Study Of Supplier Risk Warning For Petrolchemical Enterprises In Sap Environment

With the global increasing economic competition environment, the relationship of production enterprises and supplier member enterprises is closer and closer. The increased partnership brings both competitive advantages and potential risks. How to select and look for high quality suppliers, avoid risks in time is the key for enterprises to enhance the core competitiveness.Although much work has been done about supplier risks, but most of them are focused on the development of standard evaluation index, and then perform evaluation according to the standard. Thus the different procurement type specificity always is ignored and trend analysis is rarely seen on historical business data. They do too much work on the assessment, not early warning. This study is based on the large amount of historical data of petrochemical enterprises using SAP, integrated using fractal theory, analytic network process, fuzzy rough law and Markov chain theory to do risk analysis and forecast. Because the conclusion is based on the actual data base, it is fairness, justice and convincing, can truly reflect the performance of suppliers, real-time early warning supplier risk. At the same time, it can promote the benign competition between suppliers. The main work and conclusions of the study are as follows:1. Explained the topic theoretical background and practical significance, summed up the present research situation of early warning of supplier risk, determined the combination technology routes and methods of qualitative research and quantitative research to establish supplier risk early warning model and control platform under SAP environment.2. Put forward the method of using fractal theory to construct supplier risk early warning model. First of all, analyzed the complex of related information resources and the parties involved of suppliers in SAP environment, portrayed the work is huge for supplier risk early warning. Then put forward that the comprehensive prevention of petrochemical enterprise supplier risk must improve information efficiency. Because the optimal efficiency of information space have fractal characteristics, therefore supplier risk early warning model with fractal characteristics can effectively optimize the information space dimension, reduce the information cost to construct the whole early warning mechanism. Because of the self-similarity, self-organization and self optimization feature, fractal based risk early warning model can continuous learning in the practice, and further improves the risk index system.3. Preliminarily establish supplier risk assessment index system. First used the Delphi method to get the index factors, and the analytic network process (ANP) method to analyze the dependency relation between factors and their important degree, eventually established the implementation capacity evaluation index system of two grades, and calculated the weight of index.4. Further simplified and optimized the risk indexes. First of all, extracted the SAP historical data, and determined the discretization rules for excellent, good, mediate and bad according to the index of risk factors to construct rough set knowledge set for further operation. Then using rough set theory to divide equivalence classes for decision attribute set, remove unnecessary attributes, and calculate dependence degree and degree of importance for necessary attributes. Combined with the front subjective weight, get the simplified and optimized supplier risk assessment index system.Fuzzy comprehensive evaluation method was applied to evaluate suppliers according to SAP history data. First of all, defined the degree of membership function for fuzzy assessment, then calculated comprehensive evaluation value of business data according to the grade of membership and index weight, in accordance with the maximum degree of membership principle, achieved that comprehensive evaluation conclusion. Staging evaluation results can help to find unstable suppliers or suppliers with problem.Markov chain theory was used in forecasting future risk trend for suppliers. First of all, calculated one-step transfer probability matrix according to the traditional results of comprehensive assessment for suppliers, and took the last period of assessment results as the initial forecast benchmark to do future trend forecast, and found out key monitoring suppliers.5. Constructed early warning logic model for suppliers risks, and established supplier risk early warning system under SAP environment. Through the access of related business data about supplier risks from SAP system dynamically, in accordance with supplier risk assessment indicators and risk prevention and control knowledge model, analyzed supplier risk online, to control and warn supplier risk event, and effectively prevent the occurrence of supplier risks.The innovative work of the research is as follows:1. Put forward the thought of establishing the whole supplier risk early warning system based on fractal theory, effectively reduced the cost of information, and improved the efficiency of information. Continuous self optimizing and self learning of the early warning system can adapt to the changing market environment.2. With the help of rough set theory, fuzzy theory and the theory of Markov chains, according to supplier risk factors, using the large number of business data of SAP system to comprehensively evaluate and forecast supplier risks. It is proved to be a basis in fact to effectively analyze the supplier risk events.3. Established petrochemical industry supplier risk early warning model and application system under SAP environment, realized on-line monitoring and real-time warning for supplier risk events, effectively prevent the happening of supplier risk events.