[Golden Ape Characters Exhibition] Capgemini Consulting Shi Kai: In the future, we must make full use of data elements and digital products to create new advantages for enterprises to upgrade their dimensions
In 2022, I personally served a lot of real economy companies. On the one hand, I saw the challenges they faced, and on the other hand, I also worked with them to promote digital transformation. During the whole process, I discovered and summarized the relationship between data and the real economy. , and have exchanges and some consensus on the development in 2023:
Looking back at 2022, everyone is increasing investment in data to improve the ability to face market uncertainties;
Looking forward to 2023, data-driven empowerment of high-quality development of real economy enterprises will bring five major benefits.
Real economy enterprises face four major challenges of high uncertainty
2022 is a turbulent year. The political and economic order and structure are facing reconstruction. The new crown pneumonia epidemic has swept the world, and the world is facing the worst economic recession since World War II. Anti-globalization has intensified, making the already unstable world even worse. turmoil.
The environment is highly unstable, and how to deal with market uncertainty has become the biggest challenge faced by real economy enterprises, which is mainly reflected in four aspects:
1. Consumption downgrade trend
Mintel’s annual report “Chinese Consumers 2022” pointed out that due to the impact of the resurgence of the new crown epidemic on the economy and all aspects of life, the consumer market is under pressure, including more cautious consumer sentiment and potential consumption downgrades in many categories. The downgrading of consumption has led to an unprecedented desire for consumers to have a sense of control over their lives, and thus they will tend to relatively conservative consumption. This is a challenge that must be faced by real economy companies in the consumer goods category.
2. Stock market game
The “2022 China MarTech Industry Research Report” pointed out that “in recent years, the Internet traffic dividend has peaked, the cost of enterprise customer acquisition has risen sharply, and the game in the stock market has become the norm.” The essence of the game in the stock market is to dig deep into the existing market. There are customers to promote the high-quality development of the enterprise. Under such circumstances, each enterprise needs to cultivate its internal strength, take a long-term perspective, and find its own real differentiated advantages in order to gain a competitive advantage in the game.
3. The supply chain is unstable
Relying on the epidemic in 2020 will have a huge impact on the global supply chain. Semiconductor shortages, port congestion, and high freight costs… The endless supply chain problems not only disrupt the production order, but also have a negative impact on the recovery of global trade. Many industries have slashed forecasts after the economic downturn in the early days of the coronavirus crisis, and they were caught off guard when customer demand picked up sharply.
4. Increased employee pressure
According to the research in the “China Merchants Cigna Life Insurance 2022 China Health Index White Paper”, in the face of an uncertain environment, the incidence of stress among Chinese employees in 2022 will be as high as 88.1%, a year-on-year increase of 3.6 percentage points. Last year, it increased by 3.3 percentage points to 8.2%. It is worth noting that the stress incidence rate of Generation Z employees is as high as 94.1%, which is significantly higher than other groups. He and the “Millennials” are also high incidence groups of job burnout. The increased pressure of employees is a huge challenge to the development of enterprises, which means that more precise and comprehensive measures are needed to avoid risks caused by employee pressure.
Looking forward to the upcoming 2023, the epidemic is of course not completely over. Coupled with the conflict between Russia and Ukraine, the global supply chain has once again encountered difficulties. It has been forced to divert ships and planes, shut down production in affected areas, and push up energy prices that have already risen. Many real economy enterprises still face the challenge of uncertainty.
Address uncertainty with certainty using data elements
As Wu Hequan, an academician of the Chinese Academy of Engineering, pointed out, “Obtaining and analyzing data through digital means can greatly eliminate various information asymmetries, optimize resource allocation, improve the agility to respond to rapid changes in the industrial chain and supply chain, and enhance the ability to cope with uncertainties. time flexibility.”
When the real economy is facing the challenge of high uncertainty, it is necessary to make full use of data elements and digital productivity, and use the advantages of both to create a new model, so that the real economy can be plugged into the wings of the digital economy and find certainty from the data , to deal with uncertainty and achieve high-quality development.
1. The five major advantages of dimension upgrading of data production elements
Compared with physical factors of production, data, as a new factor of production, has five advantages in dimension upgrading.
