The framework to learn how to manage SMEs is as simple as management. The first is to identify the internal control problems and causes of SMEs, and the reasons for the internal management problems of SMEs. Then, we analyzed the management system management and development of the business model industry-standard model. Based on the construction of industrial subsystems, a simple subsystem conversion system is developed, and a simple exchange strategy matrix for equipment measurement and decision-making is constructed. Finally, taking CW as an example, the company’s case modeled and demonstrated the feasibility of the retrofit process, supporting the importance of the study. The experimental results show that asset specificity, organizational structure stability, cultural organization memory, and entrepreneur cognitive inertia are the main factors that promote the formation of strategic rigidity. Once the strategic rigidity is formed, it will have a negative effect on the enterprise, resulting in a lack of adaptability, lack of innovation power, and a decline in business performance, indicating the necessity and urgency of building an enterprise strategic flexibility system.

Professional auditors provide audit services to businesses and they are key participants in enterprise development. Effective identification of audit risks can help auditors plan their audit work rationally and issue correct audit opinions. In the era of big data and the Internet, enterprises generate a large amount of data in their daily operations. For auditors, it is a great challenge to use data mining algorithms, machine learning, artificial intelligence, and other emerging technologies to identify high-quality audit data from the vast amount of data of audited enterprises. At the same time, some companies may falsify and modify their financial statements for their own benefit, which further increases the difficulty for auditors in conducting audits. Traditional auditing methods are costly and consuming and cannot meet standard auditing requirements. Therefore, this study applies computer data mining algorithms to construct an audit risk model that provides a reference for auditors to conduct big data analysis and mines valuable data, thereby improving the efficiency and accuracy of the audit process.