Panoramic digital operation management system and method for enterprise operation management

Abstract

The invention discloses a panoramic digital operation management system and method for enterprise operation management, and particularly relates to the technical field of operation management, and the system comprises a database module, an enterprise operation data collection module, a market response module, a strategic decision module, an execution module, an execution monitoring module, and a continuous optimization module. According to the invention, by collecting enterprise operation data, calculating market demand indexes and matching market demand commands, accurate market dynamic information is provided for enterprises; a decision scheme is made based on the market demand command, and a decision execution effect is tracked through an execution monitoring module, a risk index is calculated, and potential problems in operation are identified; according to the risk level, the continuous optimization module automatically generates an intelligent optimization scheme through a machine learning algorithm, and feeds back the intelligent optimization scheme to the decision module to promote continuous optimization of the decision; according to the method, the intelligence and refinement level of enterprise operation is improved, and the problems of response lag, low efficiency, inaccurate decision and the like in the prior art are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of operation management, more particularly, the present application relates to a panoramic digital operation management system and method for enterprise operation management. BACKGROUND

[0002] Existing enterprise operation management systems face multiple challenges. First, in terms of data collection, many systems still rely on manual entry or periodic reports, which makes data updates not timely enough to reflect market and operational dynamics in real time. This lag leads to a lack of timely and accurate information for decision-making, affecting market response speed and decision-making timeliness. Secondly, traditional decision support systems are often based on historical data and static models, lacking dynamic analysis and prediction capabilities for real-time data, and unable to automatically adjust decision-making schemes according to changes in market demand and operational conditions, resulting in low adaptability and accuracy of decision-making schemes. Thirdly, decision monitoring mostly relies on manual intervention or periodic audits, unable to track the implementation of decision-making schemes in real time and accurately. This makes it easy for enterprises to overlook potential operational problems and bottlenecks during the execution process, delaying the discovery and adjustment of problems. In addition, existing risk assessment mechanisms are usually limited to post-analysis, unable to predict and assess potential risks through real-time monitoring, lacking intelligent early warning and feedback capabilities.

[0003] Overall, traditional systems have significant shortcomings in handling big data, real-time feedback, and intelligent decision support, which seriously affect the operational efficiency, decision-making accuracy, and response capabilities to unexpected situations of enterprises. SUMMARY

[0004] In order to overcome the above-mentioned defects of the prior art, the present application provides a panoramic digital operation management system and method for enterprise operation management, which solves the problems raised in the background art through the following scheme.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical scheme: a panoramic digital operation management system for enterprise operation management, comprising: a database module including enterprise data, market output commands, and risk levels; The enterprise data stores data in the enterprise operation process; An enterprise operation data collection module for collecting enterprise operation data and transmitting operation data to a market response module; A market response module based on operation data to calculate the order growth index per unit time and the conversion index per unit time, and calculate the market demand index according to the order growth index per unit time and the conversion index per unit time, match the market output command according to the real-time market demand index, and output the market output command to a strategic decision-making module; Strategy decision module: based on the market output command, make decision scheme and set the expected order number growth index and expected conversion index, and send to the execution module; Execution module: receive the decision scheme output by the strategy decision module, and convert it into executable operation tasks; Execution monitoring module: real-time monitoring of the implementation of the decision scheme, analyzing the operation data changes in the execution process and calculating the risk index, matching the risk level according to the risk index, and transmitting the risk level to the continuous optimization module; Continuous optimization module: based on the operation risk level provided by the execution monitoring module, using machine learning algorithm to generate intelligent optimization scheme, and transmitting the intelligent optimization scheme back to the strategy decision module; Preferably, the panoramic digital operation management method for enterprise operation management comprises: S1: collecting the operation data of the enterprise; S2: calculating the order number growth index per unit time and the conversion index per unit time, and calculating the market demand index according to the order number growth index per unit time and the conversion index per unit time; S3: matching the market output command according to the real-time market demand index, and outputting the market output command to the strategy decision module; S4: based on the market output command, making a decision scheme, and setting the expected order number growth index and the expected conversion index, and sending the decision scheme to the execution module; S5: receiving the decision scheme output by the strategy decision module, and converting it into executable operation tasks; S6: real-time monitoring of the implementation of the decision scheme, analyzing the operation data changes in the execution process and calculating the risk index, matching the risk level according to the risk index, and transmitting the risk level to the continuous optimization module; S7: based on the operation risk level, using machine learning algorithm to generate intelligent optimization scheme, and transmitting the intelligent optimization scheme back to the strategy decision module.

