Empowering Patent Lifecycle Science Management with Data

[Author] Zhang Lijie[Abstract] From the date of patent application to the date of termination of rights, patents have undergone complex evolution, with various roles involved, forming rich technical, legal, and market data and information. Through the scientific management mechanism of patent lifecycle, the existing patent case decision-making mode that mainly relies on human labor and manual operation is optimized. Under advanced data technology conditions, intelligent management is achieved by using more various data, information, and data processing technologies to get rid of the inefficiency and blind decision-making of human labor operation, and achieve the benefits of scientific management.

Against the backdrop of the United States’ overall blocking of China in various fields and the continued spread of the COVID-19 abroad, leading to the near standstill of the world economy outside China, the relative competitiveness of the Chinese market, the Chinese economy, and Chinese enterprises has increased. As enterprise competition has become increasingly fierce, according to historical experience, intellectual property rights, especially patents, as an important tool for enterprise market competition, are bound to be useful when enterprises face fierce competition. For example, the case of Cisco v. Huawei in 2003 [1], and the crazy suppression of Huawei and other Chinese enterprises by the United States using national machinery since 2019 are all examples.
Today, Internet plus, big data, cloud computing, artificial intelligence and other industries are increasingly deepening. Information (data) has become an independent factor of production. After nearly half a century of information technology, the extraordinary speed of information technology development has contributed to the explosive growth of information (data) volume and processing capacity, and big data has become a striking phenomenal feature [2]. The patent industry also benefits from the current development status of the economy, technology, and society. According to statistics from the world’s top five intellectual property offices (IP5), IP5 alone accepted 2.8 million invention patent applications in 2020, and granted a total of 1.3 million invention patents in 2020.
With the rapid development of the intellectual property industry both domestically and internationally, various theories or practices for creating, protecting, and managing intellectual property have emerged in the fields of industry, academia, and research. In the research on intellectual property protection from an ecological perspective, Yu Dengke et al. proposed the establishment of an ecological intellectual property protection platform, which should focus on reflecting the distribution, intelligence, and initiative of the intellectual property protection information platform. An intelligent platform can provide customized intellectual property information extraction services for enterprises based on information retrieval history, and automatically update, filter, organize, integrate, and report intellectual property information, providing information support for enterprise intellectual property protection information search and plan formulation; A proactive intellectual property information service platform, on the one hand, enables enterprises to proactively warn of patent infringement by others, and on the other hand, actively provides reference patent information based on the actual situation in the field of enterprise technological innovation, combining intellectual property protection with the process of technological innovation, and integrating the concept of intellectual property protection at the stage of technological innovation. Huang Tao et al. proposed that the birth of high-value patents requires the full cooperation of enterprise patent personnel, technical personnel, enterprise process personnel, and intellectual property service institutions. The process settings, quality control, communication mechanisms, and other aspects of each link need to be standardized and strictly managed. Starting from the internal and external management of the lifecycle of high-value patents in enterprises, the key links of management are sorted out and introduced. Thomas F. Quinn, Jr. [5] proposed a patent lifecycle management system that decomposes and identifies tasks in the intellectual property lifecycle as either management tasks or technical tasks. The system provides users with the option of using management agents for management tasks or technical agents for technical tasks. Cheaper management agents can be used for non-technical work, without using expensive technical agents for all tasks to control agency costs. Zhou Yanpeng et al. [6] discussed that intellectual property infrastructure construction is the nerve center for various industries to operate intellectual property, and it is necessary to use correct concepts, professional methods, and system platforms to reconstruct the intellectual property operation process. They pointed out key systems such as industrialized patent analysis system, patent risk warning system, and technology asset operation system.
Based on the above, the discussions of intellectual property industry, academia, and research outside of Mr. Zhou Yanpeng are mostly one-sided and incomplete discussions on patent lifecycle management, or although they involve lifecycle management, they lack data thinking and rely on experience management, which cannot adapt to the development trend of big data, internationalization, and intelligence of the times. Overall, there has been no proposal of the concept of scientific management of patent lifecycle.

