Digital internal control review management method and platform

Abstract

The invention relates to the related technical field of review management, in particular to a digital internal control review management method and platform, and the method comprises the steps: obtaining the purchasing and selling department business data of a target enterprise unit, and introducing supply flow information to establish a business flow chain; an open source calculation engine is utilized to construct a review risk framework, flow node risk feedback mapping is performed to establish a review risk model, internal control review is performed, potential risks are marked, similar events are extracted to mine causes, and a risk configuration cluster is generated. The technical problems that potential risks in the business circulation process cannot be monitored in real time, risk events are difficult to respond quickly and the operation stability of enterprises is hindered in the prior art are solved, the business circulation chain is tracked continuously, the potential risks in the business circulation process are predicted and identified accurately, the transparency and controllability of internal control review management are ensured, and the enterprise operation stability is improved. And the stability and the safety of an enterprise in the operation process are guaranteed to the maximum extent.

Description

Technical Field

[0001] The present invention relates to the technical field related to review management, and in particular to a digital internal control review management method and platform. Background Art

[0002] With the continuous advancement of informatization, the operation of modern enterprises is no longer limited to a single production process, but involves multiple links, including procurement, production, inventory, sales and other business areas. Therefore, maintaining efficient operation and risk control of the enterprise in a dynamically changing market environment has become a key issue in enterprise management.

[0003] At present, the internal control review management of many companies still relies on a rule-driven approach and is often limited to static, periodic assessments. Although this approach can provide certain prevention and control of known risks, it is difficult to detect potential risk points in a timely manner when faced with complex and changing market environments and internal business processes, and it lacks a flexible response mechanism.

[0004] In summary, the existing technologies have the technical problem that internal control reviews usually rely on periodic static rules, cannot monitor potential risks in the business flow process in real time, have difficulty in responding to risk events quickly, and hinder the stability of corporate operations. Summary of the invention

[0005] This application provides a digital internal control review management platform to solve the technical problems in the existing technology that internal control reviews usually rely on periodic static rules, cannot monitor potential risks in the business flow process in real time, find it difficult to respond to risk events quickly, and hinder the stability of corporate operations.

[0006] In view of the above problems, the technical solution to implement this application is:

[0007] On the one hand, the present application provides a digital internal control review management method, wherein the method includes: obtaining internal multi-source data under the department business tag of the target enterprise unit, the department business tag including a procurement tag and a sales tag; introducing supply flow information, using the department business tag as an associated index, and establishing a business flow chain, the business flow chain including multiple flow nodes; based on the internal multi-source data, using an open source interactive computing engine, constructing a review risk architecture; based on the business flow chain, continuous tracking is performed, and at the same time, the risk feedback information of multiple flow nodes of the business flow chain is mapped to the review risk architecture to obtain a review risk model; internal control review is performed using the review risk model to mark potential risk nodes; connecting to the internal control review database, extracting similar risk events using the potential risk nodes as constraints, mining risk causes and generating risk configuration clusters; and seamlessly collaboratively managing the target enterprise unit based on the potential risk nodes and the risk configuration clusters.

[0008] On the other hand, the present application provides a digital internal control review management platform, wherein the platform includes: a data acquisition module, which is used to acquire internal multi-source data under the department business tag of the target enterprise unit, and the department business tag includes a procurement tag and a sales tag; a circulation chain establishment module, which is used to introduce supply circulation information, and establish a business circulation chain with the department business tag as an associated index, and the business circulation chain includes multiple circulation nodes; an interactive computing module, which is used to build a review risk architecture based on the internal multi-source data using an open source interactive computing engine; a continuous tracking module, which is used to perform continuous tracking based on the business circulation chain, and at the same time, map the risk feedback information of multiple circulation nodes of the business circulation chain to the review risk architecture to obtain a review risk model; an internal control review module, which is used to perform internal control review with the review risk model and mark potential risk nodes; an event extraction module, which is used to connect to the internal control review database, extract similar risk events with the potential risk nodes as constraints, explore risk causes and generate risk configuration clusters; a security management module, which is used to perform seamless collaborative security management of the target enterprise unit based on the potential risk nodes and the risk configuration clusters.

[0009] In summary, one or more technical solutions provided in this application solve the technical problems that internal control reviews usually rely on periodic static rules, cannot monitor potential risks in the business flow process in real time, are difficult to respond to risk events quickly, and hinder the technical problems in the operation stability of the enterprise. It realizes the continuous tracking of the business flow chain, accurately predicts and identifies potential risks in the business flow process, ensures the transparency and controllability of internal control review management, and maximizes the technical effect of ensuring the stability and security of the enterprise in the operation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flowchart of a digital internal control review management method is provided for this application;

[0011] Figure 2 A structural diagram of a digital internal control review management platform is provided for this application.

[0012] Explanation of the accompanying drawings: data acquisition module M100, circulation chain establishment module M200, interactive computing module M300, continuous tracking module M400, internal control review module M500, event extraction module M600, security management module M700. DETAILED DESCRIPTION

[0013] Embodiment 1

[0014] The present application is described in detail below with reference to the accompanying drawings. Figure 1 As shown, the present application provides a digital internal control review management method, wherein the method includes:

[0015] S1: Acquire the internal multi-source data under the department business tag of the target enterprise unit, wherein the department business tag includes a procurement tag and a sales tag; S2: Introduce supply flow information, use the department business tag as an associated index, and establish a business flow chain, wherein the business flow chain includes multiple flow nodes; S3: Based on the internal multi-source data, use an open source interactive computing engine to build a review risk architecture.

[0016] Specifically, in enterprise management, departmental business tags refer to the unique identifier used by each department or business area. The procurement tag and sales tag are tags used to distinguish the procurement department from the sales department and identify the data of different departments. For example, the procurement tag "Procurement-001" represents the activities of a procurement department, while the sales tag "Sales-001" represents the activities of a sales department. Internal multi-source data refers to the data generated by different departments and systems within the enterprise, covering multiple information sources such as procurement, sales, inventory, and production, including transaction data, inventory data, financial data, etc. All these data can reflect all aspects of business operations and provide a basis for analysis and decision-making.

[0017] Supply flow information refers to the dynamic information of each link in the supply chain, including various data in the process of supplier selection, cargo transportation, inventory update, etc. This information helps enterprises understand the complete flow path of goods from procurement to production and then to sales, and is an important part of enterprise supply chain management; the business flow chain refers to the data and activity transmission process from one business node to another within the enterprise. The business flow chain includes multiple flow nodes (such as procurement, production, inventory, sales, etc.). Each node represents a link in the business flow, and the entire chain reflects the process of the enterprise's business from the initial stage to the final delivery.

[0018] An open source interactive computing engine is an open source computing unit that can be used to process and analyze large amounts of data. It is flexible and scalable, and can quickly handle complex computing tasks by interacting with users. Common tools include Apache Spark and Jupyter. The risk review architecture refers to a framework built based on the company's multi-source data and business flow information. It is used to identify, assess, and manage potential risks in corporate operations. It helps assess possible risk points in different business links through data analysis and modeling.

