of Shanghai Wujiaochang Shuangchuang College. Case, understanding and learning the design and implementation of the “pre-experience virtual reality” strategy. K. Weick, founder of Sense-making theory, likes to quote the famous words of the British writer EM Forster to explain the importance of “perception”: “I don’t see it, I don’t know it” (How Can I tell what I think until I see what I say?). It has a fascinating meaning with the Chinese idiom “seeing is believing” – things or things that cannot directly perceive the experience are difficult to be recognized, recognized and recognized.
In the market, the perception of the value of goods by customers is also true. Only after an intuitive experience can the customer be willing to pay for the perceived value. If you are trapped in reality, when the company can only describe a future “blueprint” for the customer, is the customer willing to pay the bill? Is the venture capital willing to invest? Are partners willing to “take in”? Too hard! Between reality and the future, there is always a “gate of unknowns”, which has become the “scorpio” of rapid growth and fission in the digital world of the future. Passing through this “scorpio” is very difficult.
The prejudice and narrowness of people’s perceptions have become the first obstacle to digital growth! Customers are only willing to pay for “real” value, but the nature of digitization is “virtual”. As long as the “virtual truth” of digital value is not recognized, recognized and recognized, digital growth is always the “single-heartedness” of enterprises. The second strategic obstacle to digital growth is the subordinate position of digital capabilities in the value chain. Those familiar with the two dimensions of the Porter Value Chain understand that technology is categorized in the Support Activities of supporting and supporting activities. It is not a primary activity that is directly related to the customer.
Data resources have long been a comprehensive source of production and have not become the dominant digital capability to create new value. On the one hand, it is plagued by management habits. Managers are accustomed to applying digitalization to the process of production back-end. They are used to regard digital construction as a “cost center” to improve the efficiency of existing organizational functions at low cost, such as faster and less. Shorter and more visible. On the other hand, data resources have not yet grown to the stage of digital capital, and they are unable to demonstrate the dominant digital capabilities of independently creating new products, services, and processes. In the new book Digital Transformation, T. Siebel, based on the industrial revolution, advocates that digital transformation will bring 10 times speed, 300 times scale, 3000 times business and social impact.
However, in addition to seeing a growing investment in information technology and the number of computers, most companies have not seen the positive profit impact of digital transformation. Conversely, the difficulty of digital technology and the ease of replication directly undermine the profit base of 25% to 40% of traditional business models (McKinsey Research Report). For many Chinese companies, the impact of online stores on physical store profits is even more shocking. If data is recognized as capital, it must clearly dominate new products, new services, and new processes. Only when the value dominated by digital capabilities is intuitively perceived, digital growth activities will change from cost centers to profit centers, and will truly occupy the dominant position in the enterprise value chain. But it encounters the third biggest obstacle to digital value: the value of digital capabilities is lagging behind. K. Arrow, the Nobel laureate in economics known as “Information Economics,” tells the “paradox of information value” in the digital transformation: the value of information, not telling you, not knowing.
When you really understand, the information loses its value. In particular, subject to the intuitive perception of people, the value of the virtual stage can only be recognized, recognized and recognized after being presented in concrete physical form. In the face of the three obstacles that caused the stagflation of digital growth, the slang image of Master Xingyun broke the direction of thinking: “The four majors are all empty, and the five connotations are not true.” The first step in the digital growth strategy is to explain “virtual truth”, and the second is to be able to “show the existing.” With the blessing of big data, cloud computing, the Internet of Things, the Internet and artificial intelligence technology, it is already a reality that data resources become digital assets. The value creation of new products, new services, and new processes led by digital capabilities has also entered the organization’s regular activities. In the past, the real estate industry has evolved because of the “pre-experience virtual reality” strategy – helping customers anticipate the value of unrealized homes through model homes and mortgage loans. Today, digital growth must also have its own “pre-experience virtual reality” strategy. Through this article, we will show that the “pre-experience virtual reality” strategy not only has theoretical support, but also has been on the road of practice. On the theoretical side, we will explain that the “pre-experience virtual reality” strategy is behind artificial science, fitting thinking and applying attachment logic. In practice, we use the “Digital Innovation Scene Lab” of Shanghai “Wujiaochang Shuangchuang College” as an example to illustrate how to design and implement the “pre-experience virtual reality” strategy.
