E-commerce ERP management system and management method thereof

Abstract

The invention discloses an electronic commerce ERP (Enterprise Resource Planning) management system and a management method thereof, and belongs to the technical field of commercial big data management. The electronic commerce ERP management method comprises the following steps: acquiring and at least acquiring purchase data of a plurality of products, market positioning data of the plurality of products, marketing data of the plurality of products, sales data of the plurality of products, logistics data of the plurality of products, storage data of the plurality of products, full life cycle data of the plurality of products and enterprise financial condition data; and analyzing the enterprise carbon resource data to obtain enterprise operation safety data, and judging whether management intervention is started or not according to the enterprise operation safety data. According to the invention, the functions of the existing electronic commerce ERP management system are expanded, the business development and management requirements of enterprises are further met, the internal communication cost and operation cost increase of the enterprises are reduced, and the loss or potential loss risk of the enterprises is reduced.

Description

Technical Field

[0001] The present invention application relates to the technical field of e-commerce big data management, and more specifically, to an e-commerce ERP management system and a management method thereof. Background Art

[0002] Enterprise Resource Planning (ERP) is a management platform based on information technology and systematic management ideas to provide decision-making and operation means for enterprise decision-makers and employees. It is used to improve enterprise business processes to enhance the core competitiveness of enterprises. The existing ERP management system has developed into the e-commerce ERP management system stage. The e-commerce ERP management system usually includes: production resource management functions, manufacturing resource management functions, financial resource management functions, sales resource management functions, procurement resource management functions, quality resource management functions, business process management functions, product data management functions, logistics resource management functions, human resource management functions and statistical analysis functions, etc. In this way, the e-commerce ERP management system can conduct real-time dynamic integrated enterprise information management for enterprises, regions, industries, etc., and complete the integration, analysis and management of internal and external resources of the enterprise.

[0003] However, with the development of the digital economy and the carbon-neutral economy, various external business activities of enterprises have also extended to the Internet of Things, big data, full life cycle management, carbon-neutral transactions, etc., which have put forward new functional requirements for the existing e-commerce ERP management systems, such as providing marketing traffic management, full life cycle management, carbon resource management, etc. Correspondingly, the existing e-commerce ERP management systems need to further support the acquisition, processing and push of data streams such as marketing traffic, full life cycle, carbon neutrality, etc., so as to complete the matching, connection and integration of internal and external information of the enterprise, and then meet the needs of the enterprise's business development and operation management, and reduce the internal and external communication and operation costs of the enterprise. Accordingly, the present invention application provides an e-commerce ERP management system and its management method. Summary of the invention

[0004] Based on this, the present invention application provides an e-commerce ERP management system and a management method thereof, aiming to partially or completely solve the above technical problems. The present invention application is implemented through the following technical solutions:

[0005] In a first aspect, the present invention provides an e-commerce ERP management system, including: a procurement unit, a product unit, a marketing unit, a sales unit, a financial unit, a logistics unit, a storage unit, a carbon resource unit, an after-sales unit and a server;

[0006] A purchasing unit, at least used to manage the purchasing data of multiple products and send it to the server;

[0007] A product unit, at least used to manage market positioning data and manufacturing data of multiple products and send them to a server;

[0008] A marketing unit manages marketing data of the plurality of products based on at least the market positioning data of the plurality of products and sends the marketing data to the server;

[0009] A sales unit, at least used to manage sales data of multiple products and send the data to a server;

[0010] The financial unit is used to manage the enterprise's financial status data and send it to the server;

[0011] The logistics unit is used to manage the logistics data of multiple products and send them to the server;

[0012] The storage unit is used to manage the storage data of multiple products and send them to the server.

[0013] A carbon resource unit, at least used to manage the enterprise carbon resource data and send it to the server;

[0014] The after-sales unit is used to manage the full life cycle data of multiple products and send it to the server;

[0015] The server analyzes at least the procurement data of multiple products, the market positioning data of multiple products, the marketing data of multiple products, the sales data of multiple products, the logistics data of multiple products, the warehousing data of multiple products, the full life cycle data of multiple products, the enterprise financial status data, and the enterprise carbon resource data to obtain the enterprise operation safety data, and determines whether to initiate management intervention based on the enterprise operation safety data; the enterprise operation safety data includes the procurement risk data, marketing risk data, logistics risk data, warehousing risk data, full life cycle management risk data, enterprise financial risk data, enterprise carbon resource risk data, a first operation safety index OS1, and a second operation safety index OS2 of multiple products. The first operation safety index OS1 is calculated through the procurement risk data, logistics risk data, and warehousing risk data of multiple products, and the second operation safety index OS2 is calculated through the marketing risk data, full life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data of multiple products.

[0016] Optionally, the procurement data of multiple products includes material data, product manufacturing equipment, marketing equipment, and carbon resource equipment procurement of multiple products; the logistics data of multiple products includes product order data and product transportation data of multiple products; the storage data of multiple products includes inventory data, inbound and outbound data, product quality data, and storage equipment data of multiple products;

[0017] The product unit includes a design management unit and a manufacturing management unit; the design management unit manages the market positioning data of multiple products at least according to the development and design conditions of different products; the manufacturing management unit obtains the manufacturing data of multiple products at least according to the manufacturing conditions of different products;

[0018] The marketing unit includes a print media unit and an electronic media unit. The print media unit manages the print marketing data of multiple products at least based on the market positioning data of multiple products; the electronic media unit manages the electronic marketing data of multiple products at least based on the market positioning data of multiple products; the print media unit is at least used to manage the print marketing data of multiple products; the print marketing data includes newspaper marketing data and magazine marketing data; the electronic media unit is at least used to manage the electronic marketing data of multiple products, and the electronic marketing data includes live broadcast marketing data, social marketing data, e-commerce marketing data, and e-commerce marketing data; the sales data of each product includes at least the total order volume, total sales, total sales volume, customer data, total gross profit margin, total cost of each product, as well as the overall sales, overall sales volume, overall customer data, overall gross profit margin, and overall cost of the enterprise; the enterprise carbon resource data includes: enterprise carbon emission data and enterprise carbon indicator data; the full life cycle data of each product includes at least: product basic data, product location data, and product operation data.

[0019] Optionally, the calculation formula of the first operation safety index OS1 is as follows:

[0020] OS1=BR+CR+SR; BR is 0 or 1, CR is 0 or 1, and SR is 0 or 1; BR is the purchasing risk of multiple products, CR is the logistics risk of multiple products, and SR is the storage risk of multiple products;

[0021] The calculation formula of the second operation safety index OS2 is as follows:

[0022] OS2=P1*MR+P2*LR+P3*FR+P4*TR; wherein, MR is the marketing risk of multiple products, P1 is the marketing risk coefficient, 0%≤P1≤300%; LR is the risk of the entire life cycle management risk, P2 is the risk coefficient of the entire life cycle management risk, 0%≤P2≤300%; FR is the enterprise financial risk, P3 is the enterprise financial management risk coefficient, 0%≤P3≤300%; TR is the enterprise carbon resource risk, P4 is the enterprise carbon resource risk coefficient, 0%≤P4≤200%.

[0023] Optionally, the calculation formula of the marketing risk MR of multiple products is as follows:

[0024] MR = (LMR + EMR + SMR) / 3; where LMR is either 0 or 1, EMR is either 0 or 1, and SMR is either 0 or 1. LMR is the total risk of live broadcast marketing of multiple products, EMR is the total risk of e-commerce marketing of multiple products, and SMR is the total risk of social marketing of multiple products.

[0025] The calculation formula for the life cycle management risk LR of multiple products is as follows:

[0026] TR = (MLR + DLR + RLR) / 3; where MLR is either 0 or 1, DLR is either 0 or 1, RLR is either 0 or 1, MLR is the total product maintenance risk of multiple products, DLR is the total product abandonment risk of multiple products, and RLR is the total product recycling risk of multiple products;

[0027] The calculation formula of enterprise financial risk FR is as follows:

[0028] FR = (MFR + PFR + DFR) / 3; where MFR is 0 or 1, PFR is 0 or 1, DFR is 0 or 1, MFR is cash flow risk, PFR is profitability risk, and DFR is debt risk;

[0029] The calculation formula of enterprise carbon resource risk TR is as follows:

[0030] TR=(TTR+ETR) / 2; TTR is 0 or 1, ETR is 0 or 1, TTR is the carbon trading risk, and ETR is the carbon emission risk.

[0031] Optionally, the enterprise operation safety data further includes: a third operation safety index OS3, and the calculation formula of the third operation safety index OS3 is as follows: OS3=|NSR1-NSR0| / 11;

[0032] NSR1 is the number of 1s in LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR, and NSR0 is the number of 0s in LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR.

[0033] Optionally, the enterprise operation safety data also includes an enterprise operation safety index OS, and the calculation formula of the enterprise operation safety index OS is as follows: OS=|OS2-OS1|*OS3-OS1*OS2 / 11.

[0034] In a second aspect, the present invention provides an e-commerce ERP management method, which adopts an e-commerce ERP management system described in any one of the first aspects above, and includes the following steps:

[0035] Step S100: Acquire procurement data of multiple products, market positioning data of multiple products, marketing data of multiple products, sales data of multiple products, logistics data of multiple products, warehousing data of multiple products, full life cycle data of multiple products, enterprise financial status data, and enterprise carbon resource data;

[0036] Step S200: Analyze at least the procurement data of multiple products, the market positioning data of multiple products, the marketing data of multiple products, the sales data of multiple products, the logistics data of multiple products, the warehousing data of multiple products, the full life cycle data of multiple products, the enterprise financial status data, and the enterprise carbon resource data to obtain enterprise operation safety data, the enterprise operation safety data including the procurement risk data of multiple products, the marketing risk data, the logistics risk data, the warehousing risk data, the full life cycle management risk data, the enterprise financial risk data, the enterprise carbon resource risk data, a first operation safety index OS1, and a second operation safety index OS2. The first operation safety index OS1 is calculated through the procurement risk data, the logistics risk data, and the warehousing risk data of multiple products, and the second operation safety index OS2 is calculated through the marketing risk data, the full life cycle management risk data, the enterprise financial risk data, and the enterprise carbon resource risk data of multiple products.