How various market entities can act rationally and beneficially in the patent lifecycle and in the context of massive data, and use scientific methods to manage patents as much as possible, has become a topic worth exploring.
Firstly, let’s define what is patent lifecycle, patent lifecycle management, and scientific management of patent lifecycle.
Everything has its birth and death. Patents themselves, as a legal right, have a statutory time limit regulation, and there are people involved in the process. From the date of application to the date of right extinction, patents undergo complex evolution, with various roles participating, forming rich technical, legal, and market data and information, while reflecting the rational or irrational decisions or judgments of active or passive participants.
The patent lifecycle refers to the period from the date of patent application to the date of termination of patent (application) rights. Patent lifecycle management refers to the collection of relevant actions taken by the rights holder themselves or through agents during the patent lifecycle to achieve their business objectives. Patent lifecycle management can be applied to individual cases, family cases, patent packages, and even all patents owned by the rights holders.
The scientific management of patent lifecycle refers to the optimization of existing patent case decision-making models that mainly rely on human labor and manual operations. Under advanced data technology conditions, intelligent management is achieved by utilizing various data, information, and data processing technologies to eliminate the inefficiency and decision-making blindness of human labor operations, and achieve the benefits of scientific management.
Why propose the concept of scientific management of patent lifecycle? Is scientific management necessary and meaningful? To answer these questions, we need to explore them in the context of reality. Based on the survey data of the China National Intellectual Property Administration’s 2019 China Patent Survey Report [7] (hereinafter referred to as the Survey), we observe and interpret from the following aspects:
（1） From the Relationship between Patents and Competitive Advantage of Enterprises
According to Table 1, the survey shows that among 4116 companies with over 100 patents, 25.3% chose “Yes, in this industry, the number of patents required for a single product is extremely high, and it is basically impossible to survive in this industry without sufficient patents”, which is significantly higher than other companies. 62.2% chose “Yes, in this industry, the number of patents required for a single product is not very high, but patents are extremely important for maintaining market share of the product”. This indicates that among enterprises with over 100 patents, patents and the number of patents owned are valued and relied upon as a competitive tool.

Table 1: The views of enterprises with different patent ownership levels on whether their industries rely on patents to obtain or maintain competitive advantages (unit:%)

Note: The effective data volume for this question is: 1 to 2 pieces, 3 to 9 pieces, 10 to 29 pieces, 30 to 99 pieces, and 100 or more pieces, respectively, with 2193, 2331, 1554, 381, and 4116 pieces, totaling 10575. The errors caused by decimal selection in this table have not been balanced.
（2） From the perspective of patent investment and output
The cost of patents generally includes research and development costs, application expenses, maintenance expenses, and related management expenses [8]. From the perspective of research and development costs, the survey data shows that 51.7% of enterprises have an average research and development cost of over 100000 yuan for invention patents; The proportion of R&D costs exceeding 500000 yuan is 25%. In the expenditure types of enterprise patent management funds, the main expenses are “expenses generated from patent applications (including agency fees)” and “expenses generated from daily maintenance of patents”, accounting for 83.2% and 68.1% respectively, while “personnel expenses generated from patent management” and “equipment expenses generated from patent management” account for 36.4% and 22.6% respectively.
Patents are assets that will continue to incur maintenance costs, and the input-output ratio is a consideration factor for whether intellectual property work can be carried out continuously in enterprises. According to the survey (see Table 2), in 2019, the effective patent implementation rate in China was 55.4%, and the patent implementation rate of enterprises was 63.7%; For enterprises, up to 36.3% of patents have not been implemented, which means they have not generated any direct income. Furthermore, from the perspective of the effective patent implementation rate of patent owners with different levels of patent ownership, taking invention patents as an example, those with 30-99 patents have the highest patent implementation rate of 69.1%, while those with more than 100 patents have the lowest implementation rate of only 23.3%. These patents do not bring any direct benefits, and can only be explained by indirect benefits that cannot be measured, such as technology reserves, image shaping, and suppression or blockade of competitors. Combined with the aforementioned research and development costs, the huge cost expenses invested by enterprises cannot bring direct income, which greatly troubles entrepreneurs and intellectual property management personnel.

