Wen | Xu Wenpu
Editor | Shi Yaqiong
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The wave of digital and intelligent transformation has swept through large domestic enterprises for many years, but there are not many successful cases.
Compared with many enterprises' digital and intelligent transformation strategies that cannot be implemented and are not consistent, Midea has planned digital intelligence as a top-level design since its transformation in 2012, and has developed benign in the implementation of landing-strategic upgrading-implementation.
It can be said that the decade of digital and intelligent transformation is also a decade of rapid development of Midea. During this period, Midea's annual revenue increased by 234% in 10 years to 341.2 billion yuan (FY2021), and net profit attributable to the parent increased by 777% to 28.6 billion yuan (as of FY2021).
Internally, at the level of enterprise operation, Midea has achieved cost reduction and efficiency increase within the group through organizational structure upgrade; In the production process, Midea opens up the walls of upstream and downstream enterprises and optimizes the relationship between purchase, sale and inventory; From the perspective of factory digital intelligence, Midea has successively declared and passed three lighthouse factories in 2022, and has harvested a total of 5 lighthouse factories.
Externally, Midea has incubated Meiyun Intelligent Data to provide services for the digital and intelligent transformation of many industries such as auto parts, electronic semiconductors, agriculture and animal husbandry food, and now its customers have covered large, medium, small and micro enterprises.
With its deep cultivation in the field of digital intelligence, on October 26-27, at the 7th IDC China Digital Transformation Annual Ceremony 2022, Midea and Meiyun Intelligent Data won the "Future Enterprise of the Year" Excellence Award at the 2022 IDC China and Asia Pacific Future Enterprise Awards for "Meiyun Intelligent Data Empowering Midea's Lighthouse Factory Digital Project".
This time, Digital Krypton interviewed Yu Haifeng, CEO of Midea Group, Yu Haifeng has been rooted in the field of enterprise digital intelligence for many years, and has provided digital intelligent transformation services for customers in multiple industries, not only for Midea's internal digital intelligent transformation experience, but also using proven Midea experience to empower the outside world.
Through dialogue with Yu Haifeng, "Digital Krypton" hopes to provide some ideas for manufacturing companies at the crossroads of transformation. Here's what the conversation is (edited by Digital Krypton):
01 Digital intelligent transformation: Regardless of the size of the enterprise, we must do a good job of top-level design
Digital Krypton: Midea Group's digital intelligence strategy has been upgraded three times in the past 10 years, what role does the top-level design of digital intelligence play in the digital transformation of enterprises?
Yu Haifeng: In 2012, Midea launched the "632 Plan", which opened up the systems, processes and data of 10 business units within the group at that time, and initially achieved the goal of using data to assist scientific decision-making, laying the foundation for all our subsequent digital and intelligent upgrade strategies.
After the "632" plan, Midea experienced "T+3", completed the channel reform and moved towards flexible manufacturing; This was followed by the "two comprehensive" strategy, which further promoted comprehensive digitalization and all-round intelligence in the group; By this year we have unveiled the "Digital Beauty 2025" blueprint.
Now, digital and intelligent transformation has become a common problem for many enterprises, and how to use data tools to make more scientific decisions and let enterprises survive in an uncertain environment has become the focus of everyone's attention. In terms of implementation, I think that all enterprises that want to transform must first do a good job of digital intelligence top-level design, generally speaking, the plan for the next three to five years can be formulated relatively quickly, and focus on the links that can generate value.
Digital Krypton: It's important to have a top-level plan, but how should companies make it, and what lessons do you think Midea can learn from?
Yu Haifeng: I think we can start from two aspects. First of all, the enterprise should sort out the core competitiveness, talent echelon and team competence range. Secondly, it is necessary to bring in external expert support, which can give suggestions based on the specific problems of the team and can also bring solution ideas from other enterprises.
Midea also initially invited a team of external experts. The decision to pat the head internally will most likely lead the enterprise to an unreliable detour. At the same time, external institutions can make convincing evaluations of various departments of the enterprise from a relatively objective standpoint, and bring past service cases, so that we can avoid some of the pits that other enterprises have stepped on.
However, both internal and external aspects of the enterprise have their own advantages and disadvantages. External experts bring fresh perspectives, tips and tools, internal teams better understand the business and realities of the company, and strategy implementation is also realized by internal teams. Therefore, the two teams need to collide while doing to eliminate the gap between them and cooperate for the common goal, rather than staying in a one-time buying and selling relationship.
