Intelligent decision-making method and system based on large model

Abstract

The invention is suitable for the technical field of enterprise decision management, and provides an intelligent decision method and system based on a large model, and the method comprises the steps: obtaining a decision target, and obtaining historical data according to the decision target; if the decision target is judged to improve the efficiency, obtaining a production demand, obtaining resource data and obtaining an existing process, analyzing the existing process according to the production demand and the resource data, and identifying unreasonable allocation of low-efficiency links and tasks in the existing process; if the decision target is determined to increase the income, obtaining an existing marketing strategy, analyzing the existing marketing strategy according to the existing product and the existing product price, and identifying whether the conversion rate of the existing marketing strategy reaches the standard; the method comprises the steps of obtaining an optimization result, obtaining an optimization qualified threshold value, comparing the optimization result with the threshold value, and judging whether optimization is qualified or not. The problems that a decision method cannot be provided according to a specific decision direction, improvement suggestions cannot be provided for an existing method, and meanwhile the effect of the decision method cannot be evaluated are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of enterprise decision-making management, and particularly relates to an intelligent decision-making method and system based on a large model. Background Art

[0002] In the process of existing product procurement, it is necessary to obtain the specific model and specific price of the product, and then determine whether to purchase and the quantity to be purchased based on the price and model. However, specific procurement methods require market analysis and trend prediction, inventory management and demand prediction, customer insight and personalization, cost accounting and financial optimization, supply chain optimization, quality control and defect detection, employee performance and training, predictive maintenance of equipment, regulatory compliance assistance, sales prediction and revenue optimization, and so on.

[0003] Once an illegal procurement behavior occurs, it must be intervened in a timely manner to avoid causing significant economic losses. Build an intelligent reach for illegal warning, ensure that user messages are reached in real time at important data nodes of illegal procurement behavior, and realize the whole-process supervision and full-process closed-loop of illegal behavior warning and rectification.

[0004] However, the existing technologies have problems that they cannot provide decision-making methods according to specific decision-making directions, cannot put forward improvement opinions on existing methods, and cannot evaluate the effects of decision-making methods. Summary of the Invention

[0005] The purpose of the embodiments of the present invention is to provide an intelligent decision-making method based on a large model, aiming to solve the problems raised in the third part of the background art.

[0006] The embodiments of the present invention are implemented as follows. An intelligent decision-making method based on a large model, the method includes:

[0007] Obtain a decision-making goal, where the decision includes improving efficiency and increasing revenue, and obtain historical data according to the decision-making goal;

[0008] If it is determined that the decision-making goal is to improve efficiency, obtain production requirements, obtain resource data, obtain the existing process, where the existing process includes task allocation and specific links, analyze the existing process according to the production requirements and resource data, and identify inefficient links and unreasonable task allocation in the existing process;

[0009] If it is determined that the decision-making goal is to increase revenue, obtain existing products, obtain the prices of existing products, obtain the existing marketing strategies, where the existing marketing strategies include product promotion and related services, analyze the existing marketing strategies according to the existing products and the prices of existing products, and identify whether the conversion rate of the existing marketing strategies meets the standard;

[0010] Obtain the optimization result, where the optimization result is the ratio of the data before optimization to the data after optimization. Obtain the qualified optimization threshold, compare the optimization result with the threshold, and determine whether the optimization is qualified.

[0011] Preferably, if it is determined that the decision-making goal is to improve efficiency, obtain the production requirements, obtain the resource data, obtain the existing process, where the existing process includes task allocation and specific links. Analyze the existing process based on the production requirements and resource data, and identify the inefficient links and unreasonable task allocation steps in the existing process, specifically including:

[0012] If it is determined that the decision-making goal is to improve efficiency, predict the production requirements based on historical data, obtain the production requirements, obtain the resource data, and determine whether the existing resources meet the production requirements according to the resource data;

[0013] Obtain the existing process, where the existing process includes task allocation and specific links. Analyze the existing process based on the production requirements and resource data, and analyze the operation time, executor, required resources, and output of the links;

[0014] Identify the inefficient links and unreasonable task allocation in the existing process, and optimize the inefficient links and unreasonable task allocation.

[0015] Preferably, if it is determined that the decision-making goal is to increase revenue, obtain the existing products, obtain the prices of the existing products, obtain the existing marketing strategies, where the existing marketing strategies include product promotion and related services. Analyze the existing marketing strategies based on the existing products and the prices of the existing products, and identify the steps for determining whether the conversion rate of the existing marketing strategies is up to standard, specifically including:

[0016] If it is determined that the decision-making goal is to increase revenue, predict the revenue target based on historical data, obtain the existing products, obtain the prices of the existing products, and determine whether the predicted revenue target can be achieved according to the existing products and the prices of the existing products;

[0017] Obtain the existing marketing strategies, where the existing marketing strategies include product promotion and related services. Analyze the customer purchase history and behavior patterns, and adjust the product prices;

[0018] Identify whether the conversion rate of the existing marketing strategies is up to standard, and optimize the unqualified marketing strategies.

[0019] Preferably, the steps of obtaining the optimization result, where the optimization result is the ratio of the data before optimization to the data after optimization, obtaining the qualified optimization threshold, comparing the optimization result with the threshold, and determining whether the optimization is qualified, specifically include:

[0020] Compare the optimization result, which is the data before optimization and the data after optimization, to obtain the optimization result, and obtain the qualified optimization threshold;

[0021] Compare the optimization result with the threshold to determine whether the optimization is qualified. If the optimization result is greater than the threshold, it is determined that the optimization is qualified;

[0022] Send the optimization result to the terminal to obtain the optimization impact, where the optimization impact includes the satisfaction impact and the competitiveness impact.

[0023] Preferably, the optimization result = (optimized data - original data) / original data × 100%.

[0024] Another object of the embodiments of the present invention is to provide an intelligent decision-making system based on a large model, the system includes:

[0025] A target module that obtains a decision-making target, where the decision-making includes improving efficiency and increasing revenue, and obtains historical data according to the decision-making target;

[0026] An efficiency improvement module, if it is determined that the decision-making target is to improve efficiency, obtains production requirements, obtains resource data, and obtains the existing process, where the existing process includes task allocation and specific links, analyzes the existing process according to the production requirements and resource data, and identifies inefficient links and unreasonable task allocations in the existing process;

[0027] A revenue increase module, if it is determined that the decision-making target is to increase revenue, obtains existing products, obtains the prices of existing products, and obtains the existing marketing strategies, where the existing marketing strategies include product promotion and related services, analyzes the existing marketing strategies according to the existing products and the prices of existing products, and identifies whether the conversion rate of the existing marketing strategies meets the standard;

[0028] A result module that obtains the optimization result, where the optimization result is the ratio of the original data to the optimized data, obtains the optimization qualification threshold, compares the optimization result with the threshold, and determines whether the optimization is qualified.