The article is divided into three parts: 1) Analysis of the reasons for the stagflation of digital growth. 2) Digital growth requires artificial science, fitted thinking, and attached logic. 3) Design and execute an instance of the “pre-experience virtual reality” strategy. Overcoming the stagflation of digital growth Digital growth has entered a stagflation phase for three reasons: 1. Failure to distinguish between data and digital capital, the potential efficiency of the company’s potential digital capital is low. 2. Customers can’t fully appreciate the new value created by digital capabilities without a full-cycle consumption loop. 3. Digital capabilities are fast-moving, and digital capital turnover is high. Upstream and downstream technology suppliers are not willing to commit easily. Data is an element of digital capital, and digital capital is data after organization. The data itself has no meaning and no purpose. Digital capital is meaningful, purposeful, and oriented, with a strategic feedback loop that can be self-organized and deeply studied. Failure to distinguish between data and digital capital makes it potentially inefficient for digital capital utilization. There are historical reasons for this situation, and there are also factors that strategize thinking behind the level of technological development. In January 2007, the first generation of smartphones appeared. Mobile internet set sail. In the next 10 years, most companies were “dataized” and simply relied on mobile device ports to naturally acquire data.
At the time, companies in the front lines of mobile Internet applications automatically received large amounts of data. Take the financial industry as an example, mobile payment is its most typical customer behavior data entry. The discussion of data privacy is temporarily shelved, and customers using mobile payments are basically unconditionally opening all relevant data to the enterprise. After experiencing the demonstration effect and internal self-learning of external leaders, financial companies realized that the interaction between bank terminal equipment and the core system of the bank is not the “8583” payment message in the traditional sense, but contains a large amount of user information and user portraits. Potential digital assets. Soon, all banks set up the Department of Big Data, and the new department collected and stored the data day and night to prepare for data assetization on a certain day. Once the collection system is put into use, the amount of data increases in geometric progression. However, the big data department of many banks is just an information archive that has changed the information medium (from paper to digital). It is not a leading department, it will not take the initiative to analyze the law of consumption behavior behind the data, and will not guide the development of new products and services based on analysis. If you love a certain brand of coffee, with high loyalty consumption and time and space, the bank’s Big Data Department does not remind you of the ability to run a coffee shop joint credit card.
The Big Data Department still performs the traditional banking model to give it the ability to accumulate data. Because there is no matching proliferative ability, the data is only resources, not capital. A digital asset is a non-monetary asset that is owned or controlled by an enterprise and exists in the form of electronic data and held in production activities for sale or in the production process. Reviewing the research of “Three Anchors Digital Currency Media” and scholar Pan Yun, digital assets can be divided into four categories according to their functions and their values, namely: 1) Data and material assets. Legally, data and material assets have clear ownership. From the source, it is accumulated by the main body participating in social activities and business activities. Formally, it is a collection of data that has a domain meaning in digital form. Its main value is reflected in the right to use ownership based on stored data.
For example, when you use the software in your phone and are asked to authorize, your behavior data has been legally collected and stored. 2) Digital currency assets. According to network contracts, such as blockchain technology, digital currency assets are issued. Technology can clarify affiliation. It can be circulated within a certain range and also has liquidity. The main value of digital currency lies in circulation and trading. The classic example is Bitcoin and the virtual digital currency (Libra) that Facebook recently tried. 3) Digital property assets. It is the result of intelligent labor that creates, disseminates, and clarifies ownership and use rights in digital form. Its main value lies in the dissemination and sharing of intellectual property products such as “Himalayan” and “Archimedes”. 4) Data model class assets. It is an information system model, algorithm and architecture for computing data. The data scientists and data computing platforms provide refined processing of digital data, the main value of which is refining and extraction. Some products and services generated using artificial intelligence algorithm patterns fall into this category.
For example, the fourth paradigm provides an artificial intelligence general algorithm and a combination of software and hardware services. The total amount of the above four types of digital assets is increasing, and the system using them is in serious shortage. Even with cloud computing technology, enterprises can collect and store data faster, more conveniently, and at lower cost, but stored data resources do not automatically become digital assets unless the enterprise establishes the digital capabilities to utilize the data. Therefore, we see a general strange phase: enterprises invest heavily in the new big data and cloud computing technology infrastructure, and the data they have in the diversity, quantity, speed and density are far different from the past. However, most companies still use traditional ideas to look at these data. For example, one of the companies we surveyed has a large group of companies that have invested in advanced IT technology to create meeting software. The software digitizes attendance and meeting time. However, no one in the company discusses how to transform the “contradictory thinking” in the meeting process into “swamp wisdom”. For the theme of the meeting, the effect of the discussion mode, using the electronic screen to speak anonymously, etc. The potential use of decision-making quality can be improved, but the company completely ignores the new organizational capabilities that can be developed. This meeting software is “overkill”. Looking at digitalization with traditional management thinking, it just digitizes the activities that exist.
