China's computer software industry analysis 1-workers

 

At present, the level of Industrial Science and Technology is far from reaching the degree where all machines replace humans. The main productive forces of all industries are workers, and workers are the most fundamental factors in all industries. Therefore, to analyze the industry, we must first analyze the workers in this industry. Here, we first analyze the computer software industry from the perspective of workers. [Yuan Yongfu copyright Co., http://www.sinoreport.net/]

Mental Workers

Computer software and other intellectual property-based industries are mainly engaged in mental workers. Therefore, the analysis of intellectual property-based industries must analyze mental workers.

Mental labor refers to the main body of labor, such as thinking and memory, which is dominated by the movements of the adult brain system and supplemented by the movements of other physiological systems. Only humans can perform mental work.

Mental labor can be divided into the following mental labor for creating knowledge (such as scientists), mental labor for imparting knowledge (such as teachers), and mental labor for managing knowledge (such as enterprise leaders) and achieve mental work of knowledge (such as engineers ).

Compared with mental workers, physical labor is labor dominated by physical labor consumption. In a broad sense, it is not only human beings that can perform physical labor. For example, in agricultural production, cattle are physical workers only in the labor process, but cattle are animals and human rights are born.

Mental labor production has the following shortcomings.

 

Fewer producers

Mental workers must have scientific and cultural knowledge, basically with a college degree or above. Even after graduation, they also need to go through long-term exploration and learning to develop practical production capabilities. It takes tens of years and a lot of money and social resources, and not everyone can become a mental worker after learning and training.

It also needs to be carefully taught when training new mental workers, which consumes a lot of energy from active mental workers, reduces the output of active mental workers, and increases the training cost of mental workers.

Due to the long training time, high training cost, and low achievement rate, the number of mental workers is small, which becomes a scarce labor resource, and the excellent ones are the targets of competition of various enterprises. Therefore, the small number of mental workers makes the intellectual property industry unable to achieve industrial production.

Physical workers are able to produce data in batches, resulting in a large quantity and low training costs. As long as you are healthy and have a normal level of intelligence, you can be competent. Therefore, traditional industries can easily obtain enough physical labor to achieve large-scale industrial production. [Yuan Yongfu copyright Co., http://www.sinoreport.net/]

 

Unstable Production Efficiency

Mental workers have large individual and time differences in productivity.

The process of mental labor is thinking. There is a big difference in the way and cognition of each person. Therefore, the labor ability of different mental workers varies greatly.

In addition, the process of thinking is greatly influenced by people's emotions and the surrounding environment. Therefore, the ability of a mental worker to work varies greatly from time to time. When the mood is high, the ability to work may be several times higher than when the mood is low.

When people encounter problems and bottlenecks in their mental work, they still need to break through the natural inspiration of mankind. Inspiration is a powerful but unreliable thing. If there is inspiration, the problem can be solved, without inspiration, it may be stuck for a long time. This will increase labor efficiency instability.

Due to the unstable mental labor efficiency, it is difficult for the intellectual property industry to carry out precise project management and financial management. enterprise management rules are complex and difficult to implement scale effects, resulting in large process control risks, therefore, there is no foundation for realizing industrial production.

From a physiological point of view, human physical labor efficiency is relatively stable, because the physical labor process is relatively simple, and in the pipeline production process, every worker only performs simple and fixed operations, but there is little difference between them. Physical labor is not affected by people's emotions and environment, but only by the fatigue of the human body. Therefore, for labor-intensive industries, precise project management and financial management can be implemented. The production management rules are simple and there are not many process control risks, so they can achieve economies of scale. Therefore, industrial production can be achieved.

 

Low team efficiency

Currently, many knowledge-intensive tasks cannot be completed by one individual, such as developing a complex software system. This requires a team of multiple people to work together. At this time, a mental worker team is working, but this team is inefficient. Main Performance:

I. Difficult task Separation

Many knowledge-intensive tasks constitute a strict whole, with at least a coherent Main Line. Although it can be roughly divided into several parts, the relationship between the parts is very close, and there are often cases of moving the whole body, so it is difficult to separate knowledge-intensive tasks. However, the mental worker team needs to divide tasks and assign them to individuals to complete the tasks. Therefore, it is easy to see that Unbalanced Task separation leads to unbalanced workload of team members, which leads to mutual waiting among members, low team efficiency.

Ii. High member communication costs

Because most knowledge-intensive tasks are closely related to each other, team members must communicate closely with other team members to complete their tasks and work collaboratively, this greatly increases the communication cost of team members.

