Enterprise purchase service integrated management system and method

Abstract

The invention is suitable for the technical field of enterprise purchase management, and provides an enterprise purchase service integrated management system and method, and the method comprises the steps: screening out all target purchase tasks which are not approved by a target enterprise auditor after a planned auditing time point of the target enterprise auditor is received, and determining a specific category and an initial priority index of each target purchase task, and extracting a historical purchase log and a historical application log of the target enterprise in a preset time period. According to the technical scheme, the priority index of the purchase task is dynamically optimized by combining the historical trend gradient and the use benefit deviation coefficient, and the actual demand and the potential delay risk of each task can be more accurately evaluated. The historical trend gradient reflects the difference between the time required for task completion and the estimated time, so that the possible delay trend is revealed; and the benefit deviation coefficient is used for comparing the actual application duration with the standard application duration to help judge whether the goods can be put into use in time or not.

Description

Technical Field

[0001] The present invention belongs to the technical field of enterprise procurement management, and in particular relates to an enterprise procurement service integrated management system and method. Background Art

[0002] At present, enterprise procurement management systems mainly rely on manual or rule-based scheduling methods to arrange and optimize the processing priority of procurement tasks. In traditional procurement management, task priorities are usually set based on static factors such as task type, procurement amount, and urgency. However, this static priority allocation method does not fully consider the dynamic changes that may occur during the execution of procurement tasks, such as delays in the actual completion time of tasks, logistics fluctuations, etc. Therefore, when facing complex and changeable tasks, existing procurement management systems often have problems such as inflexible scheduling and untimely task priority adjustment, resulting in resource waste and delays in the procurement process.

[0003] Existing technologies do not have an effective mechanism to dynamically adjust the priority of tasks. Most procurement systems rely on fixed rules to schedule tasks, and lack real-time feedback based on factors such as task execution progress and historical data to flexibly adjust priorities. This model causes the system to be very rigid when responding to changes in tasks. For example, during the execution of certain tasks, due to supply chain or logistics reasons, the scheduled completion time may be extended or completed ahead of schedule, but the existing system cannot detect and dynamically adjust the priority according to the changes in time, which may ultimately lead to inefficient approval and processing of tasks, and even affect the stability of the company's overall supply chain. Summary of the invention

[0004] The purpose of the present invention is to provide an integrated management system and method for enterprise procurement services, aiming to solve the problems raised in the background technology.

[0005] The present invention is implemented as follows: a method for integrated management of enterprise procurement services, the method comprising:

[0006] After receiving the planned review time point from the target enterprise auditor, all target procurement tasks that have not been approved by the auditor are screened out, the specific category and initial priority index of each target procurement task are determined, and the historical procurement logs and historical application logs of the target enterprise within the preset time period are extracted;

[0007] Filter out the designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed from the historical procurement logs, obtain the procurement completion time of these designated historical procurement tasks, draw a line chart of the procurement completion time based on the time sequence, calculate its change slope, and set the change slope as the historical trend gradient;

[0008] Based on the historical application log, extract the actual application time of the goods for the specified historical procurement tasks, and calculate the average actual application time of the goods;

[0009] Obtain a preset application duration comparison table, obtain the standard application duration corresponding to the specific category of the target procurement task, combine it with the average historical application duration, and calculate the use benefit deviation coefficient of the target procurement task;

[0010] Based on the historical trend gradient and the utilization benefit deviation coefficient, the initial priority index is comprehensively adjusted to generate a dynamic priority index.

[0011] As a further limitation of the technical solution of the embodiment of the present invention, the steps of selecting the designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed from the historical procurement log, obtaining the procurement completion time of these designated historical procurement tasks, and drawing a line graph of the procurement completion time based on the time sequence, calculating its change slope, and setting the change slope as the historical trend gradient include:

[0012] Retrieve historical procurement logs and select the designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed;

[0013] Parse each specified historical procurement task in turn, determine the execution time and completion time of the specified historical procurement task, and calculate the procurement completion time;

[0014] Set the completion time of the specified historical procurement task as the X-axis, and the procurement completion time as the Y-axis, draw a line graph in chronological order, calculate its change slope, and define the change slope as the historical trend gradient.

[0015] As a further limitation of the technical solution of the embodiment of the present invention, the preset application time comparison table is a reference data table for recording and setting the expected application time of goods corresponding to different specific categories of procurement tasks under standard use conditions;

[0016] The preset application time comparison table is formulated based on historical data statistics, industry standards or internal enterprise experience. Each specific category of goods corresponds to a clear standard application time.

[0017] As a further limitation of the technical solution of the embodiment of the present invention, the steps of obtaining a preset application time comparison table, obtaining the standard application time corresponding to the specific category of the target procurement task from the preset application time comparison table, combining the standard application time with the average historical application time, and calculating the use benefit deviation coefficient of the target procurement task include:

[0018] Obtain a preset application duration comparison table and search it to obtain the standard application duration corresponding to the specific category of the target procurement task;

[0019] Divide the difference between the average historical application time and the standard application time by the standard application time to calculate the utilization efficiency deviation coefficient of the target procurement task.

[0020] As a further limitation of the technical solution of the embodiment of the present invention, based on the historical trend gradient and the use benefit deviation coefficient, the initial priority index is comprehensively adjusted to generate a dynamic priority index, including:

[0021] Retrieve the priority index optimization calculation formula, and make comprehensive adjustments to the initial priority index in combination with the historical trend gradient and the use benefit deviation coefficient to generate a dynamic priority index;

[0022] Replace the initial priority index of the target procurement task and update it to the corresponding dynamic priority index.

[0023] As a further limitation of the technical solution of the embodiment of the present invention, the priority index optimization calculation formula is:

[0024] Among them, I d Refers to the dynamic priority index, I o refers to the initial priority index, n refers to the total number of target procurement tasks, T yi and T yi-1 They represent the procurement completion time of the i-th and i-1-th target procurement tasks, T xi and T xi-1 Respectively represent the completion time of the i-th and i-1-th target procurement tasks, T a Refers to the average of the historical application duration, T s Refers to the standard application duration, refers to the historical trend gradient, Refers to the utilization efficiency deviation coefficient.

