Website management diagnosis method, system, medium and equipment

Abstract

The invention provides a website management diagnosis method and system, a medium and equipment. The method comprises the following steps: collecting multi-dimensional data of a website; the collected multi-dimensional data of the network points are preprocessed, and the preprocessed multi-dimensional data are obtained; constructing a diagnostic analysis model, and analyzing the preprocessed multi-dimensional data by using the diagnostic analysis model to obtain a website diagnosis result; and displaying the website diagnosis result in a visual form. The diagnostic analysis process can be automatically completed by utilizing the diagnostic analysis model based on the preset diagnostic rule and algorithm, and the working efficiency and accuracy are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of network point management diagnosis, and in particular to a network point management diagnosis method, system, medium and equipment. Background Art

[0002] In the current logistics management practice, the evaluation of outlet operation status mostly relies on manual experience and traditional report analysis, lacking systematic and scientific diagnostic tools; this method is not only inefficient, but also difficult to fully and accurately reflect the actual situation of outlet operation, resulting in delayed problem discovery and weak targeted improvement measures. Therefore, it is particularly important to develop a diagnostic system and method that can automatically, comprehensively and quickly evaluate the outlet operation status. Summary of the invention

[0003] The main purpose of the present invention is to solve the technical problem that the evaluation of the operation status of outlets in the prior art mostly relies on manual experience and traditional report analysis, which is inefficient and difficult to fully and accurately reflect the actual situation of outlet operations.

[0004] A first aspect of the present invention provides a network point management diagnosis method, comprising: Collect multi-dimensional data of outlets; Preprocessing the collected multi-dimensional data of network points to obtain preprocessed multi-dimensional data; Construct a diagnostic analysis model, and use it to analyze the pre-processed multi-dimensional data to obtain the point diagnosis results; The network point diagnosis results are displayed in a visual form.

[0005] Optionally, in a first implementation method of the first aspect of the present invention, the multi-dimensional data of the collection outlets includes: basic information of the outlets, order splitting accuracy, market share, collection and delivery balance, abnormal suspension of shipment, and customer feedback.

[0006] Optionally, in a second implementation of the first aspect of the present invention, the preprocessing of the collected multi-dimensional data of network points includes: Performing data cleaning on the collected multi-dimensional data of the outlets to obtain cleaned multi-dimensional data of the outlets; The cleaned multi-dimensional data of the network points are subjected to data conversion processing to obtain converted multi-dimensional data of the network points.

[0007] Optionally, in a third implementation of the first aspect of the present invention, the using of the diagnostic analysis model to analyze the pre-processed multi-dimensional data to obtain a network point diagnosis result includes: The diagnostic analysis model is used to conduct analysis on the pre-processed multi-dimensional data, including branch basic information analysis, branch business volume analysis, branch customer information analysis, branch terminal data analysis, branch financial data analysis, branch timeliness quality analysis, branch service quality analysis and branch safety production analysis, to obtain corresponding indicator information, and analyze the branch diagnosis results based on the indicator information.

[0008] Optionally, in a fourth implementation of the first aspect of the present invention, basic information indicators of outlets are obtained based on the analysis of basic information of outlets, and the basic information indicators of outlets include: compliance status of outlets, staffing of outlet managers, accuracy of three-segment code sorting, and abnormal suspension area; Obtaining outlet business volume indicators based on outlet business volume analysis, the outlet business volume indicators including: market share achievement, collection and dispatch balance, and total distribution market share; Based on the branch customer information analysis, the branch customer information indicators are obtained, and the branch customer information indicators include: customer stratification; Based on the analysis of the network terminal data, the network terminal indicators are obtained, wherein the network terminal indicators include: terminal indicators and village entry targets; Obtaining branch financial indicators based on branch financial data analysis, wherein the branch financial indicators include: prepayment status; Based on the network point timeliness quality analysis, the network point timeliness quality indicators are obtained, and the network point timeliness quality indicators include: scheduled collection rate, scheduled delivery rate, scheduled sorting rate and signing rate; Obtaining service quality indicators based on the service quality analysis of the outlets, the service quality indicators including: false receipt, loss rate and damage rate; Based on the network point production safety analysis, the network point production safety indicators are obtained, and the network point production safety indicators include: safety officer deployment status and safety inspection status.