[0019] Execution steps: Obtain the internal multi-source data under the department business tag of the target enterprise unit. The data of different departments such as procurement and sales are collected independently, marked and distinguished by procurement tags and sales tags. For example, the procurement department collects supplier information, purchase orders and other data through its procurement tags, and the sales department collects sales orders, customer feedback and other data through sales tags. These tags are used to associate the data with the corresponding departments and business processes to ensure accurate classification of the data.

[0020] Supply flow information is introduced. The purpose of supply flow information is to track the flow of materials in the supply chain, such as supplier selection, procurement progress, inventory changes, etc. This information will be combined with procurement markers and sales markers to form a complete business flow chain. Each flow node in the business flow chain represents a link in the supply chain, such as procurement nodes, production nodes, warehousing nodes, and sales nodes. By combining these nodes with internal data, a comprehensive business flow chain is formed. The business flow chain reflects the flow of data and activities in the entire process from procurement to sales, providing a basis for subsequent risk assessment and optimization.

[0021] Based on internal multi-source data, an open source interactive computing engine is used for data processing and analysis. The open source engine can flexibly process computing tasks in a big data environment, such as using Apache Spark to process distributed data, or using Jupyter for real-time data analysis and interactive computing. Through these tools, it is possible to generate a review risk framework based on internal and external data, perform data modeling, identify and evaluate risks that may arise in different links, for example, there may be a risk of suppliers not delivering on time in the procurement link, there may be a risk of delays due to equipment failures in the production link, and there may be a risk of insufficient inventory due to changes in demand in the sales link. Through the above steps, by combining department markers, supply flow information, the use of open source computing engines, and the dynamic construction of the business flow chain, real-time monitoring and risk assessment of all aspects of the enterprise business are achieved.

[0022] S4: Conduct continuous tracking based on the business circulation chain, and at the same time, map the risk feedback information of multiple circulation nodes of the business circulation chain to the review risk architecture to obtain a review risk model; S5: Conduct internal control review based on the review risk model and mark potential risk nodes; S6: Connect to the internal control review database, extract similar risk events based on the potential risk nodes as constraints, explore risk causes and generate risk configuration clusters; S7: Based on the potential risk nodes and the risk configuration clusters, conduct seamless collaborative security management of the target enterprise units.

[0023] Specifically, continuous tracking of the business circulation chain refers to real-time monitoring and recording of the entire process of each business link of the enterprise (such as procurement, production, inventory, sales, etc.) to ensure that the operation and data flow of each link are not missed, which helps to discover potential problems in a timely manner and ensure the continuity and stability of the enterprise's operations; risk feedback information refers to the feedback of possible risks based on real-time data and business operations at each circulation node. For example, at the sales node, if the system finds that the order volume has dropped sharply, it means that there is a problem with market demand. This is a risk feedback information.

[0024] The review risk model refers to a model constructed by comprehensively considering each link in the business circulation chain, combining real-time data and risk feedback information, and is used to evaluate and identify potential risks. It is caused by factors such as supply chain disruptions, demand fluctuations, and production delays. The review risk model helps managers understand and respond to risks through quantitative and qualitative analysis; the internal control review database is a database that stores information such as corporate internal control audits, risk assessments, and compliance checks. It helps track and manage potential internal control issues and provides companies with a basis for historical data and risk management analysis.

[0025] Potential risk nodes refer to risk points in the business circulation chain that may be caused by certain operations or conditions. For example, a supplier's delayed delivery time may affect the production schedule, which is a potential risk node; risk configuration clusters refer to risk category clusters constructed based on data aggregation and analysis of potential risk nodes and similar risk events. Risk configuration clusters help companies understand the correlation and impact of various risk factors, thereby optimizing response measures; seamless collaborative security management is a way to strengthen the coordination and response between various business links through technical means, ensuring that various departments can collaborate quickly when responding to risks, and ensuring the safety and smoothness of corporate operations.

[0026] Implementation steps: Continuous tracking is carried out based on the business circulation chain. This process means that the system constantly monitors and records every link of the enterprise, from procurement, production to sales, to ensure that every node of the business is tracked in real time; by collecting and analyzing data, changes or potential problems at a certain node can be identified instantly. For example, if a supplier of the procurement department has a delivery delay, the event will be recorded immediately and fed back to the business circulation chain, marked as a risk point.

[0027] Mapping these feedback information to the review risk architecture, we can get the review risk model. The review risk model is constructed based on the risk feedback information of each flow node. By integrating the real-time data of different nodes, it can help enterprises comprehensively assess the potential risks in their operations. For example, if a shortage of raw materials is found during the production process, this information is automatically combined with other relevant data (such as inventory levels, supplier delivery times, etc.) to establish a review risk model. The review risk model can assess the possibility of risk occurrence and its impact on the overall operation based on the feedback from different nodes.

[0028] After obtaining the review risk model, the company will conduct an internal control review and mark potential risk nodes. This process identifies nodes that may cause serious problems through a detailed analysis of the review risk model. For example, delays in the production process may affect the efficiency of the entire supply chain, so they will be marked as potential risk nodes. Potential risk nodes may be caused by factors such as insufficient supplier capabilities and delays in production plans.

[0029] Connect to the internal control review database, use potential risk nodes as constraints, extract similar risk events, explore risk causes and generate risk configuration clusters. The internal control review database stores past internal control review data and risk events, which are associated with potential risk nodes. When a new potential risk node is discovered, similar historical risk events will be extracted from the internal control review database to help analyze the root cause of the risk event. For example, production scheduling delays may be caused by raw material shortages, and there may be similar cases in the historical database. This way, the cause of the risk can be quickly identified.

[0030] Based on potential risk nodes and risk configuration clusters, seamless collaborative security management is carried out for target enterprise units. Seamless collaborative security management emphasizes rapid response and coordination between different departments and business links to ensure that once potential risks are discovered, relevant departments can take immediate measures to avoid the spread of risks. For example, if the procurement department is unable to carry out production on time due to delayed delivery by suppliers, the production department will be automatically notified and the production plan will be adjusted. At the same time, relevant suppliers will be notified to intervene and resolve the problem to ensure the normal operation of the production line. Through the above steps, risks can be identified and responded to in real time, internal control processes can be optimized, and efficient risk management and seamless collaboration can be achieved, so that enterprises can take quick and effective measures when facing potential supply chain, production and sales risks, thereby ensuring business continuity and security.

[0031] Furthermore, based on the internal multi-source data, an open source interactive computing engine is used to construct a review risk framework. The present application method also includes:

[0032] Acquire supplier evaluation data, inventory data, and production progress data as supplementary data for internal multi-source data; based on the supplementary data, set supplier selection nodes, inventory management nodes, and production scheduling nodes in the business circulation chain; and set inventory optimization strategies based on the supplier selection nodes, inventory management nodes, and production scheduling nodes.

