Data asset handover processing method and device

Abstract

The invention discloses a data asset handover processing method and device, and relates to the technical field of Internet. A specific embodiment of the method comprises the steps of evaluating each data asset in a data asset pool according to a preset data asset evaluation rule, and determining a to-be-processed data asset according to an evaluation result; for each to-be-processed data asset, obtaining business information of the to-be-processed data asset, and determining a target handover personnel corresponding to the to-be-processed data asset through an allocation rule; each to-be-processed data asset is allocated to a corresponding target handover person, a corresponding data asset maintenance plan is generated, and the target handover person executes the data asset maintenance plan; and completing handover processing of each to-be-processed data asset by monitoring an execution result of the corresponding data asset maintenance plan. According to the embodiment, unified hosting of data asset handover can be realized, high-quality data assets are mined, the processing effect of the data assets is improved, and business loss is avoided.

Description

Technical Field

[0001] The present invention relates to the field of Internet technology, and in particular to a data asset handover processing method and device. Background Art

[0002] When staff members in the business system change (such as resignation, leave, job transfer, etc.), the data assets corresponding to the changed staff members need to be handed over. The current data asset handover solution is to determine the target handover personnel based on handover experience, and manually assign all data assets corresponding to the changed staff members to the target handover personnel to complete the data asset handover process.

[0003] In the process of implementing the present invention, the inventors found that there are at least the following problems in the prior art:

[0004] The efficiency of data asset handover is low, and high-quality data assets cannot be mined from a large number of data assets, resulting in the concealment of high-quality data assets. In addition, the determination of target handover personnel is highly subjective, and the compatibility between data assets and target handover personnel is low. As a result, the target handover personnel have poor processing effects on data assets, which can easily lead to business loss. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides a data asset handover processing method and device, which can realize unified trusteeship of data asset handover, improve the efficiency of data asset handover processing, evaluate each data asset through data asset evaluation rules, and thus mine high-quality data assets from a large number of data assets, give priority to handover processing of high-quality data assets, and determine the target handover personnel through allocation rules, thereby improving the adaptability between data assets and target handover personnel, thereby improving the processing effect of data assets by the target handover personnel and avoiding business loss.

[0006] To achieve the above objective, according to one aspect of an embodiment of the present invention, a data asset handover processing method is provided.

[0007] A data asset handover processing method, comprising: responding to a data asset handover processing request, evaluating each data asset in a data asset pool according to preset data asset evaluation rules, and determining at least one data asset to be processed based on the evaluation results; for each of the data assets to be processed, obtaining the business information of the data asset to be processed, and determining the target handover personnel corresponding to the data asset to be processed based on the business information and preset allocation rules; allocating each of the data assets to be processed to the corresponding target handover personnel, and generating a corresponding data asset maintenance plan, so that the corresponding target handover personnel can execute the corresponding data asset maintenance plan; completing the handover processing of each of the data assets to be processed by monitoring the execution results of the corresponding data asset maintenance plan.

[0008] Optionally, the data assets include pre-sales stage data, sales stage data and post-sales stage data; the evaluating each data asset in the data asset pool according to the preset data asset evaluation rules includes: obtaining the pre-sales stage data, sales stage data and post-sales stage data corresponding to the data asset; evaluating the pre-sales stage data, the sales stage data and the post-sales stage data respectively according to the weight evaluation rules corresponding to the data in each stage to obtain a first score, a second score and a third score; generating an evaluation score of the data asset through the first score, the second score and the third score.

[0009] Optionally, determining at least one data asset to be processed based on the evaluation result includes: based on a preset evaluation score threshold, taking a data asset whose evaluation score reaches the evaluation score threshold as the data asset to be processed.

[0010] Optionally, the target handover personnel corresponding to the data assets to be processed are determined according to the business information through preset allocation rules, including: determining at least one handover personnel corresponding to the business information according to the business information; for each of the handover personnel, evaluating the handover personnel according to preset handover personnel evaluation rules to generate an evaluation score for the handover personnel; and selecting the handover personnel with the highest evaluation score as the target handover personnel for the data assets to be processed.