[0029] Preferably, the efficiency improvement module includes:

[0030] An efficiency improvement unit, if it is determined that the decision-making target is to improve efficiency, predicts the production requirements according to the historical data, obtains the production requirements, obtains the resource data, and determines whether the existing resources meet the production requirements according to the resource data;

[0031] A process analysis unit that obtains the existing process, where the existing process includes task allocation and specific links, analyzes the existing process according to the production requirements and resource data, and analyzes the operation time, executor, required resources, and output of the links;

[0032] A first optimization unit that identifies inefficient links and unreasonable task allocations in the existing process and optimizes the inefficient links and unreasonable task allocations.

[0033] Preferably, the revenue increase module includes:

[0034] Increase revenue unit. If it is determined that the decision goal is to increase revenue, predict the revenue goal based on historical data, obtain existing products, obtain the prices of existing products, and determine whether the predicted revenue goal can be achieved based on the existing products and their prices;

[0035] Strategy analysis unit. Obtain existing marketing strategies, which include product promotion and related services. Analyze the customer purchase history and behavior patterns, and adjust the product prices;

[0036] Second optimization unit. Identify whether the conversion rate of existing marketing strategies meets the standard, and optimize the marketing strategies that do not meet the standard.

[0037] Preferably, the result module includes:

[0038] Optimization result unit. Compare the optimization result, which is the data before optimization and the data after optimization, to obtain the optimization result, and obtain the qualified optimization threshold;

[0039] Optimization determination unit. Compare the optimization result with the threshold to determine whether the optimization is qualified. If the optimization result is greater than the threshold, it is determined that the optimization is qualified;

[0040] Optimization impact unit. Send the optimization result to the terminal and obtain the optimization impact, which includes the satisfaction impact and the competitiveness impact.

[0041] Preferably, the optimization result = (data after optimization - data before optimization) / data before optimization × 100%.

[0042] An intelligent decision-making method based on a large model provided by an embodiment of the present invention. Obtain the decision goal, where the decision includes improving efficiency and increasing revenue. Obtain historical data according to the decision goal. If it is determined that the decision goal is to improve efficiency, obtain the production requirements, obtain the resource data, obtain the existing processes, and the existing processes include task allocation and specific links. Analyze the existing processes based on the production requirements and resource data, identify the inefficient links and unreasonable task allocations in the existing processes. If it is determined that the decision goal is to increase revenue, obtain the existing products, obtain the prices of the existing products, obtain the existing marketing strategies, and the existing marketing strategies include product promotion and related services. Analyze the existing marketing strategies based on the existing products and their prices, identify whether the conversion rate of the existing marketing strategies meets the standard, obtain the optimization result, which is the ratio of the data before optimization and the data after optimization, obtain the qualified optimization threshold, compare the optimization result with the threshold, and determine whether the optimization is qualified. This solves the problems that the existing methods cannot provide decision-making methods according to specific decision directions, cannot propose improvement opinions on the existing methods, and cannot evaluate the effects of the decision-making methods. Description of the Drawings

[0043] Figure 1Flowchart of an intelligent decision-making method based on a large model provided by an embodiment of the present invention;

[0044] Figure 2 Flowchart of steps for determining if the decision goal is to improve efficiency, analyzing the existing process based on production requirements and resource data, and identifying inefficient links and steps with unreasonable task allocation in the existing process provided by an embodiment of the present invention;

[0045] Figure 3 Flowchart of steps for determining if the decision goal is to increase revenue, analyzing the existing marketing strategy based on existing products and their prices, and identifying whether the conversion rate of the existing marketing strategy meets the standard provided by an embodiment of the present invention;

[0046] Figure 4 Flowchart of steps for obtaining the optimization result, obtaining the optimization qualification threshold, and determining whether the optimization is qualified provided by an embodiment of the present invention;

[0047] Figure 5 Architecture diagram of an intelligent decision-making system based on a large model provided by an embodiment of the present invention;

[0048] Figure 6 Architecture diagram of the efficiency improvement module provided by an embodiment of the present invention;

[0049] Figure 7 Architecture diagram of the revenue increase module provided by an embodiment of the present invention;

[0050] Figure 8 Architecture diagram of the result module provided by an embodiment of the present invention. Detailed implementation manners

[0051] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to 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 used to limit the present invention.

[0052] It can be understood that the terms "first", "second", etc. used in the present application can be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish one element from another. For example, without departing from the scope of the present application, the first xx script can be called the second xx script, and similarly, the second xx script can be called the first xx script.

[0053] As Figure 1 shown, an intelligent decision-making method based on a large model provided by an embodiment of the present invention, the method includes:

[0054] S100, Obtain the decision-making objectives. The decisions include improving efficiency and increasing revenue. Obtain historical data according to the decision-making objectives.

[0055] In this step, obtain the decision-making objectives. The decision-making objectives are the starting point for decision-making analysis, which guides subsequent data collection, analysis, and strategy implementation. The decisions include improving efficiency and increasing revenue. Improving efficiency is achieved by reducing resource consumption, increasing productivity, or accelerating the speed of business processes. In some business scenarios, improving efficiency can be achieved by reducing time, lowering costs, increasing resource utilization, etc.

[0056] Increasing revenue is achieved by increasing income, expanding market share, or improving pricing strategies, etc. This may include achieving it by increasing product sales, improving customer conversion rates, increasing customer repurchase rates, etc.

[0057] Obtain historical data according to the decision-making objectives. Historical data related to improving efficiency includes production data, operation data, resource usage, cost data, and quality data. Historical data related to increasing revenue includes sales data, market data, customer data, financial data, and activity data.

[0058] S200, If it is determined that the decision-making objective is to improve efficiency, obtain production requirements, obtain resource data, obtain the existing process. The existing process includes task allocation and specific links. Analyze the existing process according to the production requirements and resource data, and identify inefficient links and unreasonable task allocations in the existing process.

[0059] In this step, if it is determined that the decision-making objective is to improve efficiency, the goal of improving efficiency is usually to optimize the existing process, reduce resource waste, shorten the production cycle, increase production capacity, and ultimately reduce costs and increase output; obtain production requirements to get information such as the quantity of products to be produced, product types, delivery time, etc. by the enterprise; obtain resource data. Resource data includes the information of resources currently available to the enterprise, such as equipment, labor, raw materials, etc.

[0060] Obtain the existing process. The existing process data refers to the current production process of the enterprise, including task allocation, operation steps of each link, process arrangement, and resource scheduling. Analyze the existing process according to the production requirements and resource data. By analyzing the production requirements, resource data, and existing process, bottlenecks or inefficient links in the production process can be found, and inefficient links and unreasonable task allocations in the existing process can be identified, so as to optimize them.