[0033] Specifically, internal multi-source data refers to multi-dimensional data from different systems and departments within the enterprise, including sales data, inventory data, supply chain data, financial data, etc. These data sources complement each other and together provide a comprehensive perspective for the enterprise; an open source interactive computing engine is a computing tool that allows users to query, process and analyze data in an interactive way. Common open source computing engines include Apache Spark, Jupyter, etc., which can process large-scale data and support various data analysis and modeling.

[0034] Supplier evaluation data refers to the evaluation information obtained by enterprises through analyzing data on supplier performance, delivery cycle, quality control, etc. Through this evaluation, enterprises can choose better and more reliable suppliers, thereby reducing risks in the supply chain; inventory data is used to reflect the relevant information on the storage status of various types of inventory (raw materials, semi-finished products, finished products, etc.) of the enterprise, such as inventory volume, inventory turnover rate, etc.; production progress data refers to the progress of each production link in the production process of the enterprise, the execution of production plans and other data, which helps to reflect the real-time status of the production process and help enterprises monitor the execution of production plans.

[0035] The supplier selection node refers to the decision-making node used to select suitable suppliers in the business circulation chain. The supplier selection node selects reliable suppliers based on the supplier's evaluation data to ensure the timely supply of raw materials; the inventory management node is a link in the business circulation chain, responsible for optimizing and managing inventory to ensure that inventory levels and inventory turnover rates are within a reasonable range; the production scheduling node refers to the node that schedules and manages production resources to ensure the smooth progress of the production process and adjust the production plan according to inventory and production needs; the inventory optimization strategy is based on supply chain data, inventory data, production plans, etc., and sets a series of optimization measures to ensure efficient inventory management, minimized inventory backlogs, and maximized inventory turnover rates.

[0036] Execution steps: Based on the internal multi-source data, an open source interactive computing engine is introduced. This engine is used to process data from multiple sources and conduct comprehensive analysis. By using this tool, the enterprise can integrate the data from various departments and systems in real time for dynamic calculation, thereby building a review risk architecture in the system, which mainly provides a comprehensive perspective to analyze the correlation and potential risks of different data sources.

[0037] Furthermore, supplier evaluation data, inventory data and production progress data are obtained as supplementary data to the internal multi-source data. Specifically, supplier evaluation data includes evaluations of supplier quality, delivery cycle, service and other dimensions to help companies choose more reliable suppliers; inventory data reflects the company's inventory status, such as the quantity of various commodities or raw materials, inventory turnover rate, etc.; production progress data shows the progress of each production link, the execution of the production plan, etc. The supplementary data can further enrich the review risk framework and improve the accuracy of decision-making.

[0038] Based on the supplementary data, several key nodes are set up in the business circulation chain, including the supplier selection node, inventory management node and production scheduling node. At the supplier selection node, the enterprise selects the best supplier based on the supplier evaluation data to ensure that the raw materials for production are on time and meet the quality requirements; at the inventory management node, inventory is managed by analyzing inventory data to ensure that the inventory level is not too high or too low, thereby reducing inventory risks and improving the flexibility of the supply chain; the production scheduling node optimizes the production process based on production progress data to ensure that the execution of the production plan matches the inventory demand.

[0039] Enterprises formulate inventory optimization strategies based on the collected data and set node information. The inventory optimization strategy is based on inventory management nodes. Through the analysis of inventory data, reasonable inventory levels and inventory turnover rates are set to avoid excessive capital occupation or inventory backlogs. For example, if the inventory turnover rate is too low, it means that the inventory management efficiency is not high, and production scheduling or supplier management strategies may need to be adjusted; and if the inventory level is too high, it may lead to expiration or backlog risks. At this time, the inventory optimization strategy needs to be adjusted, such as increasing the order frequency or optimizing the links in the supply chain. Through the above strategies, enterprises can effectively manage their inventory, improve production efficiency, and reduce inventory costs. At the same time, they can provide more efficient support for the operation of the entire supply chain, ensuring that timely adjustments can be made in the face of market demand fluctuations or production problems to avoid potential operational risks.

[0040] Furthermore, based on the supplier selection node, inventory management node, and production scheduling node, an inventory optimization strategy is set, and the method of the present application further includes:

[0041] At the inventory management node, the inventory turnover rate is calculated; at the production scheduling node, the inventory holding rate is configured, and the inventory holding rate complies with the scheduling optimization rule; based on the inventory turnover rate and the inventory holding rate, the inventory optimization strategy is flexibly expanded.

[0042] Specifically, inventory turnover rate refers to the flow rate of inventory goods in a certain period, that is, the frequency with which inventory goods are sold or used. It is calculated as "inventory turnover rate = sales cost / average inventory", which reflects the efficiency of the company's inventory management; inventory holding rate refers to the proportion of inventory goods in the inventory in a certain period. A high inventory holding rate means that the company has a large inventory, which may lead to capital occupation and expiration risks. A low inventory holding rate may lead to supply shortage risks. The inventory holding rate is usually configured according to production plans and market demand.

[0043] Scheduling optimization rules refer to the scheduling and optimization of the production process based on production demand and inventory status. Scheduling optimization rules aim to improve production efficiency, ensure the smooth execution of production plans, and control inventory levels to avoid excessive or low inventory. Elastic expansion refers to flexible adjustments in inventory optimization strategies based on actual demand and market conditions to ensure that inventory management can adapt and adjust in different environments. Elastic expansion can make appropriate adjustments to inventory strategies based on changes in inventory turnover and inventory holding rates.

[0044] Execution steps: The inventory turnover rate is calculated at the inventory management node. The inventory turnover rate is used to measure the speed at which an enterprise sells or consumes inventory goods within a certain period of time. This indicator can help enterprises determine inventory liquidity and reflect the efficiency of inventory management. For example, if the inventory turnover rate is low, it means that the inventory liquidity is poor. The enterprise may need to consider reducing the inventory or adjusting the supply chain strategy to avoid inventory backlogs; a high inventory turnover rate indicates that the inventory goods are consumed quickly, and the enterprise may need to increase the production frequency or replenish inventory in a timely manner.

[0045] At the production scheduling node, configure the inventory holding rate and ensure that it complies with the scheduling optimization rules. The inventory holding rate refers to the proportion of inventory goods in the total inventory, which affects the risk of capital occupation and inventory backlog. The production scheduling node will adjust the production plan and inventory demand through scheduling optimization rules. For example, if an enterprise needs to increase inventory before the peak season to cope with the peak demand, it will configure the inventory holding rate based on demand forecasts to ensure that there is enough raw material and finished product inventory for the production line. In addition, the scheduling optimization rules will also consider factors such as the load of the production line and the order delivery period to reasonably arrange the production progress and reduce production delays or overproduction.