[0037] Step S300: Determine whether to initiate management intervention based on enterprise operation safety data.

[0038] Optionally, in step S200, the calculation formula of the first operation safety index OS1 is as follows:

[0039] OS1=BR+CR+SR; BR is 0 or 1, CR is 0 or 1, and SR is 0 or 1; BR is the purchasing risk of multiple products, CR is the logistics risk of multiple products, and SR is the storage risk of multiple products;

[0040] The calculation formula of the second operation safety index OS2 is as follows:

[0041] OS2=P1*MR+P2*LR+P3*FR+P4*TR; where MR is the marketing risk of multiple products, P1 is the marketing risk coefficient, 0%≤P1≤300%; LR is the risk of the entire life cycle management risk, P2 is the risk coefficient of the entire life cycle management risk, 0%≤P2≤300%; FR is the enterprise financial risk, P3 is the enterprise financial management risk coefficient, 0%≤P3≤300%; TR is the enterprise carbon resource risk, P4 is the enterprise carbon resource risk coefficient, 0%≤P4≤200%;

[0042] The calculation formula for the marketing risk MR of multiple products is as follows:

[0043] MR = (LMR + EMR + SMR) / 3; where LMR is either 0 or 1, EMR is either 0 or 1, and SMR is either 0 or 1. LMR is the total risk of live broadcast marketing of multiple products, EMR is the total risk of e-commerce marketing of multiple products, and SMR is the total risk of social marketing of multiple products.

[0044] The calculation formula for the life cycle management risk LR of multiple products is as follows:

[0045] TR = (MLR + DLR + RLR) / 3; where MLR is either 0 or 1, DLR is either 0 or 1, RLR is either 0 or 1, MLR is the total product maintenance risk of multiple products, DLR is the total product abandonment risk of multiple products, and RLR is the total product recycling risk of multiple products;

[0046] The calculation formula of enterprise financial risk FR is as follows:

[0047] FR = (MFR + PFR + DFR) / 3; where MFR is 0 or 1, PFR is 0 or 1, DFR is 0 or 1, MFR is cash flow risk, PFR is profitability risk, and DFR is debt risk;

[0048] The calculation formula of enterprise carbon resource risk TR is as follows:

[0049] TR=(TTR+ETR) / 2; TTR is 0 or 1, ETR is 0 or 1, TTR is the carbon trading risk, and ETR is the carbon emission risk.

[0050] Optionally, in step S200, the enterprise operation safety data further includes: a third operation safety index OS3, and the calculation formula of the third operation safety index OS3 is as follows:

[0051] OS3=|NSR1-NSR0| / 11; NSR1 is the number of 1s among LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR, and NSR0 is the number of 0s among LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR.

[0052] Optionally, in step S300, the enterprise operation safety data includes an enterprise operation safety index OS, and the calculation formula of the enterprise operation safety index OS is as follows:

[0053] OS=|OS2-OS1|*OS3-OS1*OS2 / 11;

[0054] Determining whether to initiate management intervention based on enterprise operation security data includes: when OS≥R1, initiate management intervention; when OS<R1, do not initiate management intervention, where R1 is a preset value or preset range.

[0055] Advantageous technical effects of the present invention application:

[0056] (1) In the present invention application, based on the existing e-commerce ERP management system, at least the e-commerce ERP management system is integrated with: market positioning functions for multiple products, marketing management functions for multiple products, sales management functions for multiple products, logistics management functions for multiple products, warehousing management functions for multiple products, full life cycle management functions for multiple products, enterprise financial management functions, and enterprise carbon resource management functions; moreover, the e-commerce ERP management system can also perform overall analysis based on the procurement data, market positioning data, marketing data, sales data, logistics data, warehousing data, full life cycle data, enterprise financial status data, and enterprise carbon resource data of multiple products to obtain enterprise operation security data for managing enterprise operation security. In this way, it can not only meet the needs of marketing, sales, logistics, transportation, delivery to customers, and full life cycle management of multiple products of the enterprise, but also meet the management requirements of the enterprise's own commercial compliance risk controllability and high digital intelligence, and can also achieve the green ecological and environmental protection goal of the enterprise's own carbon compliance, reducing the internal communication cost and operation cost increase of the enterprise, reducing the risk of direct or potential losses of the enterprise, and enhancing the value, economic value, social value, and environmental protection value of the e-commerce ERP management system.

[0057] (2) In the present invention application, based on the obtained procurement data, market positioning data, marketing data, sales data, logistics data, warehousing data, full life cycle data, financial status data, and enterprise carbon resource data, the first operation security index OS1 is further used to analyze the risks of the enterprise's procurement management, logistics management, and warehousing management, and the second operation security index OS2 and the third operation security index OS3 are used to analyze the risks of the enterprise's marketing management, full life cycle management, financial status management, and carbon resource management. Based on the first operation security index OS1, the second operation security index OS2, and the third operation security index OS3, the first operation security index OS1, the second operation security index OS2, and the third operation security index OS3 are also comprehensively used to evaluate the enterprise operation security index OS, thereby completing the evaluation of enterprise operation security from multiple dimensions. Description of the Drawings

[0058] Figure 1 is a schematic diagram of an e-commerce ERP management system of the present invention application;

[0059] Figure 2 is a schematic diagram of an electronic media unit of the present invention;

[0060] Figure 3 It is a schematic diagram of the source of the enterprise operation safety index applied by the present invention;

[0061] Figure 4 It is a schematic diagram of an e-commerce ERP management method applied by the present invention;

[0062] Description of the drawings: procurement unit—10, product management unit—20, design management unit—201, manufacturing management unit—202, marketing unit—30, print media unit—301, electronic media unit—302, live broadcast platform module—3021, e-commerce platform module—3022, social platform module—3023, TV platform module—3024, sales unit—40, finance unit—50, logistics unit—60, warehousing unit—70, carbon resource unit—80, after-sales unit—90, server—S. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure more clear, the embodiments of the present disclosure are further described in detail below in conjunction with the accompanying drawings and embodiments; it should be understood that the specific embodiments described herein are only used to explain the embodiments of the present disclosure and are not used to limit the embodiments of the present disclosure;

[0064] The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the limiting conditions for the implementation of the present invention, so they have no substantial technical significance. Any structural modification, change in proportion relationship or adjustment in size, without affecting the effects and purposes that can be produced by the present invention, should still fall within the scope of the technical contents disclosed by the present invention; at the same time, the terms such as "and" and "or" quoted in this specification are only for the convenience of description, and are not used to limit the scope of implementation. The change or adjustment of their relative relationship should also be regarded as the scope of implementation of the present invention without substantially changing the technical contents; in addition, the various embodiments of the present invention are not independent of each other, but can be combined;

[0065] The terms "first", "second" and "third" are used for descriptive purposes only and should not be understood as indicating or suggesting relative importance or implicitly indicating the number of the indicated technical features; thus, the features defined as "first", "second" and "third" may explicitly or implicitly include one or more of the features, and in the description of the present application, unless otherwise specified, "multiple" means two or more.

[0066] First, as Figure 1 As shown, the present invention provides an e-commerce ERP management system, including: a purchasing unit 10, a product unit 20, a marketing unit 30, a sales unit 40, a financial unit 50, a logistics unit 60, a warehousing unit 70, a carbon resource unit 80, an after-sales unit 90 and a server S;

[0067] The purchasing unit 10 is at least used to manage the purchasing data of multiple products and send it to the server S; the purchasing data of multiple products includes material data of multiple products, product manufacturing equipment, marketing equipment, and carbon resource equipment procurement.

[0068] In some embodiments, the material data includes at least the raw materials used to manufacture the product itself, the product manufacturing equipment includes at least the manufacturing equipment for each process link, the marketing equipment includes at least telephone equipment and webcast equipment, and the carbon resource equipment includes at least the enterprise carbon emission calculation equipment;

[0069] The product unit 20 is at least used to manage the market positioning data and manufacturing data of multiple products and send them to the server S; the product unit 20 includes a design management unit 201 and a manufacturing management unit 202; the design management unit 201 manages the market positioning data of multiple products at least according to the development and design conditions of different products; the manufacturing management unit 202 obtains the manufacturing data of multiple products at least according to the manufacturing conditions of different products;

[0070] In some embodiments, the design management unit 201 manages market positioning data of multiple products, and the market positioning data may at least include: multiple products that have not been launched, have been launched, and have been delisted, and the market positioning data may include market data of multiple products positioned in different countries and regions around the world; the manufacturing management unit 202 can obtain the manufacturing conditions of different products and obtain the manufacturing data of multiple products, and the manufacturing data may include the manufacturing data of multiple products in different countries and regions around the world.

[0071] The marketing unit 30 manages the marketing data of multiple products at least based on the market positioning data of multiple products and sends them to the server S; the marketing unit 30 includes a print media unit 301 and an electronic media unit 302. The print media unit 301 manages the print marketing data of multiple products at least based on the market positioning data of multiple products; the electronic media unit 302 manages the electronic marketing data of multiple products at least based on the market positioning data of multiple products.

