As a manifestation of GPT syndrome, I plan to write some articles about AI one after another. Just start with this one.
This article was originally posted on Sina Weibo and LinkedIn in January 2019. Just searched and it's gone. Everyone knows the reason. But, I think that little spark of thought must still be there, brewing somewhere, because the internet won't forget.
This is the first article of 2019. As the beginning of the year, we must have the momentum to look forward to the future.
Anxiety about the uncertainty of the future has been shown in almost all media recently, so there are a lot of prophecy programs. These knowledgeable masters speak with certainty, which makes me feel that it is great to read a lot. Why people read books is that they can know the rise and fall by taking history as a mirror. According to the inertia of past development, it is still possible to make short-term predictions. Where does prediction come from, knowledge + logic. The direct effect of reading.
This time, we also make a professional prediction. Talk about the next stop in business management software.
The picture below is a film I used at the Nanjing Annual Conference of Building Materials Logistics at the end of last year. The expression means that the development of management software is accompanied by economic development.
Chart: Comparison of Economic Trends and Development of Management Software
Note: The milestone in the development of management software after 2000 was marked by the acquisition of Oracle.
I mentioned in the previous article that the management software in the form of SaaS is the end of the dividend period of traditional management software. What does that mean? That is to say, from the beginning of the development of management software, it started from the optimization of inventory costs. Using some theoretical models in operations research, it has achieved great results and opened a precedent for management software to be accepted by business owners. Later, it gradually developed into internal management areas such as "production, supply and marketing make money", combining some management concepts, such as theory of constraints, supply chain, balanced scorecard, comprehensive budget, human resource model, product life cycle, sales funnel, etc. . Based on management theory, management software in the form of network and PC applications has become a trillion-dollar industry. Later, due to overproduction and the rise of the buyer's market, consumer-focused applications emerged. These are all kinds of "customer-centric" applications based on the ascendant CX-customer experience theory. The performance is from throttling software to open source software. In the past, the role of management software was to improve efficiency and save costs. The current software platformization uses the Internet to open up ideas, expand functions, and use innovative applications of enterprises to increase sales opportunities, improve customer satisfaction, and form the benefits of repeated purchases. However, the magic number 30 came into play. After more than 30 years of baptism, when users are familiar with various management theories, the bonus period of management software is over. This is why everyone feels that management software is not easy to sell. So the market is headed for a reshuffle. SaaS is the accelerator of this shuffling process.
The essence of SaaS lies in interconnection, which closely connects people and enterprises. At the same time, it also connects various applications together. The "Shared AI" in the figure below is an important force to be connected in the future, a force of "unknown influence". The era of "Internet+" is only the prelude to "AI+".
AI+ will be another bonus of future enterprise management software, and it will also be a terminator. The reason why it is said to be the "terminator" is that the basis for the existence of business organizations is from Coase's "transaction cost" theory. However, AI solves the problem of information asymmetry. When the transaction cost between individuals becomes extremely low, most enterprises will have no soil for existence. Society will undergo tremendous changes, and we don't know how to define future enterprises. This is in the long run. If you look at it in the short term, there will be very interesting dividends. I make wild guesses.
- RPA（Robot Process Automation）
Using more mature AI applications such as image recognition and voice recognition, enterprises will realize the intelligence of the financial department. Manpower will be freed up for expense reimbursement, bank reconciliation, supplier payments, budget control, and more.
- production schedule
APS (Advanced Production Scheduling) has always been a challenge, because the calculation speed problem limits the possibility of obtaining the "optimal solution", but only the "most satisfactory solution". And AI seems to be born for this specific problem. Shared AI mode will completely solve this problem. At the same time, any issues involving "planning" in operations research, such as "scheduling" in the service industry, etc., will be the field of AI. What is AI, big data + computing power, this is the key to solving planning problems.
- Industrial supply chain optimization
Realize "zero mismatch" through the optimal allocation of social resources. When every purchase decision, production decision, and service decision is optimal, we say that this has achieved the optimization of the industrial supply chain. The picture below is a video from Gao Hongbing of the Alibaba Research Institute at the 2019 New Economic Think Tank Conference yesterday. I think that is what it means.
When writing this article, I have mixed feelings in my heart. I am more uneasy and confused than excited. This stems from the fear of the AI society. I really don't want to think about a "1984" society. We are running on the runway of science and technology, and the end point is a hard concrete wall. When the end point is approaching, in order to win, do you slow down or sprint with all your strength?
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