[0025] An integrated management system for enterprise procurement services, the system comprising: a data acquisition module, a historical trend gradient acquisition module, an application time calculation module, a deviation coefficient calculation module and a priority index adjustment module, wherein:

[0026] The data acquisition module is used to screen out all target procurement tasks that have not been approved by the auditor after receiving the planned review time point of the target enterprise auditor, determine the specific category and initial priority index of each target procurement task, and extract the historical procurement log and historical application log of the target enterprise within a preset time period;

[0027] The historical trend gradient acquisition module is used to filter out the specified historical procurement tasks that are of the same specific category as the target procurement task and have been completed from the historical procurement logs, obtain the procurement completion time of these specified historical procurement tasks, and draw a line chart of the procurement completion time based on the time sequence, calculate its change slope, and set the change slope as the historical trend gradient;

[0028] The application time calculation module is used to extract the actual application time of goods for a specified historical procurement task based on historical application logs, and calculate the average actual application time of goods;

[0029] The deviation coefficient calculation module is used to obtain a preset application time comparison table, obtain the standard application time corresponding to the specific category of the target procurement task, combine it with the average historical application time, and calculate the use benefit deviation coefficient of the target procurement task;

[0030] The preset application time comparison table is a reference data table used to record and set the expected application time of goods corresponding to different specific categories of procurement tasks under standard use conditions;

[0031] The preset application time comparison table is formulated based on historical data statistics, industry standards or internal enterprise experience. Each specific category of goods corresponds to a clear standard application time;

[0032] The priority index adjustment module is used to make comprehensive adjustments to the initial priority index based on the historical trend gradient and the use benefit deviation coefficient to generate a dynamic priority index.

[0033] As a further limitation of the technical solution of the embodiment of the present invention, the historical trend gradient acquisition module specifically includes:

[0034] A log interpretation unit is used to retrieve historical procurement logs and filter out designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed;

[0035] A procurement completion time calculation unit is used to parse each designated historical procurement task in turn, determine the execution time and completion time of the designated historical procurement task, and calculate the procurement completion time;

[0036] The change slope calculation unit is used to set the completion time of the specified historical procurement task as the X-axis and the procurement completion time as the Y-axis, draw a line graph in chronological order, calculate its change slope, and define the change slope as the historical trend gradient.

[0037] As a further limitation of the technical solution of the embodiment of the present invention, the deviation coefficient calculation module specifically includes:

[0038] A standard application duration acquisition unit is used to acquire a preset application duration comparison table and search it to acquire the standard application duration corresponding to a specific category of the target procurement task;

[0039] The use efficiency deviation coefficient calculation unit is used to divide the difference between the average historical application time and the standard application time by the standard application time to calculate the use efficiency deviation coefficient of the target procurement task.

[0040] As a further limitation of the technical solution of the embodiment of the present invention, the priority index adjustment module specifically includes:

[0041] A dynamic priority index generation unit is used to retrieve the priority index optimization calculation formula, and comprehensively adjust the initial priority index in combination with the historical trend gradient and the use benefit deviation coefficient to generate a dynamic priority index;

[0042] A priority index replacement unit, used to replace the initial priority index of the target procurement task and update it to a corresponding dynamic priority index;

[0043] The priority index optimization calculation formula is:

[0044] Among them, I d Refers to the dynamic priority index, I o refers to the initial priority index, n refers to the total number of target procurement tasks, T yi and T yi-1 They represent the procurement completion time of the i-th and i-1-th target procurement tasks, T xi and T xi-1 Respectively represent the completion time of the i-th and i-1-th target procurement tasks, T a Refers to the average of the historical application duration, T s Refers to the standard application duration, refers to the historical trend gradient, Refers to the utilization efficiency deviation coefficient.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] By dynamically optimizing the priority index of procurement tasks by combining the historical trend gradient and the use of the benefit deviation coefficient, this technical solution can more accurately evaluate the actual needs and potential delay risks of each task. The historical trend gradient reflects the difference between the time required to complete the task and the estimated time, thereby revealing possible delay trends; the use of the benefit deviation coefficient helps determine whether the goods can be put into use in a timely manner by comparing the actual application time with the standard application time. After combining these two factors, the system can dynamically adjust the priority according to the specific circumstances of the task, thereby achieving more efficient allocation of resources, reducing delays and waste in the procurement process, and improving overall work efficiency and response speed.

[0047] In actual applications, after the auditor sets the audit time point based on his or her own work situation, the system will reasonably arrange the processing order of tasks according to the priority of each procurement task, ensuring that the most urgent and most critical tasks can be approved and executed in a timely manner within a limited time, thereby improving the response efficiency of the entire procurement process and the overall operation efficiency of the supply chain. This dynamic priority adjustment mechanism can be flexibly adjusted according to changes in actual needs, ensuring that various tasks are executed on demand and in priority, and improving the company's supply chain management capabilities and decision-making level. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A flowchart of a method provided by an embodiment of the present invention;

[0049] Figure 2 A flow chart of determining a historical trend gradient based on a historical purchase log in a method provided in an embodiment of the present invention;

[0050] Figure 3 A flow chart of calculating the use benefit deviation coefficient based on a preset application duration comparison table in the method provided in an embodiment of the present invention;

[0051] Figure 4 A flow chart of adjusting an initial priority index to a dynamic priority index in a method provided in an embodiment of the present invention;

[0052] Figure 5 An application architecture diagram of a system provided by an embodiment of the present invention;

[0053] Figure 6 A structural block diagram of a historical trend gradient acquisition module in a system provided by an embodiment of the present invention;

[0054] Figure 7 A structural block diagram of a deviation coefficient calculation module in a system provided by an embodiment of the present invention;

[0055] Figure 8 This is a structural block diagram of a priority index adjustment module in a system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0057] Figure 1 A flow chart of a method provided by an embodiment of the present invention is shown.

[0058] Specifically, a method for integrated management of enterprise procurement services includes the following steps:

[0059] Step S100, after receiving the planned review time point from the target enterprise auditor, screen out all target procurement tasks that have not yet been approved by the auditor, determine the specific category and initial priority index of each target procurement task, and extract the historical procurement logs and historical application logs of the target enterprise within a preset time period.

[0060] In the embodiment of the present invention, the present invention is applied to the procurement task review and priority optimization scenario of the target enterprise, aiming to help the reviewer quickly and efficiently process multiple procurement tasks to be approved within a limited time, ensure the rationality of resource allocation and priority response to urgent needs. By intelligently adjusting the priority of procurement tasks, enterprises can effectively improve the efficiency of procurement approval, reduce processing time, and meet key needs in the shortest time.