Digital Krypton: In the past 10 years of digital and intelligent transformation, Midea has invested a total of 17 billion yuan. Digital intelligent transformation means considerable cost investment, large enterprises have more resources in this regard, according to your observation of small and medium-sized enterprises current digital intelligent transformation of the urgency of the current sense of urgency?
Yu Haifeng: Everyone has a sense of urgency for transformation, but in the process of implementation, the transformation of large enterprises is more scientific and systematic, and they will consciously formulate top-level plans for digital and intelligent transformation. Small and medium-sized manufacturing enterprises are more dependent on government support policies.
At present, the local governments of the Pearl River Delta and the Yangtze River Delta have a large subsidy for the digital and intelligent transformation of factories, and some local subsidy funds will even exceed the cost of factory transformation, while some regions provide subsidies proportionally according to the cost of factory transformation. With policy support, many small and medium-sized manufacturing enterprises are transforming with the mentality of "why not", but the transformation process lacks overall planning.
In addition, we also see a trend for the digital and intelligent transformation of small and medium-sized enterprises - the industrial chain master in the industrial cluster pulls the digital intelligent transformation of upstream and downstream enterprises. Taking Meiyun Zhishu as an example, it is still very challenging for small and micro enterprises to purchase products separately, but in an industrial cluster, it is easier to let representative industry leaders drive the ecological chain to the cloud.
For example, in Foshan, we used to promote one company at a time, which was more difficult and the progress would not be fast. But today we hold a business promotion and recruit more than a dozen leading enterprises in the industry, and they will drive more than 100 upstream and downstream enterprises to sign contracts, which was unimaginable before.
Digital Krypton: Please combine the experience of beauty and enterprise service to talk about what enterprises need to pay attention to in the process of implementing digital intelligence strategy?
Yu Haifeng: First of all, digital intelligent transformation is a number one project + business leading, and enterprises need to provide support at the organizational structure level. Midea's digital transformation team was led by Fang Hongbo from the beginning, and the members were the management and business backbone of each business unit. At the same time, the trinity of IT team, decision-making data operation center and digital office responsible for landing drives Midea's digital transformation from top to bottom. We've met a lot of customers who just assign the task of digital transformation to IT, which I think is the wrong approach.
The second is to make good use of external experts and do a good job of top-level design.
The third is to find the right entry point for transformation. The top-level design should be implemented, and the entry point must be accurate enough at the beginning to effectively control business risks. More importantly, it is necessary to build confidence in the transformation of the team at the beginning, otherwise it will not only be difficult and risky to start, but also mess up will make the internal distrust of digital intelligent transformation, and it will be more difficult to push back. Midea originally used the major appliances represented by the household air conditioning division and the small household appliances represented by the micro-clear (microwave and cleaning) division as the entry point for process and business transformation, and the two pilot business units covered most business scenarios and fully polished the process and system. Think big, start small, and after the 632 project has been fully demonstrated, then replicate the successful experience to the entire department, the entire BU, and the entire group.
The fourth is that enterprises should establish their inherent digital intelligence capabilities in this process. We may need external experts to do a lot at first, but in the process, companies should continue to develop their own team's philosophy and skills. Digital intelligent transformation is not a one-time thing, in order to obtain long-term competitiveness through digital intelligence, the inherent level of digital intelligence of enterprises must also be continuously upgraded.
02 Lean manufacturing: Midea sets an annual growth target of 15%-30%.
Digital Krypton: Midea's current 5 lighthouse factories are all based on the declaration of existing factory renovation. Transformation or new construction, how should enterprises decide when upgrading the digital intelligence of factories?
Yu Haifeng: The new factory can take care of many aspects such as top-level design, system construction, talent training, and management mode from the beginning, so the overall digital and intelligent upgrade is easier to achieve, but the only drawback is the high cost.
From production line design layout, system upgrade to overall framework construction, Top-Down (top-level design) is easier to realize the overall intelligence of the factory, basically packaging the most advanced digital intelligence capabilities of the enterprise. When the plant is built, it involves the team's operations. If you are dispatching employees from an old factory, you need to adapt the workers to the transition from traditional management models to new management methods. Workers need to reduce costs and increase efficiency in accordance with the new standards, from inspections and maintenance to daily meetings, which requires the development of awareness among all employees in the factory. In addition, when planning a new factory, we use simulation software to simulate the machine capacity, production process and efficiency of the factory, and on this basis, its overall strength is constantly approaching the standard of the lighthouse factory.
