| With the intensifying development of a current round of scientific and technological revolution and industrial changes,the digital transformation of enterprises has become a general trend.As an important economic pillar industry in China,manufacturing directly affects people’s daily living standards and socio-economic evolution.Therefore,under the protest of complicated and uncertain market environment,manufacturing companies should seize the digital economy and a new generation of information technology opportunities for high-speed development,realize "intelligent manufacturing" in the production model and "value creation" in financial work,promote financial work from low value-added to high value-added,help enterprises improve management level,operating efficiency and economic benefits to create more value for enterprises and society.Budget management plays a crucial role in cost control and profit enhancement for manufacturing enterprises.It not only helps companies break down strategic goals and strengthen management and control during production and operations processes,effectively mitigating business risks,but also enhances communication and collaboration among different departments and facilitates the coordination and integration of internal resources within the company.As the development of China’s manufacturing industry is relatively mature and the current competition is increasingly fierce,the business trend of selling production is becoming increasingly obvious.Therefore,the sales budget has gradually become the starting point for most enterprises to carry out budget management.The operating conditions will also play a decisive role in production and procurement budgets.However,the current budget management work of many enterprises lacks the deep integration of emerging technologies.In addition,the business scale and departmental structure of the company are becoming larger.The high degree of integration of new generation of information technology has become an inevitable development trend.This article takes the sales budget management of Company F in the manufacturing industry as the research object.It utilizes methods such as literature review,survey,case analysis,and machine learning modeling.Additionally,it combines data warehousing techniques and machine learning algorithms to propose a sales budget management framework for Company F in the era of big data.First of all,this article sorted out and elaborated the current status of domestic and foreign research at home and abroad in recent years,and introduced relevant concepts,theoretical and technical foundations.Secondly,through online research on the company,the basic situation,organizational structure,and current status of sales budget management are introduced.The analysis reveals three issues in the company’s sales budget management: the sales revenue budget formulation is unscientific and inaccurate,the means of controlling the execution of sales expense budget is weak,and the sales budget data is incomplete and of low value.Then,through in-depth analysis of the causes of the problems,the approach of designing a sales budget management framework using big data technology and machine learning algorithms is elaborated.Firstly,to address the issues of incomplete and low-value sales budget data,a sales budget management data warehouse is designed to integrate heterogeneous and discrete sales budget-related data and enhance data management.Secondly,to tackle the problem of unscientific and inaccurate formulation of sales revenue budget,the reasons and approach of using the random forest algorithm to construct a sales revenue prediction model are explained.Sales forecasting features are selected from multiple dimensions such as historical sales data,products,customers,and economic factors.The random forest algorithm is used to achieve more accurate sales volume predictions,and the sales revenue budget is derived based on the unit price of the products,providing a reliable basis for other budgets.Thirdly,to address the weak control measures in the execution of sales expense budget,the main reasons and approach of using the logistic regression algorithm to build a sales expense budget execution risk identification model are explained.Sales expense budget execution risk identification features are selected from basic information,reimbursement transactions,and historical records.The logistic regression algorithm is used to identify risks during the execution of sales expense budget,thereby improving the efficiency of budget fund utilization in the enterprise.This article proposes a sales budget management solution for Company F in the era of big data,based on the new generation of information technology.The sales budget management data warehouse not only strengthens the company’s management of sales budget data and improves data quality but also enhances the speed of budget analysis and assessment for relevant personnel.Additionally,the application of machine learning algorithms in sales budget management not only improves the efficiency and accuracy of budget personnel but also establishes a risk control mechanism in the sales budget management process,enhancing the company’s risk warning capabilities.Furthermore,by integrating emerging technologies such as big data and machine learning algorithms with sales budget management,this article presents new approaches and methods to address traditional issues.It aims to provide more reliable foundational support for managerial decision-making and contribute to the theoretical and practical significance of sales budget management and risk control for enterprises and industries. |
