The transformation of traditional industrial enterprises in the era of big data

Sajjad Hussain
Oct 23 · 7 min read
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Enterprise business model innovation based on the Internet and big data has made traditional production, circulation, and consumption links present unprecedented “informatization”, “flattening” and “unbounded”. With the aid of big data analysis and research, the prediction of consumer behavior, demand content, structure, mode and development changes becomes more scientific. We believe that traditional industrial enterprises can take this opportunity to develop into new industries.

The severe challenges and strategic opportunities of traditional industrial enterprises

As mentioned earlier, the networked supply method mainly uses the layered decomposition of modules to achieve economies of scale, while the improvement of the ability to supply heterogeneous demand and agility is mainly achieved through the combination of modules. Therefore, in order to respond quickly and efficiently to the ever-increasing and complex and changeable heterogeneous needs of the big data era, it is imperative for networked organizations to directly meet the heterogeneous needs as much as possible, especially the final heterogeneous product needs of consumer groups Connected. However, due to the relatively long distance from the final demand for heterogeneous products in the market, how to obtain fast-changing data resources efficiently and at low cost, and complete agile production and coordinated supply by establishing an information communication mechanism in a network organization, has become a traditional industry The severe challenges faced by enterprises.

At the same time, the in-depth development of network organizations has resulted in a large amount of data, but big data is not messy, but has the necessity and regularity of organic integration with networked production systems. Mass data collection, processing, and application technologies make data a specialized asset for enterprise production and operation services, that is, the “servitization” of data assets, and then data assets enter the productive service industry. The inherent connectivity of the networked production system requires that data assets be closely coordinated with other divisions of labor, thereby turning to the collaborative evolution of manufacturing and data service industries. Therefore, it is necessary to establish a data-driven innovative manufacturing enterprise to coordinately respond to the modern contradiction between production and consumption, and thereby transform and upgrade the traditional manufacturing system.

The self-accumulation and strengthening of network organizations have led to a rapid rise in heterogeneous demand, which has been accurately characterized in the era of big data, and at the same time constitutes an indispensable and increasingly important part of the networked supply mechanism. On the one hand, in the face of demanding requirements such as large-scale heterogeneous demand and agile response pressure based on business models such as the Internet and big data, traditional industrial enterprises’ own production resource reserves, product development cycles, production and operation costs, and capacity utilization It will be difficult to deal with the level of personalization, etc.; on the other hand, the rapid rise of the networked manufacturing paradigm characterized by digitization, personalization and intelligence has provided traditional industrial enterprises with strategic opportunities for transformation and development in the era of big data. It provides a fundamental impetus for advancing the deep integration of “informatization” and “industrialization” and realizing a new type of industrialization.

The inherent synergy of heterogeneous demand and networked supply has evolved demand big data, cooperative big data, and production big data, thereby providing a strategic opportunity and a new path for traditional industrial enterprises to integrate into intelligent network organizations and transform into digital survival enterprises . Therefore, in the era of big data, traditional industrial enterprises should construct a transformation path through the three-dimensional perspective of “data-driven-open innovation-networked collaboration”, specifically, including the following aspects:

1. Accumulate data assets and build a “data-driven” enterprise

In the era of big data, data has become an asset and evolved into a relatively independent production factor, participating in the process of corporate value creation. The consumer demand-oriented “pull-type” production method has returned to its standard, highlighting the strategic value of data assets. Companies with relatively abundance of data assets and high data value applications will be closer to the frontiers of the complex and volatile market, so they can quickly and accurately respond to the heterogeneous needs of consumer groups. Therefore, building a “data-driven” manufacturing enterprise by directly or indirectly acquiring and accumulating data assets is the only way for traditional industrial enterprises to transform. Specifically, it mainly includes the following aspects:

One is to build a data aggregation and sharing platform.

Powerful companies provide consumers with products and accumulate data resources, provide data value-added services for all links of the industry chain through data storage, mining and applications, and vertically integrate the upstream and downstream of the industry chain, while weaker SMEs can Integrate into the platform to realize the indirect use and sharing of data resources.

The second is to implement a data-driven innovation strategy.

Infiltrate big data collection and application technologies into all aspects of value innovation such as product design and development, manufacturing, quality control, supply chain management, after-sales service, etc., shorten product development cycles, optimize production processes, increase added value, and enhance corporate competitiveness.