[0006] The technical effects and advantages of the present application are as follows: 1. The enterprise operation data acquisition module of the present application can obtain the order number per unit time, the effective consultation quantity per unit time and the number of customers reaching the intention per unit time in real time, and provide timely and accurate information for subsequent analysis and decision making. Through the system, the enterprise can avoid the problem of data lag in traditional systems, ensure the timeliness and accuracy of the decision basis, and improve the operation efficiency and market response ability. 2、The present application calculates market demand indicators based on real-time collected data through the market response module, and eliminates differences between different data dimensions through standardization processing, enabling enterprises to dynamically respond to market changes. This data-driven analysis method can accurately reflect real-time market demand, avoiding decision-making errors caused by static models and historical data analysis in traditional systems, and improving decision-making accuracy; 3、The present application automatically formulates and adjusts decision-making schemes in combination with market demand indicators through the strategic decision-making module, avoiding human intervention and static models in traditional decision-making processes. The system can quickly respond to market changes, flexibly adjust enterprise strategies, improve decision-making flexibility and real-time performance, and ensure that enterprises maintain competitiveness in a changing market environment; 4、The present application tracks the execution of decision-making schemes in real time through the execution monitoring module, analyzes changes in operational data, and calculates risk indicators. The system can identify potential problems and operational bottlenecks in a timely manner, provide early warning and adjust strategies, avoid losses caused by delayed problem discovery, and improve enterprise risk management capabilities; 5、The present application generates optimization schemes automatically based on operational risk levels provided by the execution monitoring module through the continuous optimization module. The system can continuously learn and adapt to changes in operations, optimize the decision-making process, and continuously improve the accuracy and efficiency of enterprise operations, enabling enterprises to achieve long-term stable development. BRIEF DESCRIPTION OF DRAWINGS

[0007] Figure 1 The system architecture of the present application is shown in the figure; Figure 2 The flowchart of the present application for obtaining market output commands is shown in the figure; Figure 3 The basic flowchart of the present application is shown in the figure. DETAILED DESCRIPTION

[0008] The technical solutions in the embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0009] Referring to Figure 1 and Figure 2 The panoramic digital operation management system for enterprise operation management shown in the figure comprises: Database module: including enterprise data, market output commands and risk levels.

[0010] The enterprise data is used for storing data in the process of enterprise operation; the market output command is intelligently matched and output according to the change of market demand index; and the risk level is automatically matched and determined according to the real-time calculated risk index.

[0011] The enterprise operation data collection module is used for collecting the operation data of the enterprise and transmitting the operation data to the market response module.

[0012] The operation data specifically includes the number of transaction orders per unit time, the number of intention clients reached per unit time and the effective consultation amount per unit time.

[0013] It is further explained that the reason for collecting the number of transaction orders per unit time, the number of intention clients reached per unit time and the effective consultation amount per unit time is that the number of transaction orders is a key index for measuring the business performance of the enterprise, which reflects the final conversion result of market demand and is the core source of revenue; the number of intention clients reached is the conversion result of the effective consultation amount, which reflects the conversion efficiency from "consultation understanding" to "clear purchase intention" of the user and directly reflects the depth of market demand; and the effective consultation amount is basic data for measuring market attraction and user attention, which reflects the active exploration intention of the user to the products or services of the enterprise per unit time and is the initial signal of market demand.

[0014] The market response module is used for calculating the transaction order number growth index per unit time and the conversion index per unit time based on the operation data, calculating the market demand index according to the transaction order number growth index per unit time and the conversion index per unit time, matching the market output command according to the real-time market demand index and outputting the market output command to the strategic decision module.

[0015] The calculation method of the transaction order number growth index per unit time and the conversion index per unit time includes that the transaction order number growth index per unit time G is calculated as follows: G is the transaction order number growth index per unit time, wherein is the transaction order number of the current time period, is the transaction order number of the previous time period; and the conversion index per unit time C is calculated as follows: C is the conversion index per unit time, O is the number of intention clients reached per unit time and V is the effective consultation amount per unit time.

[0016] The calculation method of the market demand index includes that first, the transaction order number growth index per unit time and the conversion index per unit time are combined into a two-dimensional vector , and this vector represents the two-dimensional state of market demand in a specific time period.