[0061] The planned review time point of the target enterprise reviewer refers to the time point when the reviewer is scheduled to start processing the procurement task. This time point is received and recorded by the system to trigger the subsequent priority optimization process.

[0062] During the review process, the system will screen out all target procurement tasks that have not been approved by the reviewer and determine the specific category of each task. The screening process is achieved through task status identification. Unapproved tasks will be identified by the system and relevant information will be extracted. The specific category of the task (such as material type or departmental demand, etc.) is also the result of the system's classification based on task attributes, which is one of the key factors in priority assessment.

[0063] The initial priority index is generated by existing technology and assigned to each task according to pre-set rules. The rules may include parameters such as the urgency of the task, the order of submission time, and the priority of material categories. The initial priority index serves as the basic priority reference value for each procurement task and is used for subsequent optimization and adjustment.

[0064] The preset time period is set based on the target company's purchasing habits and data representativeness. Usually the most recent time period (such as the past three months or six months) is selected to ensure the timeliness and relevance of historical data. The selection of this time period helps reflect the company's current purchasing and usage patterns and provides relatively accurate data support.

[0065] The historical procurement log and historical application log are derived from the target company's procurement management system or resource usage record system. The procurement log records the execution time, completion time, task execution status and other information of various procurement tasks, helping auditors understand the historical processing of tasks. The application log records the consumption or usage cycle data of materials in actual use. This information is used to analyze the actual benefits of materials and optimize the priority of procurement tasks.

[0066] Through the above process, the present invention can realize intelligent review and dynamic adjustment of the priority of the target enterprise's procurement tasks, and significantly improve the enterprise's procurement efficiency and responsiveness.

[0067] Furthermore, the enterprise procurement service integrated management method further includes the following steps:

[0068] Step S200, filter out the specified historical procurement tasks that are of the same specific category as the target procurement task and have been completed from the historical procurement log, obtain the procurement completion time of these specified historical procurement tasks, and draw a line graph of the procurement completion time based on the time sequence, calculate its change slope, and set the change slope as the historical trend gradient.

[0069] Specifically, Figure 2 A flow chart for determining a historical trend gradient based on historical purchase logs is shown.

[0070] Among them, the designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed are screened out from the historical procurement logs, the procurement completion time of these designated historical procurement tasks is obtained, and a line graph of the procurement completion time is drawn based on the time sequence, and its change slope is calculated, and the change slope is set as the historical trend gradient. Specifically, the following steps are included:

[0071] Step S201, retrieve the historical procurement log, and filter out the designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed;

[0072] Step S202, parsing each designated historical procurement task in turn, determining the execution time and completion time of the designated historical procurement task, and calculating the procurement completion time;

[0073] Step S203, setting the completion time of the designated historical procurement task as the X-axis, setting the procurement completion time as the Y-axis, drawing a line graph in chronological order, calculating its change slope, and defining the change slope as the historical trend gradient.

[0074] In an embodiment of the present invention, the historical procurement log of the target enterprise is first retrieved. The system will filter out all completed procurement tasks from the log according to the specific category of the target procurement task (such as office supplies, daily necessities, equipment accessories, etc.). The key to the screening lies in two points: first, the category of the task needs to be consistent with the target procurement task, and second, the status of the task must be "completed". Through these two criteria, the system can filter out historical tasks that are of the same type as the current task and have been completed, so as to ensure the comparability and representativeness of the data.

[0075] The system analyzes each filtered historical procurement task in turn, extracting the task generation time and completion time. The system calculates the procurement completion time of each task, that is, "execution time minus completion time", and records the completion time of the task. These completion time data provide the basis for subsequent trend analysis.

[0076] The system uses the completion time of each task as the X-axis and the procurement completion time as the Y-axis to draw a line graph in chronological order. Through this line graph, the system can intuitively display the changing trend of task execution time. Next, the system calculates the slope of the line graph, which represents the rate of change of the time required to complete each task, that is, the increase in the procurement completion time per unit time. In order to ensure that the data is more stable and reliable, the system will denoise the data. Specifically, the system will identify and remove abnormal data that obviously deviates from the normal range to avoid the impact of these abnormal data on trend calculations. The denoising process can use statistical methods, such as calculating the standard deviation or using median filtering to remove data points with large deviations or abnormalities. Finally, the system calculates the slope in each period of time and obtains an average value as the historical trend gradient.

[0077] The significance of the historical trend gradient is that it can analyze the changes in the execution time of a specified historical procurement task and help determine whether the completion time of the task is gradually getting longer or shorter. If the value of the historical trend gradient is large, it means that the completion time of the task is gradually increasing. This may be due to external factors (such as delivery time, logistics delays, unstable supplier delivery time, etc.) that cause the task execution time to be extended. On the contrary, if the historical trend gradient is small, it means that the completion time of the task is gradually shortened. This may be due to the improvement of these external factors, more timely distribution, and more efficient delivery.

[0078] Based on this analysis, the system can dynamically adjust the priority of procurement tasks according to the historical trend gradient. For example, when the completion time of historical tasks gradually shortens, indicating that external conditions tend to improve and task execution is more efficient, the system can consider appropriately lowering the priority of the task; and when the completion time of historical tasks gradually lengthens, indicating that external conditions such as distribution may be unstable or delayed, the system can consider increasing the priority of the task to ensure that the procurement task is completed on time as much as possible.

[0079] Through this analysis, the historical trend gradient not only helps evaluate the execution efficiency of historical procurement tasks, but also provides a strong basis for the priority adjustment of current tasks.

[0080] Furthermore, the enterprise procurement service integrated management method further includes the following steps:

[0081] Step S300, based on the historical application log, extract the actual application time of the goods of the specified historical procurement task, and calculate the average actual application time of the goods;

[0082] Step S400, obtain a preset application time comparison table, obtain the standard application time corresponding to the specific category of the target procurement task, combine it with the average historical application time, and calculate the use efficiency deviation coefficient of the target procurement task.

[0083] Specifically, Figure 3 A flow chart for calculating the use benefit deviation coefficient based on a preset application duration comparison table is shown.