[0009] Optionally, in a fifth implementation of the first aspect of the present invention, the step of constructing a diagnostic analysis model and using the diagnostic analysis model to analyze the preprocessed multi-dimensional data to obtain a network point diagnostic result includes: Use the diagnostic analysis model to analyze the pre-processed multi-dimensional data, including basic information analysis of outlets, business volume analysis of outlets, customer information analysis of outlets, terminal data analysis of outlets, financial data analysis of outlets, timeliness and quality analysis of outlets, service quality analysis of outlets, and production safety analysis of outlets, to obtain corresponding indicator information; Set judgment thresholds for each indicator; The score increase or decrease is calculated based on the judgment threshold according to the preset rules; Set different weights according to different indicators; Based on the corresponding scores of different indicators, the network point diagnosis results are calculated according to the corresponding weights of different indicators.

[0010] Optionally, in a sixth implementation of the first aspect of the present invention, presenting the network point diagnosis result in a visual form includes: Generate corresponding improvement strategies based on the corresponding scores of multiple calculation indicators; The branch diagnosis results are displayed in a visual form using charts and reports. The display content includes: diagnosis report, abnormal indicator prompts and corresponding improvement strategies.

[0011] A second aspect of the present invention provides a network point management diagnosis system, comprising: Collection module, used to collect multi-dimensional data of outlets; A preprocessing module is used to preprocess the collected multi-dimensional data of the network points to obtain preprocessed multi-dimensional data; The diagnosis module is used to build a diagnosis analysis model and use the diagnosis analysis model to analyze the pre-processed multi-dimensional data to obtain the point diagnosis results; The visualization module is used to display the network point diagnosis results in a visual form.

[0012] Optionally, in a first implementation method of the second aspect of the present invention, the multi-dimensional data of the collection outlets includes: basic information of the outlets, order splitting accuracy, market share, collection and delivery balance, abnormal suspension of shipment, and customer feedback.

[0013] Optionally, in a second implementation of the second aspect of the present invention, the preprocessing module includes: Performing data cleaning on the collected multi-dimensional data of the outlets to obtain cleaned multi-dimensional data of the outlets; The cleaned multi-dimensional data of the network points are subjected to data conversion processing to obtain converted multi-dimensional data of the network points.

[0014] Optionally, in a third implementation of the second aspect of the present invention, the diagnosis module includes: The diagnostic analysis model is used to conduct analysis on the pre-processed multi-dimensional data, including branch basic information analysis, branch business volume analysis, branch customer information analysis, branch terminal data analysis, branch financial data analysis, branch timeliness quality analysis, branch service quality analysis and branch safety production analysis, to obtain corresponding indicator information, and analyze the branch diagnosis results based on the indicator information.

[0015] Optionally, in a fourth implementation of the second aspect of the present invention, basic information indicators of outlets are obtained based on the analysis of basic information of outlets, and the basic information indicators of outlets include: compliance status of outlets, staffing of outlet managers, accuracy of three-segment code sorting, and abnormal suspension area; Obtaining outlet business volume indicators based on outlet business volume analysis, the outlet business volume indicators including: market share achievement, collection and dispatch balance, and total distribution market share; Based on the branch customer information analysis, the branch customer information indicators are obtained, and the branch customer information indicators include: customer stratification; Based on the analysis of the network terminal data, the network terminal indicators are obtained, wherein the network terminal indicators include: terminal indicators and village entry targets; Obtaining branch financial indicators based on branch financial data analysis, wherein the branch financial indicators include: prepayment status; Based on the network point timeliness quality analysis, the network point timeliness quality indicators are obtained, and the network point timeliness quality indicators include: scheduled collection rate, scheduled delivery rate, scheduled sorting rate and signing rate; Obtaining service quality indicators based on the service quality analysis of the outlets, the service quality indicators including: false receipt, loss rate and damage rate; Based on the network point production safety analysis, the network point production safety indicators are obtained, and the network point production safety indicators include: safety officer deployment status and safety inspection status.

[0016] Optionally, in a fifth implementation of the second aspect of the present invention, the diagnosis module includes: Use the diagnostic analysis model to analyze the pre-processed multi-dimensional data, including basic information analysis of outlets, business volume analysis of outlets, customer information analysis of outlets, terminal data analysis of outlets, financial data analysis of outlets, timeliness and quality analysis of outlets, service quality analysis of outlets, and production safety analysis of outlets, to obtain corresponding indicator information; Set judgment thresholds for each indicator; The score increase or decrease is calculated based on the judgment threshold according to the preset rules; Set different weights according to different indicators; Based on the corresponding scores of different indicators, the network point diagnosis results are calculated according to the corresponding weights of different indicators.

