Look at the world from another angle - business automation

Look at the world from another angle - business automation

In work and study, I often come into contact with a lot of interesting knowledge, including business model analysis, management refactoring, and new autonomous driving technologies, etc. I also have some insights into the overall logic and application of future business, so I wrote the following essays, hoping to share them with you. The essay consists of four parts: the automation of business models, the long-term integration of talents and specialties, further discussion of corporate values, and future business trends. Due to time constraints, the first part is temporarily completed.

1. Automation of business models

The topic of automation seems to have been talked about for a long time. There seems to be nothing new about the robotic arms of manufacturing companies, automatic sorting, automatic driving, etc. But if you think about it carefully, the automation of business models is rarely mentioned and studied. How to see the world from the perspective of automation, how to understand the world from the perspective of automation, and what is the thinking logic represented by automation?

I will explain my understanding of business model automation from three aspects: standardization of non-standard scenarios, sharing of human experience, and automation from 1 to N.

(1) Standardization of non-standard scenarios

At present, the most talked about in the technology industry is autonomous driving. Simply put, autonomous driving is how to use technology and algorithms to realize the safe driving of cars in complex real-world environments. Its essence is the standardization of non-standard scenarios. As the basis of the Industrial Revolution, standardization enabled mass production and management. So whether the future is standardization or personalization, there are many debates. I think the two are not contradictory, because higher-level standardization is precisely the basis of personalization.

You can see that with the development of technology, there are more and more personalized products, such as the personalization of car colors and accessories, the personalization of birthday gifts and so on. These were unimaginable in the past, because the standardization of general understanding means that the output is the same. But today's standardization is quite different from what everyone thought before. The enterprise has realized the segmentation of the product production process, and at the same time realized the standardization of the modules for individual needs.

A typical example is the customization service of a car company, in which customers can choose the color of the car, so the color of each car produced is different. This was unimaginable before, but now this printing module can print different colors for each car like a color printer, so as to realize personalized standardized production.

The standardization of non-standard scenarios reduces the role of people in non-standard scenarios and realizes the automation and personalization of business applications. It is gradually moving from simple product manufacturing to car driving, personnel management, and even business management and operations. In the later stage, we will take the amoeba model of Handu Clothing House as an example to analyze how the non-standard scenario of human resources management has achieved a higher level of standardization, ensured differentiation, and realized the automation of personnel management.

(2) Sharing of human experience

The basis of human survival is experience, and the acquisition of experience depends on trial and error. Due to the complexity of the natural environment and the fierce competition, trial and error in all directions is required under the same ecosystem. At the same time, in order to avoid systemic destruction caused by specific risks, organisms reduce systemic risks through diversity. Through the natural law of the survival of the fittest, experience is accumulated, continued and developed.

Therefore, when the ecological environment is more complex and changeable, there will be more trial and error samples. However, individual organisms are isolated islands of information, and the sharing of experience accumulation is poor, and there are a lot of repetitive trial and error. There is a certain waste of resources and low efficiency in this mode.

How can experience be shared quickly and avoid waste of resources? How can the rapid development and anti-risk stability of the system be achieved? These have always been difficult problems for human research.

In the past, we relied on writing, books, communication and exchanges to share experience. Are there better tools and ideas to solve these problems, what business models are doing these things, and where will the future model go? Maybe now we are approaching the answer with "cloud" + algorithm. Now everyone is feeding the algorithm with their own experience, and at the same time, the algorithm realizes the sharing of experience through efficient computing such as "cloud", and feeds back the improvement of trial-and-error efficiency. In the later stage, we will take autonomous driving as an example to analyze how "cloud" and algorithms can improve efficiency and stabilize the system.

(3) Automation from 1 to N

Due to the standardization of non-standard scenarios and the sharing and rapid iteration of experience, the society has now realized the mass production of commodities to the automated mass production of business models. Business development can be divided into many stages, such as from 0 to 1 stage, from 1 to N stage, from N to N+1 stage and so on. Personally, I think that the automation of the current business model mainly solves the automation from 1 to N.

Due to the standardization of non-standard scenarios, the barriers in the rapid promotion and replication of business models have been greatly reduced. In the past, we mainly relied on people to promote a certain business model, but the difference between people is relatively large, and the results achieved vary widely. Yes, and in management, as we know, the management of people is the most difficult. The standardization of non-standard scenarios reduces the barriers caused by individual differences in a specific business model. Our common examples, such as Didi Taxi, have standardized the non-standardized scenario of taxi-hailing, which has great individual differences; For example, sharing bicycles, standardizing short-term rental bicycle scenarios, and so on. These enterprise models have achieved a rapid transformation from 1 to N, and it took only a few years to realize the rapid replication that other enterprises have used for ten or even decades. (The author once used another perspective to analyze the existing business model: the essence of the current business model is the input and feedback of the human ecosystem. At this stage, the essence of enterprises is the system input method. How to realize batch standard input is the main task of modern enterprises.)

On the other hand, as the size of the previous enterprises grew larger, they often faced the dilemma of being too big to turn around. However, due to the increasing number of company levels and the distortion of information transmission, the ability to adapt to the natural environment has changed with the size of the enterprise. expanding and declining rapidly. Due to the sharing of human trial-and-error experience and the flattening of management, the current business model has gradually changed to "big, medium and small front desks". The efficiency of product iteration is greatly improved. Flexibility continues to grow. At the same time, due to its evolutionary efficiency and flexibility, in response to "natural disasters", the diversity of samples can be reduced, and the ability of ecology to resist systemic risks can be realized. In the later stage, Bianlianfeng will be used as a case to analyze the automation of operation and management, so as to achieve rapid expansion from 1 to N, and maintain a competitive vitality far exceeding that of the industry.
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