Image Figure 1: Five advantages of dimensionality enhancement of data production elements
① Easy to get
Compared with physical production factors such as minerals, land, and oil, data production factors are almost inexhaustible, easier to obtain, and universal.
② Easy to process
The processing and production of physical production factors is very limited to processing equipment and technology, the cost is high, and many technologies are controlled overseas, while the processing of data production factors is computing power and algorithm models, and a computer is enough.
③ Easy to spread
It takes a long time to transport one ton of minerals from Shanghai to New York, but a data product, such as a TikTok video, can spread to every corner of the world in just one second.
④ Easy transaction
The transaction of physical production factors is highly dependent on offline quality inspection and transaction links. The transaction of data elements can be carried out at high speed relying on the Internet, and the payment is easier.
⑤ Ease of measurement
In the industrial chain of physical production factors, every link and action of processing, handling, and transaction needs to be specially measured, such as the detection and management of inventory. The value chain of data production factors itself records all the production processes, which is easier to measure, and only with measurement can improvement be possible.
2. Five dimension-enhancing advantages of digital productivity
What matches the data production elements is digital technology, which is a new productivity in the digital age, such as cloud computing and artificial intelligence.
Image Figure 2: Five Dimensional Advantages of Digital Productivity
① Elasticity
In the productivity of the real economy era represented by electricity, the elastic expansion capability is relatively slow, and it cannot quickly increase the computing power several times in a few minutes like cloud computing capabilities.
② Flexible
The productivity of the real economy, taking the production line of automobiles as an example, if you want to change the product model, the relative complexity and workload are far greater than the function change of a software product, which reflects the flexibility of digital technology.
③ Interaction
In the era of the real economy, after a product is sold, it lacks the means to interact and communicate with users in real time. With the support of digital technologies such as the Internet of Things, enterprises can interact with users in real time.
④ Collaboration
In the era of the real economy, the organizational collaboration of enterprises is highly dependent on regions, and the efficiency of remote collaboration is very low. With the widespread application of digital technologies such as instant messaging and video voice, remote real-time collaboration can be achieved.
⑤ Scale
The productivity of the real economy is limited by space and resources, and it is difficult to scale up in a short period of time. However, the productivity of digital technology can rely on elastic computing power, easy access and rapid dissemination of data elements, and can achieve rapid scale. Modernized production, such as digital simulation testing, can increase the test iteration speed of product development by more than hundreds of times.
Relying on these ten advantages of data elements and digital productivity, building data-driven capabilities can fully empower the high-quality development of enterprises in the real economy.
Data-driven empowerment of high-quality development of enterprises in the real economy
Real economy enterprises, after the past two decades of informatization construction, many already have a solid informatization foundation. CRM, ERP, MES and other systems have supported the company’s all-round business processes, so, to a certain extent, a large amount of business has been digitized, so real economy companies have a data-driven foundation, and at the same time You will be able to obtain the five major benefits brought by data-driven.
1. Five major benefits of data-driven high-quality development of real economy enterprises
Forbes, a world-renowned research organization, pointed out that “starting in 2023, building a data-driven business model will be the core of digital transformation in all industries.” Data-driven can bring five major benefits to the high-quality development of real economy enterprises, as shown in Figure 3:
Image Figure 3: Five major benefits of data empowering the real economy
1. Improve corporate profitability
Data and digital technology can connect the upstream and downstream of the industrial chain, extend the business scope and model, and improve profitability. For example, a Fortune 500 company uses data intelligence, Internet of Things, blockchain and other technologies to run through the grain industry chain. The three major links of warehousing and circulation realize the rapid expansion of warehouse capacity under the light asset model, and connect the ecological parties such as grain consumption, finance, and logistics, and improve the efficiency of trade, logistics, and finance in the entire industrial chain. It is estimated that the 2025 grain harvest season will cover the corn industry in the five provinces of Heiji, Liaoning, Mongolia, and Henan, connecting 800,000 growers; the 2027 grain harvest season will cover soybeans, rice, wheat and other categories, connecting 1.6 million growers.