[0017] Optionally, in a sixth implementation of the second aspect of the present invention, the visualization module includes: Generate corresponding improvement strategies based on the corresponding scores of multiple calculation indicators; The branch diagnosis results are displayed in a visual form using charts and reports. The display content includes: diagnosis report, abnormal indicator prompts and corresponding improvement strategies.

[0018] A third aspect of the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program implements the steps of the above-mentioned network point management diagnosis method when executed by a processor.

[0019] A fourth aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the above-mentioned network point management diagnostic method when executed by the processor.

[0020] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention realizes the comprehensive collection and integration of network operation data based on the collected multi-dimensional data, ensuring the comprehensiveness and accuracy of the diagnosis; 2. The present invention utilizes the diagnostic analysis model based on preset diagnostic rules and algorithms to automatically complete the diagnostic analysis process, greatly improving work efficiency and accuracy; 3. The present invention uses a visual form to display the diagnosis results, so that managers can intuitively understand the operating status and problems of the outlets, providing strong support for formulating improvement measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings: Figure 1 A first flow chart of a network point management diagnosis method provided by an embodiment of the present invention.

[0022] Figure 2 A second flow chart of the network point management diagnosis method provided in an embodiment of the present invention.

[0023] Figure 3 This is a third flow chart of the network point management diagnosis method provided in an embodiment of the present invention.

[0024] Figure 4 A schematic diagram of the structure of a network point management diagnosis system provided by an embodiment of the present invention.

[0025] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The embodiment of the present invention provides a method, system, medium and device for network point management diagnosis, which collects multi-dimensional data of network points; pre-processes the collected multi-dimensional data of network points to obtain pre-processed multi-dimensional data; constructs a diagnosis analysis model, and uses the diagnosis analysis model to analyze the pre-processed multi-dimensional data to obtain network point diagnosis results; and displays the network point diagnosis results in a visual form. The present invention solves the technical problem that the evaluation of network point operation status mostly relies on manual experience and traditional report analysis, which is inefficient and difficult to fully and accurately reflect the real situation of network point operation.

[0027] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 The first embodiment of the network point management diagnosis method in the embodiment of the present invention includes: 101. Collect multi-dimensional data of outlets; In this embodiment, the multi-dimensional data includes: basic information of outlets, order splitting accuracy, market share, collection and delivery balance, abnormal suspension of shipment, and customer feedback.

[0029] This embodiment realizes the comprehensive collection and integration of network operation data based on the collected multi-dimensional data, ensuring the comprehensiveness and accuracy of the diagnosis.

[0030] 102. Preprocessing the collected multi-dimensional data of the network points to obtain pre-processed multi-dimensional data; In this embodiment, the collected multi-dimensional data of the network points are cleaned to obtain the cleaned multi-dimensional data of the network points; The cleaned multi-dimensional data of the network points are subjected to data conversion processing to obtain converted multi-dimensional data of the network points.

[0031] This embodiment can improve data quality, ensure data consistency, and improve analysis efficiency by preprocessing data.

[0032] 103. Construct a diagnostic analysis model, and use the diagnostic analysis model to analyze the pre-processed multi-dimensional data to obtain the point diagnosis results; In this embodiment, the pre-processed multi-dimensional data is subjected to a diagnostic analysis model, including branch basic information analysis, branch business volume analysis, branch customer information analysis, branch terminal data analysis, branch financial data analysis, branch time efficiency quality analysis, branch service quality analysis, and branch safety production analysis, to obtain corresponding indicator information; Specifically, the basic information indicators of the outlets are obtained based on the basic information analysis of the outlets, and the basic information indicators of the outlets include: the compliance status of the outlets, the staffing of outlet managers, the accuracy of the three-segment code sorting, and the abnormal suspension area; Obtaining outlet business volume indicators based on outlet business volume analysis, the outlet business volume indicators including: market share achievement, collection and dispatch balance, and total distribution market share; Based on the branch customer information analysis, the branch customer information indicators are obtained, and the branch customer information indicators include: customer stratification; Based on the analysis of the network terminal data, the network terminal indicators are obtained, wherein the network terminal indicators include: terminal indicators and village entry targets; Obtaining branch financial indicators based on branch financial data analysis, wherein the branch financial indicators include: prepayment status; Based on the network point timeliness quality analysis, the network point timeliness quality indicators are obtained, and the network point timeliness quality indicators include: scheduled collection rate, scheduled delivery rate, scheduled sorting rate and signing rate; Obtaining service quality indicators based on the service quality analysis of the outlets, the service quality indicators including: false receipt, loss rate and damage rate; Based on the network point production safety analysis, the network point production safety indicators are obtained, and the network point production safety indicators include: safety officer deployment status and safety inspection status.