[0061] S300, If it is determined that the decision-making objective is to increase revenue, obtain the existing products, obtain the prices of the existing products, obtain the existing marketing strategies. The existing marketing strategies include product promotion and related services. Analyze the existing marketing strategies according to the existing products and the prices of the existing products, and identify whether the conversion rate of the existing marketing strategies meets the standard.

[0062] In this step, if it is determined that the decision-making objective is to increase revenue, first, a comprehensive analysis of the existing products, product prices, and existing marketing strategies needs to be carried out. Information such as the basic characteristics, functions, market positioning, and target customer groups of each product needs to be obtained for these existing products, which can be goods of different types, series, or specifications; the existing product prices need to be obtained. Since the pricing strategy affects consumers' purchase decisions, the pricing of different products needs to be analyzed;

[0063] The existing marketing strategies need to be obtained. The existing marketing strategies include product promotion and related services. Product promotion usually refers to how to display products to target consumers, which may be through channels such as advertising, promotions, and social media; while related services refer to the added value provided during the sales process or after-sales, such as technical support, after-sales guarantee, membership services, etc.;

[0064] Based on the existing products and existing product prices, analyze the existing marketing strategies. When analyzing the existing marketing strategies, special attention needs to be paid to the effects of marketing activities, including advertising channels, promotional activities, product display methods, and their impact on the conversion rate, and identify whether the conversion rate of the existing marketing strategies meets the standard.

[0065] S400, obtain the optimization result. The optimization result is the ratio of the data before optimization to the data after optimization. Obtain the qualified optimization threshold, compare the optimization result with the threshold, and determine whether the optimization is qualified.

[0066] In this step, obtain the optimization result. When conducting marketing or operation optimization, evaluating the qualification of the optimization result is a key step. The optimization result is usually measured by comparing the data before optimization and the data after optimization, and needs to be compared with a pre-set qualified optimization threshold. If the performance of the data after optimization exceeds or reaches the threshold, it can be considered that the optimization is successful; otherwise, it means that the optimization has not achieved the expected effect and further adjustment and improvement are needed.

[0067] As Figure 2 shown, as a preferred embodiment of the present invention, if it is determined that the decision-making objective is to improve efficiency, obtain the production requirements, obtain the resource data, obtain the existing process. The existing process includes task allocation and specific links. Based on the production requirements and resource data, analyze the existing process, and identify the inefficient links and unreasonable task allocation steps in the existing process, specifically including:

[0068] S201, if it is determined that the decision-making objective is to improve efficiency, predict the production requirements based on historical data, obtain the production requirements, obtain the resource data, and judge whether the existing resources meet the production requirements according to the resource data.

[0069] In this step, if it is determined that the decision goal is to improve efficiency, by means of reasonable resource allocation and optimized production planning, possible waste and unnecessary time delays in the production process are reduced, thereby improving the overall production efficiency. Forecast production demand based on historical data. Collect historical data, including production order data, sales data, and market demand data. Through trend analysis of historical production data, predict future production demand. For example, if the number of sales orders has been on the rise in the past few months, then it can be expected that future production demand will also increase accordingly;

[0070] Obtain resource data. Resource data is the core basis for judging whether existing resources can meet production demand. Resource data includes equipment resources, human resources, and raw material resources. Based on the resource data, judge whether the existing resources meet the production demand. According to the production demand and the production capacity of the equipment, calculate the workload required for each piece of equipment in the production process. If the production capacity of the existing equipment cannot meet the production demand, it may be necessary to add equipment or adjust the production plan. According to the production demand and the man-hour plan, judge whether the existing workers have enough working hours to complete the production tasks. If more man-hours are required, additional shifts can be considered or some work can be outsourced. Check the current inventory to ensure there are enough raw materials to support production. If the existing inventory is not sufficient to support production, procurement can be advanced to avoid production interruptions.

[0071] S202, Obtain the existing process. The existing process includes task allocation and specific links. Analyze the existing process according to the production demand and resource data, and analyze the operation time, executor, required resources, and output of each link.

[0072] In this step, obtain the existing process. The existing process refers to all production links and task allocation situations from order receipt to product delivery. The process includes task allocation, specific links, operation time, executors, required resources, and output;

[0073] Analyze the existing process according to the production demand and resource data. It is necessary to conduct task allocation analysis, operation time analysis, executor analysis, required resource analysis, and output analysis. Task allocation analysis: Whether the current task allocation is reasonable, whether it can make the best use of existing resources, and whether there are unreasonable deviations in task allocation. For example, whether too heavy tasks are concentrated on a certain position; Operation time analysis: Whether the operation time of each current link is appropriate and whether there is time waste. Through production line time tracking or man-hour analysis, count the actual operation time and scheduled time of each link, calculate the time difference, and find out unnecessary time waste;

[0074] The executor analysis determines whether the executors in different links are overworking or inefficient, whether adjustments are needed, analyzes whether the workloads of certain links are unbalanced, whether there are skill matching problems, and whether it is necessary to reduce manual intervention through automation or technological upgrades;

[0075] The required resources analysis determines whether the resources required for each current link are sufficient, whether there is resource waste or shortage, analyzes whether the resources are sufficient, such as equipment and raw materials, whether they can support production requirements, whether the resource use is efficient, whether there is overuse or idle phenomenon, and whether it is necessary to increase or decrease resource investment to improve efficiency;

[0076] The output analysis determines whether the output of each link meets the expectations, whether there is quality or quantity loss, and analyzes the gap between the output and the target by statistically tracking the output quantity and quality of each link.

[0077] S203, identify the inefficient links and unreasonable task assignments in the existing process, and optimize the inefficient links and unreasonable task assignments.

[0078] In this step, identify the inefficient links and unreasonable task assignments in the existing process. Through a detailed analysis of the process, it is possible to find out which links are bottlenecks and which links are inefficient due to unreasonable task assignments, so as to take targeted optimization measures;

[0079] Compare the actual operation time of each link with the standard time, find out the links with excessive or unreasonable time, evaluate the resource allocation of each link, determine whether there is resource shortage or over-allocation, whether the existing resources can be used more efficiently, check whether the task assignment is balanced, whether certain positions are overburdened, and whether there is idle personnel or equipment;

[0080] If the operation time of a link is too long, the resource consumption is too high, or the operation steps are redundant, resulting in low overall process efficiency, it is identified as an inefficient link. If the task assignment of certain links is unbalanced, resulting in some personnel and equipment being overly busy while there are idle or underutilized resources in other links, it is identified as unreasonable task assignment;

[0081] Simplify the operation steps, reduce redundant steps, simplify complex operation processes. For links with too long operation time, especially those with high repetition and standardized operations, automated equipment can be introduced to replace manual operations or technological upgrades to improve work efficiency, reduce human errors and operation time. According to the workload and task requirements of each link, reasonably allocate personnel to ensure a balanced burden for each link. Avoid overloading certain processes while underloading other processes, resulting in resource waste or production line stagnation.