Companies that are “dataized” generally only see technology inputs, but ignore the shift in management thinking. The former is getting more and more invested, the latter is unchanged, and the potential digital capital utilization rate is definitely low. Only by thinking about “what can digital capital be?” can digital capabilities be established. Taking the automobile industry as an example, looking at digital capital from the perspective of “what may become”, the new energy automobile industry uses digital capabilities to “float five petals” in order to overcome the stagflation of digital growth. It shows the difference between digital productivity and traditional physical productivity. On the one hand, subject to the economic law of diminishing marginal benefits of tangible entity resource investment, the growth of the traditional automobile industry has the boundary between production and consumption (the entity productivity curve in Figure 1). On the other hand, smart cars that are good at using digital capabilities can derive digital capabilities multiple times. Utilizing the productivity attribute of increasing marginal efficiency of virtual digital capabilities, enterprises can have multiple proliferating value innovation effects (the digital productivity curve of Figure 1 accumulates to the innovative productivity curve). There are two major changes in new energy vehicles. It removes the exhaust pipe and establishes a digital connection antenna that reaches the sky. According to the national standard GB/T 32960, each car will generate about 50MB of data every day.
In 2018, the global delivery of new energy vehicles increased by 69% compared with the previous year. This means that tens of millions of cars and car owners data are aggregated into the car factory, the birth of these cars. Therefore, the new energy automobile factory is actively developing how to transform from the automobile manufacturing industry to the “automobile service industry.” Based on physical productivity, using the derived digital capabilities, new energy vehicles are rewriting the new relationship between physical productivity and digital innovation capabilities.
New energy vehicles are constantly improving in the direction of digital capabilities, for example, increasing the size of on-board smart large screens, real-time fault monitoring to reduce spontaneous combustion accidents, collecting component status information, built-in consumer driving behavior and energy consumption analysis. These digital capabilities were originally designed to improve the quality and driving experience of physical vehicles. Once formed, digital capabilities have become a source of value for many new business forms. In one of the author’s book “New Technology Winning”, we list at least five modes of future car life and work ecology: 1) base stations for personal mobile communications; 2) mobile robots with simple functions like the concierge; ) Digital information interface for trust and credit; 4) Fourth place outside the home, office, social place; 5) Under the support of AI technology, it is like a “Transformer”, becoming a human-machine complex, more Enhance the life and work ability of natural persons. It embodies the composite development trajectory of the digital production curve (the composite digital innovation productivity curve of Figure 1). Technology has already existed, and what is lacking is the supporting management thinking.
The new four modernization of the automotive industry has become a consensus: electric, network, automatic, sharing. The technology that has derived the new consensus already exists, namely ABC+IOT (artificial intelligence, big data, cloud computing + Internet of Things). From the management thinking, the digital growth of the automotive industry must also be adjusted to the dialectical thinking that the physical business and digital capabilities are yin and yang, and gossip. The evolutionary relationship between the entity and digital productivity illustrated in Figure 1 illustrates this dialectical thinking. The tangible physical production process is subject to the economic law of diminishing marginal benefits, and its growth can only be within the boundary curve of physical productivity. With the promotion of new technologies, the productivity boundary line can be expanded outward. But if it follows the traditional physical business model, it will be subject to the new physical productivity boundary. Virtual digital capabilities have the attributes of network effects and marginal benefits. It has the potential to expand at a low cost.
When digital capabilities lead the way in leading new products, new services, new processes, and new markets, it becomes a composite digital innovation productivity. For the dialectical relationship between the two, digital transformation experts Xu Shi and Yan Yanchun said that the physical productivity is “mother business”, and the new business derived from digital capabilities is “public business”. The male-female business is a vivid metaphor for the relationship between new digital capabilities and traditional core competencies. It should be emphasized that 1) the derived public business can be born with the environment, not just one. 2) The deep learning capability that comes with digital capabilities produces a composite digital innovation productivity (see Figure 1) (CDDC, Compound’s digitalized dynamic capability). It is not a superposition of simple abilities, but a rapid evolution using AI’s deep learning capabilities. In December 2018, after “AlphaGo”, “Deepmind” launched “AlphaZero”. It uses the Neural Network and adopts the method of Reinforcement Learning. It takes only 30 hours, from complete ignorance to the master of Go, and defeats the previous generation of “Alpha Dog”. To reach the level of deep learning in the laboratory, there is still a large distance between the digital capabilities of the enterprise. However, the technical principles are exactly the same as the composite digital innovation productivity strategy.