[0084] The process of obtaining a preset application duration comparison table, obtaining the standard application duration corresponding to the specific category of the target procurement task, combining it with the average historical application duration, and calculating the use benefit deviation coefficient of the target procurement task specifically includes the following steps:

[0085] Step S401, obtaining a preset application duration comparison table, and searching it to obtain the standard application duration corresponding to a specific category of the target procurement task;

[0086] Step S402, dividing the difference between the average historical application time and the standard application time by the standard application time to calculate the use efficiency deviation coefficient of the target procurement task.

[0087] The preset application time comparison table is a reference data table used to record and set the expected application time of goods corresponding to different specific categories of procurement tasks under standard use conditions;

[0088] The preset application time comparison table is formulated based on historical data statistics, industry standards or internal enterprise experience. Each specific category of goods corresponds to a clear standard application time.

[0089] In an embodiment of the present invention, based on the historical application log, the system extracts the actual application time of the goods of the completed procurement tasks of the same category as the target procurement task from the historical records. These application times reflect the time required for the goods to be actually put into use and completed from the completion of procurement. By counting the actual application time of all historical procurement tasks of the same category as the target procurement task, the system can calculate the average actual application time of the goods for these tasks. The calculation method is to sum up the actual application time of all historical procurement tasks and divide it by the total number of tasks, so as to obtain the average application time of the category.

[0090] For example, for goods such as office supplies, the actual usage time can be estimated through employee usage logs or inventory management records. However, for certain categories of goods, such as food items, the actual usage time may be determined through video surveillance data. For example, some food purchases may be used within a certain period of time after being stored in the warehouse. Video surveillance can help track the opening, consumption or use of these items, and then deduce their actual usage time. This method not only improves the accuracy of the data, but also ensures more efficient tracking of usage time.

[0091] The preset application time comparison table is a reference data table used to record the expected application time of goods under standard use conditions for each procurement task category. This table is usually formulated based on historical data statistics, industry standards and internal experience of the enterprise. Historical data statistics come from the company's past procurement records, industry standards are set based on the industry's general usage, and internal experience sets the standard application time based on the company's operating practices and understanding of the use of items. These reference bases help companies formulate reasonable preset application times for different types of procurement tasks.

[0092] The difference between the average historical application time and the standard application time is divided by the standard application time to calculate the use efficiency deviation coefficient of the target procurement task. The purpose is to measure the degree of deviation between the target procurement task in actual application and the expected use time. Through this deviation coefficient, the enterprise can determine whether the use efficiency of certain goods is consistent with expectations. If the actual use time is longer, it may mean that the purchased goods do not meet expectations or the actual use efficiency is low. Conversely, it may indicate that the resource use efficiency is high. This deviation coefficient can help the system dynamically adjust the priority of procurement tasks, thereby optimizing resource allocation and procurement efficiency in future procurement decisions.

[0093] Furthermore, the enterprise procurement service integrated management method further includes the following steps:

[0094] Step S500, based on the historical trend gradient and the use benefit deviation coefficient, the initial priority index is comprehensively adjusted to generate a dynamic priority index.

[0095] Specifically, Figure 4 A flow chart for adjusting an initial priority index to a dynamic priority index is shown.

[0096] Among them, based on the historical trend gradient and the use benefit deviation coefficient, the initial priority index is comprehensively adjusted to generate a dynamic priority index, which specifically includes the following steps:

[0097] Step S501, retrieve the priority index optimization calculation formula, and make comprehensive adjustments to the initial priority index in combination with the historical trend gradient and the use benefit deviation coefficient to generate a dynamic priority index;

[0098] Step S502, replacing the initial priority index of the target procurement task and updating it to the corresponding dynamic priority index.

[0099] The priority index optimization calculation formula is:

[0100] Among them, I d Refers to the dynamic priority index, I o refers to the initial priority index, n refers to the total number of target procurement tasks, T yi and T yi-1 They represent the procurement completion time of the i-th and i-1-th target procurement tasks, T xi and T xi-1 Respectively represent the completion time of the i-th and i-1-th target procurement tasks, T a Refers to the average of the historical application duration, T s Refers to the standard application duration, refers to the historical trend gradient, Refers to the utilization efficiency deviation coefficient.

[0101] In an embodiment of the present invention, the initial priority index is comprehensively adjusted based on the historical trend gradient and the use efficiency deviation coefficient, which can achieve dynamic optimization of the priority of the procurement task, thereby more accurately reflecting the actual needs of the task. The historical trend gradient reflects the changing trend in the procurement process, especially in the logistics link, and helps the system identify which tasks have large fluctuations or changes in the logistics cycle. If the logistics completion time of a task is gradually extended, its priority can be adjusted in time through the historical trend gradient to avoid the impact of logistics delays on the entire procurement process. The use efficiency deviation coefficient measures the application efficiency of the procurement task by comparing the actual application time of the goods with the preset standard application time, and then adjusts the priority to ensure the rational use of resources.

[0102] The advantage of this linkage between the two is that it can comprehensively consider factors from both logistics and practical applications, and dynamically optimize task priorities. The historical trend gradient focuses on the logistics timeliness of procurement tasks, and can monitor and respond to changes in the logistics cycle in real time to prevent tasks from missing critical time nodes due to logistics delays. At the same time, the use efficiency deviation coefficient compares the deviation between the actual usage time and the expected usage time to ensure that the priority is more in line with the actual needs of the task, rather than simply the time requirement. The combination of these two can not only optimize the priority of the task, but also make dynamic adjustments based on the actual execution of the task, making the procurement process more flexible and efficient.

[0103] Through such comprehensive adjustments, the system can find a more balanced priority allocation method between logistics fluctuations and actual application needs, thereby improving the efficiency and responsiveness of the entire procurement system. For example, when the logistics cycle of a task becomes longer, the system may automatically increase its priority, and when the actual application time is much lower than expected, the system can appropriately reduce the priority of the task to avoid waste of resources. This linkage adjustment mechanism can not only improve the timeliness of the procurement process, but also help to allocate resources more reasonably, ensure that tasks are executed as needed, and achieve the effect of optimizing procurement efficiency.

[0104] For example, the system first selects the completed historical procurement tasks of the same category as the target task from the historical procurement logs, and records the execution time and completion time of each task. By calculating the procurement completion time of each task (i.e., the time required from the start to the completion of the task), the system can evaluate the execution efficiency of the task.