Table 2 Effective Patent Implementation Rate of Patent Owners with Different Patent Ownership (Unit:%)

Note: The effective data volume for this question is: 1 to 2 pieces, 3 to 9 pieces, 10 to 29 pieces, 30 to 99 pieces, and 100 or more pieces, with 3026, 2524, 1599, 389, and 5215 pieces respectively, totaling 12753. The errors caused by decimal selection in this table have not been balanced.
The main factors that restrict the effective implementation of patent rights (see Table 3) are that patent owners with more than 100 patents choose “information asymmetry causing difficulties in patent licensing and transfer” and “lack of authoritative and trustworthy patent trading platforms”, with 56.7% and 49.8% respectively. This to some extent reflects the strong willingness of patent owners to implement patents, but the degree of mastery of market information is insufficient. In theory, the more patents there are, the harder it is to find matching market information.

Table 3: The main factors that patent owners consider to be limiting the effective implementation of patent rights based on different levels of patent ownership (unit:%)

Note: The effective data volume for this question is: 1 to 2 pieces, 3 to 9 pieces, 10 to 29 pieces, 30 to 99 pieces, and 100 or more pieces, respectively, with 3039, 2530, 1604, 390, and 5218 pieces, totaling 12781. This question is a multiple-choice question, and the sum of the percentages is greater than 100%. The errors caused by decimal selection in this table have not been balanced.
（3） From the perspective of patent authorization cycle and maintenance period
According to the survey, 62.2% of enterprise patent holders in 2019 believed that the patent examination cycle was too long to keep up with the speed of technological development, an increase of 6.5 percentage points compared to 2018; 69.1% of strategic emerging industry enterprises hold the same view. This indicates that Chinese enterprises continue to have a strong demand for improving patent examination efficiency.
The average duration of valid invention patents in China has slowly increased from 5.8 years in 2015 to 6.3 years in 2018. In 2018, the average maintenance period of valid foreign invention patents in China was 9.7 years, which was 3.4 years higher than the average maintenance period of valid domestic invention patents.
（4） From the perspective of patent management
According to the survey, 34.7% of the 10576 enterprise samples have specialized agencies for managing intellectual property affairs; The proportion of full-time and part-time intellectual property management personnel in enterprises with less than 2 employees exceeds 70%, accounting for 73.5% and 79.4% respectively; In the expenditure types of enterprise patent management funds, the main expenses are “expenses generated from patent applications (including agency fees)” and “expenses generated from daily maintenance of patents”, accounting for 83.2% and 68.1% respectively, while “personnel expenses generated from patent management” and “equipment expenses generated from patent management” account for 36.4% and 22.6% respectively.
According to the Survey, 43.4% of 3514 enterprises in the sample chose the option of “not knowing that they can file with the China National Intellectual Property Administration” when answering the question of “obstacles to the application of the patent licensing filing system”; This result is truly surprising and to some extent reflects the lack of knowledge of patent management among relevant personnel in the enterprise.
From the survey results of the above four aspects, it can be seen that enterprises generally have a positive understanding of the role of intellectual property in market competition and have already deployed a certain number of patents; Despite investing heavily in research and management costs, the implementation rate of patents is not ideal for enterprises. Enterprises have clear expectations and needs to improve implementation rates, but lack relevant information and channels. At the same time, enterprises believe that the patent examination cycle is long and cannot keep up with the speed of technological updates. On the other hand, the average maintenance period of invention patents in domestic enterprises lags significantly behind that of foreign enterprises. At the same time, we have also noticed that enterprises have significantly insufficient investment in patent management personnel and equipment, and to some extent, the professional competence of relevant intellectual property management personnel in enterprises seems to be inadequate.
To solve the problems of insufficient patent implementation rate, long authorization cycle, insufficient management personnel, and low professional competence mentioned above, while controlling the effective input and output of patents, it is worth exploring the use of data and intelligent tools for scientific management of patent lifecycle.