[0033] Set judgment thresholds for each indicator; The score increase or decrease is calculated based on the judgment threshold according to the preset rules; Set different weights according to different indicators; Based on the corresponding scores of different indicators, the network point diagnosis results are calculated according to the corresponding weights of different indicators.

[0034] This embodiment uses the diagnostic analysis model based on preset diagnostic rules and algorithms to automatically complete the diagnostic analysis process, greatly improving work efficiency and accuracy; 104. Display the network point diagnosis results in a visual form; In this embodiment, a corresponding improvement strategy is generated based on the corresponding scores of multiple calculation indicators; The branch diagnosis results are displayed in a visual form using charts and reports. The display content includes: diagnosis report, abnormal indicator prompts and corresponding improvement strategies.

[0035] This embodiment uses a visual form to display the diagnosis results, so that managers can intuitively understand the operating status and problems of the outlets, providing strong support for formulating improvement measures.

[0036] See also Figure 2 The second embodiment of the network point management diagnosis method in the embodiment of the present invention includes: 201. Collect multi-dimensional data such as outlet operation data, business volume data, customer information, etc. from various data sources; In this embodiment, the multi-dimensional data includes but is not limited to basic information of outlets, order distribution accuracy, market share, collection and delivery balance, abnormal suspension of shipment, customer feedback, etc.

[0037] 202. Perform pre-processing including cleaning and integration on the collected data to ensure the accuracy and consistency of the data; at the same time, convert the data into a format suitable for analysis according to preset data processing rules.

[0038] 203. Analyze the preprocessed data using preset diagnostic rules and algorithms to obtain analysis results, and perform point diagnosis based on the analysis results to obtain point diagnosis results; In this embodiment, the pre-processed multi-dimensional data is subjected to a diagnostic analysis model, including branch basic information analysis, branch business volume analysis, branch customer information analysis, branch terminal data analysis, branch financial data analysis, branch time efficiency quality analysis, branch service quality analysis, and branch safety production analysis, to obtain corresponding indicator information; Set thresholds, and calculate the scores of the above key indicators and corresponding thresholds according to preset rules; set different weights according to different indicators; calculate the network point diagnosis results based on the corresponding scores of different indicators and the corresponding weights of different indicators. For example: based on the rule that the total score is 100 points, divided into 20 items, each normal item gets 5 points, and abnormal items get 0 points, conduct a health assessment of the network point.

[0039] Based on the basic information of the outlets, basic information indicators of the outlets are obtained, and the basic information indicators of the outlets include: compliance status of the outlets, staffing of outlet managers, accuracy of three-segment code sorting, and abnormal suspension areas; Compliance status: whether the compliance status of the branch is normal; data source: SOA-Branch Basic Information-Compliance Status; Operation / operation / customer service manager: whether the three positions of the branch's operation manager, operation manager, and customer service manager are all staffed. If they are all assigned, then pass; otherwise fail; data source: branch manager-administrative workbench; If the three-segment code and order splitting accuracy are lower than 93%, it is normal; if it is higher than or equal to 93%, it is abnormal. The value is taken at time T-1; data source: branch order splitting configuration system-order splitting intervention-order splitting intelligent diagnosis; Abnormal suspension: whether there is an abnormal suspension area, the value is taken in the most recent week; data source: provincial and regional business managers-network managers-sub-health outlets; Obtaining outlet business volume indicators based on outlet business volume analysis, the outlet business volume indicators including: market share achievement, collection and dispatch balance, and total distribution market share; Market share: Whether the market share of outlets has reached the target value of 17%, the time is T-2; data source: Provincial and regional business manager-outlet full information warning report; Collection / dispatch balance: Only dispatching without collection means that the number of dispatches is more than 100 but the daily collection volume is less than 50. Only collecting without dispatching means that the number of collections is more than 100 but the daily delivery volume is less than 50. Meeting any one of the above conditions is defined as abnormal (unbalanced collection and dispatch). If neither of the above two conditions is met, it is normal. The value is taken from the most recent week. Data source: Provincial and regional business managers - network managers - sub-healthy outlets.