[0105] Next, the system calculates the difference between the completion time of the historical procurement task and the preset completion time, and uses the ratio of these differences to the expected completion time as the historical trend gradient. This gradient reflects whether the task takes a long time to complete. Tasks with a larger historical trend gradient mean that the task completion time is longer than the estimated time, indicating that the task may have a longer delay or slower logistics distribution. A smaller historical trend gradient means that the task completion time is close to or lower than the estimated time, and the task execution is more efficient.

[0106] Secondly, based on the historical application logs, the system extracts the actual application time of historical tasks of the same category as the target procurement task. By counting the application time of these tasks, the system calculates the average actual application time of historical tasks and compares it with the preset standard application time. The deviation coefficient is calculated by the ratio of the difference between the two and the standard application time, reflecting the degree of deviation between the actual application time and the standard application time. If the actual application time is longer than the standard time, the deviation coefficient is large, which means that the goods are not put into use as soon as possible, which may affect the priority of the task.

[0107] Finally, the system dynamically adjusts the initial priority index based on the calculated historical trend gradient and the use benefit deviation coefficient. If the historical trend gradient is large, it means that the task takes a long time to complete, and the priority may be increased; if the deviation coefficient is large, it means that the actual application time of the goods deviates greatly from the standard, and the priority may be reduced. Through this comprehensive adjustment, the system can more accurately optimize the processing priority of tasks and improve the overall efficiency of the procurement process.

[0108] In summary, by dynamically optimizing the priority index of procurement tasks by combining the historical trend gradient and the use of the benefit deviation coefficient, this technical solution can more accurately evaluate the actual needs and potential delay risks of each task. The historical trend gradient reflects the difference between the time required to complete the task and the estimated time, thereby revealing possible delay trends; the use of the benefit deviation coefficient helps determine whether the goods can be put into use in a timely manner by comparing the actual application time with the standard application time. After combining these two factors, the system can dynamically adjust the priority according to the specific circumstances of the task, thereby achieving more efficient allocation of resources, reducing delays and waste in the procurement process, and improving overall work efficiency and response speed. In addition, this dynamic priority adjustment mechanism can cope with various complex procurement needs, ensure that various tasks are completed in a timely manner according to actual needs, and enhance the company's supply chain management capabilities and decision-making level.

[0109] In an embodiment of the present invention, further, Figure 5 The application architecture diagram of the system provided by the embodiment of the present invention is shown.

[0110] Among them, in another preferred embodiment provided by the present invention, an enterprise procurement service integrated management system includes:

[0111] The data acquisition module 100 is used to screen out all target procurement tasks that have not yet been approved by the auditor after receiving the planned review time point from the auditor of the target enterprise, determine the specific category and initial priority index of each target procurement task, and extract the historical procurement logs and historical application logs of the target enterprise within a preset time period.

[0112] In the embodiment of the present invention, the present invention is applied to the procurement task review and priority optimization scenario of the target enterprise, aiming to help the reviewer quickly and efficiently process multiple procurement tasks to be approved within a limited time, ensure the rationality of resource allocation and priority response to urgent needs. By intelligently adjusting the priority of procurement tasks, enterprises can effectively improve the efficiency of procurement approval, reduce processing time, and meet key needs in the shortest time.

[0113] The planned review time point of the target enterprise reviewer refers to the time point when the reviewer is scheduled to start processing the procurement task. This time point is received and recorded by the system to trigger the subsequent priority optimization process.

[0114] During the review process, the system will screen out all target procurement tasks that have not been approved by the reviewer and determine the specific category of each task. The screening process is achieved through task status identification. Unapproved tasks will be identified by the system and relevant information will be extracted. The specific category of the task (such as material type or departmental demand, etc.) is also the result of the system's classification based on task attributes, which is one of the key factors in priority assessment.

[0115] The initial priority index is generated by existing technology and assigned to each task according to pre-set rules. The rules may include parameters such as the urgency of the task, the order of submission time, and the priority of material categories. The initial priority index serves as the basic priority reference value for each procurement task and is used for subsequent optimization and adjustment.

[0116] The preset time period is set based on the target company's purchasing habits and data representativeness. Usually the most recent time period (such as the past three months or six months) is selected to ensure the timeliness and relevance of historical data. The selection of this time period helps reflect the company's current purchasing and usage patterns and provides relatively accurate data support.

[0117] The historical procurement log and historical application log are derived from the target company's procurement management system or resource usage record system. The procurement log records the execution time, completion time, task execution status and other information of various procurement tasks, helping auditors understand the historical processing of tasks. The application log records the consumption or usage cycle data of materials in actual use. This information is used to analyze the actual benefits of materials and optimize the priority of procurement tasks.

[0118] Through the above process, the present invention can realize intelligent review and dynamic adjustment of the priority of the target enterprise's procurement tasks, and significantly improve the enterprise's procurement efficiency and responsiveness.

[0119] Furthermore, the enterprise procurement service integrated management system also includes:

[0120] The historical trend gradient acquisition module 200 is used to filter out the specified historical procurement tasks that are of the same specific category as the target procurement task and have been completed from the historical procurement logs, obtain the procurement completion time of these specified historical procurement tasks, and draw a line graph of the procurement completion time based on the time sequence, calculate its change slope, and set the change slope as the historical trend gradient.

[0121] Specifically, Figure 6It shows a structural block diagram of the historical trend gradient acquisition module 200 in the system provided by the embodiment of the present invention.

[0122] Among them, in the preferred embodiment provided by the present invention, the historical trend gradient acquisition module 200 specifically includes:

[0123] The log interpretation unit 201 is used to retrieve the historical procurement logs and filter out the designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed;

[0124] The purchase completion time calculation unit 202 is used to parse each designated historical purchase task in turn, determine the execution time and completion time of the designated historical purchase task, and calculate the purchase completion time;

[0125] The change slope calculation unit 203 is used to set the completion time of the specified historical procurement task as the X-axis and the procurement completion time as the Y-axis, draw a line graph in chronological order, calculate its change slope, and define the change slope as the historical trend gradient.

