This sharing describes a thinking model, which gives us a perspective on the development trend of information technology in various industries, that is, from automation to online to intelligent, and data is the core of this process.
Automation: The operation is automated and data can be collected automatically.
Online: The core business scenario is online again, and the data is collected and recorded online, and users can interact and feedback online. employee online, product online, customer online and management online.
Intelligent: After a large amount of data is online, the data flows and consumes. Use the data To help people make decisions or use machines to make decisions, intelligence emerges at this time, which can more accurately grasp user needs, provide products and get feedback.
Take China's logistics industry as an example. It quickly walks through the entire process. The core business of the entire logistics from receipt to delivery is online, and a large amount of data is generated and recorded, which can be used for logistics resources. Of the distribution to improve efficiency. China has experienced poor logistics efficiency and high costs. Now the cost is half that of the United States, and the efficiency is higher.
1. We can also look at other related industries:
Take the computer industry that everyone is most familiar with as an example. Computers can be said to automate calculations and use input devices to digitize information. The first most valuable companies at the time were IBM, Intel and Microsoft. When Yahoo appeared on the Internet, it became the most valuable company at the time. Of course, several major portals emerged in China. When more and more data, traditional classified information websites can no longer meet the demand, Google appears. Google uses web crawlers to structure web page information, invents search boxes to obtain user needs, and uses Page rank algorithm to accurately match The result the user wants. In a further step, Google will optimize rankings based on user click feedback and push advertisements based on user behavior and data. Google is a typical intelligent company.
Let's look at the automotive industry again. The automotive industry has begun to automate some components including automatic reversing and automatic cruise. Now Tesla has installed more sensors in the car and transmits data to the line. The feedback of these data can record the state of the car and be used to train autonomous driving technology. Autonomous driving is the direction of the future, but L5 level autonomous driving has not yet been realized. Except for the reason that sensors are too expensive, cars now only have their own data. For roads, traffic and other vehicles other than cars, the data is still It has not been done, so the current autonomous driving can only be commercialized in a specific closed environment. With the use of more and cheaper sensors in the future of 5G, companies like Google are bound to appear in the automotive industry. It is not certain whether it is Tesla or not, although it is already the world's most highly valued automotive company. China is now the largest country in the world for the production and sales of cars. Which car company can take the lead in installing these sensors on cars and using it will surely gain an advantage in future development.
The medical industry, the medical industry is a more closed industry, although it only records the test reports of patients, these data are relatively closed, and these data only reflect the patient’s situation at the time, which is equivalent to a cross section. Continuous monitoring of the health of people is more meaningful, so most of the medical industry is still at the stage of automation or even manual. Some artificial intelligence applications just look at X-rays, and IBM's Doctor Watson project has not been very successful.
We can also use the same method to analyze other industries, such as the insurance industry. Some insurance companies have begun to install sensors on insured cars so that they can obtain driving data to achieve accurate insurance pricing. The financial industry is one of the industries where the use of computers is particularly high. Alipay makes the payment process online. You can pay online, which generates a lot of payment data. In addition to the payment data, it also controls the transactions of Taobao sellers. And other data, so that it can make small loans, Ant Microfinance uses data to accurately price the borrower. Of course, a similar development process can be seen in the education, manufacturing, and retail industries.
We can also analyze from the perspective of different types of data:
Text and image data (Facebook, Twitter)
Facebook’s biggest competitor can be said to be Google. Both companies rely on advertising for their revenue, and both companies have achieved accurate advertising push without affecting the user experience. The difference is that Google uses keywords entered by users to match results to match ads, while Facebook uses social relationships and user behaviors to guess user needs to push ads. Facebook is built on the situation where users use more. The more you use such as likes, reposts, Posts, etc., the more Facebook understands you, and the more you understand, the more likely it is to push content and ads you like.
Video data (YouTube, Tiktok)
Tiktok has also achieved smart recommendations, and the company's rapid development has doubled its annual sales. Tiktok has opened a new way to classify users from Label to Tag. Although both of our words are translated as tags, Tag is equivalent to a more detailed tag. For example, if you have just met a person, you might give him/her a bigger label, where the person is, where you work, and when you spend more time with this person. Suppose two years later, you will feel like you were at the beginning. It is too rough to understand this person by labeling. Now you may know many details of this person and her/his hobbies. This is the difference between Label and Tag. TikTok uses the behavior of users to watch the market, swipe, and like, and it constantly tags people. In the end, it may know you better than you. So as to effectively get the needs of users and use smart recommendations to meet user needs.
Commodity data (Taobao, Pinduoduo)
Most of Taobao’s current input comes from advertising revenue, recommending products based on keywords that users search for products. It can be said that its model is similar to Google. It matches users' needs by getting users' search needs. Pinduoduo's CEO Huang Zheng said more than once that Pinduoduo is today's headline in the e-commerce business. Pinduoduo uses the same Tag thinking to portray users and learn more about users, so that users can buy more products through product recommendations. Pinduoduo will also find product needs from users' behaviors such as boosting, forwarding, and collection, and when it gets these needs, it will go to manufacturers for production. This is the C2M model, and reverse production according to user needs.
Map and location data (Uber, Didi)
In the past few years, the subsidy war between Uber and Didi in China is still fresh in everyone's memory. Uber has launched a sharing economy model. This model benefits from the popularity of smart phones, because maps and location information (GPS) are not only digitized but also online. Uber efficiently matches travel needs by connecting drivers and passengers at both ends. And because of this data Uber has also achieved real-time pricing (high and low peak periods), thereby taking away the largest consumer surplus. The popularity of shared bicycles also benefits from the digitization of location and map information.
Housing Information (Airbnb)
Similarly, the success of Airbnb also benefits from the digitization of housing information, including location, photos, facilities, and evaluation. Without this information, it is difficult for people to judge whether a privately rented room is good or bad. Lianjia's real estate intermediary service has been digitizing photos, facilities, locations, decorations, etc. of housing information from the beginning. The slogan is real real estate online.
Health data (Apple Watch)
Apple Watch has passed the FDA review last year and is in compliance with the use of medical devices. Apple Watch will continue to monitor your heartbeat data to find possible heart problems. As the sensors get smaller and cheaper, there will be more data and online, a new device similar to a ring worn on the finger can track 10 human body data.
Other data
As more and more sensors are developed, we can digitize more information so that we can use this data to improve efficiency and have more business opportunities.
let's summarize:
Data will become the company's most important asset in the future, and it will be more and more valued and used. From this perspective, we can analyze the development stages of various industries and possible future trends. As more sensors are developed and these sensors become cheaper and cheaper, coupled with the development of 5G, these sensors will be installed in various places and connected to the Internet, which will give a huge boost to the development of various industries. It can be said that companies of the Google level may appear in various industries.
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