For example, if a development team has three people, three two-way communication channels need to be established. Each person must maintain two communication channels. However, for large-scale knowledge-intensive tasks, three people are unable to complete the task, so6Team members. At this time, we need to establish and maintain 15 two-way communication channels. Each person has to maintain five communication channels. As a result, the communication cost increases2.5Times, the overall communication cost of the Team has increased5Times. When dozens or even hundreds of members of a team do not take effective measures for control, the communication costs within the team are unimaginable.

 

As the team communication cost increases rapidly with the team size, when the team size is too large, the internal communication workload may be greater than the actual effective workload. This severely limits the size of knowledge-intensive teams. For large-scale knowledge-intensive tasks, such as R & D of operating systems that require thousands of software engineers, the team is large and complicated to manage [Yuan Yongfu Copyright All http://www.sinoreport.net/]. If the management is not powerful, the mission will be difficult to achieve.

Compared with physical labor, it is much easier to manage physical labor teams. For example, in pipeline production, the tasks of workers are clearly divided and there is no need to communicate with each other. With a modern management level, the team of physical labor workers is sufficient to manage and maintain tens of thousands of people.

 

Lack of systematic labor management methods

In the past, people had less material and cultural needs. Therefore, the market demand for intellectual property rights was not large, which led to the low development of the intellectual property industry and the lack of strong demand for industrial production. Mental workers have been engaged in extensive labor, with low labor efficiency and lack of systematic and effective mental labor and management methods. Nowadays, with the progress of society, people's market demand for intellectual property rights is getting bigger and bigger, so there is a strong demand for industrialized production in the knowledge product industry. At this time, there is a lack of systematic mental labor and management methods. This is as follows:

I. Insufficient systematic scientific specifications for Talent Training

In China, formal school education has never talked about quality education. This is not something that keeps pace with the times. Its talents are semi-finished products and cannot be quickly integrated into social production.

As enterprises and students have considerable needs for re-education after graduation, vocational education has started to emerge. However, the vocational education industry is not standardized and mature enough, and has not gone through a period of training, therefore, it cannot be fully used.

Chinese enterprises only want mature talents who can work immediately. They are resisting graduates who have not yet been able to work. This also affects the cultivation of Chinese Knowledge talents.

Due to many reasons, the training of high-quality knowledge talents in China cannot be well carried out, and the training is not carefully managed by formal schools, vocational education institutions, and enterprises. In this case, the primary responsibility lies in formal schools, followed by vocational education institutions. Although enterprises aim to maximize their own interests, they should also recognize the benefits of training their own talents, and they must fulfill some social obligations when striving for economic benefits.

 

To sum up, all employees in the intellectual property industry are mental workers, which are quite different from the traditional mechanized manufacturing industry.

For example, the automobile manufacturing industry is a [Yuan Yongfu All Rights Reserved. This is because the automobile manufacturing industry is a fully mechanized army with a huge factory, a close assembly line, tens of thousands of skilled workers, and many industrial robots as shown in.

Because of the assembly line production model, the rules of the automobile manufacturing process are simple and efficient, and the production speed is fast, which can fully meet the customer's quantity requirements.

The following table compares traditional mechanized manufacturing and knowledge-intensive industries.

Compare items	Mechanized Manufacturing	Knowledge-intensive industries
Assembly Line	Yes.	None.
Work Mode	Large industrial production in Pipeline	Manual workshop production.
Production Team Scale	Tens of thousands	Small scale.
Production Mechanization	Highly mechanized.	Weak.
Practitioners	Simple work, fast batch training, low cost.	Complicated work content, difficult training, long time, and high cost.
Individual labor efficiency	Stable and easy to measure.	Unstable and difficult to measure.
Production Time	Three shifts.	Three shifts are not allowed.
Informatization	Msi, ERPThe data warehouse can be accessed.	Weak.

 

There is an interesting situation in the industry. The software industry provides a lot of information services for other industries, but its informatization is weak. I have never seen an overall information solution for the software industry.

Because the software industry also adopts a hands-on workshop-style production model, the increasing complexity of customer requirements will lead to a rapid increase in software development workload, resulting in insufficient development capabilities in the software industry, as a result, developers are frequently overclock and often work overtime.

Some customers have complicated requirements, making [Yuan Yongfu copyright holder.

 

Practitioners in the intellectual property industry are basically mental workers, without a clear production line or a fully mechanized production process, and basically rely on human mental work.

Let's look at the software development industry, which is basically a hands-on workshop model. This is the current level of software development is not high enough, and pipeline-based production is not available. Software development personnel training costs are high and takes a long time. Therefore, the software development capability improvement in the industry is slow, and it is estimated that this situation will not change for a long time in the future. [Yuan Yongfu copyright Co., http://www.sinoreport.net/]