[0072] In some embodiments, the print media unit 301 is at least used to manage the print marketing data of multiple products. The print marketing data may include newspaper marketing data and magazine marketing data. The newspaper marketing data may include newspaper advertisement data. The magazine marketing data may include magazine advertisement data. In this way, at least newspaper advertisements and magazine advertisement data can be managed; the electronic media unit 302 is at least used to manage the electronic marketing data of multiple products. The electronic marketing data includes live broadcast marketing data, social marketing data, e-commerce marketing data, and e-commerce marketing data. In this way, live broadcast marketing data, social marketing data, e-commerce marketing data, and television marketing data can also be managed. Exemplarily, it can be provided to obtain live broadcast marketing data through common live broadcast platforms (such as Douyin, self-media, etc.), obtain social marketing data through common social platforms (such as WeChat, Weibo, etc.), obtain e-commerce marketing data through common e-commerce platforms (such as JD.com, Taobao, etc.), and obtain television marketing data through common television (such as online TV, etc.) platforms.

[0073] The sales unit 40 is at least used to manage the sales data of multiple products and send them to the server S; the sales data of each product at least includes the total order quantity, total sales, total sales volume, customer data, total gross profit margin, total cost of each product, as well as the company's overall sales, overall sales volume, overall customer data, overall gross profit margin, and overall cost.

[0074] In some embodiments, the sales unit 40 can manage the sales data of multiple products, and the sales data of each product at least includes the order quantity, sales volume, sales volume, customer data, gross profit margin, and total cost of each product. For each product, by setting the sales price, buyer's shipping fee, product cost, platform fee, storage fee, delivery fee, tax, tariff, marketing fee, return fee and other fees of each product, it can be calculated that the gross profit of each product = sales revenue of each product - cost of each product, gross profit margin of each product = (sales revenue of each product - cost of each product) / revenue; sales revenue of each product = sales price + buyer's shipping fee, cost of each product = product cost + platform fee + storage fee + delivery fee + tax + tariff + marketing fee + return fee + other fees. On this basis, each product usually has a different order volume. According to the order volume of each product, the total sales, total sales volume, total gross profit margin, and total cost of each product can be further calculated. Total sales = sales revenue of each product * total sales volume, total cost = cost of each product * total sales volume, and total gross profit margin = (total sales - total cost) / total sales. Therefore, based on the total sales, total sales volume, total gross profit margin, and total cost of each product, the company's overall sales, overall sales volume, overall customer data, overall gross profit margin, and overall cost can be calculated. Overall sales = the sum of the total sales of multiple products, overall cost = the sum of the total costs of multiple products, overall gross profit = overall sales - overall cost, and overall gross profit margin = (overall sales - overall cost) / overall sales.

[0075] In some embodiments, the sales unit 40 can also obtain customer data for each product, and the customer data includes: basic customer information data (for example, including the customer's name, address, telephone number, owner, business manager, legal representative, corporate organizational form, etc.), customer transaction data (for example, including the customer's purchase history, order information, purchase date, shopping products, online shopping source, etc.), customer behavior data (for example, recording the customer's purchasing habits, preferences, needs and data on interactions with the company, such as website browsing data, product usage data, etc.), customer promotion data (for example, including information on promotional activities in which the customer participates, such as coupon usage, discount information, etc.), customer credit data (for example, the customer's credit status, such as repayment record, credit score, etc.), customer business data (for example, including sales performance, the quality of business managers and salesmen, and the relationship with other competitors, etc.), customer portrait data (for example, including personality, hobbies, religious beliefs, experience background, etc.), and customer follow-up data (for example, including communication records with customers, service feedback, customer satisfaction, etc.).

[0076] In some embodiments, on the basis of obtaining the basic customer information data, customer transaction data, customer behavior data, customer credit data, customer business data, customer portrait data, and customer follow-up data of each product, the overall customer data can be further obtained, and the overall customer data can include: customer grade data, customer distribution data, customer contribution data, customer follow-up data, customer trend data, etc. Customer grade data can include Class A customers, Class B customers, Class C customers, and other customers, customer distribution data can include regional distribution data, industry distribution data, and personnel distribution data; customer contribution data can include customer sales contribution data for the current year, customer historical sales contribution data, customer gross profit margin contribution data, and customer cost contribution data; customer follow-up data can include customer visit times data, customer demand data, customer feedback data, and customer service satisfaction data, and customer trend data can include customer purchase trend data, customer preference trend data, customer credit trend data, etc.

[0077] The financial unit 50 is at least used to manage the enterprise's financial status data and send it to the server S.

[0078] In some embodiments, the enterprise financial status data includes: debt-paying ability data, operating ability data, profitability data and development ability data, the debt-paying ability data includes: current ratio, quick ratio and debt-to-asset ratio, current ratio = current assets / current liabilities, quick ratio = quick assets / current liabilities, debt-to-asset ratio = total liabilities / total assets; the operating ability data includes: accounts receivable turnover rate (times), inventory turnover rate (times), total asset turnover rate, fixed asset turnover rate, accounts receivable turnover rate (times) = net operating income / average accounts receivable balance, inventory turnover rate (times) = cost of goods sold / average inventory balance, total asset turnover rate = net operating income / average total assets, fixed asset turnover rate = net operating income / average net value of fixed assets; Profitability data include: gross profit margin of main business, profit margin of main business, net asset rate, return on net assets, gross profit margin of main business = gross profit / net income of main business, profit margin of main business = profit / net income of main business, net asset rate = net profit / average total assets, return on net assets = net profit / average net assets; development capacity data include: sales growth rate, capital accumulation rate, total asset growth rate, fixed asset renewal rate, sales growth rate = sales growth this year / total sales last year = (sales this year-sales last year) / total sales last year, capital accumulation rate = owner's equity growth this year / owner's equity at the beginning of the year, total asset growth rate = total asset growth this year / total assets at the beginning of the year, fixed asset renewal rate = average net fixed asset value / average original fixed asset value. In this way, through the financial status data of the enterprise, it is possible to analyze the financial status and operating results of the enterprise, judge investment risks, understand the cash flow status, survival status, assets and liabilities status of the enterprise, and judge whether the enterprise has operating risks, debt repayment risks, illegal and irregular behaviors, etc.

[0079] The logistics unit 60 is at least used to manage the logistics data of multiple products and send them to the server S; the multiple product logistics data include product order data and product transportation data of multiple products.

[0080] In some embodiments, product order data includes information such as the source, destination, recommended transportation method, type and quantity of goods for each product order, and product transportation data includes information such as the origin, destination, transportation tool, time and cost. On this basis, by analyzing product order data, transportation capacity can be adjusted in a timely manner to ensure that all orders are delivered to customers on time; by analyzing product transportation data, delays caused by traffic congestion, limited transportation tools, etc. can be avoided. These data help companies to adjust transportation routes and transportation methods in a timely manner, optimize product logistics and transportation processes, improve product transportation efficiency, and reduce product transportation costs, thereby improving the overall operational efficiency of the company and customer delivery satisfaction.

[0081] The storage unit 70 is at least used to manage the storage data of multiple products and send it to the server S; the storage data of multiple products includes inventory data, inbound and outbound data, product quality data, and storage equipment data of multiple products.

[0082] In some embodiments, inventory data includes raw material data and product inventory data. Raw material data includes the quantity and status of raw materials. Product inventory data includes the inventory quantity, inventory location, and product status of each product. Inbound and outbound data includes the inbound and outbound status of products, reflecting the inventory flow status of products. Product quality data includes product quality grade data and product damage and scrap data. Storage equipment data includes the number of storage equipment, storage equipment operation data, and storage equipment maintenance data. On this basis, the quality of products can be monitored through testing equipment, and the storage equipment operation data can be monitored through monitoring equipment, thereby improving the utilization rate of storage equipment.

[0083] The carbon resource unit 80 is at least used to manage the enterprise carbon resource data and send it to the server S; the enterprise carbon resource data includes: enterprise carbon emission data and enterprise carbon index data.

[0084] In some embodiments, corporate carbon emission data can usually be calculated using the mass balance method. The mass balance method calculates the amount of carbon in the input material that is oxidized and emitted in the form of carbon dioxide by establishing the relationship between the mass of the input material, the mass of the output material, and the mass of the emission material. The calculation formula for corporate carbon emissions using the mass balance method is: corporate carbon emissions = carbon mass in the input material - carbon mass in the output material; corporate carbon index data includes: the amount of greenhouse gas allowed to be emitted by the enterprise in a certain period of time, which is usually allocated by the government or relevant agencies based on the historical carbon emissions and emission reduction targets of the enterprise. In this way, the corporate carbon resource data can be known, which is convenient for the management of corporate carbon resources.

[0085] The after-sales unit 90 is at least used to manage the full life cycle data of multiple products and send them to the server S; the full life cycle data of each product at least includes: product basic data, product location data, and product operation data.

[0086] In some embodiments, basic product data includes product type, product serial number, actual product production time, product design life, product location data includes the current country and region of the product, and product operation data includes whether the product is in service, product maintenance times, and product repair information. On this basis, the current status of the product can be obtained, which can be used for subsequent server analysis of the product life cycle.

[0087] Server S analyzes at least the procurement data of multiple products, the market positioning data of multiple products, the marketing data of multiple products, the sales data of multiple products, the logistics data of multiple products, the warehousing data of multiple products, the full life cycle data of multiple products, the enterprise financial status data, and the enterprise carbon resource data to obtain the enterprise operation safety data, and determines whether to initiate management intervention based on the enterprise operation safety data; the enterprise operation safety data includes the procurement risk data, marketing risk data, logistics risk data, warehousing risk data, full life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data of multiple products.