[0046] Based on inventory turnover rate and inventory holding rate, enterprises will flexibly expand inventory optimization strategies. Flexible expansion means that enterprises can flexibly adjust inventory strategies according to inventory flow conditions to cope with market changes and uncertainties in production schedules. For example, when inventory turnover rate is low, enterprises can take flexible expansion measures to reduce production scale and increase inventory turnover rate. When inventory holding rate is too high, enterprises may need to optimize procurement plans, reduce inventory levels, and reduce expiration and backlog risks. Through flexible expansion, enterprises can quickly adjust inventory management strategies in different environments to ensure stable operation of production and supply chain.

[0047] Through the above steps, companies can effectively manage inventory, improve inventory turnover, control inventory holding rates, and adapt to market changes through flexible inventory strategies, optimize production scheduling, improve overall operational efficiency, and reduce risks. At the same time, companies can reduce inventory costs, avoid capital occupation, ensure the smooth operation of production lines, and improve the efficiency of the overall supply chain.

[0048] Furthermore, based on the inventory turnover rate and the inventory holding rate, the inventory optimization strategy is flexibly expanded. The method of the present application includes:

[0049] A quadrant matrix is ​​set up through the inventory turnover rate and the inventory holding rate, and the quadrant matrix includes a first quadrant matrix, a second quadrant matrix, a third quadrant matrix, and a fourth quadrant matrix. The first quadrant matrix is ​​used to characterize areas with high inventory turnover rate and low inventory holding rate; in the second quadrant matrix and the third quadrant matrix of the quadrant matrix, a first elastic expansion strategy is set with shortage risk and expiration risk as focus points; in the third quadrant matrix and the fourth quadrant matrix of the quadrant matrix, a second elastic expansion strategy is set with backlog risk and occupancy risk as focus points; the first elastic expansion strategy and the second elastic expansion strategy are used to elastically expand the inventory optimization strategy.

[0050] Furthermore, the present application method comprises:

[0051] The second quadrant matrix is ​​used to characterize areas with high inventory turnover rates and high inventory holding rates; the third quadrant matrix is ​​used to characterize areas with low inventory turnover rates and high inventory holding rates; and the fourth quadrant matrix is ​​used to characterize areas with low inventory turnover rates and low inventory holding rates.

[0052] Specifically, inventory turnover rate refers to the number of times inventory goods are sold or consumed per unit time, reflecting the liquidity and sales speed of inventory goods. A high inventory turnover rate indicates that inventory goods are sold or used quickly, while a low inventory turnover rate may indicate inventory backlog and poor liquidity. Inventory holding rate refers to the proportion of inventory goods to total inventory. A high inventory holding rate indicates that the inventory level is high, which may bring risks of capital occupation or expiration. A low inventory holding rate may mean untimely supply or shortage. The inventory holding rate usually needs to be set based on demand forecasts and production plans.

[0053] The quadrant matrix is ​​a tool used to visualize the two variables of inventory turnover rate and inventory holding rate, dividing them into four areas to help analyze the effectiveness of different inventory strategies. The quadrant matrix can clearly display the management strategies corresponding to different inventory situations; shortage risk refers to the risk that inventory is insufficient to meet production or sales needs. If the inventory turnover rate is too high, it may lead to a lack of sufficient raw materials or goods in the production process and fail to meet demand in a timely manner.

[0054] Expiration risk refers to the loss caused by inventory goods being expired, deteriorated or no longer suitable after being in inventory for too long. Excessively high inventory holding rates may cause goods to be stranded for a long time, increasing the risk of expiration. Backlog risk refers to the risk of inventory backlogs caused by too many inventory goods, affecting capital flow and production efficiency. If the inventory holding rate is too high and the turnover rate is low, a large amount of funds may be locked in inventory, increasing the risk of backlogs.

[0055] Occupancy risk refers to the risk that inventory occupies a large amount of capital and storage space. When there is too much inventory and a large amount of capital is occupied, the company may face pressure on capital liquidity and affect its financial situation. Flexible expansion strategy refers to the flexible adjustment of inventory strategy according to changes in inventory turnover rate and inventory holding rate. Through flexible expansion, companies can increase or decrease inventory according to actual conditions and reduce risks such as shortages, expiration, backlogs or occupancy.

[0056] Implementation steps: By analyzing the inventory turnover rate and inventory holding rate, a quadrant matrix is ​​established, including the first quadrant matrix, the second quadrant matrix, the third quadrant matrix, and the fourth quadrant matrix. By combining the two variables of inventory turnover rate and inventory holding rate, the company can comprehensively evaluate the risks and optimization strategies under different inventory combinations. For example, the first quadrant represents a high inventory turnover rate and a low inventory holding rate, which indicates that the goods are circulated quickly and the inventory level is low, and there may be a risk of supply shortage; the second quadrant represents a high inventory turnover rate and a high inventory holding rate, indicating that the company has sufficient inventory but may face the risk of capital occupation; the third quadrant is characterized by a low inventory turnover rate and a high inventory holding rate, indicating that the inventory is piled up, funds are occupied, and inventory management needs to be optimized; the fourth quadrant represents a low inventory turnover rate and a low inventory holding rate, and there may be a risk of shortage at this time.

[0057] The second quadrant refers to the area where the horizontal axis represents the inventory turnover rate and the vertical axis represents the inventory holding rate. In the second quadrant, the inventory turnover rate is high and the inventory holding rate is also high, which usually indicates that the inventory goods flow quickly and the inventory is relatively sufficient. Although the inventory is sufficient, excessive inventory holding rate may lead to capital occupation or expiration risks; the third quadrant represents the situation where the inventory turnover rate is low and the inventory holding rate is high, which indicates that there are problems with the company's inventory management. Although the inventory is large, the liquidity is poor, which may lead to inventory backlog and expiration risks, increase capital occupation, and affect the company's capital turnover and financial health; the fourth quadrant matrix represents the area where both the inventory turnover rate and the inventory holding rate are low, which usually means that the company's inventory is neither effectively consumed nor replenished in time, which may lead to shortages or expiration. Such situations are usually manifested as lack of inventory liquidity, and the company may face supply chain disruptions and inventory backlogs.

[0058] By analyzing the two variables of inventory turnover rate and inventory holding rate, the quadrant matrix is ​​used to classify the inventory status and map all inventory conditions into a matrix. The four quadrants of the matrix help enterprises analyze the potential risks brought by different inventory conditions and formulate corresponding inventory optimization strategies according to the characteristics of each quadrant. To further specify, the second quadrant matrix is ​​used to describe areas with high inventory turnover rate and high inventory holding rate. At this time, although the goods can be sold or consumed quickly, an excessively high inventory holding rate may bring risks. For example, if the inventory volume is too large, the enterprise will face the problem of occupying a large amount of funds, and the liquidity of funds will be affected, and it may even cause the goods to expire or be unsalable.

[0059] The third quadrant matrix represents areas with low inventory turnover and high inventory holding rates. In this case, inventory liquidity is poor, but the inventory volume is very large, which may cause backlog risks and expiration risks; companies may find that inventory backlogs lead to increased storage costs and higher capital occupation, and some goods may expire or deteriorate due to the failure to sell or use the inventory in a timely manner.

