| A reasonable and efficient supply chain should not only ensure its high-quality service,but also minimize reasonable costs.Cost control of the whole supply chain is an effective way to achieve cost optimization.Methods such as activity-based costing,target-based costing and standard costing have been widely used in the cost control of the company's supply chain.With the expansion of the scale of the company,the internal cost information keeps increasing,and the current regression analysis method cannot meet the requirements of the company.In addition,the company cannot timely and accurately collect the cost information of upstream and downstream companies,resulting in low efficiency of supply chain cost control.However,technologies such as data collection,data import,data analysis and data mining of big data can integrate messy data and transform it into valuable information,provide companies with appropriate data analysis methods and obtain real-time cost information of upstream and downstream companies.Therefore,how to use big data technology to optimize the company's supply chain cost control is extremely important.This thesis mainly analyzes how to use big data to optimize the cost control of S company's supply chain from the upstream and downstream links of the supply chain by using methods such as literature research and interview survey,it provides a basis for enterprises to better realize cost optimization.This thesis consists of the following six parts:The first part is the introduction,which firstly introduces the background and significance of the research,then the related research review at home and abroad,and finally the research content and methods.The second part is the theory related to big data and supply chain cost control,defines the connotation of big data and supply chain cost control,and introduces the theoretical basis of supply chain cost control.The third part is the introduction of S company and the analysis of its supply chain cost control status.It mainly introduces the introduction of S company and the current situation of supply chain cost control of S company.The fourth part analyzes the necessity and feasibility of using big data to optimize the cost control of S company's supply chain.The fifth part is about the specific measures and matters needing attention to optimize S company's supply chain cost control by using big data.Enterprises can use big data technology to strengthen the research cost control,fine internal cost control,strengthen the control of sales cost.In the process of making use of big data,it is necessary to strengthen cost big data management,improve the informatization level of employees and ensure the security of relevant big data.The sixth part is the conclusion and prospect of this paper.This thesis mainly has the following conclusions.First,the company's use of big data technology is based on the widespread application of big data technology.Second,the successful application of big data technology needs to standardize the management of data.Third,companies can improve their core competitiveness by optimizing supply chain cost control with big data.This part also introduces the innovation of this paper and the research prospect.This thesis mainly adopts the method of literature research,interview survey and case analysis,and applies the method of comparative analysis and the combination of qualitative analysis and quantitative analysis to process data.The innovation of this thesis lies in the detailed analysis of the use of big data to optimize the supply chain cost control measures from the perspective of case analysis and summarized the application of big data to optimize the cost control in the enterprise matters needing attention.By using technologies such as big data mining and analysis,a large number and diverse data in the supply chain are combined to optimize the enterprise supply chain cost control,form a long-term competitive advantage and provide reference for other intelligent manufacturing enterprises. |
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