Since the principle of overcoming the internal digital capabilities of digital growth stagflation is already clear, why is growth still not going to occur? That’s because companies also need to simultaneously address a key issue for external customers and suppliers: full-cycle perceived value. For customers/users, before the completion of the full-cycle consumption closed-loop construction, customers can not fully experience the new value created by digital capabilities. For suppliers, digital capabilities are fast-moving, and digital capital turnover is high. Upstream and downstream suppliers are not willing to commit easily. As shown in Figure 2, while understanding the yin and yang dialectical relationship between digital capital and physical business, enterprises also need to use digital capabilities as a driving force to build a complete consumption closed loop for customers. The closed-loop experience of consumer value was the core of Apple’s successful business model that year. Apple Music Consumption Closed Loop (L:Loop), application package developers (AD: Application Developers), they work together: L = AD* (Ipod + Itune).
The closed loop of this value experience is the basic element of the Apple Ecology. In contrast, most companies can only provide fragmented, fragmented digital experiences. Take banks as an example, each of them emphasizes the “digital banking” strategy. In the implementation process, digitally-enabled technology companies bring a blueprint for the overall transformation of the digital transformation, but each department can only choose to promote the part that is the easiest to implement. A bank outlet, which is under the responsibility of the administrative department, is managed by the operations department, and the technology is managed by the Ministry of Science and Technology. Each department has a part of the production materials that create the value of digital assets, but the management authority and departmental interests are for each decision maker. A business “shaft” was established, separated from each other. Because the department’s goals and interests are optimized, banks can only provide intermittent digital experiences. As a result, digital banking 3.0 and the ultimate user experience on the blueprint cannot be achieved as a whole.
Without a full-cycle consumption loop, consumers can’t fully experience the new value of digital capabilities, so they are not willing to pay. Such situations are also common in other industries. For example, both Google and Amazon have developed intelligent voice control products. Many people figured out freshly when they bought Christmas gifts, and then they didn’t open them. What consumers need is not the product, but the value effect brought by the product. Because of the virtual nature of the digital economy and the systemic integrity of the consumer process (such as WinTel, Windows*Intel), consumer demand for a full-cycle closed-loop value experience far exceeds the real economy era. Establishing a full-cycle consumption closed-loop experience is an essential element in building a digital ecosystem. However, the closed loop requires the commitment and participation of upstream and downstream suppliers. As part of the entire digital ecosystem of innovation innovations, vendors are returning to the same cycle of perceived experiences: for virtual innovations inspired by digital capabilities, suppliers need an intuitive perception experience more than the ultimate customer. In the process of digital innovation industry collaboration, suppliers not only need to intuitively perceive what they can contribute, but also need to perceive the ability of the partners, and they need to share the process of system production. The general hesitation and hesitation of suppliers is rational.
The future of digital innovation is full of temptation because of the “flowers in the fog”, but because of the blurring of the touch path, it is very easy to become an illusion of “mirage”, not real enough. The technical route of digital innovation is itself a process of multi-factor contradiction and competition synergy: from a systemic point of view, on the one hand, digital technology is systematic, and suppliers of all parts of the infrastructure need to consider compatible functions; Digital technology is rapidly iterating in all dimensions. Choosing the wrong technical route and framework partners is the determined martyrs. From the perspective of organizational ecology, on the one hand, each technology development has experienced an open innovation and rapid trial and error. On the other hand, partners hope to form an exclusive system coupling relationship and maintain the stability of the established ecological environment; from the perspective of input-output value, on the one hand, the assets supported by virtual digital capabilities have a replication cost of zero, the network The effect, marginal incremental benefits and the temptation of ecological rent; on the other hand, its investment is highly specific and targeted, and once the route is wrong, everything is a bottom-up cost. End-users, enterprise customers, and virtual industry chain suppliers, the intuitive perception of these three links has become the three mountains in the process of virtual innovation cooperation. At this point, the three reasons for the stagflation of digital growth are all at the same point: although virtual digital capabilities have unprecedented potential, the virtual reality of digital innovation value is difficult to be recognized, recognized and recognized as long as it cannot directly perceive the experience.
We mentioned earlier innovations in the real estate industry: the use of model houses to provide the effect of “pre-experience virtual reality” for uncompleted commercial houses, and then to advance the value of real housing through financial securities such as mortgages and uncompleted buildings. The “pre-experience virtual reality” strategy of digital growth is far more complicated than real estate. But the mechanism is the same, and they are all designed to deal with the challenges of intuitive perception. Through the “pre-experience virtual reality” strategy, we can overcome the digital stagflation. Below, we will explain the relevant theoretical concepts first, and then report a practical case together. The theory of “pre-experience virtual reality” The value of digital innovation is first and foremost presented in virtual reality. Virtual reality and reality are equally reliable and exact. The three stakeholders involved must have a suitable form to pre-experience the full-cycle supply chain production process and the consumption process of virtual product services. The theory of “pre-experience virtual reality” explains artificial science, fitted thinking and abduction logic.