[0040] Co-distribution market share: If the outlet is co-distributed and the market share of the outlet is less than 5%, it indicates abnormality; if the outlet is co-distributed and the market share is higher than 5%, or the outlet is not co-distributed, it is normal; data source: provincial and regional business manager-network manager-sub-health outlets; Based on the branch customer information analysis, the branch customer information indicators are obtained, and the branch customer information indicators include: customer stratification; Customer stratification: Among the customers of this outlet, the number of customers with more than 3,000 tickets is less than 3 and the proportion of the number of tickets is greater than 50%, which means that this item is abnormal (the proportion of traffic customers is too large); otherwise, it is normal (balanced shipments). The value is collected at T-1. Data source: Provincial and regional business manager-customer insight; Based on the analysis of the network terminal data, the network terminal indicators are obtained, wherein the network terminal indicators include: terminal indicators and village entry targets; Terminal indicator: If the number of stores built at the outlet is ≥ the number of stores to be built, it is normal; otherwise, it is abnormal. The value is taken at T-3. Data source: Provincial and regional business manager-network manager-terminal construction Goal of entering the village: The actual number of completed indicators of the outlet (last month) entering the village is less than the number of indicators that should be completed, which means that the goal has not been achieved; if the actual completion index is greater than or equal to the expected completion index or there is no index for entering the village, then this item is normal; the data collection time is T-1 month. Data source: Provincial and regional business manager-network manager-end-to-village.

[0041] Obtaining branch financial indicators based on branch financial data analysis, wherein the branch financial indicators include: prepayment status; Prepayment: If the prepayment of the outlet is negative for 7 consecutive days, it is abnormal, otherwise it is normal. The value is taken in the most recent week. Data source: Provincial and regional business manager-network manager-sub-health outlets.

[0042] Based on the network point timeliness quality analysis, the network point timeliness quality indicators are obtained, and the network point timeliness quality indicators include: scheduled collection rate, scheduled delivery rate, scheduled sorting rate and signing rate; Scheduled collection rate: Scheduled collection rate ≥ 98% is normal, < 98% is abnormal. Value collection time T-1; data source: Provincial and regional business manager-network manager-scheduled collection rate; Timed delivery rate (early eight): If the timed delivery rate (early eight) is ≥96%, it is normal, and if it is <96%, it is abnormal. The value is taken at T-1. Data source: Provincial and regional business manager-network manager-timed delivery rate; Timed sorting rate: If the timed sorting rate is ≥98%, it is normal; if it is <98%, it is abnormal; the value is taken at T-1. Data source: Provincial and regional business manager-distribution manager-timed sorting rate; Receipt rate: +1D2359 If the receipt rate is ≥90%, it is normal; if it is <90%, it is abnormal. The value is taken at T-1. Data source: Provincial and regional business manager-Navigation-Receipt rate.

[0043] Obtaining service quality indicators based on the service quality analysis of the outlets, the service quality indicators including: false receipt, loss rate and damage rate; False Signature: It is normal if the false signature rate is lower than 0.5%, otherwise it is abnormal; the value is taken at T-2, and the data comes from: Provincial Business Manager-Customer Service Manager-False Signature Report.

[0044] Loss rate: If the loss rate is lower than 0.5%, it is normal; otherwise, it is abnormal. The value is taken at time T-2, and the data source is: Provincial and regional business manager-customer service manager-loss report.

[0045] Damage rate: It is normal if the damage rate is less than 0.5%, otherwise it is abnormal. The value is taken at T-2, and the data source is: Provincial Operation Manager-Customer Service Manager-Damage Report.

[0046] Based on the network point production safety analysis, the network point production safety indicators are obtained, and the network point production safety indicators include: safety officer deployment status and safety inspection status.

[0047] Safety officer: The branch's safety officer has been assigned, so this item is normal; otherwise, it is abnormal. Data source: Branch Manager - Administrative Workbench - Personnel Management - Safety Post.

[0048] Safety inspection: If the number of unqualified items in the twenty inspections of the outlet is greater than 0, this item is abnormal; if the number of unqualified items in the twenty inspections is 0 or there are no twenty inspection records, this item is normal. The value is the latest inspection record. Data source: Provincial and regional business manager-network manager-safety inspection.

[0049] 204. Display the results of diagnostic analysis to managers in a visual form; In this embodiment, the displayed content includes diagnostic reports, abnormal indicator prompts, improvement suggestions, etc. Through intuitive charts and reports, managers can quickly understand the operating status of the outlets and formulate targeted improvement measures accordingly.