[0060] The fourth quadrant matrix represents the area with low inventory turnover rate and low inventory holding rate. At this time, the inventory not only has poor liquidity, but the total amount is insufficient to meet market demand. The company may face shortage risks. For example, insufficient raw materials during the production process or sales interruption may lead to failure to produce in time or meet customer needs. Therefore, the company should optimize inventory by speeding up procurement, production scheduling and demand forecasting to reduce the possibility of shortages.

[0061] Therefore, for the common characteristic of high inventory holding rate corresponding to the second quadrant matrix and the third quadrant matrix, the first elastic expansion strategy should be considered, that is, reducing inventory holdings through flexible procurement or production adjustments to avoid excessive capital occupation due to excessive inventory; for the common characteristic of low inventory turnover rate corresponding to the third quadrant matrix and the fourth quadrant matrix, special attention should be paid to the risks of backlog and expiration. For this reason, the second elastic expansion strategy should be considered to improve inventory turnover rate and reduce the burden of inventory holding by optimizing production scheduling.

[0062] Preferably, in the second and third quadrants, focus on shortage risks and expiration risks, and formulate the first elastic expansion strategy accordingly. For example, when the inventory holding rate is high but the inventory turnover rate is not high enough, the company may face product expiration or unsalable products, so measures need to be taken, such as increasing production or purchasing to ensure timely circulation of inventory and reduce expiration risks. Similarly, shortage risks also need attention, and companies may need to increase purchasing or production efforts to ensure sufficient inventory and avoid supply chain disruptions.

[0063] Preferably, in the third and fourth quadrants, the risks of concern are backlog risk and occupancy risk, and a second elastic expansion strategy is set based on these risks. For example, when inventory is too high and turnover is slow, the company faces higher backlog risk and capital occupation risk. At this time, the company should optimize its inventory management strategy, reduce production scale or adjust procurement plans, reduce inventory backlogs, and release occupied funds. By mapping the inventory status to the quadrant matrix, the company can clearly see the risks of each inventory situation, formulate targeted inventory optimization strategies, reduce risks such as expiration, backlog, and occupancy, and ensure smooth production or sales, making the company's inventory management more accurate.

[0064] By adopting flexible expansion strategies according to the inventory status of different quadrants, enterprises can flexibly adjust inventory management strategies to achieve inventory optimization. For example, in the third quadrant, it is necessary to increase inventory turnover and reduce inventory holding rate, while in the first quadrant, it may be necessary to increase inventory holding rate to ensure supply chain stability. Through the above steps, enterprises can flexibly adjust production and procurement plans according to actual inventory conditions, reduce various risks (such as shortage, expiration, backlog and occupancy risks), improve the accuracy and efficiency of inventory management, and ensure smooth production and sales.

[0065] Furthermore, in the second quadrant matrix and the third quadrant matrix of the quadrant matrix, the first elastic expansion strategy is set with shortage risk and expiration risk as the focus. The method of the present application includes:

[0066] Based on the business flow chain, the response speed is continuously tracked and the delay index is quantified; in the second quadrant matrix of the quadrant matrix, the first shortage risk index and the first overdue risk index are extracted in combination with the delay index; in the third quadrant matrix of the quadrant matrix, the second shortage risk index and the second overdue risk index are extracted in combination with the delay index; the first shortage risk index and the first overdue risk index are merged, and the second shortage risk index and the second overdue risk index are merged to obtain a first elastic expansion strategy.

[0067] Specifically, shortage risk refers to the risk that inventory is insufficient to meet production, sales or other business needs. If the inventory of a certain product or raw material is lower than the minimum requirement, it may lead to production interruptions, order delays, and failure to meet customer needs in a timely manner, thereby affecting business operations and customer satisfaction; expiration risk refers to the risk that certain products in inventory (especially goods with a shelf life) will expire due to not being used or sold for a long time. It usually occurs when the inventory holding rate is too high and inventory liquidity is insufficient. The company may face problems with capital occupation and waste disposal.

[0068] The delay indicator is used to measure the time spent on a certain link or decision in the business process, especially the time delay in the supply chain or production process. A link with too long a delay usually means an untimely response, which may lead to inventory shortages or backlogs. This indicator is often used to evaluate order processing time, supplier delivery time, production scheduling time, etc.; the elastic expansion strategy refers to a mechanism that dynamically adjusts the inventory management strategy according to different inventory conditions and risk assessments. Through this strategy, enterprises can flexibly respond to the risks of too much or too little inventory according to actual conditions to achieve better inventory management.

[0069] Implementation steps: It is necessary to identify potential risk types in the second quadrant matrix and the third quadrant matrix, with special attention paid to shortage risks and expiration risks. In these two quadrants, the inventory turnover rate is low and the inventory holding rate is high, which can easily lead to inventory backlogs or expiration problems, so special attention needs to be paid to these risks; continuous tracking is carried out through the business circulation chain to quantify delay indicators. The business circulation chain represents the entire process from raw material procurement to final product sales, and the delay indicator measures the response speed of each link in this process. For example, in the links of supplier delivery, inventory management, production scheduling, etc., any delay will affect inventory turnover and demand response; by quantifying delay indicators, enterprises can evaluate which links’ delays may lead to insufficient inventory or inventory backlogs, thereby affecting the overall inventory management.

[0070] For the situation in the second quadrant matrix, due to the high inventory turnover rate and the high inventory holding rate, the company needs to extract the first shortage risk indicator and the first expiration risk indicator based on the delay indicator. In this case, the company will pay attention to the balance between shortage risk and expiration risk. For example, if the delay indicator shows that the supplier's delivery delay leads to insufficient supply of raw materials, the shortage risk may increase; at the same time, if some inventory goods are accumulated for too long, they may face the risk of expiration. At this time, combining the delay indicator can help the company determine which inventory products or raw materials may be at risk of shortage or expiration, so as to take timely replenishment or replacement measures.

[0071] Similarly, in the third quadrant matrix, the delay index is also used to extract the second shortage risk index and the second expiration risk index. In the third quadrant matrix, due to the low inventory turnover rate and the high inventory holding rate, the enterprise is facing an inventory backlog situation, so it pays more attention to the backlog risk and expiration risk. For example, the delay index shows that the production scheduling is lagging, which may cause some inventory goods to fail to be consumed in time for a long time, causing expiration problems, while the inventory turnover rate is too low, which means inventory backlog, and the shortage risk is lower. Therefore, the enterprise should further adjust its strategy according to the delay index to solve the potential problems of backlog or expiration.

[0072] The first shortage risk indicator is combined with the first expiration risk indicator, and the second shortage risk indicator is combined with the second expiration risk indicator to obtain the first elastic expansion strategy. The first elastic expansion strategy provides enterprises with flexible inventory adjustment suggestions by comprehensively analyzing different risk indicators. For example, in the second quadrant matrix, if the shortage risk is high, the purchase volume can be increased or the production plan can be adjusted to cope with it; while in the third quadrant matrix, if the expiration risk is high, the enterprise may need to speed up inventory consumption or accelerate product sales through promotions and other means. In general, this process provides enterprises with a set of flexible optimization strategies based on inventory turnover by quantifying delay indicators and combining them with the analysis of risk indicators to help them cope with various inventory risks and improve the efficiency and stability of inventory management.