They explain the feasibility of the strategy on a theoretical level. Support real and virtual true narrative language text In the face of the human brain’s ability to deal with language, facts and virtual facts have the same certainty, which is the true meaning of judgment. For the intuitive perception of the perception of factual thinking, we need to test again. According to whether we can intuitively perceive, we divide cognitive activities into “real” and “virtual”. Perceptual organs include “eyes, ears, nose, tongue, body, and meaning.” We have a preference for the perception of the visible and used physiological organs, and the ability to perceive the “intention” (brain thinking activity) because of animal habits. Modern brain neuroscientists and phonetics reveal the laws behind prejudice. In the May issue of this journal, one of the authors reported in detail the conclusions of modern scientists on the cognitive law of human beings in the “Starting the Dualistic Organization Crisis Narrative Law”: human beings are language animals. Intuitively perceived signals are still converted to language (such as self-talk) and affect human behavior. The perceptual effects of physiological organs and thinking activities are organized through the narrative language in the brain. Therefore, in the reference system of narrative language, there is no exact difference between the “reality” of physiological organs perception and the “virtual truth” that is thought through language communication, which can be the basis for people’s prediction, judgment and action. Regarding the exactness of the virtual, the previous article has done the following analysis: 1. Neuroscientist Beau Lotto studies the source of the brain’s judgments and finds two types: realistic empirical data (see, touched, heard), virtual imaginary data (imaginary, deduced, illusory) of).
The data itself has no set meaning. It only provides a precondition for people to perceive activities. The brain interprets the data in relation to each other and gives meaning. The linguist Marie-Laure Ryan’s “narratology” finds a commonality behind real and virtual reality: no matter what kind of data source is explained, human thinking is behind a set of linguistic narrative texts. Both real and virtual truth can be abstracted into the logical consistency and accessibility of linguistic narrative text. As long as you can use the narrative text to think through, it is true. Reality is really the truth (seeing, touching) that is approached and confirmed through concrete actual body perception. Virtual reality is the truth that is approached and confirmed through imagination, simulation, deduction, and gameplay. Through the narrative language of the level of thinking, the reality and the virtual reality are unified into a worldview. In this unified worldview, according to Ryan’s narratological theory, reality has already happened, and virtual reality is likely to happen in the future. The difference is that there is only one world that has already happened, a world that has been perceived by people. There may be infinite worlds that may occur. 2. People have a natural preference for reality.
On the surface, it is because the reality is highly predictable and certain. In fact, it is because the real data (see, hear, smell, etc.) is easy to access because of the existence characteristics of the sensor. To understand from neuroscience and linguistics, real data must be transformed by thinking language. In the narrative text of thinking language, perception is a pyramidal narrative process. Whether it is perceived to be true or false, it is influenced by three things: the instinct of the brain’s memory, the context of the perception, and the perceived activity that gives the data a meaningful relationship. If the perceived phenomenon is interpreted in a complete and consistent manner, and the interpretation is helpful for prediction, then it is true, otherwise it is false. Reality is still a reality, it depends on the language narrative text in the process of perception. Ryan believes that the reality of real perception is also to deal with empirical data through language narrative text. 3. People have a natural rejection bias against virtual reality. On the surface, it is because the virtual reality does not exist yet. In fact, because virtual real data (hypothesis, simulation, simulation activities, etc.) is difficult to access, because our biological sensing organs need artificial technology to process these data. It is entirely possible to approach and orchestrate this data since it has artificial intelligence, information technology, and VR technology. After the artificial technology conversion, the virtual real data achieves the same brain thinking effect as the reality, and undergoes the same narrative text interpretation, and is subject to the same true and false judgment. According to the “narratology” theory, in the world of linguistic narrative texts, virtual reality and reality are equal and homogeneous. Linguists and neuroscientists have found that in the world of linguistic narrative texts, the two are not only unified but also mutually exclusive. The only difference between virtual reality and reality is the amount of existence. The physical industry (mother business) is true. It has happened, has been perceived once, and has been in constant connection with various tangible concrete things. Therefore, its reality really only exists in a world, an already realized world. Digital innovation (public business) is virtual reality. They have infinite possibilities, they are not limited by spatiotemporal situations, they can exist in multiple virtual possible worlds at the same time. Virtual possibilities, multiple worlds exist at the same time, and are not restricted by specific real objects. These are the favorable conditions for digital innovation.
