Kechuangren, Guanyuan Data CEO Su Chunyuan: Letting the business use it is the key to tearing down the penetration wall of the BI industry

Su Chunyuan Founder and CEO of Guanyuan Data
Graduated from Carnegie Mellon University, majoring in information system management, has nearly 20 years of experience in data analysis and business intelligence management services, and is good at enterprise data analysis and strategic planning. 100 Fortune 500 companies have provided big data analysis products and services. Founded in September 2016, Guanyuan Data is committed to long-term innovation in the data intelligence industry, leading the company and team to become a global leader in intelligent analysis and decision-making.

—
Text | babayage
Edit | Laugh Laugh
18 years ago, the first wave of entering BI

The term BI (Business Intelligence) was born in the distant 1958, but the industry generally believes that it was redefined by Gartner in 1996, which is a sign that BI technology has entered the era of comprehensive commercial use. Su Chunyuan became interested in BI when "beer diapers" brought the myth of BI to the forefront for the first time. In 2022, in this era when big data + artificial intelligence technology is fully applied to all corners of life, data analysis majors in universities and colleges have exploded. But 20 years ago, data analysis was only a popular course under the information technology management major. In Carnegie Mellon's "super code farmer production base", Su Chunyuan's learning content is mostly related to coding technology, but he is most interested in a few business courses, especially the use of data analysis technology to assist business decision-making.

Before graduating, Su Chunyuan received an offer from MicroStrategy. As one of the most successful BI companies in the world in the past 20 years, MicroStrategy's talent requirements are almost tailor-made for Su Chunyuan: while proficient in data technology, Both have an understanding of business application scenarios.
Su Chunyuan naturally did not hesitate for too long.

Kechuang people: It is often said in the To B industry that there is a generation gap of 10 to 20 years between China and the United States. In your opinion, what are the similarities and differences between the current development progress of the domestic BI industry and the United States 18 years ago?

Su Chunyuan: Dr. Lu Qi summed up the five stages of enterprise IT system construction in the Qiji Innovation Forum not long ago: among them, the construction of business systems and the accumulation of business data are called System of Record, and ERP + enterprise database is the representative of this stage; System of Insight is to gain insight into valuable regular information from the precipitation data. The representative of this stage is BI; the final stage in the future will be System of Intelligence. The application of AI technology is becoming more and more popular. Through the combination of AI and BI, the system will provide Make decision suggestions and even complete the action closed loop.
The development of To B services in the United States is relatively early, and the popularity of IT technology is high. In 2004 and 2005, most multinational companies and global enterprises have completed the first stage, that is, the construction of ERP systems and databases, so the insight and decision-making system become the next-generation needs of enterprises.
At present, Chinese companies are building several generations of systems simultaneously. Recording, insight and intelligence are being carried out simultaneously. Even within the same company, there will be a hot scene of multiple steps and one step. I personally believe that in the next five years, China will have the opportunity to complete the 10-year transformation journey that the United States has taken in the field of enterprise digital and intelligent transformation.

Kechuang people: In the 10 years of working in micro-strategy, what is the scene that impressed you the most or the problem that caused you the most trouble?

Su Chunyuan: 10 years is a very long time. First, I worked as an engineer in the United States, and then I returned to China to participate in the establishment of a Chinese R&D center. What impressed me the most was the stage of building a Chinese R&D center. I experienced the feeling of intrapreneurship, from finding an office space , The interview with the front desk administration started, especially every early engineer classmate, we chatted one by one from the "dormitory".
Recruitment is an interesting memory. We hope to recruit the top R&D technical talents, but the competition for good talents is very fierce, especially when the micro-strategy software has just entered China, it has to face a lot of competition. For example, the same company is called MS for short but its reputation is not great Less Microsoft and Morgan Stanley. Therefore, in addition to promising development prospects, guaranteeing a competitive salary, and providing high-quality training at home and abroad, we also put a lot of thought into it. For example, we will spend a long time going to the campus, drinking coffee with classmates, and giving presentations. Products, visit the teachers of our classmates for endorsement, and ask the brothers and sisters who work in our US headquarters to help us with targeted publicity... I still remember sharing my choice when I graduated with my classmates, "Data analysis is the future! "For students who pass the interview, we will send a gift box to their dormitory. In addition to the exquisite offer letter, there will also be a bottle of champagne. They can share their joy with their dormitory classmates. Since 2009, we have been one of the most popular technology employer brands among the top 10 domestic universities for many years.
One of the biggest challenges in the experience of foreign companies is the trouble that the R&D team generally faces: what value does the code we type help customers achieve? In what specific ways has my work changed the world? The best talents need the most positive feedback, and the R&D team is far away from customers, especially the Chinese R&D centers of global companies will be farther away. Therefore, I promoted the establishment of some mechanisms. For example, the technical team can directly connect with customers all over the world, and colleagues can directly communicate with Fortune 500 customers remotely; we also strive to allow more employees to participate in offline customer meetings, including 1 every year. The company held a global customer conference in Las Vegas in June, allowing employees to experience how their code brings value to customers.