2. Improve production and operation efficiency
Digital technology breaks through the breakpoints of production and operation, makes business automatic and intelligent, and greatly improves the efficiency of production and operation. For example, a dairy factory built a digital factory and used 18,000 automatic control valves to create the largest “valve array” in a single dairy workshop. Driven by the data, the control valve automatically adjusts the direction according to different production links and sends the raw materials to the designated pipelines and storage tanks. The raw materials are transported to the production line of pasteurized fresh milk, yogurt, room temperature milk and other dairy products according to the production plan.
3. Improve user/customer experience
Connect users through data, directly reach and obtain customer feedback, so as to quickly respond to customer needs and improve customer experience. This is a major benefit of data empowering real economy enterprises. For example, a large-scale machinery and equipment manufacturer, through the application of the Internet of Things and big data technology, can grasp the problems of equipment in the process of customer use in real time, through remote diagnosis and analysis, achieve predictive maintenance, improve the utilization rate of equipment, and greatly improve customer service experience.
4. Improve risk compliance capabilities
Risk compliance management capabilities are the top priority for real economy companies, and often a single risk can bring huge losses. However, traditional methods are based on systems and processes, with slow response and lag. By collecting data in the business process and establishing a risk control model in real time, it can greatly improve the ability of enterprises to manage risk compliance.
5. Improve innovation ability
From the data, new insights that are not perceived and not fully grasped by many people’s experience can be discovered, thereby improving the business innovation capabilities of enterprises. Now many enterprises are carrying out data innovation competitions, allowing business, technology, and data personnel to jointly create and explore, and use data to create new business models.
The high-quality development of an enterprise is not only reflected in the above five major benefits, but also includes the sustainable development of the real economy. Data can eliminate waste, reduce carbon emissions, and enhance the sustainable development capabilities of enterprises.
2. Data empowers the sustainable development of the real economy
Sustainable development, which is very important for the high-quality development of enterprises, has become an issue of unprecedented concern to human society. Whether it is “carbon neutrality, carbon peaking” or green development among the five development concepts, they all focus on saving resources, To achieve the goal of sustainable human development.
Enterprises are an important constituent unit of society, and sustainable development is inseparable from the participation of enterprises. In recent years, the issue of ESG has become the core concern of corporate management. ESG is an acronym for the initials of the words Environmental (Environmental), Social (Social) and Governance (Governance). ESG indicators measure the sustainability of corporate development from the perspectives of environment, society, and corporate governance.
Capgemini Consulting, a world-renowned consulting company, recently released the “Corporate Sustainability Report”, proposing the path to achieve a zero-carbon enterprise, as shown in Figure 4:
Image Figure 4: Corporate Sustainability Report
Through a series of structured and systematic digital technologies and implementation methods, combined with the status quo of different companies to identify and explore high-value business scenarios, help companies achieve low-carbon sustainable development step by step.
3. High-quality business scenarios are the core of data empowerment for real economy enterprises
Enterprises face many challenges in the process of using data, such as low data quality, inconsistency of data integration, difficulty in sharing data among enterprises, etc. However, traditional data governance and other means are difficult to solve. This is because the relevant data providers and data users have not reached a consensus on the goal and cannot achieve a real win-win situation. Therefore, although many methods and tools have been adopted, and many systems have been installed, the problem of data collaboration and the driving force of pulling together has not been fundamentally solved.
Only valuable and high-quality business scenarios that can benefit multiple participants and data-related parties can fundamentally solve the problem of data empowering the business of real economy enterprises.
How to mine and identify high-quality business scenarios has become an important issue in the digital transformation of all enterprises.
The Lean Data Method Empowers the Four Great Weapons of Enterprises in the Real Economy
Lean data methodology is a set of data-driven digital transformation methodology systems based on the past two decades that I have served many domestic large-scale enterprise information constructions, digital transformation, actual combat, precipitation, and summary. It integrates lean thinking, agile manifesto, design thinking, strategic planning methods, Cynefin, and other frameworks, advocates customer value as the core, data as the production factor, waste elimination, on-demand production, and continuous iteration. In the past 10 years, This set of methods has been adopted and used for reference by many enterprises, and successfully supported their digital transformation.