[0073] Furthermore, in the second quadrant matrix of the quadrant matrix, the first shortage risk indicator and the first expiration risk indicator are extracted in combination with the delay indicator. The method of the present application includes:

[0074] Based on the delay index and production progress data, a first delay threshold is set; shortage judgment is performed based on the first delay threshold, and the shortage frequency and shortage quantity are calculated as the first shortage risk index; based on the delay index and supplier evaluation data, a second delay threshold is set; expiration judgment is performed based on the second delay threshold, and the expiration frequency and expiration quantity are calculated as the first expiration risk index.

[0075] Specifically, the delay indicator is used to measure the response speed of a certain business or production link, especially the time delay in the processing process, for example, the time difference from the receipt to the completion of an order, the delivery time of materials in the supply chain, etc. If the delay is too long, it may lead to production plan delays, inventory backlogs or shortages; the shortage risk indicator is a tool used to measure the risk of insufficient inventory to meet production or demand. It is usually determined by calculating the inventory frequency and quantity of a certain product to determine the probability of shortage and possible consequences.

[0076] The expiration risk index is used to measure the risk of inventory products exceeding their shelf life due to long-term storage. In particular, for products with a limited shelf life, the expiration risk will affect product quality and corporate losses. The delay threshold refers to the maximum acceptable delay under specific conditions. When the delay exceeds the delay threshold, an early warning signal is triggered and corresponding response measures are taken to avoid problems such as shortages or expiration due to excessive delays.

[0077] Supplier evaluation data is the evaluation result of supplier’s quality, delivery time, production capacity and other factors. These data help to determine whether the supplier can deliver on time, provide products of the required quality, and how to deal with potential risks in the supply chain. Production progress data reflects the completion status of each link in the production process, such as the processing progress of the production line, the inventory conversion rate, etc. These data help to evaluate whether production is proceeding as planned and whether it will lead to excessive or insufficient inventory.

[0078] Implementation steps: Set the first delay threshold based on the delay indicator and production progress data. The delay indicator measures the response time of a certain link in the production and supply process, and the production progress data shows whether the production is carried out on time. Setting the first delay threshold means determining a time point before which the delay is considered acceptable. After this time point, the delay will be considered too long and measures need to be taken.

[0079] The first delay threshold is used to judge shortages. If the delivery delay of a raw material supplier of a certain product exceeds the first delay threshold, a shortage risk will arise. By analyzing the delays in each link, the frequency of each shortage (i.e., the number of times the shortage occurs) and the shortage quantity (i.e., the specific number of shortages) are calculated. For example, if the production progress data shows that a batch of raw materials is not delivered on time, the company may face the risk of production stagnation. In this way, the shortage risk indicator characterizes the risk that inventory cannot meet production demand by calculating these shortage frequencies and quantities.

[0080] On this basis, the second delay threshold is set based on delay indicators and supplier evaluation data. The supplier evaluation data reflects the supplier's delivery capabilities, historical delivery timeliness and quality. These data can help companies evaluate the supply delay risks that may be brought by different suppliers. By analyzing the supplier evaluation data, companies can set a threshold for supplier delivery delays. For example, if a supplier's delivery time is consistently stable, the delay threshold may be looser; but if the supplier has a history of frequently delaying delivery, the threshold will be stricter.

[0081] By using the second delay threshold to make expiration judgments, if the delay exceeds the second delay threshold, the company will determine whether the inventory is likely to exceed the shelf life. For example, if a certain raw material provided by a supplier exceeds the set delivery deadline, it may cause the raw material to expire and become unusable, resulting in losses. Therefore, by combining delay data with supplier evaluation data, the company can predict which raw materials may face the risk of expiration and then make adjustments. The expired raw materials will be calculated for their expiration frequency (i.e., the number of times expiration occurs) and expiration quantity (i.e., the number of expired raw materials).

[0082] By combining the first shortage risk indicator with the first expiration risk indicator, and the second shortage risk indicator with the second expiration risk indicator, the first elastic expansion strategy is obtained. The first elastic expansion strategy compares the shortage risk and expiration risk of inventory, and provides elastic expansion decision support for inventory optimization. For example, a product in the second quadrant matrix may face both shortage and expiration risks. The company can adjust the procurement plan or production plan based on this risk assessment, adjust the inventory in advance, and ensure that the stock products will not expire in the short term, while meeting production and sales needs. Through the above steps, the company can dynamically evaluate and optimize the inventory management strategy to ensure that both the shortage risk is avoided and the expiration risk is effectively controlled, thereby improving the efficiency and stability of the overall supply chain.

[0083] Furthermore, the present application method comprises:

[0084] Elastic expansion capacity Among them, EOS is used to characterize the elastic expansion amount corresponding to the inventory optimization strategy, CRAI is a comprehensive risk assessment indicator, and T is a threshold parameter used to determine whether to trigger elastic expansion; the comprehensive risk assessment indicator R is used to characterize the delay index, SHR is used to characterize the inventory turnover rate, OHR is used to characterize the inventory holding rate, θ, It is the correlation angle between indicators, reflecting the strength of the correlation between DOR and SHR, DOR and OHR.

[0087] Specifically, EOS is used to characterize the elastic expansion amount corresponding to the inventory optimization strategy, and is used to quantify the inventory amount that needs to be increased or decreased when responding to risks, so as to ensure that inventory optimization can adapt to dynamic needs; the threshold parameter T is a set of preset values ​​used to determine whether to trigger elastic expansion. When the comprehensive risk assessment indicator CRAI reaches or exceeds the threshold T, elastic expansion will be automatically performed to respond to sudden demand or supply chain risks; DOR quantifies the response delay of the supply chain, indicating the time difference from order to delivery of inventory, and is a key parameter for judging whether the supply chain responds in a timely manner; SHR is used to characterize the turnover frequency of inventory, that is, the turnover rate of inventory in a certain period of time. The number of replacements reflects the turnover efficiency of products in inventory. A higher inventory turnover rate usually means that the inventory is used or sold in a timely manner, and a lower turnover rate may lead to backlogs. OHR refers to the holding status of inventory products, which usually reflects the warehouse occupancy. A high inventory holding rate means that a certain type of product in the inventory is in a backlog state for a long time, while a low holding rate indicates that the inventory liquidity is good. The correlation angle reflects the correlation strength between the delay index (DOR) and the inventory turnover rate (SHR), and the delay index (DOR) and the inventory holding rate (OHR). By calculating these correlation angles, the relationship between different risk indicators can be analyzed, thereby optimizing the inventory expansion strategy.