[0088] In some embodiments, procurement risks of multiple products include material risk data, product manufacturing risk data, etc.; marketing risk data of multiple products include live streaming marketing risk data, e-commerce marketing risk data, social marketing risk data, etc.; logistics risk data of multiple products include transportation risk data, etc.; warehousing risk data of multiple products include inventory risk data, etc.; corporate financial risk data includes cash flow risk data, profitability risk data, debt risk data, etc.; corporate carbon resource risk data includes carbon trading risk data, carbon emission risk data, etc.; full life cycle management risk data includes product maintenance risk data, product abandonment risk data, product recycling risk data, etc.

[0089] In the present invention application, on the basis of the existing e-commerce ERP management system, at least the e-commerce ERP management system is integrated with: market positioning functions of multiple products, marketing management functions of multiple products, sales management functions of multiple products, logistics management functions of multiple products, warehousing management functions of multiple products, full life cycle management functions of multiple products, enterprise financial management functions, and enterprise carbon resource management functions; and the e-commerce ERP management system can also conduct an overall analysis based on the procurement data of multiple products, market positioning data of multiple products, marketing data of multiple products, sales data of multiple products, logistics data of multiple products, warehousing data of multiple products, full life cycle data of multiple products, enterprise financial status data, and enterprise carbon resource data, and obtain enterprise operation safety data to manage enterprise operation safety, so as to meet the needs of marketing, sales, logistics, transportation, delivery and full life cycle management of multiple products of the enterprise, and meet the controllable and highly digital and intelligent management of the enterprise's own commercial compliance risks, and also achieve the green ecological and environmental protection goals of the enterprise's own carbon compliance, reduce the internal communication costs and operating cost increases of the enterprise, reduce the direct losses or potential loss risks of the enterprise, and enhance the value, economic value, social value and environmental protection value of the e-commerce ERP management system.

[0090] Optionally, the electronic marketing data includes the total electronic marketing yield SC, the total electronic marketing expenditure EC and the total electronic marketing sales ES. The electronic marketing data includes live broadcast marketing data, social marketing data and e-commerce marketing data. The live broadcast marketing data includes the live broadcast marketing yield L16, live broadcast sales L14 and live broadcast expenditure L10. The social marketing data includes the social marketing yield S16, social sales S14 and social advertising expenditure S10. The e-commerce marketing data includes the e-commerce marketing yield E16, e-commerce advertising sales E14 and e-commerce advertising expenditure E10.

[0091] In this application, electronic marketing data includes electronic marketing yield SC, electronic marketing expenditure EC and electronic marketing sales ES, live broadcast marketing data includes live broadcast marketing yield L16, live broadcast sales L14, live broadcast expenditure L10, social marketing data includes social marketing yield S16, social sales S14, social advertising expenditure S10, e-commerce marketing data includes e-commerce marketing yield E16, e-commerce advertising sales E14, e-commerce advertising expenditure E10. In this way, live broadcast marketing data, social marketing data, e-commerce marketing data and TV marketing data can also be managed.

[0092] In some embodiments, in daily life, compared with the print media unit 301, the electronic media unit 302 has become the mainstream way for people to buy products in daily life. The electronic media unit 302 includes a live broadcast platform module 3021, an e-commerce platform module 3022, a social platform module 3023, and a TV platform module 3024. It should be noted that the TV platform module 3024 is not necessary considering the cost of the enterprise. In some embodiments, the electronic media unit 302 includes live broadcast platform marketing data, social platform marketing data, and e-commerce platform marketing data.

[0093] In some embodiments, the live broadcast platform marketing data includes: the live broadcast platform click-through rate L11, which is the ratio of sellers clicking into the live broadcast room during display, and the value is calculated by dividing the click volume by the exposure volume, where the exposure volume refers to the number of exposures in the live broadcast room, indicating the number of times the ad push users browse the display, and the click volume refers to the number of clicks in the live broadcast room, indicating the number of times the live broadcast room is clicked after being browsed and displayed by users; the average live broadcast cost per person L12 is the ratio of the live broadcast cost to the total number of viewers in the live broadcast room, and the live broadcast cost L10 indicates the cost incurred for live broadcasting and exposing products in the platform live broadcast room; the live broadcast platform order volume L13 is the number of orders for live broadcast products and other products purchased at the set time; the live broadcast sales volume L14 is the total sales volume of live broadcast products and other products purchased at the set time; the live broadcast conversion rate L15 refers to the ratio of the live broadcast platform order volume after the live broadcast to the total number of viewers in the live broadcast room, which is used to measure the level of the live broadcast channel in converting viewers into transaction users; the live broadcast marketing yield L16 is the ratio of the live broadcast sales volume L14 to the live broadcast cost L10.

[0094] In some embodiments, social platform marketing data includes: social platform advertising click-through rate S11, which is the ratio of advertisements clicked by buyers when displayed, and the value is calculated by dividing the number of clicks by the number of exposures, where the number of exposures refers to the number of advertisement exposures, indicating the number of times the advertisement is viewed and displayed by users who push the advertisement, and the number of clicks refers to the number of advertisement clicks, indicating the number of times the advertisement is clicked after being viewed and displayed by users who push the advertisement; the average click fee on the social platform S12 is the ratio of social advertising expenditure to clicks, indicating the cost generated by each user click behavior, and the social advertising expenditure S10 indicates the cost generated by user click behavior or exposure on the e-commerce platform; the number of social platform advertising orders S13 is the number of orders for advertising products and other products purchased at a set time; the social advertising sales S14 is the total sales of advertising products and other products purchased at a set time; the advertising conversion rate S15 refers to the ratio of advertising orders to clicks, which is used to measure the level at which advertising channels convert ordinary users into transaction users; the social marketing yield S16 is the ratio of social advertising sales E14 to social advertising expenditure S10.

[0095] In some embodiments, the marketing data of the e-commerce platform includes: the click-through rate of e-commerce platform advertisements E11, which is the ratio of advertisements clicked by buyers when displayed, and the value is calculated by dividing the number of clicks by the number of exposures, where the number of exposures refers to the number of advertisement exposures, indicating the number of times the advertisement is viewed and displayed by users who push the advertisement, and the number of clicks refers to the number of advertisement clicks, indicating the number of times the advertisement is clicked after being viewed and displayed by users who push the advertisement; the average click fee of the e-commerce platform E12, which is the ratio of the e-commerce advertisement expenditure to the number of clicks, indicating the cost generated by each user click behavior; the e-commerce advertisement expenditure E10, which indicates the cost generated by user click behavior or exposure of the e-commerce platform; the number of e-commerce platform advertisement orders E13, which is the number of orders for advertisement products and other products purchased at a set time; the e-commerce advertisement sales E14, which is the total sales of advertisement products and other products purchased at a set time; the e-commerce conversion rate E15, which is the ratio of advertisement orders to clicks, and is used to measure the level at which advertising channels convert ordinary users into transaction users; the e-commerce marketing rate of return E16 is the ratio of the e-commerce advertisement sales E14 expenditure to the e-commerce advertisement expenditure E10.

[0096] In some embodiments, the set time may be 1 day or 2 days or 3 days or 5 days or 7 days or 15 days or 30 days or 90 days or 180 days or 365 days.

[0097] In some embodiments, the total e-marketing cost refers to the sum EC of the live broadcast cost L10, social advertising cost S10, and e-commerce advertising cost E10 at the set time, that is, EC=L10+S10+E10. The total e-marketing sales refers to the sum ES of the live broadcast sales L14, social advertising sales S14, and e-commerce advertising sales E14 at the set time, that is, ES=L14+S14+E14. The total e-marketing rate of return ESC is the ratio of the total e-marketing sales ES to the total e-marketing cost EC, that is, ESC=ES / EC=(L14+S14+E14) / (L10 +S10+E10), the total return on live marketing LC is the ratio of live sales L14 to total e-marketing expenditure EC, that is, LC=L14 / EC=L14 / (L10+S10+E10), the total return on social marketing SC is the ratio of social advertising sales S14 to total e-marketing expenditure EC, that is, SC=S14 / EC=S14 / (L10+S10+E10), and the total return on e-commerce marketing EC is the ratio of e-commerce advertising sales E14 to total e-marketing expenditure EC, that is, EC=E14 / EC=E14 / (L10+S10+E10). In this way, we can see the comparison of marketing effects between live marketing, social advertising marketing, and e-commerce advertising marketing, which can help companies choose a reasonable combination of one or more marketing methods at a reasonable cost.

[0098] Optionally, the enterprise carbon resource data also includes: enterprise carbon difference rate data, carbon market carbon trading data; carbon market carbon trading data includes: carbon trading average price data, carbon trading volume activity data, carbon trading volume efficiency data; carbon trading average price data includes carbon trading daily average price, carbon trading weekly average price, carbon trading monthly average price, carbon trading quarterly average price, carbon trading annual average price; carbon trading volume activity data includes carbon trading volume daily activity, carbon trading volume weekly activity, carbon trading volume quarterly activity, carbon trading volume annual activity; carbon trading volume efficiency data includes carbon trading daily volume efficiency, carbon trading weekly volume efficiency, carbon-to-carbon trading quarterly volume efficiency, carbon trading volume annual efficiency.