[0082] Such as Figure 3As shown, as a preferred embodiment of the present invention, if it is determined that the decision-making goal is to increase revenue, obtain existing products, obtain the prices of existing products, obtain existing marketing strategies, where the existing marketing strategies include product promotion and related services, and analyze the existing marketing strategies based on the existing products and the prices of existing products to identify whether the conversion rate of the existing marketing strategies meets the standard, specifically includes:

[0083] S301, if it is determined that the decision-making goal is to increase revenue, predict the revenue target based on historical data, obtain existing products, obtain the prices of existing products, and determine whether the predicted revenue target can be achieved based on the existing products and the prices of existing products.

[0084] In this step, if it is determined that the decision-making goal is to increase revenue, it is necessary to comprehensively analyze existing products, the prices of existing products, historical data, etc., predict the revenue target and determine whether the existing products and their prices can achieve this goal. Predict the revenue target based on historical data, where the historical data includes sales data, market trends, seasonal fluctuations, and promotional effects. Based on the analysis of historical data, predict the revenue target for a certain future period, such as a quarter, half-year, or whole year;

[0085] Obtain existing products, obtain the prices of existing products, list all the current products of the company, including their models, functions, target markets, and consumer groups. Different products may have different market positions and pricing strategies, and each product needs to be analyzed separately to determine the current market price and pricing strategy of each product. The pricing strategy may include high-end pricing and penetration pricing;

[0086] Determine whether the predicted revenue target can be achieved based on the existing products and the prices of existing products. Analyze the market demand for each product based on market research and historical sales data. Predict the future demand for each product based on market trends and changes in consumer behavior. The demand for a product can be predicted through factors such as market share and consumer purchase preferences. Based on the above data and analysis, calculate whether each product can contribute sufficient sales volume and sales revenue to achieve the predicted revenue target.

[0087] For example, a smartphone (Model A): The expected sales volume is 11,000 units, the price is set at 3,000 yuan, and the revenue is: 11,000 × 3,000 = 33,000,000 yuan;

[0088] If the price is reduced by 10%, the expected sales volume is increased to 12,650 units, and the revenue is: 12,650 × 2,700 = 34,155,000 yuan;

[0089] The increase in sales volume and price adjustment after the price reduction make the revenue of the smartphone sufficient to reach or even exceed the target.

[0090] S302. Obtain the existing marketing strategies. The existing marketing strategies include product promotion and related services. Analyze the customer purchase history and behavior patterns, and adjust the product price.

[0091] In this step, obtain the existing marketing strategies. The marketing strategies include product promotion and related services. Product promotion refers to the process of conveying product information to the target customer group through various marketing channels, such as advertising, promotions, social media, and email. Related services refer to the additional services or value provided to consumers during or after the sales process, aiming to enhance the customer's purchase experience and improve customer loyalty.

[0092] Analyze the customer purchase history and behavior patterns. The customer purchase history includes the purchase frequency, purchase amount, purchase preferences, and purchase channels. The customer behavior patterns include browsing behavior, conversion path, time factors, and response patterns. Based on the analyzed customer purchase history and behavior patterns, the product price can be adjusted to increase product sales, attract more consumers, and ultimately increase revenue.

[0093] For those customers who often make purchases, they can be stimulated to buy more products through customized preferential policies, exclusive discounts, membership systems, etc. For those customers who are more price-sensitive, limited-time discounts, discount promotions, or coupons can be provided to encourage them to make purchases. For those customers who tend to buy high-end products, their needs can be met by enhancing the product value, improving the product functions, or launching a higher-priced customized version. For repeat customers, their loyalty can be increased and they can be stimulated to continue purchasing through methods such as providing point rewards and rebates.

[0094] S303. Identify whether the conversion rate of the existing marketing strategies meets the standard, and optimize the marketing strategies that do not meet the standard.

[0095] In this step, identify whether the conversion rate of the existing marketing strategies meets the standard. The conversion rate refers to the completion rate of a specific action, such as purchase, click, and registration. The conversion rates include purchase conversion rate, click-through conversion rate, registration conversion rate, and shopping cart addition conversion rate.

[0096] Evaluate whether the conversion rate of the marketing strategies meets the standard. Compare the conversion rate of the current marketing strategies with past performance to see if it has reached the historical average level or growth expectation. Optimize the marketing strategies that do not meet the standard, and optimize the advertising channels and promotion methods. If the conversion rate of a certain advertising channel is low, such as social media advertising and display advertising, through A / B testing and data analysis, find the best-performing advertising channel, concentrate the budget on the efficient channels, test different advertising creatives, copywriting, and pictures, and find the combination that can most arouse customers' interest and promote clicks and purchases. Optimize the content of the advertisement, such as the title, pictures, videos, etc., according to customer behavior to make it more attractive.

[0097] As Figure 4 shown, as a preferred embodiment of the present invention, for the step of obtaining the optimization result, where the optimization result is the ratio of the data before optimization to the data after optimization, obtaining the qualified optimization threshold, comparing the optimization result with the threshold, and determining whether the optimization is qualified, specifically includes:

[0098] S401, compare the optimization result which is the data before optimization and the data after optimization to obtain the optimization result, and obtain the qualified optimization threshold.

[0099] In this step, when comparing the optimization result which is the data before optimization and the data after optimization, the data before optimization refers to the benchmark value of relevant indicators before the implementation of the optimization measures, and the data after optimization refers to the new data after the implementation of the optimization measures. The data after optimization reflects the impact of the optimization measures on various indicators;

[0100] Optimization result = (data after optimization - data before optimization) / data before optimization × 100%

[0101] This ratio reflects the proportion of the optimization effect. If the ratio is greater than 1, it indicates that the optimization has achieved a positive improvement; if the ratio is equal to 1, it means there is no change before and after optimization; if the ratio is less than 1, it means that the optimization has not achieved the expected effect;

[0102] Obtain the qualified optimization threshold, which is used to evaluate whether the optimization result meets the expected goal. An enterprise can set the qualified threshold according to the changing trend of historical data. If the improvement brought by past optimization measures is usually 20%, then 20% can be set as the qualified threshold.

[0103] S402, compare the optimization result with the threshold to determine whether the optimization is qualified. If the optimization result is greater than the threshold, it is determined that the optimization is qualified.