Founded Guanyuan, only to better serve Chinese enterprises

Su Chunyuan's entrepreneurial idea sprung up around 2013. As the MicroStrategy China R&D Center's service to global customers is getting better, Su Chunyuan has accumulated a growing confusion in his heart.
At that time, some leading domestic BI companies had already emerged, showing the vigorous vitality that the emerging industry should have. However, from Su Chunyuan's perspective, it is a different scene: if it is just a replica of the foreign development model and the development process of BI on a global scale is repeated, Chinese companies may need to wait 10 years to enjoy the 2013 Annual level of BI services.
How can this cycle be shortened? Obviously in China, but unable to directly provide the best BI services for Chinese enterprises, this sentiment gradually accumulated and fermented, and finally in the chaos of confusion and anxiety, a seed related to mission and responsibility was bred. Su Chunyuan decided to start her own business, devoting her years of technology and service accumulation, only to serve Chinese enterprises well.
In 2015, To B gradually replaced the Internet and became the new hot word of the times, and technological applications such as big data and artificial intelligence ushered in its own DT (Data technology) era. Sensing that the time was ripe, Su Chunyuan decided to resign. After a year of preparation and in-depth thinking, Guanyuan Data was officially established in 2016.

Kechuangren: One of the most concerned topics in "Technology People" is how to plan strategic positioning and clarify their differentiated advantages in future market competition when start-ups enter an industry. What decisions were made?

Su Chunyuan: Data intelligence companies are also divided into two categories. One is those with more significant short-term value, such as companies with data sources, specific algorithm models, and huge customized projects, which are also close to money; the other It is a relatively hard-working category with long-term sustainable value. It is essentially a software & SaaS company. Through product polishing, various data are aggregated and refined to provide decision-making analysis for enterprises. Guanyuan is the second type of enterprise, which is the route choice of Guanyuan, and provides services for the majority of decision makers based on products.
The second is to focus on vertical industries and choose new consumption and new retail as the first base. There are multiple considerations here:
First of all, after years of rapid development, the new retail and new consumer industries have become an excellent hotbed for technology-based To B service companies, with fast iteration, large scale, strong vitality, and one of the best data foundations.
Secondly, this industry is very market-oriented, you don’t need to rely on relationships, as long as you have technology and ability, you can win customers.
Third, most of the enterprises in the new retail and new consumer industries have been exposed to or even native to Internet technology. Their ability to identify service value is very good, and their ability to accept new things is high, so the cost of education is relatively low.
Fourth, the new retail and new consumer industries, that is, the initial e-commerce field, have cultivated a large number of digital talents. Many people later turned to other fields with digital experience, providing decision analysis services for this industry, and radiating ability to other industries. stronger. Later, it was proved that our judgment was correct, and some companies with high thresholds would ask when they communicated if you had any successful cases of serving the e-commerce industry.

Kechuang people: Many practitioners of data intelligence enterprises will choose the financial industry when subdividing industries, because the data foundation is the most complete and the technology acceptance is the highest, but from Guanyuan’s point of view, it seems that the weight of industry vitality is higher than that of data foundation. completeness?

Su Chunyuan: Good question. The data foundation of the financial industry is indeed the best, but the financial industry is relatively conservative, and the threshold for a start-up is very high, so we have accumulated for a few years and then fully cut into finance.
The retail and consumption industry is large enough, and like finance, it belongs to the industry with huge volume and scale. We believe that the soil of the industry is extremely important. Referring to the development history of foreign To B giants, SAP was initially rooted in Germany's advanced industrial manufacturing, and then gradually expanded to all walks of life. This type of industry has the most real market feedback mechanism, the most intense competition, and the most frequent iterative optimization, which must correspond to the most advanced productivity and decision-making capabilities.
In China, which industry is relatively the most innovative and leading? There is no doubt that retail consumption, and the business iteration and data innovation of this industry, not only lead other domestic industries, but also lead the world. Guanyuan hopes to cultivate the top data decision-making ability together with such an industry.