[0126] In an embodiment of the present invention, the historical procurement log of the target enterprise is first retrieved. The system will filter out all completed procurement tasks from the log according to the specific category of the target procurement task (such as office supplies, daily necessities, equipment accessories, etc.). The key to the screening lies in two points: first, the category of the task needs to be consistent with the target procurement task, and second, the status of the task must be "completed". Through these two criteria, the system can filter out historical tasks that are of the same type as the current task and have been completed, so as to ensure the comparability and representativeness of the data.

[0127] The system analyzes each filtered historical procurement task in turn, extracting the task generation time and completion time. The system calculates the procurement completion time of each task, that is, "execution time minus completion time", and records the completion time of the task. These completion time data provide the basis for subsequent trend analysis.

[0128] The system uses the completion time of each task as the X-axis and the procurement completion time as the Y-axis to draw a line graph in chronological order. Through this line graph, the system can intuitively display the changing trend of task execution time. Next, the system calculates the slope of the line graph, which represents the rate of change of the time required to complete each task, that is, the increase in the procurement completion time per unit time. In order to ensure that the data is more stable and reliable, the system will denoise the data. Specifically, the system will identify and remove abnormal data that obviously deviates from the normal range to avoid the impact of these abnormal data on trend calculations. The denoising process can use statistical methods, such as calculating the standard deviation or using median filtering to remove data points with large deviations or abnormalities. Finally, the system calculates the slope in each period of time and obtains an average value as the historical trend gradient.

[0129] The significance of the historical trend gradient is that it can analyze the changes in the execution time of a specified historical procurement task and help determine whether the completion time of the task is gradually getting longer or shorter. If the value of the historical trend gradient is large, it means that the completion time of the task is gradually increasing. This may be due to external factors (such as delivery time, logistics delays, unstable supplier delivery time, etc.) that cause the task execution time to be extended. On the contrary, if the historical trend gradient is small, it means that the completion time of the task is gradually shortened. This may be due to the improvement of these external factors, more timely distribution, and more efficient delivery.

[0130] Based on this analysis, the system can dynamically adjust the priority of procurement tasks according to the historical trend gradient. For example, when the completion time of historical tasks gradually shortens, indicating that external conditions tend to improve and task execution is more efficient, the system can consider appropriately lowering the priority of the task; and when the completion time of historical tasks gradually lengthens, indicating that external conditions such as distribution may be unstable or delayed, the system can consider increasing the priority of the task to ensure that the procurement task is completed on time as much as possible.

[0131] Through this analysis, the historical trend gradient not only helps evaluate the execution efficiency of historical procurement tasks, but also provides a strong basis for the priority adjustment of current tasks.

[0132] Furthermore, the enterprise procurement service integrated management system also includes:

[0133] The application time calculation module 300 is used to extract the actual application time of goods for a specified historical procurement task based on the historical application log, and calculate the average actual application time of goods;

[0134] The deviation coefficient calculation module 400 is used to obtain a preset application time comparison table, obtain the standard application time corresponding to the specific category of the target procurement task, combine it with the average historical application time, and calculate the utilization efficiency deviation coefficient of the target procurement task.

[0135] Specifically, Figure 7 The structure block diagram of the deviation coefficient calculation module 400 in the system provided by the embodiment of the present invention is shown.

[0136] Among them, in the preferred implementation manner provided by the present invention, the deviation coefficient calculation module 400 specifically includes:

[0137] The standard application duration acquisition unit 401 is used to acquire a preset application duration comparison table and search it to acquire the standard application duration corresponding to a specific category of the target procurement task;

[0138] The use efficiency deviation coefficient calculation unit 402 is used to divide the difference between the average historical application time and the standard application time by the standard application time to calculate the use efficiency deviation coefficient of the target procurement task.

[0139] The preset application time comparison table is a reference data table used to record and set the expected application time of goods corresponding to different specific categories of procurement tasks under standard use conditions;

[0140] The preset application time comparison table is formulated based on historical data statistics, industry standards or internal enterprise experience. Each specific category of goods corresponds to a clear standard application time.

[0141] In an embodiment of the present invention, based on the historical application log, the system extracts the actual application time of the goods of the completed procurement tasks of the same category as the target procurement task from the historical records. These application times reflect the time required for the goods to be actually put into use and completed from the completion of procurement. By counting the actual application time of all historical procurement tasks of the same category as the target procurement task, the system can calculate the average actual application time of the goods for these tasks. The calculation method is to sum up the actual application time of all historical procurement tasks and divide it by the total number of tasks, so as to obtain the average application time of the category.

[0142] For example, for goods such as office supplies, the actual usage time can be estimated through employee usage logs or inventory management records. However, for certain categories of goods, such as food items, the actual usage time may be determined through video surveillance data. For example, some food purchases may be used within a certain period of time after being stored in the warehouse. Video surveillance can help track the opening, consumption or use of these items, and then deduce their actual usage time. This method not only improves the accuracy of the data, but also ensures more efficient tracking of usage time.

[0143] The preset application time comparison table is a reference data table used to record the expected application time of goods under standard use conditions for each procurement task category. This table is usually formulated based on historical data statistics, industry standards and internal experience of the enterprise. Historical data statistics come from the company's past procurement records, industry standards are set based on the industry's general usage, and internal experience sets the standard application time based on the company's operating practices and understanding of the use of items. These reference bases help companies formulate reasonable preset application times for different types of procurement tasks.

[0144] The difference between the average historical application time and the standard application time is divided by the standard application time to calculate the use efficiency deviation coefficient of the target procurement task. The purpose is to measure the degree of deviation between the target procurement task in actual application and the expected use time. Through this deviation coefficient, the enterprise can determine whether the use efficiency of certain goods is consistent with expectations. If the actual use time is longer, it may mean that the purchased goods do not meet expectations or the actual use efficiency is low. Conversely, it may indicate that the resource use efficiency is high. This deviation coefficient can help the system dynamically adjust the priority of procurement tasks, thereby optimizing resource allocation and procurement efficiency in future procurement decisions.

[0145] Furthermore, the enterprise procurement service integrated management system also includes:

[0146] The priority index adjustment module 500 is used to comprehensively adjust the initial priority index based on the historical trend gradient and the use benefit deviation coefficient to generate a dynamic priority index.

[0147] Specifically, Figure 8 It shows a structural block diagram of the priority index adjustment module 500 in the system provided by an embodiment of the present invention.