The Wujiaochang Innovation and Entrepreneurship Institute (referred to as Shuangchuang College) organized by the Yangpu District Government of Shanghai has tried to implement the strategy of “pre-experience virtual reality” by means of “digital ecological co-creation camp”. Their case shows that with the expected application scenarios, real customers can design a digital new business cycle full-cycle consumption closed loop. It not only allows end consumers to experience the value of digital innovation in advance, but also unites a series of “virtual truths” that upstream and downstream suppliers perceive new formats, pre-preparing the roles and digital capabilities involved. Shuangchuang College fits into two important concepts of the theory of “pre-experience virtual reality”: fitting thinking and abduction logic. Fitting thinking and abduction logic of artificial science Inspired by Marx’s Critique of Political Economy, productivity determines the relationship of production, and production relations counteracts productivity. The two together affect the formation of production methods. Production methods not only refer to technology, but also include the world view and thinking methods behind the technology. As an unprecedented technology for human beings, the potential that virtual digital capabilities can achieve and the objects that can be served are generally different from the past physical capabilities. A paradigm represents a series of corresponding worldviews, epistemologies, and methodologies. Corresponding to the productivity of virtual digital technology is the anthropomorphic logic of the world view of artificial science, the epistemology of fitted thinking and the guiding design method. Nobel economist H. Simon first proposed the “Social” form of management in the field of management, which is different from the natural world. The Sciences of the Artificial should have a fitting mind, follow the absolution logic and use design methods. His “artificial science” theory 50 years ago was the right time for digital transformation.
Simon believes that physics, chemistry, etc. are natural sciences. Natural science is a simple law behind the discovery of seemingly complex phenomena. Engineering, economic, and social development planning are the sciences of the artificial. Artificial science is to design and achieve the goals pursued by people and society. The man-made science is forward-looking, looking at the future tense, design-oriented. Design is to create a series of process activities, through the production of “Artefacts” (literally translated as artifacts), designed to help the “customer” transition from the current state to the pursuit of state. Simon believes that in the era of artificial science, it is more appropriate to fit the thinking. Analytical thinking applies to the research and discovery of the natural sciences because it assumes that the objective world has a law waiting to be discovered. In the human world, everything is thought out by people. Economics, urban planning, and even information technology, they are not natural, they are all people think of. For the world you want to come out, fitting thinking is more appropriate. Fitting refers to the goal of artificially imagining, creatively integrating existing elements, and creating ingredients, techniques, and forms that have never existed before. Human fitting activities can have natural components, but are not completely restricted by nature. People can use natural conditions to achieve people’s wishes and goals. For example, the periodic table of elements is a rule of chemical analysis. Synthetic chemical materials are new substances that people produce according to the law and according to the functional goals of human needs. The fitting needs to obey the laws of nature, but the materials and phenomena after fitting have their own new laws and artificial laws. Simon emphasized that after the advent of digital computers, the characteristics of artificial science became more apparent. Digital calculations are faster, more abstract, and more symbolic, and are more suitable for simulating system behavior. Because of abstraction and symbolization, the use of fitting thinking is more space.
People can simulate fitting activities in the digital world, virtual design products, and modify, perfect, and then real production at the virtual level. Compared with the publication of “Artificial Science” 50 years ago, in the post-Internet era, the ABC digitization capabilities of Artificial Intelligence, Big Data, and Cloud Computing have undergone geometric progression. Variety. Applying Simon’s “artificial science” thinking, ABC’s ability has made technical preparations for comprehensive subversive changes in social and economic activities, namely in the form of digital simulation: 1) designing supply and demand relationships; 2) testing production and consumption processes; ) Building customer value preferences; 4) and helping customers experience the value of delivery. Associated with the fitted thinking is the Abductive logic. Popular translation, abduction logic can also be called “attachment logic.” The attachment is a fusion. Liu Wei’s “Wen Xin Diao Long·Attachment” contains: “What is the attachment? It is the general arts and sciences, the system is the first and the last, the set and the win, the end of the world, the first one, the one that makes the miscellaneous and the more.” As a method of reasoning, the American philosopher Charles Peirce uses abduct logic to distinguish between inductive and deductive logic. He suggested finding the most explanatory theory among all the possibilities. This theoretical explanation is not necessarily absolutely correct, but it must be the most likely and closest to real knowledge at that time. In the exploration of knowledge, the abduction logic has a “gradually certain” attitude towards the phenomenon that is not known. It does not care about perfect interpretation, and it is more inclined to answer the highest probability of the moment. It accepts theoretical standards that are satisfactory under limited conditions.