1. Four components of lean data methodology
Building a data-driven enterprise is not only a technical matter, but also a complex issue involving strategy, organization, culture, process, governance, collaboration, technology, and data systemization. Lean data methodology consists of four major parts, as shown in Figure 5:
Image Figure 5: Lean Data Methodology
① Lean Data Manifesto
The Lean Data Manifesto includes values and principles of action, which can help those involved in digital transformation reach agreement on values and codes of conduct, thereby minimizing friction and enhancing internal collaboration.
② Lean digital transformation path
Lean data methodology divides data-driven digital transformation into three stages, exploration and planning, construction and operation optimization. Taking customer value as the core, responding to market uncertainty with the certainty of data, driving the overall construction with value scenarios, and ultimately building a data-driven enterprise.
③ Six capabilities of a lean digital enterprise
Data-driven is the goal that lean digital enterprises need to establish. To achieve this goal, it is necessary to build six major capabilities, namely lean data strategic planning capabilities around business value, lean data products that can create benefits and value for enterprises, and lean data products that promote governance through application. Data governance, full-link data collaborative innovation and one-stop unified data middle-end capabilities, all must be based on a data-driven organizational culture.
④ Lean Data Workshop
The lean data method emphasizes the integration of business and technology, process and data, and discovers value scenarios through exploration and co-creation, rather than copying best practices from top to bottom. In order to enable business personnel to fully align with their goals and comprehensively diverge business scenarios, lean data methods are developed
Know the industry’s first digital card script kill, use a set of lean data cards, let business, technology, and data personnel interact in the game, and conduct interesting explorations in all directions without blind spots, and finally reach an agreement to form a digital transformation Item checklist and action plan.
2. Lean data workshop helps real economy enterprises find high-quality business scenarios
How to find a high-quality business scenario where all stakeholders agree, work together, and connect data is the biggest challenge for many enterprises in their digital transformation. In order to solve this problem, I have integrated traditional strategic planning, business consulting methods and agile and lean methods in the past ten years. I was inspired by card-style board games and script killing, and invented a set of card-style data work. Workshop can use ten types of cards to comprehensively decompose the complex and vague systematic work of digital transformation into scenarios that can be focused and realized step by step.
This card workshop includes ten kinds of cards, as shown in Figure 6:
Image 6: Lean Data Card Workshop
By aligning the vision, decomposing the goals, unifying the standards of business value, and then using the four original methods of the Lean Data Methodology to comprehensively explore, identify, and diverge the data asset blueprint, combined with data intelligence technology, align the goals and arrange and combine all business value scenarios , and then prioritize the scenarios, generate a project list, action measures, and match them with corresponding resources and tools. This process, through an easy-to-understand, lively and interesting form, allows everyone to complete the implementation of data-driven digital transformation in an entertaining and entertaining manner.
In the past four years, I have summarized this original summary methodology in China into a 300,000-word digital transformation book “Lean Data Methodology-Data-Driven Digital Transformation”, which will be released soon. The book has been recommended by more than 50 domestic experts and scholars in the field of digitalization, and it is called “the boat across the river and the bridge across the river for digital transformation”.
·About Shi Kai:
Mr. Shi Kai is the author and founder of “Lean Data Methodology-Data-Driven Digital Transformation”, author of the public account “Kaige Storytelling”, Vice President of Capgemini Consulting Asia Pacific, Chief Data Innovation Officer of Asia Pacific, and former Alibaba Cloud China General Manager of District Consulting, General Manager of Thoughtworks Data Intelligence.
The inventor of lean data methodology, has more than 20 years of practical experience in the digital transformation of enterprise information construction, and has explored in practice, actual combat, and summed up the value of lean thinking and digital transformation as the core, scenario-driven data-driven digital transformation methodology, and tools system, and has received good feedback in many enterprise applications.
Mr. Shi Kai is the CIO branch of the China Software Association, a distinguished expert of the Big Data Committee of the China Academy of Information and Communications Technology, the core creative expert of “T/SIA 035–2022 Digital Manager Ability Evaluation Standards for Enterprises and Institutions”, and the global DataIQ100 data enabler, 2019 China Enterprise digital leader.
