【CXO观点】国务院发展研究中心原副主任张军扩：数字化转型重在制度创新和环境优化
党的二十大报告指出，要“坚持把发展经济的着力点放在实体经济上”“促进数字经济和实体经济深度融合”。我国是世界第一制造业大国，也是数字技术大国，在经济全球化遭遇逆流、新一轮科技革命和产业变革突飞猛进、数字技术加速与制造业深度融合的大背景之下，加快推进实体经济数字化转型，加快建设现代化产业体系，是大势所趋、必由之路，对提升企业竞争力水平、实现区域经济高质量发展、顺利推进我国现代化进程，都具有十分重要的意义。
党的十八大以来，党中央高度重视实体经济的智能化数字化转型发展，各部门各地区积极响应、迅速行动，纷纷结合自身实际制定行动计划和实施方案，实体经济特别是制造业数字化转型取得了积极进展，具备了良好基础。有关资料显示，目前我国制造业数字化、网络化、智能化水平不断提升，已培育出具有一定影响力的工业互联网平台超过150家，工业设备连接数量超过7900万台（套）。同时也要看到，我国实体经济数字化转型尚处于从试点培育到快速成长的过渡阶段，进一步转型的潜力和空间依然很大、任务依然艰巨，还面临着关键技术和产业基础薄弱、复合型人才缺口较大、工业物联网标准尚不健全、数据安全法规保障滞后等一系列突出问题，亟需通过政府、企业、社会等各方面协同发力加以解决。
需要明确的一点是，无论是智能化改造还是数字化转型，企业都是实施主体和主要力量。转型的最终目的，是提高企业、产业的竞争力和盈利能力。政府发挥作用的关键，就是要从克服和缓解企业转型面临的各种问题、困难和制约因素出发，尽可能创造有利的外部环境，为企业赋能，增强其转型的能力、意愿和信心。立足当前，实现实体经济数字化转型，关键在于制度的不断创新完善和环境的不断优化，以下六个方面是最为重要的。
第一，进一步推动相关基础设施建设。
制造业的数据主要来源于机器设备数据、工业信息化数据和产业链数据，生产设备的数字化程度直接决定了生产数据采集能力。近年来，我国虽然在生产设备数字化和工业互联网平台建设等方面进展显著，但也存在一些短板，下一步要着眼于提升内外贯通能力，协同推进内网和外网建设。一方面，要进一步促进企业内部设备的技术改造。我国制造业门类众多、市场主体数量庞大、技术水平参差不齐，要想进入人机互联阶段，数字化、网络化、智能化改造的任务依然很重。为此，要综合运用财政、金融等手段，激励和支持企业运用先进适用技术改造建设企业内网。另一方面，要进一步支持企业建设5G全连接工厂，持续增强企业外联能力与稳定性。
第二，促进制造业数据的联通与共享。
数据的联通与共享既是数字化智能化转型的前提基础，更是充分释放数据潜在经济价值的关键所在。目前制约数据联通共享的因素主要有二：一是标准问题，二是数据安全问题。调研发现，当前制造业企业的存量设备供应商和型号众多，由于各家设备接口不统一，通信协议不兼容，往往需要进行数字化改造才能接入系统当中，不仅增加了连接上云的难度，也增加了连接成本。处于同一产业集群及不同产业集群间的利益相关企业，出于商业利益和风险规避的考虑，共享涉及生产经营等企业数据的意愿不高。此外，由于目前缺少具有公信力的数据共享机制，产业链数据更加难以互通。因此，下一步要聚焦促进数据联通与共享这一重点，进一步完善工业设备的互联互通标准，推动工业设备接口互认、协议兼容，提升行业设备的联动能力；加快研究制定统一的工业大数据管理制度和标准规范，提升工业数据治理能力，促进数据合理流动、安全交易、共享使用。
第三，强化专业型和复合型人才供给。
与过去的信息化主要侧重于企业流程再造不同，基于新一代信息技术与先进制造技术深度融合的企业数字化智能化转型，不仅仅是一种技术转型，更是一种思维方式与经营模式的深层转型，是涉及企业战略、组织、运营、人才等的体系化变革和全方位创新。因此，推动企业数字化智能化转型，既需要企业领导人立足行业发展大势，以数字化转型带动整体战略升级，也需要全体员工对数字化转型的支持，特别是需要既懂数字化技术又懂经营业务的高级复合型专业人才的支持。调研显示，高级复合型人才短缺是当前企业转型一个重要的制约因素。为此，要强化政策引导作用，充分发挥高校、企业、平台等各方主体优势，立足产业转型需求和人才梯队的有机组合，多维度完善数字化转型人才的培养体系。同时，要努力打造数字化转型人才共享资源池和数据库，综合采用企业内训支持、专家顾问服务、联合培养认证等方式，实现高端人力资源的跨界流转与开放共享。
第四，支持培育数字化转型集成服务商。
对于制造业企业来说，绝大多数并不具备数字化转型的技术积累、人才队伍和集成解决能力，需要服务商对企业进行专业诊断，提供从规划设计、系统开发、建设部署到运营维护的一揽子服务。调研发现，目前，在企业数字化转型集成服务市场上，服务商服务能力和质量参差不齐，一些服务商的集成能力、智能化能力存在不足。为此，一方面，要通过政府采购等适当方式，激励集成服务商结合既往经验，梳理形成分行业、分区域、分类型的数字化转型方案及推进路径，形成经济适用的标准化模块，降低方案成本。另一方面，要鼓励和促进不同行业、专业领域的服务商，通过联合或合作等方式，形成综合服务能力，提供集成改造和整合方案，并支持其将各种制造经验数字化、模块化、通用化，赋能更多传统制造企业。
第五，完善关键共性技术研发的支持政策。
目前，我国制造业对外技术依存度较高,一些关键核心技术受制于人，产业发展需要的高端设备、基础零部件、元器件、关键材料等很多依赖进口，产业链供应链补齐尚需时日。破解关键共性技术难题是一个系统工程，需要久久为功、多措并举。一方面，要进一步完善对关键共性技术研发的支持政策，把支持的重点放在智能传感器、云化工业软件、云计算中心等关键技术领域，激发创新合力。另一方面，要加强产学研用的对接沟通，联合开发面向制造业数字化智能化转型等需求的系统和装备，用好用足相关财政支持政策，助力装备企业在实用迭代之中实现质量提升。
第六，着力优化营商环境和发展环境。
有关调研发现，当前企业数字化转型面临的一个突出问题是发展战略缺位、转型缺乏方向。近年来，受国际形势等影响，企业经营环境面临较多的不确定性。数字化转型本质在于“转型”，未来愿景不明，转型方向不清，数字化的方向也难以确定，动力和能力自然就会不足。当前情况下，促进企业数字化智能化转型，不能就数字化论数字化，必须首先解决好企业发展环境、发展方向与发展信心问题。换句话说，除了要注重优化与数字化智能化直接相关的外部政策环境外，还要高度重视进一步优化企业发展的大环境，包括监管政策的进一步透明和稳定、营商环境的进一步优化、重点领域改革的加快推进等。只有这样，企业数字化智能化转型才能具有更坚实的基础，也才能取得更好和更可持续的效果。
翻译：
The report to the 20th National Congress of the Communist Party of China pointed out that we should "stick to the focus of economic development on the real economy" and "promote the deep integration of the digital economy and the real economy". China is the world's largest manufacturing country and digital technology power. Under the background of countercurrent of economic globalization, rapid progress of a new round of scientific and technological revolution and industrial change, and the deep integration of digital technology and manufacturing, accelerating the digital transformation of the real economy and accelerating the construction of a modern industrial system is the general trend and the only way. It is of great significance to enhance the competitiveness of enterprises, realize the high-quality development of regional economy, and promote the modernization process smoothly.