[0104] In this step, after comparing the optimization result with the threshold and obtaining the optimization result ratio and the qualified optimization threshold, the next step is to compare the two. Through the comparison, an enterprise can determine whether the optimization is successful and decide whether to continue with the optimization or adjust the strategy;

[0105] If the optimization result ratio is greater than or equal to the qualified optimization threshold, the optimization result is considered qualified and the optimization measure is successful;

[0106] If the optimization result ratio is less than the qualified optimization threshold, the optimization result is considered unqualified and the optimization measure has not achieved the expected effect. At this time, it may be necessary to re-evaluate the optimization strategy, find out the reasons for non-compliance, and further adjust.

[0107] S403, send the optimization result to the terminal and obtain the optimization impact, where the optimization impact includes the satisfaction impact and the competitiveness impact.

[0108] In this step, the optimization results are sent to the terminals, and the optimization results are passed on to each terminal or relevant department, such as the marketing team, the product development team, the customer service team, etc. The purpose of passing on the optimization results is to enable relevant personnel to make more accurate subsequent decisions based on the optimization effects;

[0109] Obtain the optimization impacts. The optimization impacts include the satisfaction impact and the competitiveness impact. Customer satisfaction is an important indicator for measuring the response of the optimization results to the customer experience and user needs. Optimization is not only about improving business efficiency and profit, but also about whether customers are satisfied with aspects such as the quality, price, and purchase experience of the product or service. Customer satisfaction is directly related to customer loyalty, repurchase rate, and word-of-mouth spread;

[0110] The competitiveness impact is the impact of the optimization measures on the enterprise's market competitive position. This includes the advantages of the enterprise in the market compared to competitors, whether the optimization measures make the enterprise's products or services more attractive, and whether they can help the enterprise stand out in the fierce market competition.

[0111] Through the evaluation of these two impacts, the enterprise can more comprehensively judge the effects of the optimization measures, and then adjust the strategy or further strengthen the optimization direction.

[0112] As Figure 5 shown, a large model-based intelligent decision-making system provided by an embodiment of the present invention, the system includes:

[0113] A target module 100, configured to obtain a decision-making target, the decision-making includes improving efficiency and increasing revenue, and obtain historical data according to the decision-making target.

[0114] In this system, the target module 100 obtains a decision-making target. The decision-making target is the starting point for decision-making analysis, which guides subsequent data collection, analysis, and strategy implementation. The decision-making includes improving efficiency and increasing revenue. Improving efficiency is achieved by reducing resource consumption, increasing productivity, or accelerating the speed of business processes. In some business scenarios, improving efficiency can be achieved by reducing time, lowering costs, and increasing resource utilization;

[0115] Increasing revenue is achieved by increasing income, expanding market share, or improving pricing strategies, etc. This may include achieving it by increasing product sales, improving customer conversion rates, and increasing customer repurchase rates;

[0116] Historical data related to the decision-making target is obtained. Historical data related to improving efficiency includes production data, operation data, resource usage, cost data, and quality data. Historical data related to increasing revenue includes sales data, market data, customer data, financial data, and activity data.

[0117] The efficiency improvement module 200 is used to, if it is determined that the decision-making goal is to improve efficiency, obtain production requirements, obtain resource data, and obtain the existing process. The existing process includes task allocation and specific links, and analyze the existing process according to the production requirements and resource data to identify inefficient links and unreasonable task allocation in the existing process.

[0118] In this system, if the efficiency improvement module 200 determines that the decision-making goal is to improve efficiency, the goal of improving efficiency is usually to optimize the existing process, reduce resource waste, shorten the production cycle, enhance production capacity, and ultimately reduce costs and increase output; obtain production requirements to get information such as the quantity, variety, and delivery time of products that the enterprise needs to produce; obtain resource data, and the resource data includes the resource information currently available to the enterprise, such as equipment, labor, raw materials, etc.

[0119] Obtain the existing process. The existing process data refers to the current production process of the enterprise, including task allocation, operation steps of each link, process arrangement, and resource scheduling. Analyze the existing process according to the production requirements and resource data. By analyzing the production requirements, resource data, and existing process, bottlenecks or inefficient links in the production process can be found, and inefficient links and unreasonable task allocation in the existing process can be identified, so as to carry out optimization.

[0120] The revenue increase module 300 is used to, if it is determined that the decision-making goal is to increase revenue, obtain existing products, obtain the prices of existing products, obtain existing marketing strategies. The existing marketing strategies include product promotion and related services, and analyze the existing marketing strategies according to the existing products and the prices of existing products to identify whether the conversion rate of the existing marketing strategies meets the standard.

[0121] In this system, if the revenue increase module 300 determines that the decision-making goal is to increase revenue, it is first necessary to comprehensively analyze the existing products, product prices, and existing marketing strategies. Obtain existing products. These products can be commodities of different types, series, or specifications. The analysis of existing products requires understanding information such as the basic characteristics, functions, market positioning, and target customer groups of each product; obtain the prices of existing products. The price strategy will affect consumers' purchase decisions, so it is necessary to analyze the pricing of different products.

[0122] Obtain existing marketing strategies. The existing marketing strategies include product promotion and related services. Product promotion usually refers to how to display products to target consumers, which may be through channels such as advertising, promotion, and social media; while related services refer to the added value provided during the sales process or after-sales, such as technical support, after-sales guarantee, membership services, etc.

[0123] Analyze the existing marketing strategies based on the existing products and their prices. When analyzing the existing marketing strategies, special attention should be paid to the effectiveness of marketing activities, including advertising channels, promotional activities, product display methods, and their impact on conversion rates, and identify whether the conversion rates of the existing marketing strategies meet the standards.

[0124] The result module 400 is used to obtain the optimization result. The optimization result is the ratio of the data before optimization to the data after optimization. Obtain the qualified optimization threshold, compare the optimization result with the threshold, and determine whether the optimization is qualified.

[0125] In this system, the result module 400 obtains the optimization result. When conducting marketing or operation optimization, evaluating the qualification of the optimization result is a key step. The optimization result is usually measured by comparing the data before optimization and the data after optimization, and needs to be compared with a pre-set qualified optimization threshold. If the performance of the data after optimization exceeds or reaches the threshold, it can be considered that the optimization is successful; otherwise, it means that the optimization does not meet the expected effect and further adjustment and improvement are required.

[0126] As Figure 6 shown, as a preferred embodiment of the present invention, the efficiency improvement module 200 includes:

[0127] The efficiency improvement unit 201 is used to, if it is determined that the decision target is to improve efficiency, predict the production demand according to historical data, obtain the production demand, obtain the resource data, and judge whether the existing resources meet the production demand according to the resource data.