[0011] Optionally, the handover personnel is evaluated according to preset handover personnel evaluation rules to generate an evaluation score for the handover personnel, including: obtaining the risk control dimension data, capability dimension data and load dimension data of the handover personnel within a preset time period; according to the evaluation rules corresponding to each dimension data, the risk control dimension data, the capability dimension data and the load dimension data are evaluated respectively to obtain a risk control dimension score, a capability dimension score and a load dimension score; and the handover personnel's evaluation score is generated through the risk control dimension score, the capability dimension score and the load dimension score.

[0012] Optionally, the handover processing of each of the data assets to be processed is completed by monitoring the execution results of the corresponding data asset maintenance plan, including: for each of the data assets to be processed, monitoring the execution results of the corresponding data asset maintenance plan, and when the execution result is incomplete, redetermining the target handover personnel for the data assets to be processed, and assigning the data assets to be processed to the new target handover personnel, generating a new data asset maintenance plan, so that the new target handover personnel executes the new data asset maintenance plan, and completing the handover processing of the data assets to be processed by monitoring the execution results of the new data asset maintenance plan.

[0013] Optionally, after determining at least one data asset to be processed according to the evaluation results, the method further includes: according to the evaluation score threshold, treating the data assets whose evaluation scores do not reach the evaluation score threshold as data assets to be optimized; for each of the data assets to be optimized, optimizing the data assets to be optimized by completing information until the evaluation score of the data asset to be optimized reaches the evaluation score threshold.

[0014] According to another aspect of an embodiment of the present invention, a data asset handover processing device is provided.

[0015] A data asset handover processing device, comprising: a data asset to be processed determination module, used to respond to a data asset handover processing request, evaluate each data asset in a data asset pool according to a preset data asset evaluation rule, and determine at least one data asset to be processed based on the evaluation result; a target handover personnel determination module, used to obtain the business information of each data asset to be processed, and determine the target handover personnel corresponding to the data asset to be processed according to the business information and preset allocation rules; a data asset to be processed allocation module, used to allocate each data asset to be processed to a corresponding target handover personnel, and generate a corresponding data asset maintenance plan, so that the corresponding target handover personnel can execute the corresponding data asset maintenance plan; an execution result monitoring module, used to complete the handover processing of each data asset to be processed by monitoring the execution result of the corresponding data asset maintenance plan.

[0016] Optionally, the data assets include pre-sales stage data, sales stage data and after-sales stage data; the module for determining data assets to be processed is also used to: obtain the pre-sales stage data, sales stage data and after-sales stage data corresponding to the data assets; evaluate the pre-sales stage data, the sales stage data and the after-sales stage data according to the weight evaluation rules corresponding to the data in each stage, and obtain a first score, a second score and a third score; generate an evaluation score for the data asset through the first score, the second score and the third score.

[0017] Optionally, the to-be-processed data asset determination module is further configured to: based on a preset evaluation score threshold, take data assets whose evaluation scores reach the evaluation score threshold as the to-be-processed data assets.

[0018] Optionally, the target handover personnel determination module is also used to: determine, based on the business information, at least one handover personnel corresponding to the business information; for each of the handover personnel, evaluate the handover personnel according to preset handover personnel evaluation rules to generate an evaluation score for the handover personnel; and select the handover personnel with the highest evaluation score as the target handover personnel for the data assets to be processed.

[0019] Optionally, the target handover personnel determination module is also used to: obtain the risk control dimension data, capability dimension data and load dimension data of the handover personnel within a preset time period; evaluate the risk control dimension data, the capability dimension data and the load dimension data respectively according to the evaluation rules corresponding to each dimension data to obtain the risk control dimension score, the capability dimension score and the load dimension score; generate the evaluation score of the handover personnel through the risk control dimension score, the capability dimension score and the load dimension score.

[0020] Optionally, the execution result monitoring module is also used to: for each of the data assets to be processed, monitor the execution result of the corresponding data asset maintenance plan; if the execution result is incomplete, redetermine the target handover personnel for the data assets to be processed, and assign the data assets to be processed to the new target handover personnel, generate a new data asset maintenance plan, and have the new target handover personnel execute the new data asset maintenance plan; and complete the handover processing of the data assets to be processed by monitoring the execution result of the new data asset maintenance plan.

[0021] Optionally, it also includes a data asset optimization module, which is used to: according to the evaluation score threshold, treat the data assets whose evaluation scores do not reach the evaluation score threshold as data assets to be optimized; for each data asset to be optimized, optimize the data asset to be optimized by completing information until the evaluation score of the data asset to be optimized reaches the evaluation score threshold.