Since the 18th CPC National Congress, the CPC Central Committee has attached great importance to the intelligent digital transformation and development of the real economy. Various departments and regions have responded positively and acted quickly, and formulated action plans and implementation plans based on their own actual conditions. The digital transformation of the real economy, especially the manufacturing industry, has made positive progress and has a good foundation. Relevant data show that at present, the digital, network and intelligent level of Chinese manufacturing industry continues to improve, has cultivated more than 150 industrial Internet platforms with a certain influence, and the number of industrial equipment connection more than 79 million (sets). At the same time, it should also be noted that the digital transformation of Chinese real economy is still in a transition stage from pilot cultivation to rapid growth. The potential and space for further transformation are still large and the task is still difficult. It is also faced with a series of outstanding problems, such as weak key technologies and industrial foundation, large gap of compound talents, imperfect standards of industrial Internet of Things and lagging data security regulations. It is urgent to solve the problem through the concerted efforts of the government, enterprises, society and other aspects.
It needs to be made clear that enterprises are the main implementers and forces of both intelligent transformation and digital transformation. The ultimate goal of transformation is to improve the competitiveness and profitability of enterprises and industries. The key for the government to play its role is to start from overcoming and easing various problems, difficulties and constraints faced by enterprises in their transformation, to create a favorable external environment as far as possible, empower enterprises and enhance their ability, willingness and confidence in transformation. Based on the current situation, the key to realize the digital transformation of the real economy lies in the continuous innovation and improvement of the system and the continuous optimization of the environment. The following six aspects are the most important.
First, further promote relevant infrastructure development. The data of manufacturing industry mainly comes from machine and equipment data, industrial informatization data and industrial chain data. The digitalization degree of production equipment directly determines the production data collection ability. In recent years, although China has made remarkable progress in digitization of production equipment and construction of industrial Internet platforms, there are still some shortcomings. The next step should focus on improving internal and external penetration ability and promoting the construction of internal and external networks in a coordinated way. On the one hand, to further promote the enterprise internal equipment technical transformation. Our manufacturing industry has many categories, a large number of market subjects and uneven technical level. If we want to enter the man-machine interconnection phase, the task of digital, network and intelligent transformation is still very heavy. To this end, we should make comprehensive use of fiscal and financial means to encourage and support enterprises to use advanced and applicable technologies to transform and construct enterprise internal networks. On the other hand, further support should be given to enterprises in building fully connected 5G factories to continuously enhance their outreach capacity and stability.