[0017] Subsequently, the order number growth index per unit time and the conversion index per unit time are standardized, specifically including: standardization of the order number growth index per unit time wherein is the standardized value of the order number growth index per unit time, is the historical mean of the order number growth index per unit time, is the historical standard deviation of the order number growth index per unit time; standardization of the conversion index per unit time wherein is the standardized value of the conversion index per unit time, is the historical mean of the conversion index per unit time, is the historical standard deviation of the conversion index per unit time; It needs to be further explained that wherein, is the original index value at the i-th time point, and n is the sample size of the historical index data, is the historical mean of the index; wherein, is the historical standard deviation of the index.

[0018] Then, according to the standardization of the order number growth index per unit time and the standardization of the conversion index per unit time the market demand index is further calculated, specifically including: calculating the market demand index D by the Euclidean distance formula wherein, D is the market demand index.

[0019] Finally, according to the real-time market demand index, the market output command is matched, specifically including: when D is less than 1, the market output command is "normal"; when D is greater than or equal to 1 and less than 3, the market output command is "significant"; when D is greater than or equal to 3, the market output command is "extreme", and then the market output command is sent to the strategic decision module.

[0020] It needs to be further explained that: the threshold values 1 and 3 are set according to the following basis: the threshold value 1 is the 30th percentile value of the industry average market demand index, and the threshold value 3 is the 90th percentile value of the industry average market demand index. The threshold values are updated once a year according to the industry annual report.

[0021] Strategic decision module: based on the market output command, a decision scheme is made and sent to the execution module; When the market output command is "normal", it means that the market demand fluctuation is within the normal range, the market state has not changed significantly, and the operation state is stable. The specific decision-making scheme includes maintaining the existing operation strategy and market positioning, following the established plan, and continuously monitoring market dynamics and operation data to ensure stability.

[0022] When the market output command is "significant", it means that the market demand has a significant upward trend, and the specific strategy scheme includes increasing production capacity or inventory level to meet the growing market demand, strengthening market promotion and brand promotion, and further expanding market share. greater than 0, greater than 0, which means that the market demand has a significant upward trend, and the specific strategy scheme includes increasing production capacity or inventory level to meet the growing market demand, strengthening market promotion and brand promotion, and further expanding market share. greater than 0, less than 0, which means that the market attractiveness has improved, but the consumer purchase intention has weakened, and the strategy scheme includes optimizing website design, improving product recommendation accuracy, improving customer experience, and improving conversion rate to ensure that traffic can be converted into sales. less than 0, greater than 0, which means that the market demand is weak, but the potential user purchase intention is strong, and the strategy scheme includes strengthening customer maintenance and segmentation, conducting more refined marketing for existing users, accurately targeting advertising and promotion, and further improving conversion efficiency. less than 0, less than 0, which means that the market demand has decreased in the short term or the influence of competitors has caused customer loss, and the strategy scheme includes strengthening brand image, improving product quality, and other measures to regain customer attention, adjusting price strategy and promotion activities according to market demand changes, and improving market competitiveness.

[0023] When the market output command is "extreme", it means that the market demand has a significant upward trend or the market has a short-term surge due to successful promotion activities, and the specific strategy scheme includes rapidly expanding production and logistics capacity to meet the market demand surge, ensuring the stability and efficiency of the supply chain, increasing marketing investment, optimizing product promotion, further consolidating market position, and maintaining growth momentum. greater than 0, greater than 0, which means that the market demand has a significant upward trend or the market has a short-term surge due to successful promotion activities, and the specific strategy scheme includes rapidly expanding production and logistics capacity to meet the market demand surge, ensuring the stability and efficiency of the supply chain, increasing marketing investment, optimizing product promotion, further consolidating market position, and maintaining growth momentum. greater than 0, less than 0, which means that the market attractiveness has improved, but the user's purchase conversion has been inhibited by some factors, and the strategy scheme includes improving customer experience, optimizing products and services, improving conversion effect, and adjusting pricing reasonably to avoid excessive price fluctuations causing market rebound. less than 0, When greater than 0, the market demand drops sharply, but the enterprise can effectively attract high-intention customers in the remaining traffic. The strategy includes: quickly adjusting product pricing and promotion strategies, reactivating market demand, focusing on existing core customer groups, and improving customer loyalty through customized services; when less than 0, less than 0, the number of completed orders and conversion rates drop sharply, and market demand shrinks sharply. The strategy includes: adjusting business strategy, reducing losses, managing inventory and financial chain, reducing financial pressure due to demand shrinkage, finding new business opportunities, and expanding new market areas.