For Midea, we can complete the transformation of the existing high-quality factory in 2 years and pass the declaration of the lighthouse factory, which is inseparable from the foundation laid by our long-term adherence to digital and intelligent transformation.
Digital Krypton: What exactly does Midea's accumulation in the digital intelligent chemical factory mean?
Yu Haifeng: In terms of talent training, we have Midea Academy, which cooperates with factories and production and research colleges around the world to jointly cultivate talents in the intelligent manufacturing industry. In terms of production line transformation, we have a lot of cost-based thinking, because the cost of overturning all factory renovations is very large. We will also use simulation software to simulate the production line to explore which processes are more cost-effective to use human-robot collaboration or replace with automated robots. In order to improve the team's overall awareness of lean manufacturing concepts, we set a factory capacity growth target of 15%-30% every year, and then promote it.
Digital Krypton: According to your observation, are there any differences in the declaration standards of lighthouse factories from 2018 to 2022, and what technology and application trends behind this reflect?
Yu Haifeng: With the development of technology, lighthouse factories have increased their requirements for AI-driven intelligence and green sustainability. On the other hand, we also see no change in the basic concepts of lean manufacturing, automation, and digitalization, but the implementation is more refined and clear, and the improvement of key performance indicators such as agility, speed to market, batch reduction, on-time delivery and customization is more important.
03 Cost center becomes profit center: capacity covers large, medium, small and micro enterprises
Digital Krypton: Meiyun Intelligent Data was incubated from within Midea, what stages has it gone through in the process of marketization?
Yu Haifeng: Founded at the end of 2016, Meiyun Intelligent Data has refined Midea's manufacturing capabilities, R&D capabilities, marketing capabilities and end-to-end capabilities in the process of digital intelligent transformation into a methodology. At the same time, Midea also took out the internal system and was committed to creating a standard industrial software.
In the process of productization, in order to adapt to the specific scenarios of various industries, Meiyun has been serving leading customers in various industries from 2020 to 2021, and building a complete set of digital intelligent processes and systems with customers. By absorbing the opinions of leading customers in the industry and precipitating industry service experience, Meiyun's industry solutions now cover more than 40 subdivided industries such as auto parts, electronic semiconductors, agriculture and animal husbandry food.
In 2022, we opened up our services to small and medium-sized enterprises based on the more standardized nature of our solutions. In order to better serve small and micro customers, we are also further focusing on and cloudifying product functions, and charging by category, usage time and frequency to meet the needs of micro enterprises. At present, we internally plan large, medium and micro enterprises into three growth curves, and we have complete product line coverage for these three types of customers.
Digital Krypton: According to your observation, what stage is the digital and intelligent transformation of domestic enterprises? What are the differences compared to foreign countries?
Yu Haifeng: Large domestic enterprises, especially large private enterprises, have changed rapidly. In recent years, many large private enterprises have entered a more mature stage of digital and intelligent transformation. A significant difference at home and abroad in this regard is that foreign digital intelligent products have a high degree of standardization, and foreign companies also tend to purchase different products to achieve enterprise transformation, and different products and systems are connected through standard agreements. However, large domestic enterprises tend to build their own teams and customized systems.
How to plan the cost of digital intelligent transformation in the whole life cycle of enterprises, not just stop at one-time solutions, is the status quo that large domestic enterprises need to change. This change requires the acceptance of software products and standard software vendors by large enterprises. In China, it may take another three to five years for large enterprises to accept the digital transformation service from solution-oriented to product-oriented.
Medium-sized companies now have no problem accepting standard software, but the problem is that most of the software is not done well and key functions are not focused enough. In terms of products, domestic substitution is an opportunity for the industry. However, there is still a big gap in industrial software such as CAD and CAE in China. I think it will take 5-10 years for the product strength of domestic software to peak.
For small and micro enterprises, the transformation through the industrial chain has formed a trend. Small and micro enterprises mainly purchase SaaS products to transform, which still tests the product power of domestic products. The SaaS model is a clear trend, and domestic digital intelligent transformation products must first achieve standardization, and then focus on specific functions. I think it may take another 10 years for China to achieve modernization and digital intelligence, including small and micro enterprises.
![54-year-old "Wu Song" Ding Haifeng: Chopping wood and barbecue in the American woods, the mansion is full of style[fig]](data:image/gif;base64,R0lGODlhAQABAIAAAP///wAAACwAAAAAAQABAAACAkQBADs=)