Pierce does not oppose the logic of induction and deduction, but believes that the logic of abduction can open people’s ideas in an unknown state, develop more hypotheses, and lay the foundation for the next deduction and inductive reasoning. Pierce’s abduction logic also deeply influenced the “pragmatism” philosophy. Pay attention to practical effects, accept a constantly improving attitude, and emphasize “thinking” as a “doing” service. This pragmatic philosophy illuminates the torch of thought in the process of American modern industrial revolution. For the abduction logic, many natural scientists disagree that it is not as rigorous as deductive and inductive logic, and lacks the reliability to repeatedly verify hypothetical relationships. But there are also social scientists who hold the opposite view. They believe that the falsification method of the natural sciences is an “inference to the Worst Explanation” (IWE), because the conclusion style of the orthodox mathematical statistics method must be “assuming no causal relationship, the proof conclusion is ‘Cannot rule out causality.’ The attitude of this falsification method is negative and cautious. It is of great help to the natural sciences in finding objective laws. However, in the social sciences, negative or positive attitudes directly affect the effects of social practice. In contrast, the abduction logic is “Inference to the Best Explanation (IBE).” Its methodology is in line with the attitude of positive action. The abduction logic is once again highly regarded, not only because it is compatible with new social science thinking such as artificial science and fitted thinking, but also found to have complementary links with synergy in natural science research and Belles probability theory. In this regard, it is discussed separately. In short, when discussing virtual digital innovation, we must not only accept the “artificial science” worldview, but also the epistemology of fitting thinking and abduction logic.
The case we will discuss next reflects the above theoretical explanation from a practical perspective. Digital ecological co-creation camp How to create a digital new format based on the data accumulated by the original entities? How to help corporate customers pre-experience the value of new business? How do you let suppliers feel the innovation possibilities brought by system synergy? These three issues correspond to the three causes of the stagflation of digital growth. In theory, we put forward the strategy of “pre-experience virtual reality”. In general, the reliability of the new theory requires a large amount of historical empirical research to support it. Before the new theory did not have a lot of evidence, there were always some brave practitioners who pushed the innovation model first with a keen market sense. The “Digital Eco-Creation Camp” (referred to as the Ecological Camp) of Shanghai Wujiaochang Innovation and Entrepreneurship Institute is a representative case. In our opinion, the lab is using ABC’s technical capabilities to try to “pre-experience virtual reality.” The basic activities of the laboratory include: 1) inviting large enterprises to propose their own innovative wishes and needs; 2) inviting small and medium-sized enterprises in the region to simulate new business formats that fulfill customer wishes and needs; 3) customers in the digital supply and demand simulation supply and demand process Experience the feasibility of the new format, understand the value of the new format to their end customers; 4) Participate in the enterprise to understand the digital ecological relationship, recognize their respective roles, the conditions for cooperation between upstream and downstream. 5) Considering the advantages of virtual technology, the participating parties complete a full cycle experience of production and consumption.
Figure 3 shows the work plan of the digital eco camp. Let us see how this work program can be applied to the automotive industry. Taking a large enterprise in the automotive industry as a corporate customer, a group of small and medium-sized enterprises fit their new business formats in the automotive industry with their different digital transformation technologies. The following is a memorandum of cooperation between corporate customers and digital transformation providers. Presented: large car customers From: Digital Innovation Supplier Alliance Theme: Developing digital assets for large car companies Industry Background: The automotive industry is a traditional industry, but has gone through at least three revolutionary stages, from mechanization to electronics, from regional manufacturing to global production, from brand-led to service value-added. Car companies are entering the fourth revolutionary phase: from vehicles to car networking, a new species that can rely on digital capital to derive a variety of formats. The digital capital of the Internet of Vehicles: With the brand of car enterprises emerging in the form of new energy sources, Tesla, Weilai, Xiaopeng Automobile, etc., are accumulating new energy sources for vehicles and enterprises. After the Internet + car, the attraction of the car company has two attractors, tangible cars and intangible data. With the ABC technology blessing, the value of the Internet of Vehicles is skyrocketing with the attraction of intangible data. In theory, every car company must pay attention to digital transformation. Every car must be viewed in the concept of car networking, because it is a service node in the transportation service transportation process, and the car company has the most complete data, it knows The most secret. But this is not the case. On the one hand, car companies generally know that they need to install a large number of sensors for new cars, and even increase the car entertainment facilities, so that the car becomes a digital experience medium that is n times larger than the mobile phone. On the other hand, car companies have no endogenous strategic force to convert large amounts of data into digital assets.