[0128] In this module, if the efficiency improvement unit 201 determines that the decision target is to improve efficiency, by reasonable resource allocation and optimized production planning, reduce the possible waste and unnecessary time delays in the production process, thereby improving the overall production efficiency. Predict the production demand according to historical data, collect historical data, including production order data, sales data and market demand data, and predict the future production demand through trend analysis of historical production data. For example, if the number of sales orders has shown an upward trend in the past few months, it can be expected that the future production demand will also increase accordingly;

[0129] Obtain resource data. The resource data is the core basis for judging whether the existing resources can meet the production requirements. The resource data includes equipment resources, human resources, and raw material resources. Judge whether the existing resources meet the production requirements according to the resource data. Calculate the workload required for each piece of equipment during the production process based on the production requirements and the production capacity of the equipment. If the production capacity of the existing equipment cannot meet the production requirements, it may be necessary to add equipment or adjust the production plan. Judge whether the existing workers have enough working hours to complete the production tasks according to the production requirements and the working hour plan. If more working hours are needed, additional shifts can be considered or part of the work can be outsourced. Check the current inventory to ensure that there are enough raw materials to support production. If the existing inventory is not enough to support production, procurement can be carried out in advance to avoid production interruption.

[0130] The process analysis unit 202 is used to obtain the existing process. The existing process includes task allocation and specific links. Analyze the existing process according to the production requirements and resource data, and analyze the operation time, executor, required resources, and output of each link.

[0131] In this module, the process analysis unit 202 obtains the existing process. The existing process refers to all the production links and task allocation situations from order receipt to product delivery. The process includes task allocation, specific links, operation time, executors, required resources, and output.

[0132] Analyze the existing process according to the production requirements and resource data. Task allocation analysis is required to determine whether the current task allocation is reasonable, whether it can make the most of the existing resources, and whether there are unreasonable deviations in task allocation, such as excessive tasks concentrated on a certain position. Operation time analysis is to determine whether the operation time of each current link is appropriate and whether there is time waste. By tracking the production line time or conducting working hour analysis, count the actual operation time and scheduled time of each link, calculate the time difference, and find out unnecessary time waste.

[0133] Executor analysis is to determine whether the executors of different links are overworked or inefficient and whether adjustments are needed. Analyze whether the workload of some links is unbalanced, whether there are skill matching problems, and whether it is necessary to reduce manual intervention through automation or technological upgrading.

[0134] Required resource analysis is to determine whether the resources required for each current link are sufficient, whether there is resource waste or shortage, and analyze whether the resources are sufficient, such as equipment and raw materials, to support the production requirements. Whether the resource use is efficient, whether there is overuse or idleness, and whether it is necessary to increase or decrease resource investment to improve efficiency.

[0135] Output analysis determines whether the output of each process meets the expectations and whether there are losses in quality or quantity. By statistically tracking the output quantity and quality of each process, the gap between the output and the target is analyzed.

[0136] The first optimization unit 203 is used to identify inefficient processes and unreasonable task allocations in the existing process and optimize the inefficient processes and unreasonable task allocations.

[0137] In this module, the first optimization unit 203 identifies inefficient processes and unreasonable task allocations in the existing process. Through a detailed analysis of the process, it can find out which processes are bottlenecks and which processes are inefficient due to unreasonable task allocations, and then take targeted optimization measures.

[0138] Compare the actual operation time of each process with the standard time to find out the processes with excessive or unreasonable time. Evaluate the resource allocation of each process to determine whether there is a shortage or over-allocation of resources, whether the existing resources can be utilized more efficiently, check whether the task allocation is balanced, whether some positions are overburdened, and whether there is any idle personnel or equipment.

[0139] A process with an overly long operation time, excessive resource consumption, or redundant operation steps, resulting in low overall process efficiency, is identified as an inefficient process. An unreasonable task allocation is identified when the task allocation of some processes is unbalanced, causing some personnel and equipment to be overly busy while there are idle or underutilized resources in other processes.

[0140] Simplify the operation steps, reduce redundant steps, and simplify complex operation processes. For processes with overly long operation times, especially those with high repetition and standardized operations, automated equipment can be introduced to replace manual operations or technological upgrades can be carried out to improve work efficiency, reduce human errors and operation time. According to the workload and task requirements of each process, reasonably allocate personnel to ensure a balanced burden for each process. Avoid overburdening some processes while underloading others, resulting in resource waste or production line stagnation.

[0141] As Figure 7 shown, as a preferred embodiment of the present invention, the revenue increase module 300 includes:

[0142] The revenue increase unit 301 is used to, if it is determined that the decision target is to increase revenue, predict the revenue target based on historical data, obtain existing products, obtain the prices of existing products, and determine whether the predicted revenue target can be achieved based on the existing products and the prices of existing products.

[0143] In this module, if the revenue increase unit 301 determines that the decision goal is to increase revenue, it is necessary to comprehensively analyze existing products, existing product prices, historical data, etc., predict the revenue goal, and judge whether the existing products and their prices can achieve this goal. Predict the revenue goal based on historical data, which includes sales data, market trends, seasonal fluctuations, and promotional effects. Based on historical data analysis, predict the revenue goal for a certain future period, such as quarterly, semi-annual, or annual;

[0144] Obtain existing products and existing product prices. List all the current products of the company, including their models, functions, target markets, and consumer groups. Different products may have different market positions and pricing strategies, and each product needs to be analyzed separately to determine the current market price and pricing strategy of each product. The pricing strategy may include high-end pricing and penetration pricing;

[0145] Judge whether the predicted revenue goal can be achieved based on existing products and existing product prices. According to market research and historical sales data, analyze the market demand for each product. Based on changes in market trends and consumer behavior, predict the future demand for each product. The demand for a product can be predicted based on factors such as market share and consumer purchase preferences. According to the above data and analysis, calculate whether each product can contribute sufficient sales volume and sales revenue to achieve the predicted revenue goal.

[0146] For example, for a smartphone (model A): The expected sales volume is 11,000 units, the pricing is 3,000 yuan, and the revenue is: 11,000×3,000 = 33,000,000 yuan;

[0147] If the price is reduced by 10%, the expected sales volume is increased to 12,650 units, and the revenue is: 12,650×2,700 = 34,155,000 yuan;

[0148] The increased sales volume and price adjustment after the price reduction make the revenue of the smartphone sufficient to reach or even exceed the goal.

[0149] The strategy analysis unit 302 is used to obtain existing marketing strategies. Existing marketing strategies include product promotion and related services, analyze customers' purchase history and behavior patterns, and adjust product prices.

[0150] In this module, the strategy analysis unit 302 obtains existing marketing strategies. Marketing strategies include product promotion and related services. Product promotion refers to the process of conveying product information to the target customer group through various marketing channels, such as advertising, promotions, social media, and email. Related services refer to the additional services or values provided to consumers during or after the sales process, aiming to enhance the customer's purchase experience and improve customer loyalty;

[0151] Analyze the customer purchase history and behavior patterns. The customer purchase history includes purchase frequency, purchase amount, purchase preferences, and purchase channels. The customer behavior patterns include browsing behavior, conversion paths, time factors, and response patterns. Based on the analyzed customer purchase history and behavior patterns, the product price can be adjusted to increase product sales, attract more consumers, and ultimately increase revenue.