[0148] In a preferred embodiment of the present invention, the priority index adjustment module 500 specifically includes:

[0149] The dynamic priority index generating unit 501 is used to retrieve the priority index optimization calculation formula, and comprehensively adjust the initial priority index in combination with the historical trend gradient and the use benefit deviation coefficient to generate a dynamic priority index;

[0150] The priority index replacement unit 502 is used to replace the initial priority index of the target procurement task and update it to the corresponding dynamic priority index.

[0151] The priority index optimization calculation formula is:

[0152] Among them, I d Refers to the dynamic priority index, I orefers to the initial priority index, n refers to the total number of target procurement tasks, T yi and T yi-1 They represent the procurement completion time of the i-th and i-1-th target procurement tasks, T xi and T xi-1 Respectively represent the completion time of the i-th and i-1-th target procurement tasks, T a Refers to the average of the historical application duration, T s Refers to the standard application duration, refers to the historical trend gradient, Refers to the utilization efficiency deviation coefficient.

[0153] In an embodiment of the present invention, the initial priority index is comprehensively adjusted based on the historical trend gradient and the use efficiency deviation coefficient, which can achieve dynamic optimization of the priority of the procurement task, thereby more accurately reflecting the actual needs of the task. The historical trend gradient reflects the changing trend in the procurement process, especially in the logistics link, and helps the system identify which tasks have large fluctuations or changes in the logistics cycle. If the logistics completion time of a task is gradually extended, its priority can be adjusted in time through the historical trend gradient to avoid the impact of logistics delays on the entire procurement process. The use efficiency deviation coefficient measures the application efficiency of the procurement task by comparing the actual application time of the goods with the preset standard application time, and then adjusts the priority to ensure the rational use of resources.

[0154] The advantage of this linkage between the two is that it can comprehensively consider factors from both logistics and practical applications, and dynamically optimize task priorities. The historical trend gradient focuses on the logistics timeliness of procurement tasks, and can monitor and respond to changes in the logistics cycle in real time to prevent tasks from missing critical time nodes due to logistics delays. At the same time, the use efficiency deviation coefficient compares the deviation between the actual usage time and the expected usage time to ensure that the priority is more in line with the actual needs of the task, rather than simply the time requirement. The combination of these two can not only optimize the priority of the task, but also make dynamic adjustments based on the actual execution of the task, making the procurement process more flexible and efficient.

[0155] Through such comprehensive adjustments, the system can find a more balanced priority allocation method between logistics fluctuations and actual application needs, thereby improving the efficiency and responsiveness of the entire procurement system. For example, when the logistics cycle of a task becomes longer, the system may automatically increase its priority, and when the actual application time is much lower than expected, the system can appropriately reduce the priority of the task to avoid waste of resources. This linkage adjustment mechanism can not only improve the timeliness of the procurement process, but also help to allocate resources more reasonably, ensure that tasks are executed as needed, and achieve the effect of optimizing procurement efficiency.

[0156] For example, the system first selects the completed historical procurement tasks of the same category as the target task from the historical procurement logs, and records the execution time and completion time of each task. By calculating the procurement completion time of each task (i.e., the time required from the start to the completion of the task), the system can evaluate the execution efficiency of the task.

[0157] Next, the system calculates the difference between the completion time of the historical procurement task and the preset completion time, and uses the ratio of these differences to the expected completion time as the historical trend gradient. This gradient reflects whether the task takes a long time to complete. Tasks with a larger historical trend gradient mean that the task completion time is longer than the estimated time, indicating that the task may have a longer delay or slower logistics distribution. A smaller historical trend gradient means that the task completion time is close to or lower than the estimated time, and the task execution is more efficient.

[0158] Secondly, based on the historical application logs, the system extracts the actual application time of historical tasks of the same category as the target procurement task. By counting the application time of these tasks, the system calculates the average actual application time of historical tasks and compares it with the preset standard application time. The deviation coefficient is calculated by the ratio of the difference between the two and the standard application time, reflecting the degree of deviation between the actual application time and the standard application time. If the actual application time is longer than the standard time, the deviation coefficient is large, which means that the goods are not put into use as soon as possible, which may affect the priority of the task.

[0159] Finally, the system dynamically adjusts the initial priority index based on the calculated historical trend gradient and the use benefit deviation coefficient. If the historical trend gradient is large, it means that the task takes a long time to complete, and the priority may be increased; if the deviation coefficient is large, it means that the actual application time of the goods deviates greatly from the standard, and the priority may be reduced. Through this comprehensive adjustment, the system can more accurately optimize the processing priority of tasks and improve the overall efficiency of the procurement process.

[0160] In summary, by dynamically optimizing the priority index of procurement tasks by combining the historical trend gradient and the use of the benefit deviation coefficient, this technical solution can more accurately evaluate the actual needs and potential delay risks of each task. The historical trend gradient reflects the difference between the time required to complete the task and the estimated time, thereby revealing possible delay trends; the use of the benefit deviation coefficient helps determine whether the goods can be put into use in a timely manner by comparing the actual application time with the standard application time. After combining these two factors, the system can dynamically adjust the priority according to the specific circumstances of the task, thereby achieving more efficient allocation of resources, reducing delays and waste in the procurement process, and improving overall work efficiency and response speed. In addition, this dynamic priority adjustment mechanism can cope with various complex procurement needs, ensure that various tasks are completed in a timely manner according to actual needs, and enhance the company's supply chain management capabilities and decision-making level.

[0161] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0162] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0163] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0164] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An integrated management method for enterprise procurement services, characterized in that: The method comprises: After receiving the planned review time point from the target enterprise auditor, all target procurement tasks that have not been approved by the auditor are screened out, the specific category and initial priority index of each target procurement task are determined, and the historical procurement logs and historical application logs of the target enterprise within the preset time period are extracted; Filter out the designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed from the historical procurement logs, obtain the procurement completion time of these designated historical procurement tasks, draw a line chart of the procurement completion time based on the time sequence, calculate its change slope, and set the change slope as the historical trend gradient; Based on the historical application log, extract the actual application time of the goods for the specified historical procurement tasks, and calculate the average actual application time of the goods; Obtain a preset application duration comparison table, obtain the standard application duration corresponding to the specific category of the target procurement task, combine it with the average historical application duration, and calculate the use benefit deviation coefficient of the target procurement task; Based on the historical trend gradient and the utilization benefit deviation coefficient, the initial priority index is comprehensively adjusted to generate a dynamic priority index.