[0099] In some embodiments, based on the enterprise carbon emission data C1 and carbon index data C3, the enterprise carbon balance rate C=(C3-C1) / C3 can be calculated, the carbon trading average price CP refers to the total carbon trading transaction amount divided by the total carbon trading transaction volume at a set time, the carbon trading transaction volume activity NP refers to the number of carbon transactions at a set time divided by the total carbon trading transaction volume, and the carbon trading sales efficiency SP refers to the total carbon trading transaction amount at a set time divided by the total number of carbon transactions. By analyzing these data, the company's existing carbon resources, carbon market efficiency, participant activity, market carbon trading price rationality, and future trends in the carbon market can be evaluated, thereby providing a decision-making basis for corporate carbon resource management.

[0100] In some embodiments, the carbon trading market usually includes: current price information (opening price, highest price, lowest price, average transaction price, closing price), current price changes (rise and fall) and current trading volume (total transaction volume, total transaction amount, listing agreement transaction volume, listing agreement transaction amount, bulk agreement transaction volume, bulk agreement transaction amount), etc. On this basis, the average price data of carbon trading includes the average price of carbon trading day, the average price of carbon trading week, the average price of carbon trading month, the average price of carbon trading quarter, and the average price of carbon trading year; the activity data of carbon trading volume includes the daily activity of carbon trading volume, the weekly activity of carbon trading volume, the quarterly activity of carbon trading volume, and the annual activity of carbon trading volume; the efficiency data of carbon trading volume includes the daily transaction efficiency of carbon trading volume, the weekly transaction efficiency of carbon trading volume, the quarterly transaction efficiency of carbon trading volume, and the annual efficiency of carbon trading volume. In this way, the enterprise carbon trading, carbon trading market data, and carbon trading market dynamics can be obtained, which can provide a decision-making basis for the enterprise carbon resource management.

[0101] Optionally, the full life cycle data of each product also includes product age index data, product maintenance index data, product recycling index data, and product abandonment index data.

[0102] In some embodiments, based on the product type, product serial number, actual time of product production, product design life, current country and region of the product, whether the product is in service, number of product maintenance, product maintenance information, and sales volume of each product, the product age index can be calculated as the difference between the design life of the product and the service life of the product divided by the design life of the product, the product maintenance index is the number of product maintenance divided by the service life of the product, the product recycling index is the number of product recycling divided by the sales volume of each product, and the product abandonment index is the number of product abandonment divided by the sales volume of each product. In this way, the age index of the product in use can be determined through the age index data, and the different life cycle states of the product can be correspondingly guided through the age index, so that multiple product life cycle situations can be analyzed, and predictive maintenance of the product can be achieved, and sales personnel or after-sales personnel can be scientifically guided to whether to perform maintenance management on the customer's in-service products. It can also provide decision-making basis for product design management, manufacturing management, marketing management, sales management and carbon resource management, improve the product service capabilities of the enterprise, and promote the effective use of resources and sustainable development of the environment.

[0103] The server analyzes at least the procurement data of multiple products, the market positioning data of multiple products, the marketing data of multiple products, the sales data of multiple products, the logistics data of multiple products, the warehousing data of multiple products, the full life cycle data of multiple products, the enterprise financial status data, and the enterprise carbon resource data to obtain the enterprise operation safety data, and determines whether to initiate management intervention based on the enterprise operation safety data; the enterprise operation safety data includes the procurement risk data, marketing risk data, logistics risk data, warehousing risk data, full life cycle data management risk data, enterprise financial risk data, and enterprise carbon resource risk data of multiple products.

[0104] In some embodiments, procurement risk data of multiple products include material risk data, product manufacturing risk data, etc., marketing risk data of multiple products include live streaming marketing risk data, e-commerce marketing risk data, social marketing risk data, logistics risk data of multiple products include transportation risk data, etc., warehousing risk data of multiple products include inventory risk data, etc., corporate financial risk data includes cash flow risk data, profitability risk data, debt risk data, corporate carbon resource risk data includes carbon trading risk data, carbon emission risk data, and full life cycle management risk data includes product maintenance risk data, product abandonment risk data, product recycling risk data, etc.

[0105] Therefore, based on the purchase data of the above-mentioned multiple products, the market positioning data of multiple products, the marketing data of multiple products, the sales data of multiple products, the logistics data of multiple products, the warehousing data of multiple products, the full life cycle data of multiple products, the enterprise financial status data, and the enterprise carbon resource data, the existing ERP management system independently manages the purchase data, market positioning data, marketing data, sales data, logistics data, warehousing data, full life cycle data, financial status data, and enterprise carbon resource data, and cannot analyze the purchase data, market positioning data, marketing data, sales data, logistics data, warehousing data, full life cycle data, financial status data, and enterprise carbon resource data as a whole to obtain the enterprise operation situation, nor can it analyze and warn the enterprise operation safety and make reasonable management decision intervention. To this end, the applicant has conducted research on this and used the above-mentioned e-commerce ERP management system to help analyze, manage and intervene in the safety of enterprise operations.

[0106] Optionally, the enterprise operational safety data includes a first operational safety index OS1 and a second operational safety index OS2. The first operational safety index OS1 is calculated through procurement risk data, logistics risk data, and warehousing risk data of multiple products. The second operational safety index is calculated through marketing risk data, life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data of multiple products.

[0107] In some embodiments, in normal business of an enterprise, generally speaking, the procurement risk data of multiple products include material risk data, product manufacturing risk data, etc. The results of logistics risk data and product manufacturing risk data are usually risky (which can be represented by 1) or risk-free (which can be represented by 0 risk), and the procurement risk BR of multiple products can be obtained accordingly, and BR takes one of 0 or 1; the logistics risk data CR of multiple products include transportation risk data, etc. The results of transportation risk data are usually risky (which can be represented by 1) or risk-free (which can be represented by 0 risk), and the logistics risk CR of multiple products can be obtained accordingly, and CR takes one of 0 or 1; the storage risk data SR of multiple products include inventory risk data, etc. The results of inventory risk data are usually risky (which can be represented by 1) or risk-free (which can be represented by 0), and the storage risk of multiple products can be obtained accordingly, and SR takes one of 0 or 1. Using the procurement risk of multiple products, the logistics risk of multiple products, and the storage risk of multiple products, the first operation safety index OS1 can be calculated, and the calculation formula of the first operation safety index OS1 is as follows:

[0108] OS1=BR+CR+SR;

[0109] Among them, BR takes one of 0 or 1, CR takes one of 0 or 1, and SR takes one of 0 or 1; BR is the procurement risk of multiple products, CR is the logistics risk of multiple products, and SR is the warehousing risk of multiple products.

[0110] In some embodiments, generally speaking, procurement risk data, logistics risk data, and warehousing risk data are usually problems that can be completely resolved in the actual trading process of the enterprise, and will not pose a serious impact on the operational safety of the enterprise. They are usually consistent with the operating conditions of most existing medium and large-scale enterprises.

[0111] In some embodiments, the second operation safety index OS2 is calculated by using marketing risk data of multiple products, life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data. The calculation formula of the second operation safety index OS2 is as follows:.

[0112] OS2=P1*MR+P2*LR+P3*FR+P4*TR;

[0113] Among them, MR is the marketing risk of multiple products, P1 is the marketing risk coefficient, 0%≤P1≤300%; LR is the life cycle management risk, P2 is the life cycle management risk coefficient, 0%≤P2≤300%; FR is the enterprise financial risk, P3 is the enterprise financial management risk coefficient, 0%≤P3≤300%; TR is the enterprise carbon resource risk, P4 is the enterprise carbon resource risk coefficient, 0%≤P4≤200%.

[0114] In some embodiments, the marketing risk data of multiple products include live broadcast marketing risk data, e-commerce marketing risk data, and social marketing risk data. Accordingly, the usual risk results are risk (which can be represented by 1) and no risk (which can be represented by 0). The risk results can be obtained by machine analysis or artificial mathematical and physical logic deduction and judgment. The marketing risk MR of multiple products includes the total live broadcast marketing risk LMR of multiple products, the total e-commerce marketing risk EMR of multiple products, and the total social marketing risk SMR of multiple products. On this basis, the calculation formula of the marketing risk MR of multiple products is as follows:

[0115] MR = (LMR + EMR + SMR) / 3;

[0116] Among them, LMR takes one of 0 or 1, EMR takes one of 0 or 1, and SMR takes one of 0 or 1. LMR is the total risk of live broadcast marketing of multiple products, EMR is the total risk of e-commerce marketing of multiple products, and SMR is the total risk of social marketing of multiple products.

[0117] In some embodiments, the full life cycle management risk data of multiple products include product maintenance risk data, product disposal risk data, and product recycling risk data. Accordingly, the usual results are risk (which can be represented by 1) and no risk (which can be represented by 0). The risk results can be obtained by machine analysis or manual mathematical and physical logic deduction and judgment. The full life cycle management risk LR of multiple products includes the total product maintenance risk MLR of multiple products, the total product disposal risk DLR of multiple products, and the total product recycling risk RLR of multiple products. On this basis, the calculation formula of the full life cycle management risk LR of multiple products is as follows:

[0118] TR = (MLR + DLR + RLR) / 3;

[0119] Among them, MLR takes one of 0 or 1, DLR takes one of 0 or 1, RLR takes one of 0 or 1, MLR is the total product maintenance risk of multiple products, DLR is the total product abandonment risk of multiple products, and RLR is the total product recycling risk of multiple products.

