Mid-platform type: Is the mid-platform you heard really a mid-platform?

In the previous lecture, I took you on a journey of nearly ten years of middle platform development, understood the background of middle platform development from the perspective of time, and also helped you analyze some of the reasons behind the rise of middle platform.

However, when we talked about it in the end, until now, there is still a lot of confusion about the concept of the middle platform. What exactly is the middle platform? What should the middle platform look like? What are the types? What is the value to the enterprise? Do I need to build a middle platform? These questions may still not have a definite answer in your mind.

Today I will take you to take a look at some different types of middle platforms that have appeared so far, and see if we can find some common characteristics behind these seemingly different types of middle platforms. In the next lecture, I will take you to explore the essence of middle platforms and answer your doubts.

As for the classification of mid-platforms, I have divided the current ones into two categories: “mainstream” and “non-mainstream”. Let me take you through them one by one.

# Mainstream representative: Business data dual middle platform

Central Product Platform

The term business is actually quite broad. I have heard many people say that business is not the same concept. Therefore, I have done some research. In simpler terms, business refers to the business-related affairs that need to be handled in various industries in order to sell products and exchange profits. Therefore, in the early days, we usually referred to sales as salespeople.

NetEase Vice President Wang Yuan once mentioned at the NetEase Cloud Innovation Summit: “All mid-platforms are Central Product Platforms”. I also agree with this statement because, in a broad sense, all mid-platforms, whether they are Central Product Platforms, data mid-platforms, or others, are for business, for enterprises to sell products and exchange profits at lower costs, higher quality, and faster response times.

Looking at it from a different perspective, from the perspective of enterprise architecture, application architecture, technical architecture, and data architecture all need to match the company’s business architecture, because “business”, that is, selling products and exchanging profits, is the core goal of the enterprise.

Okay, since all the middle platforms are Central Product Platform, what does the Central Product Platform in the business data dual middle platform that we often mention represent? In my opinion, The Central Product Platform that we often mention is a narrow business concept. The Central Product Platform needs to specifically carry out the necessary business elements to support business development, encapsulating the necessary problem space solutions that need to be solved to ensure the smooth development of business .

This may sound empty, but I have a trick. When I think about the Central Product Platform, I keep asking myself one question: What are the core issues that need to be solved for the smooth development of the enterprise’s business?

For example, in the scenario of e-commerce, if I were an e-commerce company and my business needed to develop smoothly, that is, to sell my products to users in exchange for profits, the core issues that generally need to be solved are:

• Who are my users? Where do they come from?
• What products do I sell? Where do they come from?
• How can I let users know about the products I sell?
• Why would users buy the products I sell?
• How do users buy?
• How to deliver the goods?
• How do users return or exchange goods?
• How to make users keep buying?

These are the most basic and core issues that an e-commerce business needs to solve in order to operate normally. In DDD (Domain-Driven Design), there is a proprietary term for the core problem space that these enterprises need to pay attention to in business development, which is the problem domain . The commonly used terms such as user domain and order domain also come from this.

For different Lines of Business of an e-commerce company, it is mostly due to different products sold, regions sold, and client bases. However, these problems also need to be solved, and in most cases, the solutions are similar. This is why the Central Product Platform can exist.

Therefore, the Central Product Platform we often mention can be understood as a narrow definition of the Central Product Platform. It abstracts and encapsulates solutions to the same problem domain from different Lines of Business, and takes into account the specific needs of each Line of Business through mechanisms such as configuration, plug-in, and service, to achieve business support for different Lines of Business.

Data mid-platform

After discussing Central Product Platform, let’s take a look at the currently most popular data mid-platform. Why is data mid-platform so popular? I have summarized several main reasons.

1. Quick results. Currently, the problem for most traditional enterprises is still the lack of data communication. The phenomenon of “data silos” is quite serious. The construction of a data mid-platform directly solves pain points and has strong driving force.
2. The burden of organizational adjustment is small. Generally speaking, enterprises of a certain scale already have a Big data or BI team, which naturally carries relevant functions and does not require further major organizational adjustments.
3. There is a certain technical foundation reserve. Most enterprises have been building data warehouses for many years, or have built big data technology platforms for many years with the wave of big data in recent years.
4. The trend is inevitable. Everyone is talking about the DT (Data Technology) era, and enterprises have a deeper understanding of the value of data. Everyone has realized that data is no longer just a tool for operational analysis, but has gradually become the core asset and competitiveness of enterprises.

With minimal organizational changes, established technical foundation, obvious pain points, low cost, and quick results, it is the trend of the times. Therefore, it is not surprising that data mid-platform has become a hot topic of concern.

However, since we are now talking about business digitization and data commercialization, and since the two concepts are also transforming and integrating with each other, what is the relationship between data mid-platform and Central Product Platform? What is data mid-platform? What are the differences and connections with the data warehouse and Big data platform built in the past?

I believe that these are also issues that many colleagues who pay attention to data mid-platform are particularly concerned about.

