R&D digital management is the use of computers, networks, communications, big data, and artificial intelligence and other technologies, the R&D management object (such as: people, things, things, knowledge), management and management activities quantitatively, so that the management of digitalization, interconnectivity, intelligence, in order to achieve the goals of the R & D management management of the management of the management of the activities and methods.
R&D digital management is a management method that combines human management and technology management. Management theories and methods are digitally integrated into standard specifications, processes, and system tools to achieve scientific and standardized management, improve R&D management, and reduce management costs.
The model of R&D digital management is as follows:
-- Pictures from the book "R&D Lean Digital Management"
Why digital management
1) We often hear: R&D inefficiency, low quality, etc. with qualitative words to describe the R&D capabilities of the situation But how can we accurately find the problem; R & D management also often take some measures to improve efficiency or quality, but the results whether to improve, and how much to improve, this high in which low in which how to judge, whether there is a scientific basis; when the product is put on the market did not achieve the expected results, whether it is the R & D capabilities of the problem or the positioning of the product, and how to judge; how can we effectively improve the R & D team The first step in the process is to make sure that you have the right tools for the right job.
Most of the R&D management is based on the manager's experience, however, the current market competition environment has changed a lot compared to the past, and the judgment based on experience alone will often have high risk; with the expansion of the R&D team, the manager does not have the energy to grasp all the information of the team, and without the support of the data, the manager can't pinpoint the problem, and can't achieve the The company's business model is based on the idea that the company's business model is a "digital" one.
Digital management can quantify the work process and results of R&D teams and individuals; it can accurately analyze the efficiency, quality, cost, and revenue, and discover the relationship between R&D behaviors and results, as well as the problems that exist; and then scientifically formulate improvement management plans based on the results of the analysis to improve the effectiveness of R&D.
This is the first time that a R&D team has been able to achieve this goal.
2) The management experience of R&D managers is summarized in the work process through continuous trial and error and learning, which is a very important asset. But most of this experience belongs to individuals, if you do not pay attention to the accumulation of experience in the company level precipitation, once the manager left, these experiences will be lost, there is no data on the enterprise as no yesterday, no history, once made mistakes will still be made, once paid "tuition" to continue to pay, so the experience of the digital management is also very important. The digital management of experience is also very important.
3) R&D management digital, online, intelligent can significantly improve the quality of management efficiency, reduce management costs. For example: R & D digital management can open the front-end business, product, R & D, operation of the chain, can make the product development cycle of information between the relevant parties to maximize the **** enjoy, reduce the time difference in the communication of information transfer, to reduce the distortion of the human information transfer, or some related parties because of the ineffective work caused by the failure to accept the information, so as to improve the overall efficiency of the collaborative efforts and quality; can be a large number of repetitive labor by the Machine automation instead of implementation, improve implementation efficiency, quality and reduce labor costs. The implementation of good digital management in the efficiency of the enterprise can be reduced to fight the non-digital management of the enterprise.
Digital management and experience management are mutually reinforcing.
Management experience gives digital management to provide the basis for the program, digital management can enrich the management experience, the two complement each other.
-- Pictures from the book "R&D Lean Digital Management"
R&D management can first set up a digital management program through the historical management experience, and then carry out management practice, analyze and verify the advantages and disadvantages of the digital management program in the process of practice, and summarize the lessons learned from the practice as a new management. The lessons learned in practice can be digitally recorded as new management experience. The experience of management and digital management to promote each other, the formation of a virtuous cycle of improvement.
Take the game of Go as an example, in the past, people play Go is to rely on their own day-to-day practice experience, while the robot AlphaGo (AlphaGo) is a combination of human experience and big data technology, analysis and precipitation of all possible permutations and combinations of Go, as well as the corresponding processing program have formed the data, so that then rely on the experience of people and robots to compete with the robot is not able to win. Alpha Go is a game of experience and experience. Alpha Go is an example of the combination of experience and digitization.
What to focus on when implementing digital management
What to focus on when implementing digital management, this article selects four points to briefly introduce.
1 To manage digitally, data is the foundation.
How to collect data, what data to collect, what kind of data system to establish, and how to ensure the quality and scope of data are all issues to consider.
1) Data collection needs to be managed in an integrated manner
R&D management data comes from our daily work, every position in R&D, every person is carrying out R&D-related activities, are in possession of the relevant resources, have information about these resources. The quality of R&D data is the basis for the effective implementation of R&D digital management. Different employees will bring different results, so data management can not rely only on personal initiative, the need for systematic management.
2) R&D data should be clearly categorized
The relevant information about people, things, and materials involved in the full cycle of product development should be sorted out and categorized. Clear data classification can promote comprehensive data collection, as well as reasonable storage of data, easy to analyze and summarize the data later.
3) Data collection should be closely integrated with the establishment & implementation of management standards
In order to guarantee the quality of the source data, it is necessary to clarify what source needs what kind of records, and to form normative requirements in the collection of data information fields, the format of the data, the data record carriers, and the form of data storage and transmission. So it is very important to establish management processes, systems, norms and other standards.
4) Data collection should be closely integrated with the establishment of the management system
In terms of improving data quality, it is a perfect practice to integrate the management system and process specifications into the software system. On the one hand, the software system strictly restricts the content and format of the collected data, data storage and transmission methods, thus greatly guaranteeing the quality of the relevant data; on the other hand, the staff can perform strictly according to the process specification without having to memorize and frequently consult the process specification documents, which is conducive to the implementation of the specification. In addition, through the software system to manage the daily work of R & D, can improve the efficiency and quality of work, reduce management costs.
2 digital management should be carried out around the management objectives, not for digital digitalization and digitalization
R & D digital management, the first to determine the objectives of management, through the objectives to guide the direction; around the management objectives to develop a measurement program (including the measurement indicators, dimensions of the set), and the development and implementation of management standards (processes, systems, norms, etc.), around the goal of data collection, Data processing, data analysis, the formation of reports to management decision-making or automated processing.
3 To pay attention to the development of data thinking
To carry out digital management, data thinking is important.
"Data thinking is a mode of thinking about things based on data, a quantitative mode of thinking, a mode of thinking that values facts and pursues truth." -- "Managing Change with Data in the Enterprise"
And its counterpart is empirical thinking. Empirical thinking is a form of thinking that decides problems on the basis of experience, and it is the most basic/general form of thinking. Data management involves the management of the enterprise change, the enterprise to effectively promote the change of digital management, we need to cultivate managers of data thinking, the need to establish a data culture in the enterprise.
4?Digital management is a continuous improvement process
Digital management applied to R&D management is a continuous improvement process. Digital management is a complex system, is in practice, constantly groping, improve, perfect, not a handful. It needs to be built to a certain magnitude to play a real role in R&D management. Therefore, it needs to grow in the care and nurture of R&D management in the early stage. With the improvement of management standards and systems, the data level, indicators, dimensions, etc. grow to a certain level can help R & D management. Digital management of R&D data is seamlessly integrated with the MASI improvement cycle, creating a self-growing cycle of rapid iteration.
For reasons of space, this post introduces these first, about more R&D digital management content, you can read "R&D Lean Digital Management".
For more on R&D digital management, you can read Lean Digital Management for R&D.