Second, promote the connectivity and sharing of manufacturing data. Data connectivity and sharing is not only the premise of digital intelligent transformation, but also the key to fully release the potential economic value of data. At present, there are two main factors restricting the sharing of data connectivity: one is the standard problem, the other is the data security problem. According to the survey, the current manufacturing enterprises have a large number of equipment suppliers and models in stock. Due to the inconsistent interfaces and incompatible communication protocols of each equipment, digital transformation is often needed to access the system, which not only increases the difficulty of connecting to the cloud, but also increases the connection cost. For the consideration of commercial interests and risk avoidance, stakeholder enterprises in the same industrial cluster or among different industrial clusters are not willing to share enterprise data related to production and operation. In addition, due to the lack of credible data sharing mechanism, industrial chain data is more difficult to communicate. Therefore, the next step should focus on the promotion of data connectivity and sharing, further improve the standards of industrial equipment connectivity, promote the mutual recognition and protocol compatibility of industrial equipment interface, improve the linkage ability of industrial equipment; We will accelerate the research and formulation of unified industrial big data management systems, standards and norms, improve the capacity of industrial data governance, and promote the rational flow of data, secure transactions and shared use of data.
Third, strengthen the supply of professional and compound talents. Different from the past informatization, which mainly focuses on enterprise process reengineering, the enterprise digital intelligent transformation based on the deep integration of the new generation of information technology and advanced manufacturing technology is not only a kind of technological transformation, but also a deep transformation of thinking mode and business mode. It is a systematic transformation and all-round innovation involving enterprise strategy, organization, operation and talent. Therefore, to promote the digital intelligent transformation of enterprises, not only enterprise leaders need to base on the development trend of the industry and promote the overall strategic upgrading through digital transformation, but also need the support of all employees for digital transformation, especially the support of senior composite professionals who understand both digital technology and business. Research shows that the shortage of senior compound talents is an important restriction factor in the current enterprise transformation. Therefore, it is necessary to strengthen the guiding role of policies, give full play to the main advantages of universities, enterprises, platforms and other parties, and improve the training system of digital transformation talents in multiple dimensions based on the organic combination of industrial transformation needs and talent echelon. At the same time, efforts should be made to build a shared resource pool and database for talents in digital transformation. Internal training support, expert consulting services, joint training certification and other methods should be comprehensively adopted to realize cross-border circulation and open sharing of high-end human resources.
Fourth, we will support the cultivation of integrated service providers for digital transformation. For manufacturing enterprises, most of them do not have the technology accumulation, talent team and integrated solution ability for digital transformation, so they need service providers to make professional diagnosis for enterprises and provide a package of services from planning and design, system development, construction and deployment to operation and maintenance. It is found that, at present, in the enterprise digital transformation integrated service market, service capabilities and quality of service providers are uneven, and some service providers have insufficient integration capabilities and intelligent capabilities. Therefore, on the one hand, it is necessary to encourage integrated service providers to form digital transformation schemes and promotion paths by industry, region and type by government procurement and other appropriate ways, so as to form economical and applicable standardized modules and reduce program costs. On the other hand, it is necessary to encourage and promote service providers in different industries and professional fields to form comprehensive service capabilities, provide integrated transformation and integration solutions through joint or cooperative means, and support them to digitize, modularize and generalize various manufacturing experiences so as to empower more traditional manufacturing enterprises.
Fifth, we will improve policies to support research and development of key generic technologies. At present, our manufacturing industry is highly dependent on foreign technology, and some key core technologies are controlled by others. Industrial development needs high-end equipment, basic parts, components, key materials and so on, and it will take time to complete the industrial chain and supply chain. Solving the key generic technical problems is a systematic project, which requires a long effort and multiple measures. On the one hand, it is necessary to further improve the supporting policies for the research and development of key generic technologies, focusing on key technology fields such as smart sensors, cloud chemical industry software and cloud computing centers, so as to stimulate innovation synergy. On the other hand, we need to strengthen communication between enterprises, universities and research institutes, jointly develop systems and equipment that meet the needs of the digital and intelligent transformation of the manufacturing industry, and make full use of relevant financial support policies to help equipment enterprises achieve quality improvement in practical iteration.
Sixth, we need to improve the business and development environment. It is found that a prominent problem facing enterprises in digital transformation is the absence of development strategy and the lack of direction in transformation. In recent years, influenced by the international situation, the business environment of enterprises is faced with more uncertainties. The essence of digital transformation is "transformation". The future vision is unclear, the direction of transformation is unclear, and the direction of digitalization is difficult to determine, so the motivation and ability will naturally be insufficient. Under the current circumstances, to promote the transformation of enterprise digitalization and intelligence, we must first solve the problems of enterprise development environment, development direction and development confidence. In other words, in addition to optimizing the external policy environment directly related to digital intelligence, we should also attach great importance to further optimizing the overall environment for enterprise development, including more transparent and stable regulatory policies, further optimization of the business environment, and acceleration of reform in key areas. Only in this way, the digital intelligent transformation of enterprises can have a more solid foundation, but also can achieve better and more sustainable results.
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