The pit of start-ups, find the right 3F to overcome the high wall of trust Science and technology creators: Since you accurately predicted that when the start-up companies entered the market, they would encounter an insurmountable trust gap, what methods did Guanyuan use to overcome this? question?

Su Chunyuan: I know a lot of truth, but I still can't live my life well. This question gave us a lot of headaches at the beginning (laughs). Guanyuan has been determined to serve the most advanced and innovative customers since its inception. After all, my three co-founders and I have backgrounds in making top 500 enterprise-level products. However, the threshold for top customers is indeed high, and the cycle is very long. Therefore, my first entrepreneurial awareness is to face the reality, first serve those medium-sized customers who are willing to embrace innovation, and then continue to break through the boundaries of our capabilities. . Later, we found out that Salesforce was the same in the early days, starting with small and medium customers and getting bigger, and we were relieved.
And there is deep logic in it. For a startup, especially a company aiming to be a great product, it’s important to have your own rhythm. If you cannot respond calmly for short-term orders, the huge pressure will lead to the deformation of the company's strategic actions, and you will be coerced into the rhythm and needs of the other party. In fact, there are many early-stage enterprises in China who are bound by a few large customers, which essentially deviated from the track of making products. The further back, the more difficult it is to realize the definition of enterprise-level standard products, because there are already mixed in the early product logic. Due to the personalized needs of too many large customers, the historical burden has increased exponentially.
Therefore, we have always been very grateful to the customers who accompanied Guanyuan to grow up. Although everyone joked that the early customers were mainly "family, friend, fool", we are very grateful, and later found that the people who chose Guanyuan had advanced vision and wisdom. entrepreneur. For the first batch of customers, we are still working closely together. This is one of the most memorable moments on the road to entrepreneurship.

Kechuang people: During the review, it is often easy to clearly divide the various stages of enterprise development, but when they are in it, how do entrepreneurs judge the current stage? For example, if you also choose to develop steadily for a period of time, how to judge whether this period of time is regarded as a stable base, improving self-reliance, or falling into the trap of being rich and easy?

Su Chunyuan: A very vivid question, are we at the beginning of the Long March, or have we arrived in Yan'an, or have we been able to attack in an all-round way? To be honest, this is a topic that I have been thinking about over the years.
In the end, I have a very simple experience: what stage your business is in depends on the customer group you are serving at the moment - in your analogy, the territory you control, whether it really belongs to you or not.
At the beginning of its establishment, customers were mostly introduced by word of mouth.
But once this stage is passed—the sign of passing this stage is that the prototype of the product is basically clear—it is necessary to quickly find the real base, polish the benchmark, build the moat, and absolutely cannot be trapped in the comfort zone.
Finding a base is to subdivide customers. Most of the time, it is to lock in an industry, and new companies are not in a hurry to go to the sea. In "Crossing the Divide", it is said to be a big fish in a small pond. I very much agree with this point of view.
The next step is to polish the benchmark. After we built a few smaller brands, we quickly came into contact with leading brands such as Unilever, Anta, Yuanqi Forest, and Michelle Ice City, and constantly improved our service capabilities for leading customers.
The third step is to build a moat. When you enter a larger battlefield, there will be stronger opponents. You must not be satisfied with "I can", at least within a certain period of time to achieve "others can't".
The completion of these three steps means that the market you currently occupy truly belongs to you, and you can plan the offensive direction in the next stage. The next step is to use the scale of customers and the number of customers as a mirror to judge the development strategy as clearly as possible. In this regard, we have put a lot of effort into studying and studying IBM and Huawei's BLM (Business Leadership Model) strategic methodology, combined with entrepreneurial practice, and do practice and iteration every quarter. It has entered the 8th version, and has also transformed into Guanyuan. own strategic management practices.
In addition, in addition to rational methods, founders must not only bear the pressure of short-term business, but also constantly think about the long-term, especially the most essential and important issues in the industry. They must be based on deep thinking to form their own Judge the future of the industry, so that you can see the future more accurately and farther than your competitors.

Domestic data service companies should help customers solve basic data problems Kechuang people: You have mainly served global customers in the BI industry for the first 10 years, while Guanyuan is for domestic companies. What are the obvious differences between the two, and whether they directly affect the products? Form and service mode?

