Research On Data Management Capability Maturity Assessment And Optimization Path Of XCMG

Currently,the country is vigorously developing the digital economy and accelerating the implementation of the national big data strategy and the construction of new infrastructure such as the industrial Internet of Things and data centers.Data management is highly valued by the state and favorable policies are constantly being added.In order to adapt to digital development,enterprises need to create information management systems in order to improve data utilization and reduce the cost of management and operation,thus promoting sustainable development.The explosive growth of data can easily cause problems such as poor data quality and inconsistent data standards,resulting in a waste of data assets that cannot be used to their proper value.This limits the development of enterprise data management capabilities.In this thesis,we firstly analyze the current situation of data management capability of XCMG and construct a data management capability maturity assessment model.Secondly,the questionnaire was used to obtain the relative importance of the experts’ indicators for data management capability maturity assessment.Using hierarchical analysis to determine the weight of each indicator in the model on XCMG ’s data management capability.Through the questionnaire survey method,I obtained the data about the current status of data management capability implementation in XCMG.On this basis,I use the fuzzy comprehensive evaluation method to derive the rank affiliation of each index,so as to determine that XCMG ’s data management capability maturity level is at the robust level.And I analyzed that XCMG has problems in data strategy assessment and data integration and sharing,and is still in the managed level.Again,I trained the BP neural network with the evaluation results of 50 experts on the status of XCMG ’s data management capability as the sample data and constructed the BP neural network evaluation model.Through the constructed evaluation model,the overall data management capability of XCMG was evaluated,and the error between the evaluation result and the real value could be controlled within 1.5%,which verified the feasibility and Scientific of the model.By adjusting the sub-competency items under the weak indicators,the adjusted indicators are brought into the constructed evaluation model to conclude how the sub-competency items can be adjusted to best improve the level of data management capability.Then bringing the optimized metrics into the model can be concluded that the adjusted metrics can better improve the level of data management capability.The adjusted data management capability maturity level of XCMG can reach the quantitative management level.Finally,the optimization path and guarantee measures are proposed according to the indexes to be improved to achieve the purpose of continuously optimizing the data management capability of XCMG.This thesis carries out data management capability maturity assessment of XCMG and adjusts indicators to predict data management capability with the help of BP neural network prediction model,which can effectively achieve the purpose of improving data management capability by optimizing indicators.The research in this thesis also provides a reference for other manufacturing companies to assess and optimize their data management capability.