Research On Business Process Improvement Of S Group’s Financial Sharing Center Based On Process Mining

In the Internet era,the construction of enterprise informatization is the general trend,and corporate financial management is also at an important juncture of change and transformation.As the starting point of enterprise financial transformation,the construction of Financial Shared Service Center(FSSC)can further promote the integration of industry and finance,realize the effective allocation of enterprise resources,enhance the risk management and control capabilities of enterprises,provide support for enterprise decision-making,and thus improve the economic benefits of enterprises.However,the development of financial shared services in China is relatively slow compared with Western countries,and the application mode is not mature,especially in business process management,there are still common problems such as low process operation efficiency,unreasonable resource allocation,and low degree of standardization.Therefore,it is especially important to re-engineer and optimize the business processes of the financial sharing center.Based on this background,how to apply emerging intelligent technologies to the business process optimization of the financial sharing center is one of the issues that group enterprises focus on at present.In this paper,S Group,a large coal enterprise,is selected as a case enterprise,and the literature research method,case analysis method and process mining algorithm are used to study it.Firstly,this paper collects and researches relevant literature at home and abroad,and has a deeper understanding of the concepts and research status of financial sharing center and business process reengineering.Secondly,the construction of the financial sharing center of S Group is explained,including the construction background and related content.After understanding the basic situation of the financial sharing center of the case company,the Devil Box Evaluation System was introduced to make a preliminary diagnosis of the performance of its business process,and found that there were deficiencies in its business process,such as low efficiency,imperfect risk management and control,and ineffective communication and feedback mechanism.Finally,the process mining technology is introduced to mine the business process data of S Group,and corresponding optimization suggestions are put forward according to the mining results.The main part of this paper selects two types of business processes with the highest frequency of use from the business processes currently online in the S Group Sharing Center,adopts α algorithms from the perspective of workflow,Disco and Pro M programs mine the event logs of related processes,analyze the decision delay points and decision redundancy points in the process,simplify them,and introduce Intelligent Character Recognition(ICR)technology.Speech recognition technology,employee credit rating evaluation and other means to optimize the design of related processes,and evaluate the optimization effect,it is found that the improved business process has significantly improved the operation efficiency and quality,and can strengthen centralized management and reduce enterprise operating costs.The research results of this paper are helpful to solve the problems of inefficient business processes and insufficient risk management and control of the financial sharing center of S Group.This kind of problem is the most typical problem in enterprise process management,and this paper provides new ideas and methods to solve such problems,which has certain reference significance for other companies in the same industry.At the same time,driven by business and technical factors,this paper excavates and optimizes the business process of the enterprise sharing center from the perspective of the system data of the financial sharing center,so as to promote enterprises to effectively use the data resources generated under the financial sharing mode,give full play to the advantages of the financial sharing center to a greater extent,and further enrich the theoretical research content of financial intelligence landing.