[0022] According to yet another aspect of the embodiments of the present invention, an electronic device is provided.

[0023] An electronic device comprises: one or more processors; a memory for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the data asset handover processing method provided in an embodiment of the present invention.

[0024] According to yet another aspect of an embodiment of the present invention, a computer readable medium is provided.

[0025] A computer-readable medium stores a computer program, which, when executed by a processor, implements the data asset handover processing method provided in an embodiment of the present invention.

[0026] An embodiment of the above invention has the following advantages or beneficial effects: by responding to a data asset handover processing request, each data asset in the data asset pool is evaluated according to a preset data asset evaluation rule, and at least one data asset to be processed is determined according to the evaluation result; for each data asset to be processed, the business information of the data asset to be processed is obtained, and according to the business information, the target handover personnel corresponding to the data asset to be processed is determined according to the preset allocation rule; each data asset to be processed is allocated to the corresponding target handover personnel, and a corresponding data asset maintenance plan is generated, so that the corresponding target handover personnel can perform the corresponding The data asset maintenance plan is executed; by monitoring the execution results of the corresponding data asset maintenance plan, the technical solution for the handover processing of each data asset to be processed is completed, which can realize the unified trusteeship of data asset handover and improve the efficiency of data asset handover processing. By evaluating each data asset through the data asset evaluation rules, high-quality data assets can be mined from a large number of data assets, and high-quality data assets are given priority for handover processing. In addition, the target handover personnel are determined through the allocation rules to improve the adaptability between data assets and target handover personnel, thereby improving the processing effect of data assets by the target handover personnel and avoiding business loss.

[0027] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings are used to better understand the present invention and do not constitute an improper limitation of the present invention.

[0029] Figure 1 is a schematic diagram of the main steps of a data asset handover processing method according to an embodiment of the present invention;

[0030] Figure 2 is a schematic diagram of a process for evaluating data assets according to an embodiment of the present invention;

[0031] Figure 3 is a flowchart of a data asset handover processing method according to an embodiment of the present invention;

[0032] Figure 4 is a schematic diagram of main modules of a data asset handover processing device according to an embodiment of the present invention;

[0033] Figure 5 is an exemplary system architecture diagram to which embodiments of the present invention may be applied;

[0034] Figure 6 It is a schematic diagram of the structure of a computer system of a terminal device or a server suitable for implementing an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0036] It should be noted that the collection, collection, updating, analysis, processing, use, transmission, storage and other aspects of user personal information involved in the technical solution of the present invention are in compliance with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken for user personal information to prevent illegal access to user personal information data and maintain the security of user personal information, network security and national security.

[0037] Figure 1 It is a schematic diagram of the main steps of a data asset handover processing method according to an embodiment of the present invention.

[0038] like Figure 1 As shown, a data asset handover processing method according to an embodiment of the present invention mainly includes the following steps S101 to S104.

[0039] Step S101: In response to a data asset handover request, each data asset in the data asset pool is evaluated according to a preset data asset evaluation rule, and at least one data asset to be processed is determined based on the evaluation result. The data assets may include pre-sale stage data, sale stage data, and post-sale stage data.

[0040] Figure 2 It is a schematic diagram of a process of evaluating data assets according to an embodiment of the present invention.

[0041] like Figure 2 As shown, in one embodiment, evaluating each data asset in the data asset pool according to preset data asset evaluation rules can include: obtaining pre-sales stage data, sales stage data, and post-sales stage data corresponding to the data asset; evaluating the pre-sales stage data, sales stage data, and post-sales stage data according to the weight evaluation rules corresponding to each stage data, respectively, to obtain a first score, a second score, and a third score; and generating an evaluation score for the data asset through the first score, the second score, and the third score.