[0088] Implementation steps: Establish the calculation formula of comprehensive risk assessment index CRAI: Furthermore, θ, It is the correlation angle between indicators, reflecting the strength of the correlation between DOR and SHR, and DOR and OHR. For example, by observing the correlation between DOR and SHR, we can determine the relationship between delays and inventory turnover, and help understand the causes of inventory backlogs or shortages. If a product has a high DOR and a low SHR, it may be because of delivery delays that reduce inventory turnover efficiency. A preliminary judgment on elastic expansion can be made based on the correlation of different indicators.

[0089] Preferably, when the CRAI triggers the threshold T, the elastic expansion amount EOS is calculated as follows: The value of EOS directly reflects the amount of inventory that needs to be expanded under the current risk situation. The relationship between different indicators is verified through actual production and supply chain data, and the elastic expansion amount EOS is adjusted accordingly to ensure that the inventory is not overstocked or in short supply.

[0090] In summary, the beneficial effects of the embodiments of the present application are:

[0091] 1. By introducing a data-based intelligent review and risk management mechanism, the effectiveness and efficiency of internal control review have been significantly improved. Multi-source data of target enterprise units has been obtained and integrated, which can track and evaluate the operating status of each link of the enterprise in real time, dynamically identify potential risks, and reduce the lag of static review methods.

[0092] 2. Build a business circulation chain, and based on the tracking information and risk feedback of the circulation chain, be able to timely discover risks at different nodes and form a comprehensive risk review model, so as to accurately predict and identify potential risks.

[0093] 3. Make the company's internal control review more flexible and real-time, effectively reduce the risks in the company's operations, improve the transparency and controllability of management, and use the risk assessment model for dynamic adjustment. The company can implement refined risk management strategies to maximize the stability and security of the company during operations.

[0094] 4. Due to the continuous tracking of response speed based on the business circulation chain, the delay index is quantified; in the second quadrant matrix of the quadrant matrix, the first shortage risk index and the first expiration risk index are extracted in combination with the delay index; in the third quadrant matrix of the quadrant matrix, the second shortage risk index and the second expiration risk index are extracted in combination with the delay index; the first shortage risk index and the first expiration risk index, the second shortage risk index and the second expiration risk index are combined to obtain the first elastic expansion strategy. By quantifying the delay index and combining the analysis of the risk index, a set of flexible optimization strategies based on inventory circulation is provided for enterprises to help them deal with various inventory risks and improve the efficiency and stability of inventory management.

[0095] Embodiment 2

[0096] Based on the same inventive concept as the digital internal control review management method in the above embodiment, Figure 2 As shown, the embodiment of the present application provides a digital internal control review management platform, wherein the platform includes:

[0097] The data acquisition module M100 is used to acquire the internal multi-source data under the department business tag of the target enterprise unit, wherein the department business tag includes a purchase tag and a sales tag;

[0098] The circulation chain establishment module M200 is used to introduce supply circulation information, use the department business tag as an associated index, and establish a business circulation chain, wherein the business circulation chain includes multiple circulation nodes;

[0099] An interactive computing module M300, for building a review risk framework based on the internal multi-source data using an open source interactive computing engine;

[0100] The continuous tracking module M400 is used to continuously track based on the business flow chain, and at the same time, map the risk feedback information of multiple flow nodes of the business flow chain to the review risk architecture to obtain a review risk model;

[0101] The internal control review module M500 is used to perform internal control review based on the review risk model and mark potential risk nodes;

[0102] The event extraction module M600 is used to connect to the internal control review database, extract similar risk events based on the potential risk nodes as constraints, mine risk causes and generate risk configuration clusters;

[0103] The security management module M700 is used to perform seamless collaborative security management on the target enterprise unit according to the potential risk nodes and the risk configuration cluster.

[0104] Furthermore, the interactive computing module M300 is also used to execute the following method:

[0105] Obtain supplier evaluation data, inventory data, and production progress data as supplementary data for internal multi-source data;

[0106] Based on the supplementary data, a supplier selection node, an inventory management node, and a production scheduling node are set in the business flow chain;

[0107] An inventory optimization strategy is set based on the supplier selection node, inventory management node, and production scheduling node.

[0108] Furthermore, the interactive computing module M300 is also used to execute the following method:

[0109] At the inventory management node, calculating inventory turnover rate;

[0110] At the production scheduling node, an inventory holding rate is configured, and the inventory holding rate complies with a scheduling optimization rule;

[0111] Based on the inventory turnover rate and the inventory holding rate, the inventory optimization strategy is flexibly expanded.

[0112] Furthermore, the interactive computing module M300 is also used to execute the following method:

[0113] A quadrant matrix is ​​set by the inventory turnover rate and the inventory holding rate, wherein the quadrant matrix includes a first quadrant matrix, a second quadrant matrix, a third quadrant matrix, and a fourth quadrant matrix, wherein the first quadrant matrix is ​​used to characterize areas with high inventory turnover rate and low inventory holding rate;

[0114] In the second quadrant matrix and the third quadrant matrix of the quadrant matrix, a first elastic expansion strategy is set with shortage risk and expiration risk as the focus;

[0115] In the third quadrant matrix and the fourth quadrant matrix of the quadrant matrix, a second elastic expansion strategy is set with backlog risk and occupation risk as focus points;

[0116] The inventory optimization strategy is elastically expanded using the first elastic expansion strategy and the second elastic expansion strategy.

[0117] Furthermore, the interactive computing module M300 is also used to execute the following method:

[0118] The second quadrant matrix is ​​used to characterize areas with high inventory turnover and high inventory holding rates;

[0119] The third quadrant matrix is ​​used to characterize areas with low inventory turnover and high inventory holding rates;

[0120] The fourth quadrant matrix is ​​used to characterize areas with low inventory turnover and low inventory holding rates.

[0121] Furthermore, the interactive computing module M300 is also used to execute the following method:

[0122] Continuously track response speed based on the business flow chain and quantify delay indicators;

[0123] In the second quadrant matrix of the quadrant matrix, the first shortage risk indicator and the first overdue risk indicator are extracted in combination with the delay indicator;

[0124] In the third quadrant matrix of the quadrant matrix, the second shortage risk indicator and the second overdue risk indicator are extracted in combination with the delay indicator;

[0125] The first shortage risk indicator and the first expiration risk indicator are combined, and the second shortage risk indicator and the second expiration risk indicator are combined to obtain a first elastic expansion strategy.

[0126] Furthermore, the interactive computing module M300 is also used to execute the following method:

[0127] Based on the delay indicator and the production progress data, setting a first delay threshold;

[0128] Perform shortage judgment based on the first delay threshold, and calculate shortage frequency and shortage amount as the first shortage risk indicator;

[0129] Setting a second delay threshold based on the delay indicator and the supplier evaluation data;

[0130] The second delay threshold is used to perform expiration judgment, and the expiration frequency and expiration amount are calculated as the first expiration risk indicator.