[0120] In some embodiments, the enterprise financial risk data includes cash flow risk data, profitability risk data, and debt risk data. Accordingly, the usual results are risk (which can be represented by 1) and no risk (which can be represented by 0). The risk results can be obtained by machine analysis or manual mathematical and physical logic deduction and judgment. The enterprise financial risk FR includes cash flow risk MFR, profitability risk PFR, and debt risk DFR. On this basis, the calculation formula of the enterprise financial risk FR is as follows:

[0121] FR = (MFR + PFR + DFR) / 3;

[0122] Among them, MFR takes one of 0 or 1, PFR takes one of 0 or 1, and DFR takes one of 0 or 1. MFR is the cash flow risk, PFR is the profitability risk, and DFR is the debt risk.

[0123] In some embodiments, the enterprise carbon resource risk data includes carbon trading risk data and carbon emission risk data. Accordingly, the usual results are risk (which can be represented by 1) and no risk (which can be represented by 0). The risk results can be obtained by machine analysis or artificial mathematical and physical logic deduction and judgment. The enterprise carbon resource risk TR includes carbon trading risk TTR and carbon emission risk ETR. On this basis, the calculation formula of the enterprise carbon resource risk TR is as follows:

[0124] TR = (TTR + ETR) / 2;

[0125] Among them, TTR takes one of 0 or 1, and ETR takes one of 0 or 1. TTR is the carbon trading risk; ETR is the carbon emission risk.

[0126] In some embodiments, generally speaking, marketing risk data, life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data usually have a great impact on the safety of enterprise operations. Accordingly, marketing risk data, life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data usually occupy different levels of importance under different economic and social situations. Through the settings of P1, P2, P3, and P4, the impact of marketing risk data, life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data on enterprise operations and operational safety analysis, evaluation, and early warning is balanced, so that the second operational safety index OS2 can be consistent with the actual operating conditions of most existing medium and large-scale enterprises.

[0127] Optionally, the enterprise operation safety data also includes a third operation safety index OS3, which is used to analyze the number of 0 or 1 in LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR. It can analyze the overall status of marketing risk, full life cycle data risk, enterprise financial risk number, and enterprise carbon resource risk, and can also analyze the proportion of risky and non-risky in marketing risk, full life cycle data risk, enterprise financial risk number, and enterprise carbon resource risk. The calculation formula of the third operation safety index OS3 is as follows:

[0128] OS3 = |NSR1-NSR0| / 11;

[0129] NSR1 is the number of 1s among LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR, and NSR0 is the number of 0s among LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR.

[0130] Optionally, as Figure 3 shown, the enterprise operation security data further includes the enterprise operation security index OS, and the calculation formula of the enterprise operation security index OS is as follows: OS = |OS2 - OS1| * OS3 - OS1 * OS2 / 11.

[0131] In the application of the present invention, the first operation security index OS1 is used to analyze the risks of the enterprise's procurement management, logistics management, and warehousing management, and the second operation security index OS2 and the third operation security index OS3 are used to analyze the risks of the enterprise's marketing management, full life cycle management, financial status management, and carbon resource management. Based on the first operation security index OS1, the second operation security index OS2, and the third operation security index OS3, the first operation security index OS1, the second operation security index OS2, and the third operation security index OS3 are also comprehensively used to evaluate the enterprise operation security index OS, so as to complete the evaluation of the enterprise operation security from multiple dimensions.

[0132] Optionally, when OS ≥ R1, the e-commerce ERP management system starts management intervention, and when OS < R1, the e-commerce ERP management system does not start management intervention, where R1 is a preset value or a preset range.

[0133] When OS ≥ R1, when the e-commerce ERP management system starts management intervention, the management intervention includes: reminding or suspending services for one or more of the procurement unit 10, product unit 20, marketing unit 30, sales unit 40, financial unit 50, logistics unit 60, warehousing unit 70, carbon resource unit 80, and after-sales unit 90 to investigate specific risk points in the enterprise operation; when OS < R1, the e-commerce ERP management system does not start management intervention, and the e-commerce ERP management system provides services normally, so as to meet the needs of the enterprise's business development and management, reduce the internal communication cost and operation cost increase of the enterprise, and reduce the risk of losses or potential losses of the enterprise.

[0134] In the second aspect, as Figure 4 shown, the present invention application provides an e-commerce ERP management method, which adopts an e-commerce ERP management system according to any one of the above first aspects, and includes the following steps:

[0135] Step S100: Acquire procurement data of multiple products, market positioning data of multiple products, marketing data of multiple products, sales data of multiple products, logistics data of multiple products, warehousing data of multiple products, full life cycle data of multiple products, enterprise financial status data, and enterprise carbon resource data;

[0136] Step S200: Analyze at least the procurement data of multiple products, the market positioning data of multiple products, the marketing data of multiple products, the sales data of multiple products, the logistics data of multiple products, the warehousing data of multiple products, the full life cycle data of multiple products, the enterprise financial status data, and the enterprise carbon resource data to obtain enterprise operation safety data, the enterprise operation safety data including the procurement risk data of multiple products, the marketing risk data, the logistics risk data, the warehousing risk data, the full life cycle management risk data, the enterprise financial risk data, the enterprise carbon resource risk data, a first operation safety index OS1, and a second operation safety index OS2. The first operation safety index OS1 is calculated through the procurement risk data, the logistics risk data, and the warehousing risk data of multiple products, and the second operation safety index OS2 is calculated through the marketing risk data, the full life cycle management risk data, the enterprise financial risk data, and the enterprise carbon resource risk data of multiple products.

[0137] Step S300: Determine whether to initiate management intervention based on enterprise operation safety data.

[0138] In the present application, when the e-commerce ERP management method adopts any one of the e-commerce ERP management systems described in the first aspect, it includes the technical content, technical effects and technical problems solved by any one of the e-commerce ERP management systems described in the first aspect, which will not be repeated here.

[0139] In step S200, procurement risk data of multiple products include material risk data, product manufacturing risk data, etc., marketing risk data of multiple products include live marketing risk data, e-commerce marketing risk data, social marketing risk data, logistics risk data of multiple products include transportation risk data, etc., warehousing risk data of multiple products include inventory risk data, etc., corporate financial risk data includes cash flow risk data, profitability risk data, debt risk data, corporate carbon resource risk data includes carbon trading risk data, carbon emission risk data, and full life cycle management risk data includes product maintenance risk data, product abandonment risk data, product recycling risk data, etc.

[0140] Therefore, based on the above-mentioned procurement data of multiple products, market positioning data of multiple products, marketing data of multiple products, sales data of multiple products, logistics data of multiple products, warehousing data of multiple products, full life cycle data of multiple products, enterprise financial status data, and enterprise carbon resource data, the existing ERP management system independently manages procurement data, market positioning data, marketing data, sales data, logistics data, warehousing data, full life cycle data, financial status data, and enterprise carbon resource data, and cannot analyze the procurement data, market positioning data, marketing data, sales data, logistics data, warehousing data, full life cycle data, financial status data, and enterprise carbon resource data as a whole to obtain the enterprise operation situation, nor can it analyze and warn the enterprise operation safety and make reasonable management decision intervention. To this end, the applicant has conducted research on this and used the e-commerce ERP management method to help analyze, manage, and intervene in the safety of enterprise operations.

[0141] In the present application, in step S200, the enterprise operation safety data includes a first operation safety index OS1 and a second operation safety index OS2. The first operation safety index OS1 is calculated through procurement risk data, logistics risk data, and warehousing risk data of multiple products. The second operation safety index OS2 is calculated through marketing risk data, life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data of multiple products.

[0142] Obviously, in normal business of an enterprise, generally speaking, the procurement risk data of multiple products include material risk data, product manufacturing risk data, etc. The results of logistics risk data and product manufacturing risk data are usually risky (can be represented by 1) or risk-free (can be represented by 0 risk), and the procurement risk BR of multiple products can be obtained accordingly, and BR takes one of 0 or 1; the logistics risk data CR of multiple products include transportation risk data, etc. The results of transportation risk data are usually risky (can be represented by 1) or risk-free (can be represented by 0 risk), and the logistics risk CR of multiple products can be obtained accordingly, and CR takes one of 0 or 1; the storage risk data SR of multiple products include inventory risk data, etc. The results of inventory risk data are usually risky (can be represented by 1) or risk-free (can be represented by 0), and the storage risk of multiple products can be obtained accordingly, and SR takes one of 0 or 1. Using the procurement risk of multiple products, the logistics risk of multiple products, and the storage risk of multiple products, the first operation safety index OS1 can be calculated. The calculation formula of the first operation safety index OS1 is as follows:

[0143] OS1=BR+CR+SR;

[0144] Among them, BR takes one of 0 or 1, CR takes one of 0 or 1, and SR takes one of 0 or 1; BR is the procurement risk of multiple products, CR is the logistics risk of multiple products, and SR is the warehousing risk of multiple products.

[0145] In some embodiments, generally speaking, procurement risk data, logistics risk data, and warehousing risk data are usually problems that can be completely resolved in the actual trading process of the enterprise, and will not pose a serious impact on the operational safety of the enterprise. They are usually consistent with the operating conditions of most existing medium and large-scale enterprises.

[0146] In some embodiments, the second operation safety index OS2 is calculated by using marketing risk data of multiple products, life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data. The calculation formula of the second operation safety index OS2 is as follows:.

[0147] OS2=P1*MR+P2*LR+P3*FR+P4*TR;

[0148] Among them, MR is the marketing risk of multiple products, P1 is the marketing risk coefficient, 0%≤P1≤300%; LR is the life cycle management risk, P2 is the life cycle management risk coefficient, 0%≤P2≤300%; FR is the enterprise financial risk, P3 is the enterprise financial management risk coefficient, 0%≤P3≤300%; TR is the enterprise carbon resource risk, P4 is the enterprise carbon resource risk coefficient, 0%≤P4≤200%.

