In the previous sales model, enterprises basically prioritized meeting users' demands while neglecting their after-sales experience. Nowadays, while meeting the demands, it is also necessary to identify the value gaps that users cannot see and think from the users' perspective. Therefore, in the era of Industry 4.0, leveraging data analysis to enhance the innovation capacity of enterprises is an important way for them to survive.
Merchants sell products, while users value the value that products bring to life, that is, to obtain a better quality of life by purchasing your products. What does the value creation of an enterprise mean? In simple terms, it means that users like your product and are willing to spend money to purchase it. The uncertainties in the manufacturing system that cannot be quantified or grasped by enterprise decision-makers exist not only in the manufacturing process but also in the usage of products. China's manufacturing industry has always focused its vision and energy on solving visible problems, including dealing with visible problems and influencing factors in the production process. And compete hard to meet users' visible needs. In the new environment of the Fourth Industrial Revolution, enterprises must be more adept at competing and innovating in these invisible worlds, including identifying the invisible value gaps of users and managing and avoiding the invisible influencing factors in manufacturing. For business operators, it is crucial to change the previous mindset of viewing issues from a technical perspective, learn to think in reverse, seek potential demands from the value side of users, and learn to shift their thinking.
In the book "Industrial Big Data", Li Jie proposed two concepts: "Master control Innovation" and "scrambled egg Model", providing enterprises with a new perspective on innovation. That is, by adding intelligent software and analysis services to products, enabling them to be equipped with application software tailored to different usage requirements, more value can be created for customers without changing the hardware design. This innovative model is often low-cost and high-return. The core lies in creating from the "invisible demands" of customers through "Internet of Things and Service Network" and "cyber-physical systems".
Break through the red ocean of price competition
John Deere is a traditional agricultural machinery manufacturing enterprise in the United States. The low-priced agricultural machinery from countries such as China and Brazil entering the United States has had a great impact on them. But what they are pondering is what the true value of farmers is among options such as agricultural machinery and crops? Perhaps people might think that what farmers need is agricultural machinery. This is our traditional mindset. However, if we consider it from the farmers' perspective, we will find that what they need is not agricultural machinery, but the management of soil quality and crop yields. Agricultural machinery is merely a means for farmers to fulfill these demands. After understanding the real needs of users, John Deere began to analyze the gap in user needs. Thus, they found that in the process of loosening, irrigating and fertilizing the soil, farmers mainly relied on tutorials and experience, but did not understand the true composition state of the soil. Therefore, for the entire land mortgage, an undifferentiated management and cultivation method was adopted. After realizing the real demand gap of users, John Deere's thinking changed from the previous "selling agricultural machinery to farmers" to "helping farmers increase their harvest".
So where is the invisible gap in the value demand of farmers? Crops require soil, water, humidity, fertilizers, etc. However, the condition of the soil, environmental conditions, and the optimal matching of water and fertilizers are all invisible demands of farmers. If farmers can be provided with this information, the competitiveness will naturally increase. So John Deere installed GPS and sensors for testing soil composition on agricultural machinery. Before planting, the composition of each piece of land could be detected and analyzed. These data were transmitted to the cloud via wireless network to calculate the composition of various fertilizers in each piece of land. Users can obtain the report of soil state analysis and the application degree of different crops through the APEX™ Farm Management platform. Then, according to the crops that farmers plan to grow, provide the types and quantities of fertilizers that need to be applied, and tell farmers the information of fertilizer manufacturers to help them place orders online. In this way, while enhancing the competitiveness of the products, it is also possible to charge intermediary fees from fertilizer manufacturers and management fees for the output value from farmers. So John Deere changed from a company selling agricultural machinery to a company selling crop growth management services. Agricultural machinery from countries like China and Brazil is still competing on price in the red ocean, but John Deere has already made money from providing services in the blue ocean.
2. A new thinking of value-oriented change
GE Aircraft Engine, a subsidiary of GE, changed its company name to "GE Aviation" in 2005, which represented a transformation of the business model. The original engine company only produced engines, while the renamed GE Aviation offers a complete set of solutions including operation and maintenance management, capability guarantee, operation optimization and financial planning. It can also provide various services such as safety controls, air traffic control controls, scheduling optimization and flight information prediction. The value space brought by the services has become even greater.
For example, the "On-Wing Support" service provided by GE Aviation monitors the health status of the engine during the flight, predicts the possible failure risks, and can prepare the spare parts and technicians and other resources required for maintenance at the corresponding airport before the aircraft lands, thereby greatly improving the utilization rate of the engine. Meanwhile, security has also been well guaranteed. After the launch of this service, flights from Chicago, USA to Shanghai only need a 3-hour turnaround time after landing to carry passengers from Shanghai back to Chicago. The flight turnover rate has been greatly improved, bringing considerable value growth to airlines. With these services, what GE sells is no longer or not just engines, but aviation management services. In this way, engine manufacturers have transformed from mere providers of engine units in the past to service providers of shipping information management nowadays.
3. What will create value in the future?
Nowadays, humanity is entering the "Industry 4.0" era, which is an era where the physical material world and the virtual network world are integrated. When we talk about the changes brought about by industrial transformation, we often tend to focus on its representative technological features while neglecting the original driving force that prompts this transformation, that is, the eternal pursuit of value creation. If the first three industrial revolutions significantly enhanced productivity in terms of mechanization, scale, standardization and automation, then the major difference between Industry 4.0 and the previous three industrial revolutions lies in that it no longer starts from the productivity demands at the manufacturing end, but takes the value demands at the user end as the starting point of the entire industrial chain. The essence of changing the previous driving model of the industrial value chain from the production end to the consumption end is to provide customized products and services based on the value demands of users, and take this as the common goal of the entire industrial chain, so that all links of the entire industrial chain can achieve collaborative optimization: all of this is the transformation of the industrial perspective.