[0152] For customers who often make purchases, they can be stimulated to buy more products through customized preferential policies, exclusive discounts, membership systems, etc. For customers who are more price-sensitive, limited-time discounts, discount promotions, or coupons can be provided to encourage them to make purchases. For customers who tend to buy high-end products, their needs can be met by enhancing the product value, improving the product functions, or launching a higher-priced customized version. For repeat customers, loyalty can be increased and they can be stimulated to continue purchasing through methods such as providing point rewards and rebates.

[0153] The second optimization unit 303 is used to identify whether the conversion rate of the existing marketing strategies meets the standard and optimize the marketing strategies that do not meet the standard.

[0154] In this module, the second optimization unit 303 identifies whether the conversion rate of the existing marketing strategies meets the standard. The conversion rate refers to the completion rate of a specific action, such as purchase, click, and registration. The conversion rates include purchase conversion rate, click conversion rate, registration conversion rate, and shopping cart addition conversion rate.

[0155] Evaluate whether the conversion rate of the marketing strategies meets the standard. Compare the conversion rate of the current marketing strategy with past performance to see if it has reached the historical average level or growth expectation. Optimize the marketing strategies that do not meet the standard, optimize the advertising channels and promotion methods. If the conversion rate of a certain advertising channel is low, such as social media advertising and display advertising, through A / B testing and data analysis, find the best-performing advertising channel and concentrate the budget on the efficient channels. Test different advertising creatives, copywriting, and pictures to find the combination that can most arouse customer interest and promote clicks and purchases. Optimize the content of the advertisement such as the title, picture, video, etc. according to customer behavior to make it more attractive.

[0156] As Figure 8 shown, as a preferred embodiment of the present invention, the result module 400 includes:

[0157] The optimization result unit 401 is used to compare the data before optimization and the data after optimization for the optimization result, obtain the optimization result, and acquire the qualified optimization threshold.

[0158] In this module, the optimization result unit 401 compares the optimization result, which is the data before optimization and the data after optimization. The data before optimization refers to the benchmark value of relevant indicators before the implementation of optimization measures, and the data after optimization refers to the new data after the implementation of optimization measures. The data after optimization reflects the impact of optimization measures on various indicators;

[0159] Optimization result = (Data after optimization - Data before optimization) / Data before optimization × 100%

[0160] This ratio reflects the proportion of the optimization effect. If the ratio is greater than 1, it indicates that the optimization has achieved a positive improvement; if the ratio is equal to 1, it means there is no change before and after optimization; if the ratio is less than 1, it means the optimization has not achieved the expected effect;

[0161] Obtain the qualified threshold for optimization to evaluate whether the optimization result meets the expected goal. An enterprise can set the qualified threshold according to the changing trend of historical data. If the improvement brought by past optimization measures is usually 20%, then 20% can be set as the qualified threshold.

[0162] The optimization determination unit 402 is used to compare the optimization result with the threshold to determine whether the optimization is qualified. If the optimization result is greater than the threshold, it is determined that the optimization is qualified.

[0163] In this module, after the optimization determination unit 402 compares the optimization result with the threshold and obtains the optimization result ratio and the qualified threshold for optimization, the next step is to compare the two. Through this comparison, an enterprise can determine whether the optimization is successful and decide whether to continue with optimization or adjust the strategy;

[0164] If the optimization result ratio is greater than or equal to the qualified threshold for optimization, the optimization result is considered qualified and the optimization measure is successful;

[0165] If the optimization result ratio is less than the qualified threshold for optimization, the optimization result is considered unqualified and the optimization measure has not achieved the expected effect. In this case, it may be necessary to re-evaluate the optimization strategy, find out the reasons for non-compliance, and make further adjustments.

[0166] The optimization impact unit 403 is used to send the optimization result to the terminal and obtain the optimization impact, where the optimization impact includes the satisfaction impact and the competitiveness impact.

[0167] In this module, the optimization impact unit 403 sends the optimization result to the terminal, and the optimization result is transmitted to each terminal or relevant departments, such as the marketing team, the product development team, the customer service team, etc. The purpose of transmitting the optimization result is to enable relevant personnel to make more accurate subsequent decisions based on the optimization effect;

[0168] Obtain the optimization impact, which includes the satisfaction impact and the competitiveness impact. Customer satisfaction is an important indicator to measure the response of the optimization result to the customer experience and user needs. Optimization is not only about improving business efficiency and profit, but also about whether customers are satisfied with aspects such as the quality, price, and purchase experience of the product or service. Customer satisfaction is directly related to customer loyalty, repurchase rate, and word-of-mouth spread;

[0169] The competitiveness impact is the impact of the optimization measures on the enterprise's market competition position. This includes the advantages of the enterprise in the market compared to competitors, whether the optimization measures make the enterprise's products or services more attractive, and whether they can help the enterprise stand out in the fierce market competition.

[0170] By evaluating these two impacts, the enterprise can more comprehensively judge the effect of the optimization measures, and then adjust the strategy or further strengthen the optimization direction.

[0171] In one embodiment, a computer device is proposed. The computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0172] Obtain the decision-making goal, where the decision includes improving efficiency and increasing revenue, and obtain historical data according to the decision-making goal;

[0173] If it is determined that the decision-making goal is to improve efficiency, obtain the production demand, obtain the resource data, obtain the existing process, where the existing process includes task allocation and specific links, analyze the existing process according to the production demand and resource data, and identify the inefficient links and unreasonable task allocation in the existing process;

[0174] If it is determined that the decision-making goal is to increase revenue, obtain the existing products, obtain the existing product prices, obtain the existing marketing strategies, where the existing marketing strategies include product promotion and related services, analyze the existing marketing strategies according to the existing products and existing product prices, and identify whether the conversion rate of the existing marketing strategies meets the standard;

[0175] Obtain the optimization result, where the optimization result is the ratio of the data before optimization to the data after optimization, obtain the optimization qualification threshold, compare the optimization result with the threshold, and judge whether the optimization is qualified.