[0024] For the market output command, the system will synchronize the expected completed order growth index and the expected conversion index and send it to the execution module.

[0025] Execution module: receives the decision scheme output by the strategic decision module and converts it into executable operation tasks.

[0026] When the market output command is "normal", the execution module's specific operations for the decision scheme at this time include: maintaining existing strategies, following the established plan, and performing routine periodic tasks in each department, with resources allocated according to historical norms.

[0027] When the market output command is "significant", the execution module's specific operations for the decision scheme at this time include: when greater than 0, greater than 0, the production department formulates a production plan, the procurement department stocks up raw materials, the warehouse department expands its capacity, and the marketing department formulates a promotion plan; when greater than 0, less than 0, the technology department optimizes the website's key pages, and the data department optimizes the recommendation algorithm; the customer service department sorts out high-frequency question templates, and the operation department synchronously collects visitor experience feedback; when less than 0, greater than 0, the operation department completes customer segmentation (high / medium / low value), high-value customers are assigned dedicated customer service, the marketing department targets users with a historical conversion rate of ≥30% for targeted promotion, and allocates exclusive discount resources; when less than 0, less than 0, the marketing department completes competitor price research, the finance department approves core product price reductions, and the operation department launches promotional activities.

[0028] When the market output command is "extreme", the execution module's specific operations for the decision scheme at this time include: when greater than 0, When greater than 0, the production department activates the standby production line, the logistics department interfaces with temporary transport capacity, the procurement department starts the emergency mechanism, increases raw material inventory, the marketing department adds budget, and synchronizes inventory dynamics; when greater than 0, the data department locates the conversion loss link (such as the payment page), the technical department optimizes the payment steps; the operation department launches preferential activities, and the customer service department opens a response hotline; when less than 0, the operation department screens high-intention users, and targetedly issues exclusive discount coupons; the sales department one-on-one pushes customized solutions; when less than 0, the sales department starts to clear up unsold goods, the financial department monitors the fund chain, suspends non-core investment, the marketing department completes new area research, and the management layer evaluates focusing on other core products.

[0029] The execution monitoring module: real-time monitoring of the implementation of the decision scheme, analyzing the operation data changes in the execution process and calculating the risk index, matching the risk level according to the risk index, and transmitting the risk level to the continuous optimization module.

[0030] The specific analysis method of the risk index includes: first, based on the implementation of the decision scheme, obtaining the actual order number growth index in the current unit time and the actual conversion index in the current unit time , then calculating the order number growth index deviation value and the conversion index deviation value .

[0031] It needs to be further explained that the specific analysis method of the order number growth index deviation value includes: ; the specific analysis method of the conversion index deviation value includes: .

[0032] Then, based on the order number growth index deviation value and the conversion index deviation value , the specific analysis method includes using the Euclidean distance to calculate the risk index .

[0033] Finally, based on the risk index matching the corresponding risk level, specifically including: when less than , the risk level is "low risk"; when greater than or equal to and less than , the risk level is "medium risk"; when greater than or equal to When the risk level is "high risk".

[0034] It should be further explained that: And The acquisition method specifically includes: The 90% quantile value of the historical risk index, The 99% quantile value of the historical risk index, and the threshold can be dynamically calibrated according to the enterprise quarterly operation target deviation rate (±5%).

[0035] Continuous optimization module: based on the operation risk level provided by the execution monitoring module, an intelligent optimization scheme is generated using a machine learning algorithm, and the intelligent optimization scheme is returned to the strategic decision module.

[0036] The machine learning algorithm refers to a gradient boosting decision tree algorithm.

[0037] It should be further explained that: an intelligent optimization model is constructed based on the gradient boosting decision tree algorithm, which automatically generates optimization strategy schemes for different risk levels under the operation state, and the model takes the transaction order growth index deviation value, the conversion index deviation value and the risk index calculated from the two as training characteristic variables, and establishes a mapping mechanism from risk input to optimization scheme output.

[0038] It should be further explained that: the training data of the gradient boosting decision tree algorithm is the operation data of the past 12 months, including input features (risk level, market output command, transaction order growth index deviation, conversion index deviation) and output labels (adjustment amplitude of optimization strategy); Algorithm parameters: tree depth 5, learning rate 0.1, iteration number 100, and loss function is mean square error; The model is retrained once every quarter with new data to ensure adaptability.

