Research On The Optimization Of P Company’s Intelligent Vehicle Project Management Process Based On Demand Uncertainty

With the majestic development and wide application of artificial intelligence and big data technology,in the wave of new four modernizations of automobiles,the"Intelligent Vehicle Innovation Development Strategy"^[1]national policy was introduced to support the development of intelligent vehicles,and intelligence has become one of the keys in the new four modernizations of automobiles.The in-vehicle central control host has also changed from a traditional entertainment car machine to an important carrier for realizing automobile intelligence,and the intelligent demand of automobile users for intelligent applications,network interconnection,and human-vehicle interaction is also getting higher and higher.As a supplier of intelligent car parts,in order to cope with market demand and long-term development of enterprises,Company P should standardize business processes,improve the delivery quality of intelligent car machine projects,how to achieve efficient and high-quality implementation of projects with optimal resource allocation,and how to enhance the satisfaction of car customers and the competitiveness of enterprises themselves.It has become particularly important and urgent to establish a management process based on the overall perspective of enterprise management that is suitable for the characteristics of intelligent vehicle parts companies.This thesis focuses on the intelligent vehicle project management process of Company P’s uncertain needs,focusing on the problems existing in Company P’s project management process.Through the sorting out and analysis of the problems in the project management process of the intelligent car machine of Company P,it was found that in the project management process of the intelligent car machine of Company P,there was insufficient pre-planning of the project and the consideration of the project was not comprehensive,resulting in overspending of the project cost budget;The company’s project management process and the relationship between the department is loose,the responsibilities between the departments are unclear,the functions overlap,and the authority is overlapped,resulting in waste of human resources;The lack of effective information sharing mechanism,the existence of a serious departmental wall between departments,resulting in a decline in employee cohesion,resulting in complex personnel relations,unable to stimulate employee enthusiasm,difficult to create and achieve added value for the enterprise,low project collaboration work efficiency;The overall status of the project is not clear,affecting the progress of project delivery and many other problems.Based on process management,combined with project management theory,the literature research method,case study method,expert interview method,questionnaire survey and statistical analysis method are selected and used.Optimize the problems in the project management process of P company’s intelligent car machine.Identify optimization objectives,principles,and optimization methods for the project management process.By combining theoretical knowledge with practical cases,this thesis focuses on the optimization of the project management process of intelligent car machine of Company P.According to different problems,the project management process of P company’s intelligent car machine is optimized by changing the process mode,optimizing the organizational structure and optimizing the project management process.A sustainable end-to-end project management process has been established,and a safeguard measure has been formulated with a management system and organizational structure,supported by an information system.Through the optimization of the project management process,the operational efficiency and market competitiveness of the P company are improved,and the management level of the intelligent vehicle project is improved.It also provides reference and reference for other industries seeking to optimize the project process.