[0050] See also Figure 3 The third embodiment of the network point management diagnosis method in the embodiment of the present invention includes: 301. Construct a network management APP through the network point management diagnosis method; 302. Use the Network Manager APP to analyze the outlets and obtain 360 analysis reports.

[0051] Among them, 360 analysis reports include: Regional screening conditions: headquarters-region-business province-grid area; Network condition screening: all networks, sub-health networks, abnormal networks; SELECTED selection box for network scale: all, large scale, medium scale, small scale, and very small scale; Statistical dimensions: “aggregate dimension”, “network dimension”; The summary report analysis fields include: Branch basic information, abnormal assessment information, customer information, branch basic summary, branch management personnel; The analysis fields of the branch report include: Branch basic information, abnormal assessment information, customer information, branch basic summary, branch management personnel; Click on the branch name link to drill down and analyze the data.

[0052] The above describes the network point management diagnosis method in the embodiment of the present invention. The following describes the network point management diagnosis system in the embodiment of the present invention. Figure 4 In one embodiment of the present invention, a network point management diagnosis system includes: Collection module 401, used to collect multi-dimensional data of outlets; In this embodiment, the multi-dimensional data includes: basic information of outlets, order splitting accuracy, market share, collection and delivery balance, abnormal suspension of shipment, and customer feedback.

[0053] A preprocessing module 402 is used to preprocess the collected network point multi-dimensional data to obtain preprocessed multi-dimensional data; In this embodiment, the collected multi-dimensional data of the network points are cleaned to obtain the cleaned multi-dimensional data of the network points; The cleaned multi-dimensional data of the network points are subjected to data conversion processing to obtain converted multi-dimensional data of the network points.

[0054] The diagnosis module 403 is used to construct a diagnosis analysis model and use the diagnosis analysis model to analyze the pre-processed multi-dimensional data to obtain a point diagnosis result; In this embodiment, the pre-processed multi-dimensional data is subjected to a diagnostic analysis model, including branch basic information analysis, branch business volume analysis, branch customer information analysis, branch terminal data analysis, branch financial data analysis, branch time efficiency quality analysis, branch service quality analysis, and branch safety production analysis, to obtain corresponding indicator information; Specifically, the basic information indicators of the outlets are obtained based on the basic information analysis of the outlets, and the basic information indicators of the outlets include: the compliance status of the outlets, the staffing of outlet managers, the accuracy of the three-segment code sorting, and the abnormal suspension area; For example: compliance status, whether the compliance status of the branch is normal; Operations / operation / customer service manager: whether the three positions of operations manager, operation manager, and customer service manager of the branch are all staffed. If all are assigned, the branch passes; otherwise, the branch fails. It is normal if the accuracy of three-segment code and order splitting is lower than 93%, and it is abnormal if it is higher than or equal to 93%. The value is taken at time T-1; Abnormal suspension, whether there is an abnormal suspension area, the value is taken in the most recent week.

[0055] Obtaining outlet business volume indicators based on outlet business volume analysis, the outlet business volume indicators including: market share achievement, collection and dispatch balance, and total distribution market share; For example: market share, whether the market share of outlets reaches the target value of 17%, the time is T-2; Balanced collection / dispatch: only dispatching without collection means that there are more than 100 parcels to be delivered but the daily collection volume is less than 50 parcels; only collecting without dispatching means that there are more than 100 parcels to be collected but the daily delivery volume is less than 50 parcels. If any of the above conditions is met, it is defined as abnormal (unbalanced collection and dispatch); if neither of the above conditions is met, it is normal. The value is taken in the most recent week; Shared market share: if the outlet is shared and its market share is lower than 5%, it indicates an abnormality; if the outlet is shared and its market share is higher than 5%, or the outlet is not shared, it indicates normal.

[0056] Based on the branch customer information analysis, the branch customer information indicators are obtained, and the branch customer information indicators include: customer stratification; For example, in customer stratification, among the customers of this branch, the number of customers with more than 3,000 tickets is less than 3 and the proportion of the number of items is greater than 50%, which means that this item is abnormal (the proportion of traffic customers is too large); otherwise, it is normal (balanced delivery). The value is taken at T-1.

[0057] Based on the analysis of the network terminal data, the network terminal indicators are obtained, wherein the network terminal indicators include: terminal indicators and village entry targets; For example, if the number of stores that have been built is greater than the number of stores that should be built, it is normal; otherwise, it is abnormal. The value is taken at T-3; The target of entering the village is that the actual number of completed indicators of the branch (last month) entering the village is less than the number of indicators that should be completed, which means that the target has not been achieved; if the actual completion index is greater than or equal to the expected completion index or there is no target for entering the village, then this item is normal. The data collection time is T-1 month.