The big data department of the car enterprise is similar to the big data department of the bank. There is no dominant position. For the two sides of the car – both physical form and The digital assets generated during the interaction between the people and the car, the helm of the car enterprise has a good understanding, but the cognitive and operational directions are not utilized. Our role and contribution: We are a group of potential suppliers with deep technical expertise. Our role is to serve the digital value innovation of car companies. Based on the professional background, we share a variety of application scenarios for digital capital with car companies. Using the characteristics of digital technology virtual simulation, we designed a system closed loop of “production-marketing-consumption-service-upgrading”. In this process, each participant in the closed loop of the system can experience the value in advance, pre-perceive the synergistic production and consumption activities, and pre-understand a complete business operation requirement and characteristics. Strategy initiation activities: 1) A common understanding of the potential of digital capital. 2) Bring home the digital capital. Data must be returned to the car to reflect the dialectical relationship between the “public business” and the “parent business” between the physical business and the digital business, in order to reflect the virtual reality in different application scenarios (the value of consistent expression, production and Consumption activities). 3) Start with a familiar entity and digital format link. First, quantify the life cycle of the car. Second, organize significant data, such as driving habits and travel habits.
Thirdly, refining customer data for the most value-added financial services business (helping banks do consumer finance, credit card business, helping securities companies to do data-based risk control, and helping insurance companies do big data actuarial). At the same time, pay close attention to the development trend of “data sovereignty” technology, making it difficult to replicate business models. Tangible and intangible outputs: 1) A systematic, mutually exercised programme.
2) A clear set of supply chain partnerships. 3) A digital format value that has been experienced. 4) A true commercial commitment to create synergy. The working direction of the digital ecological camp is consistent with the “pre-experience virtual reality” strategy theory. From the perspective of future refined management, it can also learn from the strategic theory and enhance the experience in four aspects (see Figure 4): 1) Product tokens. The product is regarded as the medium of value transmission, and in the form of design intangible and tangible output, it vividly reflects the relationship between production and consumption that is worth pursuing. At this point, the product becomes a token of the value signal.
2) Organize activities. Only after the interactive activities become a series of routine activities, people will feel the institutionalized industrial chain cooperation and feel the promise of stability. Establishing successful routines (Routines) is the basis for all parties to recognize, recognize, and recognize synergies. 3) Composite system. Digital capabilities are based on physical production. Once generated, it empowers and proliferates the entire system. In this way, there is an organic and mutually beneficial relationship between digital productivity and physical productivity. The closer the relationship is embedded, the more orderly, the higher the system recombination level, and the stronger the system supports the subsequent innovation format.
4) Language compliance. Virtual systems are created by people and serve people. People are the “animals” of language symbols. Form a set of exclusive language symbol system, which provides a cultural system that nourishes cooperative behavior for collective activities that experience “pre-experience virtual reality”. There are many ways to implement the “pre-experience virtual reality” strategy. Participants in the Digital Eco Camp developed the implementation method of the “Scenario Lab” using the resource conditions of “Double Innovative College”.
It is a choice worth learning. Large companies, such as Ali and Tencent, can use internal testing platforms to help internal departments and core customers to experience digital innovation products in advance, and have already achieved results. However, the internal test platform of large enterprises is based on the subjective will of the core enterprises. Most of the selected ecological enterprises are “invested” or “submitted” and have certain limitations. From the perspective of the big ecological point of no presupposition, the best platform of the scenario laboratory should be a socialized alliance platform to test virtual digital ecological products. The government background and non-profit characteristics of “Double Innovative College” just set the conditions for establishing a socialized virtual cooperation platform, and all the capital and government support funds need to find new economic kinetic energy through this new ecological way. seed”.
In the first phase, Shuangchuang College organized small and medium-sized enterprises with deep technology to establish a common thinking framework for thinking and discussing practical issues around digital innovation. In the second stage, using the credit of government agencies, large companies that have experienced digital ecological dividends, such as Shanghai Pudong Development Bank and Haitong Securities, are invited to participate in the course to “send strategic issues” to potential technology suppliers. The strategic issue has both the “bottleneck” task at the present stage and the forward-looking vague thinking. The third stage is to jointly plan projects worthy of research and development. In the fourth stage, a commercialization method, model and landing route are formed (see Figure 5). The digital eco-creative camp and scenario lab has just begun.
The empirical data for judging it has yet to be collected. However, we know that it is a temporary advanced practice: 1) It embodies the theoretical concepts of “artificial science”, “fitting thinking” and “astrolog logic”. 2) A similar approach has taken effect elsewhere. The “design sprint” developed by Google Ventures, a Google company, is based on the same theoretical concept. The “design thinking structure” developed by Ideo Design and the Stanford University School of Design is the same construction process. 3) It is more regular than other current innovation resources organizations.