In today's manufacturing system, there are many uncertain factors that cannot be quantified or grasped by decision-makers. These uncertain factors exist not only in the manufacturing process but also in the usage process outside the manufacturing process. The first three industrial revolutions mainly addressed visible problems, such as avoiding product defects, preventing processing failures, and enhancing equipment efficiency and reliability. These problems are often relatively easy to solve in industrial production because they are visible and measurable. However, invisible problems are usually manifested as a decrease in myocardial infarction of the equipment, health deterioration, wear and tear of components, and high operational risks. These factors are difficult to quantitatively present through measurement and represent uncontrollable risks in industrial production. Most visible problems are caused by the accumulation of these invisible factors to a certain extent. Therefore, the focus and competitive point of Industry 4.0 lies in the avoidance and transparent presentation of these invisible factors.
Another feature is the extension of the manufacturing process and manufacturing value to the usage process. It is not only about manufacturing a product, but also about how to use it well to maximize its value. The value innovation and creation of products are no longer merely oriented towards meeting users' visible demands. Instead, they need to utilize users' usage data to create usage scenario simulations and identify the gaps in users' demands from these simulations. These are known as "invisible demands". For example, people who buy cars all put forward the demand for fuel efficiency. Therefore, various car manufacturers are committed to improving models and engines to make cars more fuel-efficient, but seldom pay attention to the impact of users' driving habits on fuel consumption. It is evident that market competition in the era of Industry 4.0 will shift from meeting customers' visible demands in the past to identifying the gaps in users' demands.
In the past, we almost reached the end of the production value chain after selling products to customers. However, in the era of Industry 4.0, the value chain has been further extended: using products as the carrier of services and using usage data as the medium of services. During the usage process, we constantly explore the gaps in user demands and utilize the information generated by data mining to create value for users. Therefore, in the future, what the industrial sector sells to users will no longer be products but valuable capabilities. The service industries corresponding to these capabilities will no longer offer users limited choices as they did in the past. Instead, they will provide customized optimal matching solutions based on users' usage scenarios and demands. Since each user's usage data is customized, this means that users are no longer just a sample of statistical results. Rather, it is a rich and highly individualized individual.
Take a common example. In the past, when we bought insoles, as long as we remembered the size, everyone got the same insoles. However, each of us has different foot shapes, weights, standing postures and walking habits. Therefore, no single insole can meet the needs of everyone of the same size at the same time. Before selling insoles to users, Dr.Scholl's Company in the United States will first have users stand on a pedal connected to a sensor. The system will record the pressure distribution on the soles of the users' feet when they stand, and users can obtain a customized insole based on this. There is still more value space to be explored. For example, when collecting foot pressure data, the pressure distribution of walking and running is equally important. These data can also be sold to shoe-making companies, which can recommend a suitable pair of shoes to users after they purchase insoles. If these data are combined with medical research, they can also alert users to the potential risks of foot and knee injuries caused by standing postures and running habits, and provide users with suggestions for improving their habits.
So, data remains an important medium for providing customized products to users. In the era of Industry 4.0, manufacturing will connect end users with the manufacturing system through data. These data will automatically determine the decisions of each link in the production system, achieving a seamless integration of the upstream and downstream of production. The difficulty of human work will be greatly reduced. Under this mode, the organizational structure of the factory will tend to be flat, and the utilization of production resources will also be more optimized.
4. Business Model and Intelligent Service System - Opportunity Space in the Future Industrial Sector
Industry 4.0 is not merely a revolution in manufacturing, but a more profound transformation. Revolutionary changes will occur in innovation models, business models, service models, industrial chains and value chains. The revolution in manufacturing is merely the fundamental condition for the realization of Industry 4.0. Its fundamental driving force comes from the innovative technological changes in business models and intelligent service systems. These two aspects are the key to future competition in the industrial sector. The manufacturing system is like the "egg yolk" of Industry 4.0. While we are making the "egg yolk" good, we should also strive to expand the "protein".
Laozi said, "What exists is regarded as benefit, and what is not is regarded as use." If we use a cup as a metaphor, the seemingly "non-existent" space within the cup is the true carrier of value. China's manufacturing industry must learn to analyze and utilize the value inside cups: Although the manufacturing equipment is produced by the Germans, we need to know better how to use it. If Chinese enterprises can achieve higher efficiency, higher quality, lower cost and lower pollution than German factories through the analysis of usage data, then the Germans should, in turn, learn from the Chinese how to use the equipment to create value.
Discovering the gaps in user value, identifying and managing invisible issues, achieving a worry-free production environment, and providing customized products and services for users all rely on the analysis and mining of data. I believe that the focus of Industry 4.0 will be in China, as China is not only a major manufacturing country in the world but also a major user country. Whether it is manufacturing equipment or terminal consumer goods, China has a huge amount of usage data. However, these data have not been well analyzed and utilized. Therefore, they are still just potential and have not become true competitiveness.
The opportunity space in the future industrial sector can be divided into four parts: The first part is to meet users' visible demands and solve visible problems. Within this space, there are still lessons that Chinese manufacturing needs to catch up on, such as quality, pollution and waste issues. What is needed is continuous improvement and constantly perfected standardization. The second part lies in avoiding visible problems. It is necessary to mine new knowledge from the usage data to add value to the original production system and products. The third part lies in using innovative methods and technologies to solve unknown problems. For instance, self-reflective devices and the use of smart bracelets to manage sleep quality are examples that make invisible problems transparent and then manage and solve those that are completely invisible. The fourth part is to identify and address the invisible value gaps and avoid the influence of invisible factors. This part requires the use of functional information generated by data analysis to create new knowledge and value, which is also the ultimate goal of Industry 4.0.