[0058] Obtaining branch financial indicators based on branch financial data analysis, wherein the branch financial indicators include: prepayment status; For example, if the prepayment of a branch is negative for 7 consecutive days, it is abnormal, otherwise it is normal. The value is taken in the latest week.

[0059] Based on the network point timeliness quality analysis, the network point timeliness quality indicators are obtained, and the network point timeliness quality indicators include: scheduled collection rate, scheduled delivery rate, scheduled sorting rate and signing rate; For example: scheduled collection rate, if the scheduled collection rate is ≥98%, it is normal, and if it is <98%, it is abnormal. The value is taken at time T-1.

[0060] Timed delivery rate (early eight), if the timed delivery rate (early eight) ≥ 96% is normal, and if it is less than 96%, it is abnormal. The value is taken at time T-1.

[0061] Timing sorting rate, if the timing sorting rate is ≥98%, it is normal, if it is <98%, it is abnormal. The value is taken at T-1.

[0062] Acceptance rate, +1D2359 acceptance rate ≥ 90% is normal, < 90% is abnormal. The value is taken at T-1.

[0063] Obtaining service quality indicators based on the service quality analysis of the outlets, the service quality indicators including: false receipt, loss rate and damage rate; For example: false receipt, it is normal if the false receipt rate is less than 5 / 10,000, otherwise it is abnormal. The value is taken at time T-2.

[0064] Loss rate: If the loss rate is lower than 5 / 10,000, it is normal; otherwise, it is abnormal. The value is taken at time T-2.

[0065] Damage rate: if the damage rate is lower than 5 / 10,000, it is normal; otherwise, it is abnormal. The value is taken at time T-2.

[0066] Obtaining outlet safety production indicators based on outlet safety production analysis, wherein the outlet safety production indicators include: safety officer deployment and safety inspection; For example: safety officer, the branch’s safety officer has been assigned, this item is normal; otherwise it is abnormal.

[0067] Safety inspection, if the number of unqualified items in the twenty inspections of the outlet is greater than 0, this item is abnormal; if the number of unqualified items in the twenty inspections is 0 or there are no twenty inspection records, this item is normal. The value is the latest inspection record.

[0068] Set judgment thresholds for each indicator; The score increase or decrease is calculated based on the judgment threshold according to the preset rules; Set different weights according to different indicators; Based on the corresponding scores of different indicators, the network point diagnosis results are calculated according to the corresponding weights of different indicators.

[0069] For example: Based on the rule that the total score is 100 points, divided into 20 items, 5 points for normal items and 0 points for abnormal items, a health assessment of the outlets is conducted.

[0070] This embodiment uses the diagnostic analysis model based on preset diagnostic rules and algorithms to automatically complete the diagnostic analysis process, greatly improving work efficiency and accuracy; A visualization module 404 is used to display the network point diagnosis results in a visual form; In this embodiment, the visualization module 404 includes: Generate corresponding improvement strategies based on the corresponding scores of multiple calculation indicators; The branch diagnosis results are displayed in a visual form using charts and reports. The display content includes: diagnosis report, abnormal indicator prompts and corresponding improvement strategies.

[0071] This embodiment uses a visual form to display the diagnosis results, so that managers can intuitively understand the operating status and problems of the outlets, providing strong support for formulating improvement measures.

[0072] above Figure 4 The network point management diagnosis system in the embodiment of the present invention is described in detail from the perspective of modular functional entities, and the electronic device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0073] Figure 5 7 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device 700 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 710 (for example, one or more processors) and a memory 720, and one or more storage media 730 (for example, one or more mass storage devices) storing application programs 733 or data 732. Among them, the memory 720 and the storage medium 730 can be temporary storage or permanent storage. The program stored in the storage medium 730 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the electronic device 700. Furthermore, the processor 710 may be configured to communicate with the storage medium 730 to execute a series of instruction operations in the storage medium 730 on the electronic device 700.

[0074] The electronic device 700 may also include one or more power supplies 740, one or more wired or wireless network interfaces 750, one or more input / output interfaces 750, and / or one or more operating systems 731, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 5 The structure of the electronic device shown does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine some components, or arrange the components differently.

[0075] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the network management diagnostic method.