The core of scientific management of patent lifecycle lies in utilizing data technology and tools to assist in management decisions, improve decision-making efficiency, and ensure decision-making effectiveness. We will discuss how to carry out scientific management of the patent lifecycle from several aspects: (1) clarifying management objectives, principles, and methods; (2) necessary organizational and personnel conditions; (3) necessary tools and system conditions; (4) user awareness and willingness.
（1） Management objectives, principles, and methods
The purpose of market entities applying for patents is to bring business value, and it is best to achieve maximum value at the lowest possible cost, which follows the entrepreneurial mindset; The realization of patent value lies in the future, and there is significant uncertainty. In the case of uncertain future returns, controlling input costs is also a natural requirement for enterprises. Therefore, obtaining patent rights and controlling cost inputs have become the first two management objectives of patent lifecycle management. The process of obtaining patent rights is closely related to the needs of enterprise operation. During the existing technology search stage before the application is submitted by the agent or internal staff of the enterprise, as well as the relevant technical literature cited by the intellectual property authority during the examination process, which may affect the free operation of the enterprise, controlling risks and removing obstacles have become the third management goal; In order to realize the market value of patents and improve implementation rates, the prerequisite is to discover or search for potential trading partners, which is the fourth management objective.
When achieving the above management goals, with the increase of the number of patents owned by market entities to a certain extent, as well as the rapid growth of patents in major global market countries and fierce market competition under globalization conditions, relying on human resources or traditional case management systems is no longer effective in managing enterprise intellectual property. Instead, relying on data technology with the help of big data to achieve scientific management should be adopted. Therefore, comprehensive dataization, process automation, and decision intelligence are the principles for building scientific management cases.
On the basis of the above management objectives and principles, it is necessary to establish relevant patent databases, continuously improve the collection and standardization of patent related products and technical data, design relevant workflows, and rely on data technology to generate relevant decisions.
（2） Organizational setup and personnel requirements
If an agency or enterprise’s intellectual property department establishes a scientific management mechanism for the patent lifecycle, it should include software development teams, data teams, and personnel who are proficient in patent practices in major countries or regions, as well as software and data engineers.
（3） Tool or system conditions
We need the following tools or systems to achieve scientific management: (1) a case management system that provides various data on the progress of cases in different countries, such as deadlines, costs, status, related product information, technical information, etc. (2) a global patent database and retrieval system that provides patent big data (3) a scientific management engine that provides intelligent decision-making, including acceleration/delay examination engines, hedging engines, patent maintenance engines, and rights protection engines. The scientific management engine integrates various data and information, and produces various decision recommendations based on rules for decision-makers to refer to. The scientific management engine can be established from the dimensions of patent application confirmation, maintenance, hedging, and rights protection according to management needs. The scientific management engine is at the core, and other systems or tools are connected to its underlying implementation to provide data support.
（4） User awareness and willingness
Enterprise decision-makers should fully recognize the significance of big data and informatization in the scientific management of intellectual property creation, protection, management, and implementation, and have a sustained and firm willingness to invest in enterprise intellectual property management personnel and supporting systems, tools, and equipment. Of course, self-developed scientific management system tools are not practical or necessary for most enterprises or agencies. As a flexible solution, they can also be purchased from the market or jointly developed.

Below, examples will be given to illustrate the mechanism of using various data or information to carry out scientific management of the patent lifecycle in different scenarios, as shown in Figure 1 and Table 4. Based on the dynamic acquisition of data or information such as products/technologies, patents, costs, markets, policies, etc., the scientific management engine intelligently generates various decision suggestion schemes according to the set calculation rules, providing users with decision-making references.

Figure 1: Scientific Management Mechanism for Patent Lifecycle
Table 4 Operating Elements of Scientific Management Mechanism for Patent Lifecycle