Regarding the relationship between Central Product Platform and data mid-platform, I agree with the viewpoint mentioned by Xie Chunliang, the technical solution director of Alibaba, in an InfoQ interview: " Central Product Platform is generating data, data mid-platform is doing secondary processing of data, and then serving the business with the results, empowering the business with data and intelligence. "

The key difference between data mid-platform and traditional data warehouses and data platforms lies in the fact that data mid-platform has taken a step forward and towards business compared to data warehouses and Big data platforms. It no longer only focuses on the construction of the technical level of Big data foundation, but also pays more attention to enterprise-level data governance and data assets, including but not limited to data asset management (quality, cost, security), data service construction, and data system construction (unified models and indicators).

For the sake of convenience, at ThoughtWorks, we often compare the data mid-platform to a Data Factory. It collects data from the raw material warehouse, processes it through the factory assembly line, and finally enters the product warehouse as a data product. Through the data store, it empowers the front-end or Central Product Platform in various ways (such as data API), and the entire process is coordinated and scheduled through the control center.

This metaphor vividly embodies the process of secondary processing of data by the data mid-platform, and also describes the intelligent processing of data through the data laboratory, and the relevant processing of data governance and assetization through Office.

After introducing our most common business data dual middle platform, here is a summary.

The Central Product Platform and the data mid-platform complement each other, support each other, and input and output each other. The Central Product Platform carries the general business capabilities of the enterprise, empowering multiple Lines of Business; the data mid-platform empowers the business in terms of data and intelligence through secondary processing of business data and feedback to the Central Product Platform. The close cooperation between the two has built a powerful rear artillery group for the enterprise in the business battlefield, which constitutes the most famous business data dual-middle platform model.

# Non-mainstream series

In addition to the dual middleware for business data, various middleware have also emerged, and the appearance of these middleware has made the originally clear concept of middleware somewhat blurred. Next, I will quickly introduce to you some middleware that I have come into contact with in recent years. In the process of my narration, you can also think about which of these middleware are Li Kui and which are Li Gui, who truly deserves the title of middleware, and who is here to ride on traffic.

Technology mid-platform

In addition to the dual middleware for business data, the most commonly mentioned one, in my opinion, is the technology mid-platform, which is between mainstream and non-mainstream. Compared with the Central Product Platform and the data mid-platform, the boundary of the technology mid-platform is also clearer. Simply put, it integrates and packages the ability to use cloud or other infrastructure and various technology Middleware capabilities under CloudNative. It filters out technical details, provides a simple, consistent, and easy-to-use application technology infrastructure capability interface, and helps the front-end and the rapid construction of the Central Product Platform and data mid-platform. However, there are also opinions in the industry that the technology mid-platform does not have strong business attributes, but is just a collection of Middleware, at most it can be considered a Middleware platform, not a mid-platform. What do you think?

R & D middle platform

Software development is a project that involves management, processes, testing, team collaboration, and so on. How to precipitate an enterprise’s development process and best practices into reusable “capabilities” to help the rapid development and iteration of innovative applications is also something we see many enterprises doing. We can call this platform that focuses on development efficiency management a R & D platform.

Mobile middle platform

In the era of mobile Internet, the principle of mobile first has become an indisputable fact. By encapsulating and precipitating the general technical components in the App development process into the mobile middleware, a large number of existing components and capabilities can be reused when building a new App to quickly build and respond.

Management middle platform

Recently, many enterprises have started to try to apply the middle platform thinking to the internal of the enterprise, and re-platform/set up functional teams for “people”, “things”, “processes” and “enterprise operations”. They attempt to accelerate the standardization of enterprise management and improve operational capabilities through the construction of set up functional teams.

Organization mid-platform

In Mr. Mu Sheng’s book “Unleashing Potential: The Evolution Roadmap of Platform Organizations”, he proposed the concept of an organizational middle platform by analyzing the evolution process of Haier’s platform organization. The organizational middle platform is similar to internal venture capital and innovation incubation institutions in enterprises, providing front-end organizations and teams with innovative front-end applications similar to investment evaluation (project screening), investment management, and post-investment management (incubation and risk control), truly supporting the rapid iteration and large-scale innovation of front-end organizations and applications from an organizational and institutional perspective.

Well, that’s all for the non-mainstream series. In fact, there are far more than that. Other platforms such as financial middle platform, procurement middle platform, supply chain management, AI middle platform, operation middle platform, security middle platform, management middle platform, etc. have also appeared in our field of vision. Today, I will not expand on them one by one.

# Summarize thinking

Finally, let’s make a summary. In this lecture, I took you through the common types of middle platforms on the market. At this point, you may feel more confused than before. There are so many different types of middle platforms, and you can’t tell which one is Li Kui or Li Gui. The ultimate question of what a middle platform is must still be lingering in your mind.

Don’t worry, through the divergence of the first two lectures, I want you to open your horizons like me, establish a global perspective from the dimensions of time and space, and in the next lecture, we will do the first convergence to explore the essence of the middle platform.

Finally, I’ll leave you with a few thought-provoking questions:

• Does your own company have a middle platform? What type is it?
• Do you have a different understanding of these middle platforms mentioned above?
• Besides what we talked about today, what other types of mid-platform have you seen?
• Do you have a standard to judge which ones are mid-platform?