The third is to play the “positive feedback effect” of big data.

By obtaining consumer demand data, enterprises provide products for them, and at the same time they generate consumer demand data on a larger scale, which in turn encourages enterprises to create better quality products and form a positive feedback effect of a virtuous circle.

The fourth is to explore the “manufacturing as a service” cloud manufacturing model.

Supported by technologies such as cloud computing, Internet of Things, and intelligence, enterprises store data resources such as software and hardware, enterprises, and knowledge on the cloud manufacturing service platform. Consumers creatively use cloud manufacturing to meet heterogeneous needs and truly achieve consumer-oriented Manufacturing processes and data assets serve the manufacturing industry.

2. Implement an open innovation strategy to reconstruct the competitiveness of industrial enterprises

The networked supply mechanism not only promotes the formation of a global manufacturing network, but also forms a global innovation network. In the era of big data, on the one hand, traditional manufacturing companies must face rising heterogeneous demands and fierce market competition. Can they directly or indirectly obtain data resources at any time, optimize and reengineer production processes and decision-making management, and become a winning company. The core competitiveness of the market; on the other hand, the supply of products of manufacturing companies increasingly requires cross-field cooperation, that is, design and development, mechanical manufacturing, software development, supply chain management and other cross-professional and cross-border teams.

With the rapid rise of information technologies such as the Internet, cloud computing, and big data, the spillover of technology and knowledge has accelerated, the technology life cycle has been shortened, the ability to use professional knowledge to innovate and profitability has decreased, and the risk of enterprise R&D has increased. External innovation and commercial promotion have become equally important. Unlike the closed innovation paradigm that focuses on the “virtuous circle” of internal R&D within the enterprise, open innovation pays more attention to the two-way flow of innovation resources inside and outside the organization.

Therefore, it is necessary to achieve synergistic innovation effects through an open innovation paradigm. While using traditional innovation models, it is necessary to focus on seeking ideas, capital and technologies with lower external costs and higher efficiency, such as the use of cooperative R&D, technology licensing, and business crowds. Packaging, industry-university-research cooperation, supplier and user innovation, etc. Create a global manufacturing network organization with the concepts of openness, sharing and equality, especially seeking global value chain integration under the networked and informationized innovation system, and enhance the added value of manufacturing industry, thereby reconstructing the international competitiveness of industrial enterprises .

3. Incorporate into intelligent networked organizations to achieve collaborative transformation of enterprises

The Internet, cloud computing, big data and other information technology revolutions have promoted the rapid reconstruction of relations between people, people and organizations, and organizations and organizations. Consumers and producers have formed a continuously accumulated and strengthened network organization, which inevitably requires traditional enterprises. In particular, industrial enterprises carry out structural reforms and integrate into intelligent network organizations to achieve collaborative transformation of enterprises. Specifically, the construction and integration of industrial enterprises into intelligent network organizations are mainly reflected in the following levels:

One is the formal level

Adopt the pan-Internet paradigm, that is, traditional industrial enterprises and enterprises with mobile terminals, network platforms, software applications, and data assets build an integrated network organization to form the best paradigm for enterprises to accumulate data assets and play their value.

The second is the content level

Connecting the industrial Internet means using the Internet and big data to transform traditional industrial manufacturing, breaking through the constraints of physical distance, time cost, and information asymmetry, transforming traditional enterprise production organization methods and spatial organization methods, and transforming physical resource advantages into data resource advantages. Manufacturing is highly digitized, networked and intelligent, and is more adapted to the heterogeneous needs of the big data era.

The third is the essential level

Through organizational collaborative innovation to drive members to improve production and innovation efficiency, maintain organizational vitality, coordinate production relations, use internal and external resources, etc., promote the integration of traditional industrial enterprises themselves, and cross-border integration with other industries, while also achieving external complexity Dynamic matching and integrated innovation of the changing environment.

The fourth is the result level

Drive the transformation and upgrading of traditional industrial enterprises with informatization, and promote the in-depth integration of the penetration, crossover, and reorganization of the information industry and the industrial industry through the integration of intelligent network production organizations, and realize the transformation and development of new industrialization while improving new competitiveness.

Data Prophet

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