[0149] In some embodiments, the marketing risk data of multiple products include live broadcast marketing risk data, e-commerce marketing risk data, and social marketing risk data. Accordingly, the usual results are risk (which can be represented by 1) or no risk (which can be represented by 0). The risk results can be obtained by machine analysis or manual mathematical and physical logic deduction and judgment. The marketing risk MR of multiple products includes the total live broadcast marketing risk LMR of multiple products, the total e-commerce marketing risk EMR of multiple products, and the total social marketing risk SMR of multiple products. On this basis, the calculation formula of the marketing risk MR of multiple products is as follows:

[0150] MR = (LMR + EMR + SMR) / 3;

[0151] Among them, LMR takes one of 0 or 1, EMR takes one of 0 or 1, and SMR takes one of 0 or 1. LMR is the total risk of live broadcast marketing of multiple products, EMR is the total risk of e-commerce marketing of multiple products, and SMR is the total risk of social marketing of multiple products.

[0152] In some embodiments, the full life cycle management risk data of multiple products include product maintenance risk data, product disposal risk data, and product recycling risk data. Accordingly, the usual results are risk (which can be represented by 1) and no risk (which can be represented by 0). The risk results can be obtained by machine analysis or manual mathematical and physical logic deduction and judgment. The full life cycle management risk LR of multiple products includes the total product maintenance risk MLR of multiple products, the total product disposal risk DLR of multiple products, and the total product recycling risk RLR of multiple products. On this basis, the calculation formula of the full life cycle management risk LR of multiple products is as follows:

[0153] TR = (MLR + DLR + RLR) / 3;

[0154] Among them, MLR takes one of 0 or 1, DLR takes one of 0 or 1, RLR takes one of 0 or 1, MLR is the total product maintenance risk of multiple products, DLR is the total product abandonment risk of multiple products, and RLR is the total product recycling risk of multiple products.

[0155] In some embodiments, the enterprise financial risk data includes cash flow risk data, profitability risk data, and debt risk data. Accordingly, the usual results are risk (which can be represented by 1) and no risk (which can be represented by 0). The risk results can be obtained by machine analysis or manual mathematical and physical logic deduction and judgment. The enterprise financial risk FR includes cash flow risk MFR, profitability risk PFR, and debt risk DFR. On this basis, the calculation formula of the enterprise financial risk FR is as follows:

[0156] FR = (MFR + PFR + DFR) / 3;

[0157] Among them, MFR takes one of 0 or 1, PFR takes one of 0 or 1, and DFR takes one of 0 or 1. MFR is the cash flow risk, PFR is the profitability risk, and DFR is the debt risk.

[0158] In some embodiments, the enterprise carbon resource risk data includes carbon trading risk data and carbon emission risk data. Accordingly, the usual results are risk (which can be represented by 1) and no risk (which can be represented by 0). The risk results can be obtained by machine analysis or artificial mathematical and physical logic deduction and judgment. The enterprise carbon resource risk TR includes carbon trading risk TTR and carbon emission risk ETR. On this basis, the calculation formula of the enterprise carbon resource risk TR is as follows:

[0159] TR = (TTR + ETR) / 2;

[0160] Among them, TTR takes one of 0 or 1, and ETR takes one of 0 or 1. TTR is the carbon trading risk; ETR is the carbon emission risk.

[0161] In some embodiments, generally speaking, marketing risk data, full life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data usually have a great impact on the operation safety of an enterprise. Correspondingly, marketing risk data, full life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data usually occupy different importance levels under different economic, social, and other circumstances. Through the settings of P1, P2, P3, and P4, the impacts of marketing risk data, full life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data on the analysis, evaluation, and early warning of enterprise operation and operation safety are balanced, so that the second operation safety index OS2 can be consistent with the actual operation of most existing medium and large-sized enterprises above a certain scale.

[0162] Optionally, in step S200, the enterprise operation safety data further includes a third operation safety index OS3. The third operation safety index OS3 is used to analyze the number of 0s or 1s in LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR. It can analyze the overall status of the marketing risk level, full life cycle data risk level, enterprise financial risk level, and enterprise carbon resource risk level as a whole, and can also analyze the proportion of risky and risk-free in the marketing risk level, full life cycle data risk level, enterprise financial risk level, and enterprise carbon resource risk level. The calculation formula of the third operation safety index OS3 is as follows:

[0163] OS3 = |NSR1 - NSR0| / 11;

[0164] NSR1 is the number of 1s in LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR, and NSR0 is the number of 0s in LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR.

[0165] Optionally, as Figure 3 shown, in step S300, the enterprise operation safety data includes an enterprise operation safety index OS. The calculation formula of the enterprise operation safety index OS is as follows:

[0166] OS = |OS2 - OS1| * OS3 - OS1 * OS2 / 11;

[0167] The determination of whether to initiate management intervention based on the enterprise operation safety data includes: when OS ≥ R1, initiate management intervention; when OS < R1, do not initiate management intervention, where R1 is a preset value or preset range.

[0168] In the application of the present invention, the first operation safety index OS1 is used to analyze the risks of the enterprise's procurement management, logistics management, and warehousing management, and the second operation safety index OS2 and the third operation safety index OS3 are used to analyze the risks of the enterprise's marketing management, full life cycle management, financial status management, and carbon resource management. Based on the first operation safety index OS1, the second operation safety index OS2, and the third operation safety index OS3, the first operation safety index OS1, the second operation safety index OS2, and the third operation safety index OS3 are also comprehensively utilized to evaluate the enterprise operation safety index OS, thereby completing the evaluation of the enterprise operation safety from multiple dimensions.

[0169] In the application of the present invention, in step S300, determining whether to initiate management intervention according to the enterprise operation safety data includes: when OS≥R1, initiating management intervention; when OS<R1, not initiating management intervention, where R1 is a preset value or a preset range.

[0170] When OS≥R1, when the e-commerce ERP management method initiates management intervention, the management intervention includes: reminding or suspending services for one or more of the procurement unit 10, product unit 20, marketing unit 30, sales unit 40, financial unit 50, logistics unit 60, warehousing unit 70, carbon resource unit 80, and after-sales unit 90 to identify specific risk points in the enterprise operation; when OS<R1, the e-commerce ERP management method does not initiate management intervention, and the e-commerce ERP management system provides services normally, thereby meeting the needs of the enterprise's business development and management, reducing the increase in the enterprise's internal communication cost and operation cost, and reducing the risk of the enterprise's losses or potential losses.

[0171] In the application of the present invention, the e-commerce ERP management method expands the functions of the existing ERP method. Based on the management method of the existing e-commerce ERP management system, at least the e-commerce ERP management method can conduct overall analysis according to the procurement data of multiple products, the market positioning data of multiple products, the marketing data of multiple products, the sales data of multiple products, the logistics data of multiple products, the warehousing data of multiple products, the full life cycle data of multiple products, the enterprise financial status data, and the enterprise carbon resource data to obtain enterprise operation safety data for managing the enterprise operation safety. In this way, it can not only meet the needs of the enterprise's marketing, sales, logistics, transportation, delivery to customers, and full life cycle management of multiple products, but also meet the enterprise's own business compliance risk control and highly digital intelligent management, and can also achieve the enterprise's own carbon emission reduction and green ecological environmental protection goals, reduce the increase in the enterprise's internal communication cost and operation cost, reduce the risk of the enterprise's direct losses or potential losses, and enhance the value, economic value, social value, and environmental protection value of the e-commerce ERP management method and the e-commerce ERP management system.

[0172] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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, they should be considered to be within the scope of this specification.

[0173] Those skilled in the art can understand that the steps, measures, and schemes in the various operations, methods, and processes discussed in the present application can be alternated, changed, combined, or deleted; further, other steps, measures, and schemes in the various operations, methods, and processes discussed in the present application can also be alternated, changed, rearranged, decomposed, combined, or deleted; further, the steps, measures, and schemes in the prior art that are similar to those disclosed in the present application can also be alternated, changed, rearranged, decomposed, combined, or deleted;

[0174] The above-described embodiments only express several implementation methods of the embodiments of the present disclosure, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the patent scope of the embodiments of the present disclosure. It should be pointed out that, for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the embodiments of the present disclosure, which all belong to the protection scope of the embodiments of the present disclosure. Therefore, the protection scope of the embodiments of the present disclosure shall be based on the attached claims.

Claims

1. An e-commerce ERP management system, comprising: The purchasing unit, product unit, marketing unit, sales unit, financial unit, logistics unit, storage unit, carbon resource unit, after-sales unit and server are characterized by: A purchasing unit, at least used to manage the purchasing data of multiple products and send it to the server; A product unit, at least used to manage market positioning data and manufacturing data of multiple products and send them to a server; A marketing unit manages marketing data of the plurality of products based on at least the market positioning data of the plurality of products and sends the marketing data to the server; A sales unit, at least used to manage sales data of multiple products and send the data to a server; The financial unit is used to manage the enterprise's financial status data and send it to the server; The logistics unit is used to manage the logistics data of multiple products and send them to the server; The storage unit is used to manage the storage data of multiple products and send them to the server. A carbon resource unit, at least used to manage the enterprise carbon resource data and send it to the server; The after-sales unit is used to manage the full life cycle data of multiple products and send it to the server; The server analyzes at least the procurement data of multiple products, the market positioning data of multiple products, the marketing data of multiple products, the sales data of multiple products, the logistics data of multiple products, the warehousing data of multiple products, the full life cycle data of multiple products, the enterprise financial status data, and the enterprise carbon resource data to obtain the enterprise operation safety data, and determines whether to initiate management intervention based on the enterprise operation safety data; the enterprise operation safety data includes the procurement risk data, marketing risk data, logistics risk data, warehousing risk data, full life cycle management risk data, enterprise financial risk data, enterprise carbon resource risk data, a first operation safety index OS1, and a second operation safety index OS2 of multiple products. The first operation safety index OS1 is calculated through the procurement risk data, logistics risk data, and warehousing risk data of multiple products, and the second operation safety index OS2 is calculated through the marketing risk data, full life cycle management risk data, enterprise financial risk data, and enterprise carbon resource risk data of multiple products.