[0176] In one embodiment, a computer-readable storage medium is provided. A computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the processor is caused to execute the following steps:

[0177] Obtain the decision-making goal, where the decision includes improving efficiency and increasing revenue, and obtain historical data according to the decision-making goal;

[0178] If it is determined that the decision-making objective is to improve efficiency, obtain production requirements, obtain resource data, obtain the existing process, where the existing process includes task allocation and specific links, analyze the existing process based on production requirements and resource data, and identify inefficient links and unreasonable task allocations in the existing process;

[0179] If it is determined that the decision-making objective is to increase revenue, obtain the existing products, obtain the prices of the existing products, obtain the existing marketing strategies, where the existing marketing strategies include product promotion and related services, analyze the existing marketing strategies based on the existing products and the prices of the existing products, and identify whether the conversion rate of the existing marketing strategies meets the standard;

[0180] Obtain the optimization result, where the optimization result is the ratio of the data before optimization to the data after optimization, obtain the qualified optimization threshold, compare the optimization result with the threshold, and determine whether the optimization is qualified.

[0181] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown in sequence according to the arrows, these steps do not necessarily need to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily need to be executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages does not necessarily need to be sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0182] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0183] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0184] The above embodiments merely represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent for the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention should be subject to the appended claims.

[0185] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent decision-making method based on a large model, characterized in that: The method comprises: Obtaining decision goals, where the decision includes improving efficiency and increasing revenue, and obtaining historical data based on the decision goals; If the decision-making goal is to improve efficiency, obtain production requirements, obtain resource data, and obtain existing processes, including task allocation and specific links. Analyze the existing processes based on production requirements and resource data to identify inefficient links in the existing processes and unreasonable task allocation; If the decision-making goal is to increase revenue, obtain existing products, obtain existing product prices, and obtain existing marketing strategies, where the existing marketing strategies include product push and related services, analyze the existing marketing strategies based on the existing products and existing product prices, and identify whether the conversion rate of the existing marketing strategies meets the standards; Obtain the optimization result, which is the ratio of the data before optimization to the data after optimization, obtain the optimization qualified threshold, compare the optimization result with the threshold, and judge whether the segment optimization is qualified.

2. According to claim 1, a large model-based intelligent decision-making method is characterized in that: If the decision-making goal is to improve efficiency, obtain production requirements, obtain resource data, and obtain existing processes, the existing processes include task allocation and specific links, analyze the existing processes according to production requirements and resource data, identify inefficient links in the existing processes and unreasonable task allocation steps, specifically including: If it is determined that the decision-making goal is to improve efficiency, the production demand is predicted based on historical data, the production demand is obtained, resource data is obtained, and it is determined whether the existing resources meet the production demand based on the resource data; Obtain the existing process, including task allocation and specific links, analyze the existing process according to production demand and resource data, and analyze the operation time, executors, required resources and output of the links; Identify inefficient links and unreasonable task allocation in existing processes, and optimize them.

3. The intelligent decision-making method based on a large model according to claim 1, characterized in that: If the decision-making goal is to increase revenue, the steps of obtaining existing products, obtaining existing product prices, and obtaining existing marketing strategies, wherein the existing marketing strategies include product push and related services, analyzing the existing marketing strategies based on the existing products and existing product prices, and identifying whether the conversion rate of the existing marketing strategies meets the standards specifically include: If the decision-making goal is determined to be to increase revenue, the revenue target is predicted based on historical data, existing products are obtained, the prices of existing products are obtained, and it is determined whether the predicted revenue target can be achieved based on the existing products and their prices; Obtain existing marketing strategies, including product push and related services, analyze customer purchase history and behavior patterns, and adjust product prices; Identify whether the conversion rate of existing marketing strategies meets the standards and optimize those that do not.

4. The intelligent decision-making method based on a large model according to claim 1, characterized in that: The step of obtaining the optimization result, which is the ratio of the data before optimization to the data after optimization, obtaining the optimization qualified threshold, comparing the optimization result with the threshold, and judging whether the optimization is qualified specifically includes: Compare the optimization results to the data before and after optimization, obtain the optimization results, and obtain the optimization qualified threshold; Compare the optimization result with the threshold to determine whether the optimization is qualified. If the optimization result is greater than the threshold, the optimization is determined to be qualified. The optimization result is sent to the terminal to obtain the optimization impact, which includes the satisfaction impact and the competitiveness impact.

5. The intelligent decision-making method based on a large model according to claim 1, characterized in that: The optimization result = (data after optimization - data before optimization) / data before optimization × 100%.

6. An intelligent decision-making system based on a large model, characterized in that: The system comprises: A target module obtains decision targets, including improving efficiency and increasing revenue, and obtains historical data according to the decision targets; The efficiency improvement module, if the decision goal is to improve efficiency, obtains production requirements, resource data, and existing processes, wherein the existing processes include task allocation and specific links, analyzes the existing processes according to production requirements and resource data, and identifies inefficient links in the existing processes and unreasonable task allocation; The revenue increase module, if it is determined that the decision goal is to increase revenue, obtains existing products, obtains existing product prices, obtains existing marketing strategies, and the existing marketing strategies include product push and related services, analyzes the existing marketing strategies based on the existing products and existing product prices, and identifies whether the conversion rate of the existing marketing strategies meets the standards; The result module obtains the optimization result, which is the ratio of the data before optimization to the data after optimization, obtains the optimization qualified threshold, compares the optimization result with the threshold, and determines whether the optimization is qualified.

7. The intelligent decision-making system based on a large model according to claim 6, characterized in that: The efficiency improvement module comprises: The efficiency improvement unit, if it is determined that the decision goal is to improve efficiency, predicts production demand based on historical data, obtains production demand, obtains resource data, and determines whether existing resources meet production demand based on the resource data; The process analysis unit obtains the existing process, including task allocation and specific links, analyzes the existing process according to production demand and resource data, and analyzes the operation time, executors, required resources and output of the links; The first optimization unit identifies inefficient links and unreasonable task allocation in the existing process and optimizes them.

8. The intelligent decision-making system based on a large model according to claim 7, characterized in that: The revenue increasing module comprises: Increase the revenue unit. If the decision goal is determined to be to increase revenue, predict the revenue target based on historical data, obtain existing products, obtain the prices of existing products, and determine whether the predicted revenue target can be achieved based on the existing products and their prices; Strategy analysis unit, which obtains existing marketing strategies, including product push and related services, analyzes customer purchase history and behavior patterns, and adjusts product prices; The second optimization unit identifies whether the conversion rate of existing marketing strategies meets the standards and optimizes those that do not.

9. The intelligent decision-making system based on a large model according to claim 8, characterized in that: The result module includes: The optimization result unit compares the optimization result to the data before and after optimization, obtains the optimization result, and obtains the optimization qualified threshold; The optimization judgment unit compares the optimization result with the threshold value to judge whether the optimization is qualified. If the optimization result is greater than the threshold value, the optimization is judged to be qualified. The optimization impact unit sends the optimization result to the terminal to obtain the optimization impact, which includes the satisfaction impact and the competitiveness impact.

10. The intelligent decision-making system based on a large model according to claim 9, characterized in that: The optimization result = (data after optimization - data before optimization) / data before optimization × 100%.

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