Su Chunyuan: There are many differences. The most obvious difference is in data foundation and data literacy. It cannot be simply summarized as mature and primary. It feels more like: serving foreign customers is running on a complete and coherent road. You can maintain A stable high-speed run to the end; to serve domestic customers, one section is a very good highway, and the next section may be a country road. You have to constantly adjust the driving mode, and your products must also have strong adaptability.
For example, the data quality of many domestic customers is uneven, especially the business is constantly innovating. As a result, the same product is reflected in many different links or channels, and the data caliber is inconsistent, which requires some manual processing. match.
Therefore, we have developed many products and services, such as SmartETL, to help customers preprocess various data before analysis; and we provide mobile BI, in the form of no-code drag-and-drop, within a few hours , which can support customers to publish different mobile analysis boards for different departments and roles, and directly access corporate WeChat, Dingding or Feishu, which is very popular. These down-to-earth product innovations have become a high-value point that Guanyuan has been particularly recognized by the industry in the past few years.
In addition, you may have heard the phrase "everyone is a data analyst". The popularity of data analysis capabilities is relatively better in foreign countries, but it is relatively difficult to achieve in domestic soil. What domestic customers need is not just a self-service analysis tool, but a one-stop product and industry best practices to empower different roles within the enterprise. They may be analysts willing to do data exploration, or they may be Business executives who wish to learn from industry analysis scenarios are more likely to be the majority of front-line business decision makers who directly consume the constructed analysis scenarios.

Kechuangren: "Science and Technology People" recently discussed a topic internally, why most domestic To B companies use industry solutions as the entry point, rather than taking the tool route, perhaps the customer's purchasing tendency largely determines the To B service. form?

Su Chunyuan: Yes, only in the industry can more value directly act on customer scenarios be deposited, and then directly empower customers.

Kechuang people: The SmartETL you mentioned has been proven to be a very effective data infrastructure product in at least a certain industry. The domestic big data industry generally has problems in data governance. Has Guanyuan considered industrial data governance? Capability as a separate product line?

Su Chunyuan: I have studied the ETL field abroad before, and found that the foreign division of labor is indeed very professional. Many companies do this thing and cooperate with BI companies upstream and downstream. The phenomenon you mentioned does exist in China. Many companies do a lot of things, and it feels all-encompassing, which corresponds to the work done by many foreign listed companies. The value proposition of Guanyuan is very clear, that is, a one-stop analysis platform with BI as the core. In China, the market penetration rate of BI is only single digits, while in the global market this figure exceeds 30%, and individual advanced countries are close to 50%, which is a gap of nearly 10 times and a potential of 10 times; in addition, AI+BI It is also our future layout of BI. In essence, this is advanced analysis. After BI is used in depth, it is a natural high-level high-value scenario.
Therefore, until the BI industry truly matures, we will most likely not rashly enter other fields.

Focus on the data granularity revolution Kechuang people: You have mentioned the data granularity revolution many times in your past interviews. Can you systematically share the mechanism that produces this phenomenon and your insights into it?

Su Chunyuan: This phenomenon actually originates from customer scenarios. The inspiration we got when colliding with customers is that the more skilled we are in the application of BI, the more customers will feel that BI and AI are not metaphysics, their essence is digital operation, and it is not easy to deal with it every day. It must be a grand proposition, and the more common scenario is fine-tuning and detail optimization.
It is very difficult to predict the purchase volume after one month, but dividing a month into 4 weeks and a week into 7 days, the refinement of data granularity has improved the accuracy of data operations, the generation of continuous data, and the accurate accumulation of historical data , which can generate more valuable executable strategies in tiny scenarios. In the Internet field, AB testing may not be new, but in other industries, product selection, optimization and iteration can be achieved through refined data operations, and it is still the ability of a few players.
A beverage brand can implement different distribution strategies in different areas based on the granularity of data; a convenience store enterprise can formulate different data models on a single store basis, which can be refined to the placement of a certain product Strategy; the data that a sales manager can grasp is refreshed every 5 minutes from T+1 in the past, and problems and opportunities can be found in a timely manner; customer decision-making meetings have changed from monthly meetings, weekly meetings, and conferences to more frequent, A brief, specific exchange of information…
The change in data granularity is not only a quantitative change, but its impact on business operations is the gap between slash-and-burn cultivation and nuclear weapons. All business managers should pay attention to this change and embrace the decision-making particles that the change in data granularity will inevitably bring. degree change.