2. An e-commerce ERP management system according to claim 1, characterized in that: The procurement data of multiple products includes the material data, product manufacturing equipment, marketing equipment, and carbon resource equipment procurement of multiple products; the logistics data of multiple products includes the product order data and product transportation data of multiple products; the warehousing data of multiple products includes the inventory data, inbound and outbound data, product quality data, and warehousing equipment data of multiple products; The product unit includes a design management unit and a manufacturing management unit; the design management unit manages the market positioning data of multiple products at least according to the development and design conditions of different products; A manufacturing management unit, at least based on the manufacturing conditions of different products, obtains manufacturing data of a plurality of products; The marketing unit includes a print media unit and an electronic media unit, wherein the print media unit manages print marketing data of a plurality of products based on at least the market positioning data of the plurality of products; an electronic media unit for managing electronic marketing data for a plurality of products based at least on the market positioning data for the plurality of products; The print media unit is at least used to manage the print marketing data of multiple products; the print marketing data includes newspaper marketing data and magazine marketing data; the electronic media unit is at least used to manage the electronic marketing data of multiple products, and the electronic marketing data includes live broadcast marketing data, social marketing data, e-commerce marketing data, and e-commerce marketing data; the sales data of each product at least includes the total order volume, total sales, total sales volume, customer data, total gross profit margin, total cost of each product, as well as the overall sales volume, overall sales volume, overall customer data, overall gross profit margin, and overall cost of the enterprise; Enterprise carbon resource data include: enterprise carbon emission data and enterprise carbon index data; the full life cycle data of each product includes at least: product basic data, product location data, and product operation data.

3. An e-commerce ERP management system according to claim 2, characterized in that: The calculation formula of the first operation safety index OS1 is as follows: OS1=BR+CR+SR; Among them, BR takes one of 0 or 1, CR takes one of 0 or 1, and SR takes one of 0 or 1; BR is the procurement risk of multiple products, CR is the logistics risk of multiple products, and SR is the storage risk of multiple products; The calculation formula of the second operation safety index OS2 is as follows: OS2=P1*MR+P2*LR+P3*FR+P4*TR; Among them, MR is the marketing risk of multiple products, P1 is the marketing risk coefficient, 0%≤P1≤300%; LR is the life cycle management risk, P2 is the life cycle management risk coefficient, 0%≤P2≤300%; FR is the enterprise financial risk, P3 is the enterprise financial management risk coefficient, 0%≤P3≤300%; TR is the enterprise carbon resource risk, P4 is the enterprise carbon resource risk coefficient, 0%≤P4≤200%.

4. An e-commerce ERP management system according to claim 3, characterized in that: The calculation formula for the marketing risk MR of multiple products is as follows: MR = (LMR + EMR + SMR) / 3; Among them, LMR takes one of 0 or 1, EMR takes one of 0 or 1, SMR takes one of 0 or 1, LMR is the total risk of live broadcast marketing of multiple products, EMR is the total risk of e-commerce marketing of multiple products, and SMR is the total risk of social marketing of multiple products; The calculation formula for the life cycle management risk LR of multiple products is as follows: TR = (MLR + DLR + RLR) / 3; Among them, MLR takes one of 0 or 1, DLR takes one of 0 or 1, RLR takes one of 0 or 1, MLR is the total product maintenance risk of multiple products, DLR is the total product abandonment risk of multiple products, and RLR is the total product recycling risk of multiple products; The calculation formula of enterprise financial risk FR is as follows: FR = (MFR + PFR + DFR) / 3; Among them, MFR takes one of 0 or 1, PFR takes one of 0 or 1, DFR takes one of 0 or 1, MFR is cash flow risk, PFR is profitability risk, DFR is debt risk; The calculation formula of enterprise carbon resource risk TR is as follows: TR = (TTR + ETR) / 2; Among them, TTR takes one of 0 or 1, and ETR takes one of 0 or 1. TTR is the carbon trading risk; ETR is the carbon emission risk.

5. An e-commerce ERP management system according to claim 4, characterized in that: Enterprise operation safety data also includes: the third operation safety index OS3, the calculation formula of the third operation safety index OS3 is as follows: OS3 = |NSR1-NSR0| / 11; NSR1 is the number of 1s in LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR, and NSR0 is the number of 0s in LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR.

6. An e-commerce ERP management system according to claim 5, characterized in that: Enterprise operation safety data also includes the enterprise operation safety index OS. The calculation formula of the enterprise operation safety index OS is as follows: OS=|OS2-OS1|*OS3-OS1*OS2 / 11.

7. An e-commerce ERP management method, using an e-commerce ERP management system according to any one of claims 1 to 6, characterized in that: The following steps are involved: Step S100: Acquire procurement data of multiple products, market positioning data of multiple products, marketing data of multiple products, sales data of multiple products, logistics data of multiple products, warehousing data of multiple products, full life cycle data of multiple products, enterprise financial status data, and enterprise carbon resource data; Step S200: Analyze at least the procurement data of multiple products, the market positioning data of multiple products, the marketing data of multiple products, the sales data of multiple products, the logistics data of multiple products, the warehousing data of multiple products, the full life cycle data of multiple products, the enterprise financial status data, and the enterprise carbon resource data to obtain enterprise operation safety data, the enterprise operation safety data includes the procurement risk data of multiple products, the marketing risk data, the logistics risk data, the warehousing risk data, the full life cycle management risk data, the enterprise financial risk data, the enterprise carbon resource risk data, the first operation safety index OS1, and the second operation safety index OS2. The first operation safety index OS1 is calculated through the procurement risk data, the logistics risk data, and the warehousing risk data of multiple products, and the second operation safety index OS2 is calculated through the marketing risk data, the full life cycle management risk data, the enterprise financial risk data, and the enterprise carbon resource risk data of multiple products. Step S300: Determine whether to initiate management intervention based on enterprise operation safety data.

8. An e-commerce ERP management method according to claim 7, characterized in that: In step S200, the calculation formula of the first operation safety index OS1 is as follows: OS1=BR+CR+SR; Among them, BR takes one of 0 or 1, CR takes one of 0 or 1, and SR takes one of 0 or 1; BR is the procurement risk of multiple products, CR is the logistics risk of multiple products, and SR is the storage risk of multiple products; The calculation formula of the second operation safety index OS2 is as follows: OS2=P1*MR+P2*LR+P3*FR+P4*TR; Among them, MR is the marketing risk of multiple products, P1 is the marketing risk coefficient, 0%≤P1≤300%; LR is the risk of the whole life cycle management risk, P2 is the risk coefficient of the whole life cycle management risk, 0%≤P2≤300%; FR is the enterprise financial risk, P3 is the enterprise financial management risk coefficient, 0%≤P3≤300%; TR is the enterprise carbon resource risk, P4 is the enterprise carbon resource risk coefficient, 0%≤P4≤200%; The calculation formula for the marketing risk MR of multiple products is as follows: MR = (LMR + EMR + SMR) / 3; Among them, LMR takes one of 0 or 1, EMR takes one of 0 or 1, SMR takes one of 0 or 1, LMR is the total risk of live broadcast marketing of multiple products, EMR is the total risk of e-commerce marketing of multiple products, and SMR is the total risk of social marketing of multiple products; The calculation formula for the life cycle management risk LR of multiple products is as follows: TR = (MLR + DLR + RLR) / 3; Among them, MLR takes one of 0 or 1, DLR takes one of 0 or 1, RLR takes one of 0 or 1, MLR is the total product maintenance risk of multiple products, DLR is the total product abandonment risk of multiple products, and RLR is the total product recycling risk of multiple products; The calculation formula of enterprise financial risk FR is as follows: FR = (MFR + PFR + DFR) / 3; Among them, MFR takes one of 0 or 1, PFR takes one of 0 or 1, DFR takes one of 0 or 1, MFR is cash flow risk, PFR is profitability risk, DFR is debt risk; The calculation formula of enterprise carbon resource risk TR is as follows: TR = (TTR + ETR) / 2; Among them, TTR takes one of 0 or 1, and ETR takes one of 0 or 1. TTR is the carbon trading risk; ETR is the carbon emission risk.

9. An e-commerce ERP management method according to claim 8, characterized in that: In step S200, the enterprise operation safety data also includes: a third operation safety index OS3, and the calculation formula of the third operation safety index OS3 is as follows: OS3=|NSR1-NSR0| / 11-OS1*OS2 / 11; NSR1 is the number of 1s in LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR, and NSR0 is the number of 0s in LMR, EMR, SMR, MLR, DLR, RLR, MFR, PFR, DFR, TTR, and ETR.

10. An e-commerce ERP management method according to claim 9, characterized in that: In step S300, the enterprise operation safety data includes the enterprise operation safety index OS, and the calculation formula of the enterprise operation safety index OS is as follows: OS=|OS2-OS1|*OS3-OS1*OS2 / 11; Determining whether to initiate management intervention based on enterprise operation safety data includes: when OS≥R1, initiate management intervention; when OS<R1, do not initiate management intervention, where R1 is a preset value or preset range.

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