[0131] Furthermore, the interactive computing module M300 is also used to execute the following method:

[0132] Elastic expansion capacity Among them, EOS is used to characterize the elastic expansion amount corresponding to the inventory optimization strategy, CRAI is a comprehensive risk assessment indicator, and T is a threshold parameter used to determine whether to trigger elastic expansion;

[0133] The comprehensive risk assessment indicators R is used to characterize the delay index, SHR is used to characterize the inventory turnover rate, OHR is used to characterize the inventory holding rate, θ, It is the correlation angle between indicators, reflecting the strength of the correlation between DOR and SHR, DOR and OHR.

[0136] In summary, any step can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor, and no unnecessary restrictions are made here.

[0137] Furthermore, the above-mentioned technical scheme only reflects the preferred technical scheme of the technical scheme of the embodiment of the present application. Some changes that may be made to some parts thereof by technicians in this technical field all reflect the novel principles of the embodiment of the present application. Obviously, technicians in this field can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. A digital internal control review management method, characterized in that: The method comprises: Acquire internal multi-source data under department business tags of the target enterprise unit, wherein the department business tags include a purchasing tag and a sales tag; Introducing supply flow information, using the department business tag as an associated index, and establishing a business flow chain, wherein the business flow chain includes multiple flow nodes; Based on the internal multi-source data, an open source interactive computing engine is used to build a review risk framework; Based on the business flow chain, continuous tracking is performed, and at the same time, risk feedback information of multiple flow nodes of the business flow chain is mapped to the review risk architecture to obtain a review risk model; Conduct internal control review using the review risk model and mark potential risk nodes; Connect to the internal control review database, extract similar risk events based on the potential risk nodes as constraints, explore risk causes and generate risk configuration clusters; Based on the potential risk nodes and the risk configuration cluster, seamless collaborative security management is performed on the target enterprise unit.

2. A digital internal control review management method as claimed in claim 1, characterized in that: Based on the internal multi-source data, using an open source interactive computing engine, constructing a review risk framework, the method further includes: Obtain supplier evaluation data, inventory data, and production progress data as supplementary data for internal multi-source data; Based on the supplementary data, a supplier selection node, an inventory management node, and a production scheduling node are set in the business flow chain; An inventory optimization strategy is set based on the supplier selection node, inventory management node, and production scheduling node.

3. A digital internal control review management method as claimed in claim 2, characterized in that: Based on the supplier selection node, the inventory management node, and the production scheduling node, an inventory optimization strategy is set, and the method further includes: At the inventory management node, calculating inventory turnover rate; At the production scheduling node, an inventory holding rate is configured, and the inventory holding rate complies with a scheduling optimization rule; Based on the inventory turnover rate and the inventory holding rate, the inventory optimization strategy is flexibly expanded.

4. A digital internal control review management method as claimed in claim 3, characterized in that: Based on the inventory turnover rate and the inventory holding rate, the inventory optimization strategy is elastically expanded, and the method includes: A quadrant matrix is ​​set by the inventory turnover rate and the inventory holding rate, wherein the quadrant matrix includes a first quadrant matrix, a second quadrant matrix, a third quadrant matrix, and a fourth quadrant matrix, wherein the first quadrant matrix is ​​used to characterize areas with high inventory turnover rate and low inventory holding rate; In the second quadrant matrix and the third quadrant matrix of the quadrant matrix, a first elastic expansion strategy is set with shortage risk and expiration risk as the focus; In the third quadrant matrix and the fourth quadrant matrix of the quadrant matrix, a second elastic expansion strategy is set with backlog risk and occupation risk as focus points; The inventory optimization strategy is elastically expanded using the first elastic expansion strategy and the second elastic expansion strategy.

5. A digital internal control review management method as claimed in claim 4, characterized in that: The second quadrant matrix is ​​used to characterize areas with high inventory turnover and high inventory holding rates; The third quadrant matrix is ​​used to characterize areas with low inventory turnover and high inventory holding rates; The fourth quadrant matrix is ​​used to characterize areas with low inventory turnover and low inventory holding rates.

6. A digital internal control review management method as claimed in claim 5, characterized in that: In the second quadrant matrix and the third quadrant matrix of the quadrant matrix, a first elastic expansion strategy is set with shortage risk and expiration risk as focus points, and the method includes: Continuously track response speed based on the business flow chain and quantify delay indicators; In the second quadrant matrix of the quadrant matrix, the first shortage risk indicator and the first overdue risk indicator are extracted in combination with the delay indicator; In the third quadrant matrix of the quadrant matrix, the second shortage risk indicator and the second overdue risk indicator are extracted in combination with the delay indicator; The first shortage risk indicator and the first expiration risk indicator are combined, and the second shortage risk indicator and the second expiration risk indicator are combined to obtain a first elastic expansion strategy.

7. A digital internal control review management method as claimed in claim 6, characterized in that: In the second quadrant matrix of the quadrant matrix, the first shortage risk indicator and the first overdue risk indicator are extracted in combination with the delay indicator. The method includes: Based on the delay indicator and the production progress data, setting a first delay threshold; Perform shortage judgment based on the first delay threshold, and calculate shortage frequency and shortage amount as the first shortage risk indicator; Setting a second delay threshold based on the delay indicator and the supplier evaluation data; The second delay threshold is used to perform expiration judgment, and the expiration frequency and expiration amount are calculated as the first expiration risk indicator.

8. A digital internal control review management method as claimed in claim 7, characterized in that: Elastic expansion capacity Among them, EOS is used to characterize the elastic expansion amount corresponding to the inventory optimization strategy, CRAI is a comprehensive risk assessment indicator, and T is a threshold parameter used to determine whether to trigger elastic expansion; The comprehensive risk assessment index CRAI= DOR is used to characterize the delay index, SHR is used to characterize the inventory turnover rate, OHR is used to characterize the inventory holding rate, θ, It is the correlation angle between indicators, reflecting the strength of the correlation between DOR and SHR, DOR and OHR.

9. A digital internal control review management platform, characterized in that: A digital internal control review management method for implementing any one of claims 1 to 8, wherein the platform comprises: A data acquisition module, used to acquire internal multi-source data under department business tags of a target enterprise unit, wherein the department business tags include a purchase tag and a sales tag; A circulation chain establishment module, used to introduce supply circulation information, use the department business tag as an associated index, and establish a business circulation chain, wherein the business circulation chain includes multiple circulation nodes; An interactive computing module, used to construct a review risk framework based on the internal multi-source data using an open source interactive computing engine; A continuous tracking module is used to continuously track based on the business flow chain, and at the same time, map the risk feedback information of multiple flow nodes of the business flow chain to the review risk architecture to obtain a review risk model; An internal control review module, used to conduct internal control review based on the review risk model and mark potential risk nodes; An event extraction module is used to connect to the internal control review database, extract similar risk events based on the potential risk nodes as constraints, mine risk causes and generate risk configuration clusters; The security management module is used to perform seamless collaborative security management on the target enterprise unit based on the potential risk nodes and the risk configuration cluster.

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