[0039] It needs to be further explained that: for the case of "low risk" level, it indicates that the overall fluctuation of the current operation state is not large, and the deviation is within the acceptable range. In such scenarios, the model outputs the optimal light intervention optimization strategy, which includes but is not limited to: maintaining the original operation rhythm, coordinating small-scale optimization of price strategy, member pushing mechanism or traffic entrance distribution, and enhancing operation stability; When the risk level is "medium risk", it indicates that the current transaction order number and conversion level has shown a certain degree of incoordination or downward trend, and urgent adjustment intervention is needed. At this time, the model will generate a moderate adjustment optimization strategy, which includes but is not limited to: optimizing user conversion links on the key path, adjusting the pricing structure of key products, carrying out stage preferential activities and improving traffic targeting efficiency to enhance conversion rate and drive sales recovery; When the risk level is "high risk", it means that the transaction order number and conversion indicators have deviated by a large margin, and the enterprise operation is in an obviously abnormal state. At this time, the model outputs a strong intervention optimization strategy, which includes but is not limited to: quickly adjusting product supply plan, concentrating resources for high-value customer retention, carrying out deep discount and combination marketing, dynamically adjusting promotion rhythm and advertising budget allocation, and even suggesting to suspend part of the operation plate to reduce loss, to ensure that the enterprise has enough response flexibility during the risk outbreak period.

[0040] Finally, the optimization strategy is transmitted back to the strategic decision module.

[0041] Reference Figure 3 , a panoramic digital operation management method for enterprise operation management, comprising: S1: collecting enterprise operation data; S2: calculating the transaction order number growth index per unit time and the conversion index per unit time, and calculating the market demand index according to the transaction order number growth index per unit time and the conversion index per unit time; S3: matching market output commands according to real-time market demand index, and outputting market output commands to the strategic decision module; S4: based on the market output command, formulating a decision scheme, setting an expected transaction order number growth index and an expected conversion index, and sending the decision scheme to the execution module; S5: receiving the decision scheme output by the strategic decision module and converting it into executable operation tasks; S6: real-time monitoring of the implementation of the decision scheme, analyzing the changes of operation data in the execution process and calculating the risk index, matching the risk level according to the risk index, and transmitting the risk level to the continuous optimization module; S7: based on the operation risk level, using machine learning algorithm to generate intelligent optimization scheme, and transmitting the intelligent optimization scheme back to the strategic decision module.

[0042] The present application collects enterprise operation data, specifically including the number of orders per unit time, the number of customers who reach an agreement and the effective consultation volume; based on the above data, the order growth index and the conversion index per unit time are calculated, and the market demand index is calculated by the Euclidean distance formula after standardizing the two; according to the market demand index, the market output command is matched and output to the strategic decision module; the strategic decision module formulates a decision scheme based on the market output command, maintains the existing strategy in the "normal" state, and adopts the corresponding strategy according to the positive and negative combination of the standardized values of the order growth index and the conversion index in the "significant" and "extreme" states, while setting the expected order growth index and conversion index; the execution module receives the decision scheme, converts it into executable tasks, specifies the responsible department and allocates resources; the execution monitoring module monitors the implementation of the decision in real time, calculates the order growth index deviation and the conversion index deviation, obtains the risk index through the Euclidean distance, matches the low, medium and high risk levels according to the dynamically adjusted threshold and transmits to the continuous optimization module; the continuous optimization module generates an intelligent optimization scheme based on the risk level using the gradient boosting decision tree algorithm and feeds back to the strategic decision module.

[0043] Secondly: the drawings of the disclosed embodiments of the present application only involve the structures involved in the disclosed embodiments of the present application, other structures can refer to the usual design, and in the case of no conflict, the same embodiment and different embodiments of the present application can be combined with each other; Finally: the above only describes the preferred embodiments of the present application and is not used to limit the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A panoramic digital operations management system for enterprise operations management, characterized by, The application relates to a market response system for enterprises, which comprises the following modules: a database module, which comprises enterprise data, market output commands and risk levels; the enterprise data stores data in the process of enterprise operation; an enterprise operation data collection module, which is used for collecting enterprise operation data and transmitting the operation data to a market response module; the market response module calculates a transaction order quantity growth index per unit time and a conversion index per unit time based on the operation data, calculates a market demand index according to the transaction order quantity growth index per unit time and the conversion index per unit time, matches market output commands according to the real-time market demand index, and outputs the market output commands to a strategic decision module; the strategic decision module formulates a decision scheme based on the market output commands, sets an expected transaction order quantity growth index and an expected conversion index, and sends the indexes to an execution module; the execution module receives the decision scheme output by the strategic decision module and converts the decision scheme into executable operation tasks; an execution monitoring module, which monitors the implementation of the decision scheme in real time, analyzes the operation data changes in the execution process and calculates a risk index, matches a risk level according to the risk index, and transmits the risk level to a continuous optimization module; the continuous optimization module generates an intelligent optimization scheme based on the operation risk level provided by the execution monitoring module, and transmits the intelligent optimization scheme back to the strategic decision module.