（1） Case management during the application process
Scenario 1: Acceleration or Delay Decision
The company has patent applications in China, the United States, and Europe, and plans to launch the corresponding products in China first. Depending on the market performance of the products, it will decide when to launch the related products in the United States or Europe
Based on the matching product launch deadline, the scientific management engine automatically matches the acceleration or delay review conditions of each country according to the product launch deadline and the current review progress and legal status of cases in China, the United States, and Europe, and provides corresponding operation plans including workflow, documents, and expenses. Customers make acceleration or delay decisions based on product planning and other conditions such as budget, greatly improving decision-making efficiency and reducing decision-making costs.
Scenario 2: Risk avoidance decisions during the application process
If there is a corresponding product under development or production in the patent application, it is necessary to continuously monitor whether there is a risk of infringing third-party patent rights. During the process of this patent application or family patent application, the intellectual property authority may review the X-class patent documents referenced in the patent application, which may pose a risk to the product’s market launch. The scientifically managed hedging decision engine can automatically identify the X-class documents and expand them, and issue warnings. Patent agents or intellectual property lawyers can intervene in a timely manner and cooperate with R&D and marketing departments to deal with it. For example, in line with the enterprise’s intellectual property strategy, or by adopting invalid target patents, changing product designs, altering product launch areas, or even collaborating with competitors, patents can be transformed from weapons of competition into a link for cooperation between companies.
（2） Case management after authorization
Scenario 1: Patent Maintenance Decision
The annual fee after authorization is a visible direct cost, while deciding whether to continue maintaining the patent is a larger and more difficult to accurately calculate indirect cost. Using a patent maintenance management engine to reduce evaluation costs and clearly display the direct cost of the patent has become an inevitable choice for scientific decision-making.
The patent maintenance management engine takes the legal status of this case and family cases as the legal dimension, quality value parameters as the market dimension, and combines direct cost and policy support income as the cost dimension to provide decision-makers with reference opinions and greatly reduce indirect decision-making costs.
Scenario 2: Rights Protection Decision
Patents are an important competitive tool in business operations. Collecting competitive information and discovering competitors are prerequisites for patent application.
As for invention or utility model patents, when they are used as reference patents by intellectual property offices in various countries to review others’ patent applications, the rights protection engine can promptly discover, identify, and prompt them for reference in rights protection decisions.
In terms of design patents, the rights protection engine automatically compares the design views of this case with those of others, identifies similar designs, and prompts similar information for reference in rights protection decisions.

With the continuous accumulation of enterprise patents, the traditional manual operation mode of the case lifecycle can no longer meet the further requirements of the industry for creating quality, protection effect, application efficiency, and management level. The scientific management of the case lifecycle using data and data technology to assist decision-making provides feasible solutions for enterprises; The concept and implementation conditions of scientific management of patent lifecycle, as well as examples of application scenarios, provide a useful foundation and starting point for the development and exploration of industry theory.
The scientific management of data enabled patent lifecycle is based on the author’s organization’s experience in layout, application, maintenance, and operation of over 300000 patents from major countries around the world, as well as the author’s 13 years of IPR from Fortune 500 companies Based on practical experience and the summary of the utilization and development of intellectual property process planning and management, big data, systematization, and intelligence in the current organization over the past 8 years, it is proposed that the basic conditions for implementing data enabled patent lifecycle scientific management are complete global patent data, intelligent patent retrieval and analysis tools, and intelligent multi country patent management systems. The data, tools, and systems must be highly intelligent and collaborative. The current intellectual property market format is outside the author’s organization, mainly consisting of agency agencies, data companies, operation companies, and patent management software companies operating in a decentralized manner or with two or more business capabilities, and the business scope is mostly limited to the current situation in China, which does not yet have the conditions, knowledge, Ability and experience, At the same time, empowering the scientific management of patent lifecycle with data belongs to practice and practice, requiring continuous verification and exploration, gradually forming a system and theory.

references
【1】 Sun Li The battle between Cisco and Huawei Beijing: China Yanshi Publishing House, 2003
【2】 Alibaba Research Institute Internet plus: From IT to DT. Beijing: China Machine Press, 2015
【3】 Yu Dengke, Chen Hua, Zhou Rong Research on Intellectual Property Protection from an Ecological Perspective Theory and Exploration, 2013 (5): 14-19
【4】 Huang Tao, Li Hui Enterprise high-value patent lifecycle management Chinese Inventions and Patents, 2019 (1): 56-58
【5】 Thomas F. Quinn, Jr.. Patent Life Cycle Management System. US20190295201A1. USPTO, 2019.
【6】 Zhou Yanpeng and others Smart Wealth Password: Winning and Monetizing Smart Property Taipei City: CommonWealth Magazine, 2015
【7】 Intellectual Property Development Research Center of the China National Intellectual Property Administration 2019 China Patent Investigation Report China National Intellectual Property Administration, 2019
【8】 Donald S. Rimai. Patent Engineering: A Guide to Building a Valuable Patent Portfolio and Controlling the Marketplace. Scrivener Publishing LLC, 2016.