[0076] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0077] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0078] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A network point management diagnosis method, characterized in that: include: Collect multi-dimensional data of outlets; Preprocessing the collected multi-dimensional data of network points to obtain preprocessed multi-dimensional data; Construct a diagnostic analysis model, and use it to analyze the pre-processed multi-dimensional data to obtain the point diagnosis results; The network point diagnosis results are displayed in a visual form.

2. The network point management diagnosis method according to claim 1, characterized in that: The multi-dimensional data of the collection outlets include: basic information of the outlets, order splitting accuracy, market share, collection and delivery balance, abnormal suspension of shipment and customer feedback.

3. The network point management diagnosis method according to claim 1, characterized in that: The preprocessing of the collected multi-dimensional data of network points includes: Performing data cleaning on the collected multi-dimensional data of the outlets to obtain cleaned multi-dimensional data of the outlets; The cleaned multi-dimensional data of the network points are subjected to data conversion processing to obtain converted multi-dimensional data of the network points.

4. The network point management diagnosis method according to claim 1, characterized in that: The method of using the diagnostic analysis model to analyze the pre-processed multi-dimensional data to obtain the point diagnosis result includes: The diagnostic analysis model is used to conduct analysis on the pre-processed multi-dimensional data, including branch basic information analysis, branch business volume analysis, branch customer information analysis, branch terminal data analysis, branch financial data analysis, branch timeliness quality analysis, branch service quality analysis and branch safety production analysis, to obtain corresponding indicator information, and analyze the branch diagnosis results based on the indicator information.

5. The network point management diagnosis method according to claim 4, characterized in that: Based on the basic information of the outlets, basic information indicators of the outlets are obtained, and the basic information indicators of the outlets include: compliance status of the outlets, staffing of outlet managers, accuracy of three-segment code sorting, and abnormal suspension areas; Obtaining outlet business volume indicators based on outlet business volume analysis, the outlet business volume indicators including: market share achievement, collection and dispatch balance, and total distribution market share; Based on the branch customer information analysis, the branch customer information indicators are obtained, and the branch customer information indicators include: customer stratification; Based on the analysis of the network terminal data, the network terminal indicators are obtained, wherein the network terminal indicators include: terminal indicators and village entry targets; Obtaining branch financial indicators based on branch financial data analysis, wherein the branch financial indicators include: prepayment status; Based on the network point timeliness quality analysis, the network point timeliness quality indicators are obtained, and the network point timeliness quality indicators include: scheduled collection rate, scheduled delivery rate, scheduled sorting rate and signing rate; Obtaining service quality indicators based on the service quality analysis of the outlets, the service quality indicators including: false receipt, loss rate and damage rate; Based on the network point production safety analysis, the network point production safety indicators are obtained, and the network point production safety indicators include: safety officer deployment status and safety inspection status.

6. The network point management diagnosis method according to claim 5, characterized in that: The diagnostic analysis model is constructed, and the pre-processed multi-dimensional data is analyzed using the diagnostic analysis model to obtain the network point diagnosis results, including: Use the diagnostic analysis model to analyze the pre-processed multi-dimensional data, including basic information analysis of outlets, business volume analysis of outlets, customer information analysis of outlets, terminal data analysis of outlets, financial data analysis of outlets, timeliness and quality analysis of outlets, service quality analysis of outlets, and production safety analysis of outlets, to obtain corresponding indicator information; Set judgment thresholds for each indicator; The score increase or decrease is calculated based on the judgment threshold according to the preset rules; Set different weights according to different indicators; Based on the corresponding scores of different indicators, the network point diagnosis results are calculated according to the corresponding weights of different indicators.

7. The network point management diagnosis method according to claim 1, characterized in that: The network point diagnosis results are displayed in a visual form, including: Generate corresponding improvement strategies based on the corresponding scores of multiple calculation indicators; The branch diagnosis results are displayed in a visual form using charts and reports. The display content includes: diagnosis report, abnormal indicator prompts and corresponding improvement strategies.

8. A network point management diagnosis method, characterized in that: include: Collection module, used to collect multi-dimensional data of outlets; A preprocessing module is used to preprocess the collected multi-dimensional data of the network points to obtain preprocessed multi-dimensional data; The diagnosis module is used to build a diagnosis analysis model and use the diagnosis analysis model to analyze the pre-processed multi-dimensional data to obtain the point diagnosis results; The visualization module is used to display the network point diagnosis results in a visual form.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the network point management diagnosis method according to any one of claims 1 to 7 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the computer program is executed by a processor, the steps of the network point management diagnosis method according to any one of claims 1 to 7 are implemented.

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