2. The panoramic digital operations management system for enterprise operations management of claim 1, wherein, The operation data required by the enterprise operation data collection module specifically comprises the following: the transaction order quantity per unit time, the number of customers reaching an intention per unit time and the effective consultation quantity per unit time.

3. The panoramic digital operations management system for enterprise operations management of claim 1, wherein, The transaction order quantity growth index per unit time in the market response module is calculated in the following manner: first, the difference between the transaction order quantity in the current time period and the transaction order quantity in the previous time period is calculated, then the difference is divided by the transaction order quantity in the previous time period, and finally the transaction order quantity growth index is obtained; the conversion index per unit time is calculated in the following manner: the number of customers reaching an intention per unit time is divided by the effective consultation quantity per unit time, and the conversion index per unit time is obtained.

4. The panoramic digital operations management system for enterprise operations management of claim 1, wherein, The market demand index is calculated in the following manner: a index vector is set, then the transaction order quantity growth index per unit time and the conversion index per unit time are standardized, then the market demand index is calculated based on the standardized indexes, and finally the market output commands are matched according to the real-time market demand index, and the market output commands are output to the strategic decision module.

5. The panoramic digital operations management system for enterprise operations management of claim 1, wherein, The strategic decision module formulates a corresponding decision scheme based on the market output commands, sets an expected transaction order quantity growth index and an expected conversion index, and sends the indexes to the execution module.

6. The panoramic digital operations management system for enterprise operations management of claim 1, wherein, The execution module disassembles the decision scheme into specific subtasks and clearly defines the corresponding responsible departments, and then allocates resources according to the subtask requirements.

7. The panoramic digital operations management system for enterprise operations management of claim 1, wherein, The risk index in the execution monitoring module is calculated in the following manner: first, the transaction order quantity growth index deviation and the conversion index deviation are calculated, then the Euclidean distance is used to represent and calculate the risk index.

8. The panoramic digital operations management system for enterprise operations management of claim 7, wherein, The specific calculation method of the order growth index deviation comprises: calculating the difference between the actual order number and the expected order number in a unit time, and dividing the difference by the expected order number to obtain the order growth index deviation. The calculation method of the conversion index deviation comprises: calculating the difference between the actual conversion index and the expected conversion index in a unit time, and dividing the difference by the expected conversion index to obtain the conversion index deviation. The specific calculation method of the risk index comprises: calculating the square root of the sum of squares of the order growth index deviation and the conversion index deviation to obtain the risk index, and finally matching the risk level in the database according to the risk index, and outputting the risk level to the continuous optimization module.

9. The panoramic digital operations management system for enterprise operations management of claim 1, wherein, The continuous optimization module generates an intelligent optimization scheme based on the operation risk level provided by the execution monitoring module using a machine learning algorithm, and transmits the intelligent optimization scheme back to the strategic decision module, wherein the machine learning algorithm refers to a gradient boosting decision tree algorithm.

10. A panoramic digital operation management method for enterprise operation management, for using the panoramic digital operation management system for enterprise operation management according to any one of claims 1-9, characterized in that, Comprise: S1: collecting operation data of an enterprise; S2: calculating the order growth index in a unit time and the conversion index in a unit time, and calculating the market demand index according to the order growth index in a unit time and the conversion index in a unit time; S3: matching market output commands according to real-time market demand indexes, and outputting the market output commands to the strategic decision module; S4: formulating a decision scheme based on the market output commands, setting expected order growth indexes and expected conversion indexes, and sending the decision scheme to the execution module; S5: receiving the decision scheme output by the strategic decision module and converting it into executable operation tasks; S6: monitoring the implementation of the decision scheme in real time, analyzing the changes in operation data during the execution process and calculating the risk index, matching the risk level according to the risk index, and transmitting the risk level to the continuous optimization module; S7: generating an intelligent optimization scheme based on the operation risk level using a machine learning algorithm, and transmitting the intelligent optimization scheme back to the strategic decision module.

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