2. The enterprise procurement service integrated management method according to claim 1 is characterized in that: The steps of selecting the designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed from the historical procurement log, obtaining the procurement completion time of these designated historical procurement tasks, drawing a line graph of the procurement completion time based on the time sequence, calculating its change slope, and setting the change slope as the historical trend gradient include: Retrieve historical procurement logs and select the designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed; Parse each specified historical procurement task in turn, determine the execution time and completion time of the specified historical procurement task, and calculate the procurement completion time; Set the completion time of the specified historical procurement task as the X-axis, and the procurement completion time as the Y-axis, draw a line graph in chronological order, calculate its change slope, and define the change slope as the historical trend gradient.

3. The enterprise procurement service integrated management method according to claim 1 is characterized in that: The preset application time comparison table is a reference data table used to record and set the expected application time of goods corresponding to different specific categories of procurement tasks under standard use conditions; The preset application time comparison table is formulated based on historical data statistics, industry standards or internal enterprise experience. Each specific category of goods corresponds to a clear standard application time.

4. The enterprise procurement service integrated management method according to claim 3 is characterized in that: The steps of obtaining a preset application duration comparison table, obtaining the standard application duration corresponding to the specific category of the target procurement task, combining it with the average historical application duration, and calculating the use benefit deviation coefficient of the target procurement task include: Obtain a preset application duration comparison table and search it to obtain the standard application duration corresponding to the specific category of the target procurement task; Divide the difference between the average historical application time and the standard application time by the standard application time to calculate the utilization efficiency deviation coefficient of the target procurement task.

5. The enterprise procurement service integrated management method according to claim 3 is characterized in that: Based on the historical trend gradient and the use benefit deviation coefficient, the initial priority index is comprehensively adjusted to generate a dynamic priority index, including the following steps: Retrieve the priority index optimization calculation formula, and make comprehensive adjustments to the initial priority index in combination with the historical trend gradient and the use benefit deviation coefficient to generate a dynamic priority index; Replace the initial priority index of the target procurement task and update it to the corresponding dynamic priority index.

6. The enterprise procurement service integrated management method according to claim 5 is characterized in that: The priority index optimization calculation formula is: Among them, I d Refers to the dynamic priority index, I o refers to the initial priority index, n refers to the total number of target procurement tasks, T yi and T yi-1 They represent the procurement completion time of the i-th and i-1-th target procurement tasks, T xi and T xi-1 Respectively represent the completion time of the i-th and i-1-th target procurement tasks, T a Refers to the average of the historical application duration, T s Refers to the standard application duration, refers to the historical trend gradient, Refers to the utilization efficiency deviation coefficient.

7. An integrated enterprise procurement service management system, characterized in that: The system includes: a data acquisition module, a historical trend gradient acquisition module, an application duration calculation module, a deviation coefficient calculation module and a priority index adjustment module, wherein: The data acquisition module is used to screen out all target procurement tasks that have not been approved by the auditor after receiving the planned review time point of the target enterprise auditor, determine the specific category and initial priority index of each target procurement task, and extract the historical procurement log and historical application log of the target enterprise within a preset time period; The historical trend gradient acquisition module is used to filter out the specified historical procurement tasks that are of the same specific category as the target procurement task and have been completed from the historical procurement logs, obtain the procurement completion time of these specified historical procurement tasks, and draw a line chart of the procurement completion time based on the time sequence, calculate its change slope, and set the change slope as the historical trend gradient; The application time calculation module is used to extract the actual application time of goods for a specified historical procurement task based on historical application logs, and calculate the average actual application time of goods; The deviation coefficient calculation module is used to obtain a preset application time comparison table, obtain the standard application time corresponding to the specific category of the target procurement task, combine it with the average historical application time, and calculate the use benefit deviation coefficient of the target procurement task; The preset application time comparison table is a reference data table used to record and set the expected application time of goods corresponding to different specific categories of procurement tasks under standard use conditions; The preset application time comparison table is formulated based on historical data statistics, industry standards or internal enterprise experience. Each specific category of goods corresponds to a clear standard application time; The priority index adjustment module is used to make comprehensive adjustments to the initial priority index based on the historical trend gradient and the use benefit deviation coefficient to generate a dynamic priority index.

8. The enterprise procurement service integrated management system according to claim 7 is characterized in that: The historical trend gradient acquisition module specifically includes: A log interpretation unit is used to retrieve historical procurement logs and filter out designated historical procurement tasks that are of the same specific category as the target procurement task and have been completed; A procurement completion time calculation unit is used to parse each designated historical procurement task in turn, determine the execution time and completion time of the designated historical procurement task, and calculate the procurement completion time; The change slope calculation unit is used to set the completion time of the specified historical procurement task as the X-axis and the procurement completion time as the Y-axis, draw a line graph in chronological order, calculate its change slope, and define the change slope as the historical trend gradient.

9. The enterprise procurement service integrated management system according to claim 8, characterized in that: The deviation coefficient calculation module specifically includes: A standard application duration acquisition unit is used to acquire a preset application duration comparison table and search it to acquire the standard application duration corresponding to a specific category of the target procurement task; The use efficiency deviation coefficient calculation unit is used to divide the difference between the average historical application time and the standard application time by the standard application time to calculate the use efficiency deviation coefficient of the target procurement task.

10. The enterprise procurement service integrated management system according to claim 9, characterized in that: The priority index adjustment module specifically includes: A dynamic priority index generation unit is used to retrieve the priority index optimization calculation formula, and comprehensively adjust the initial priority index in combination with the historical trend gradient and the use benefit deviation coefficient to generate a dynamic priority index; A priority index replacement unit, used to replace the initial priority index of the target procurement task and update it to a corresponding dynamic priority index; The priority index optimization calculation formula is: Among them, I d Refers to the dynamic priority index, I o refers to the initial priority index, n refers to the total number of target procurement tasks, T yi and T yi-1 They represent the procurement completion time of the i-th and i-1-th target procurement tasks, T xi and T xi-1 Respectively represent the completion time of the i-th and i-1-th target procurement tasks, T a Refers to the average of the historical application duration, T s Refers to the standard application duration, refers to the historical trend gradient, Refers to the utilization efficiency deviation coefficient.

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