Future Planning: AI+BI
Value Proposition: Make the Business Useful Science and Technology People: From Guanyuan's point of view, what are the next ways to greatly increase the penetration rate of BI in the Chinese market?

Su Chunyuan: There is a huge opportunity for business departments to use BI directly. Among Chinese customers, BI is mainly provided to the IT department for reporting purposes, and many business values require the participation of the IT department in order to be truly implemented. How can businesses build their own application scenarios directly through BI? If this hurdle can be solved, the penetration rate of BI will undoubtedly increase significantly.

In the traditional model, BI tools are sold to Party A in a buyout system, and Party A’s IT team undertakes the right and responsibility for use. All front-line needs must be processed and transmitted by the IT team, so there is a slow feedback, long cycle, and low frequency. status of use.
In the Guanyuan customer scenario, the customer's front-line sales representatives must be able to see the product sales data on the mobile terminal at any time: daily, weekly, sales of other sales personnel, business status of the store, etc. It is no longer necessary to apply for permission to the IT team, and it does not require IT technology to operate.

Kechuang people: How many challenges does the migration of user portraits bring to product design from the use of IT teams to the use of business teams?

Su Chunyuan: Guanyuan's product design concept is reverse design under the premise of clear goals. No one has made such an attempt in the past 10 years, and many things can only be explored and iterated by themselves. The birth of SmartETL is also based on the consideration of ease of use. If we want business personnel to use it, we must have low-cost data base optimization capabilities; and the mobile terminal has naturally become a necessary usage scenario; in addition , after the business personnel became the main users, it brought concurrent pressure, from dozens, hundreds to thousands, tens of thousands of people, every morning at a fixed time, a large number of business personnel began to look at data, analysis, and decision-making. The information received is different, fine-grained permissions, resource isolation, etc., which require the support of a high-performance, high-stability enterprise-level data architecture.
In addition to these, the most critical part is the combination of AI and BI.

Kechuangren: When Guanyuan announced the C round of financing at the beginning of this year, you mentioned that the deepening of the intelligent analysis product matrix is one of the main investment directions of funds. Can you share your insights on the future of AI+BI?

Su Chunyuan: The commercial application of BI has been nearly 30 years. In the past, the problem it has been trying to solve is "analyzing historical data - giving diagnosis, that is, action suggestions". Combined with AI, it can cross the current capability radius of BI and realize future-oriented action recommendations, that is, business forecasting. At present, Guanyuan has launched in-depth cooperation in the direction of AI + BI with leading customers such as Unilever and Bank of Ningbo.
Through the combination of BI analysis platform and data science and advanced analysis capabilities, the integration of AI technology can enable customers to "use more deeply and predict more accurately", and finally expand high-value forecasting scenarios in various directions.
The threshold for AI prediction is indeed high, and the construction of a general AI platform is even more difficult. Fortunately, Guanyuan has already implemented some AI prediction scenarios in cooperation with Unilever. Next, we will help more The customer completes the landing.

Kechuang people: Guanyuan's development plan in the future? I am more curious, as a leading company in the industry, does it have the spare capacity to solve the talent problem that is obviously restraining the development of the data industry?

Su Chunyuan: To answer your curious questions first, Guanyuan currently promotes the cultivation of data talents through cooperation with customers with a relatively high input-output ratio. At the level of people and 10,000 people, a mature and reliable training system is needed. We will cooperate with customers to hold various data-driven business development competitions. For example, a leading joint-stock bank that cooperated with us recently has more than 100 internal registration teams. Much beyond our expectations. Under the customer's business system and driven by the personal development of employees, talent training can be promoted more effectively and at a lower cost.
When it comes to the future of Guanyuan, "making the business work" is one of our long-term value propositions. We have continuously verified this concept in the scenarios of nearly 500 customers. I hope that there will be 5,000 and 50,000 companies in the next five years Organizations in the industry can also enjoy the huge data value of "making business use".
This is also the most exciting vision for every traveler in Guanyuan, to become a global leader in intelligent decision-making, and to allow 10 million users to enjoy the value of data.
The future of this industry is very big. There is no shortage of a certain product or a certain company, but the underlying logic and underlying cognition that can truly build the foundation of the industry's development requires someone to explore, popularize, and build consensus. This is also the challenge we face, and we hope to find more partners to practice our vision of the future together. As the saying goes, the best way to predict the future is to create it together.