[0042] Specifically, the pre-sales stage data refers to data related to pre-sales behavior, which may include historical visit times and lead conversion rates, among which the historical visit times refer to the sum of visits to the same customer, and the lead conversion rate may be calculated as: the number of leads converted into business opportunities / total number of leads*100%. The evaluation rules corresponding to the pre-sales stage data may include: for the number of historical visits, if the number of historical visits is less than 2 times, the score of the historical visits is 10 points, if the number of historical visits is greater than 5 times, the score of the historical visits is 60 points, if the number of historical visits is between 2 times and 5 times, the score of the historical visits is 40 points; for the lead conversion rate, if the lead conversion rate is less than the first conversion rate threshold, the score of the lead conversion rate is 10 points, if the lead conversion rate is greater than the second conversion rate threshold, the score of the lead conversion rate is 60 points, if the lead conversion rate is between the first conversion rate threshold and the second conversion rate threshold, the score of the lead conversion rate is 40 points, wherein the first conversion rate threshold may be 20% of the average conversion rate of all data assets of the same business line within a preset time period, and the first conversion rate threshold may be 30% of the average conversion rate of all data assets of the same business line within a preset time period; the score of the historical number of visits and the score of the lead conversion rate are weighted averaged to obtain a first score, wherein the weight of the score of the historical number of visits may be 30%, and the weight of the score of the lead conversion rate may be 70%.

[0043] The data in the mid-sales stage refers to the data related to the mid-sales behavior, which may include the business opportunity signing rate, customer cooperation rate, and business opportunity promotion efficiency. The business opportunity signing rate may be calculated as follows: the number of signed business opportunities / the total number of business opportunities*100%, and the customer cooperation rate may be calculated as follows: the number of cooperated customers / the total number of customers*100%. The business opportunity promotion efficiency refers to the average time taken from creation to signing of all business opportunities corresponding to the data asset to be processed. The evaluation rules corresponding to the data in the mid-sales stage may include: for the business opportunity signing rate, if the business opportunity signing rate is less than the first signing rate threshold, the score of the business opportunity signing rate is 10 points, if the business opportunity signing rate is greater than the second signing rate threshold, the score of the business opportunity signing rate is 60 points, if the business opportunity signing rate is between the first signing rate threshold and the second signing rate threshold, the score of the business opportunity signing rate is 40 points, wherein the first signing rate threshold may be 20% of the average signing rate of all data assets of the same business line in a preset time period, and the first signing rate threshold may be 30% of the average signing rate of all data assets of the same business line in a preset time period; for the customer cooperation rate, if the customer cooperation rate is less than the first cooperation rate threshold, the score of the customer cooperation rate is 10 points, if the customer cooperation rate is greater than the second cooperation rate threshold, the score of the customer cooperation rate is 60 points, and if the customer cooperation rate is between the first cooperation rate threshold and the second cooperation rate threshold values, the customer cooperation rate score is 40 points, wherein the first cooperation rate threshold can be 10% of the average cooperation rate of all data assets in the same business line within the preset time period, and the second cooperation rate threshold can be 30% of the average cooperation rate of all data assets in the same business line within the preset time period; for business opportunity promotion efficiency, if the business opportunity promotion efficiency is greater than 5 days, the business opportunity promotion efficiency score is 10 points, if the business opportunity promotion efficiency is less than 3 days, the business opportunity promotion efficiency score is 60 points, if the business opportunity promotion efficiency is between 3 days and 5 days, the business opportunity promotion efficiency score is 40 points; the weighted average of the scores including the business opportunity signing rate, the customer cooperation rate and the business opportunity promotion efficiency is obtained to obtain the second score, wherein the weight of the business opportunity signing rate score can be 40%, the weight of the customer cooperation rate score can be 40%, and the weight of the business opportunity promotion efficiency score can be 20%.

[0044] After-sales stage data refers to data related to after-sales behavior, which may include renewal ratio, number of after-sales maintenance visits, and proportion of tapped customers, among which the renewal ratio may be calculated as: number of renewed customers / total number of customers in the previous time period*100%, number of after-sales maintenance visits refers to the sum of the number of visits to customers in the after-sales stage, and the proportion of tapped customers may be calculated as: number of tapped customers / total number of customers*100%. Evaluation rules corresponding to after-sales stage data may include: for renewal ratio, if the renewal ratio is 0, the score of renewal ratio is 10 points, if the renewal ratio is greater than 50%, the score of renewal ratio is 60 points, if the renewal ratio is between 0 and 50%, the score of renewal ratio is 40 points; for after-sales maintenance visits, if the number of after-sales maintenance visits is less than 2 times, the score of after-sales maintenance visits is 10 points, if the number of after-sales maintenance visits is greater than 5 times, the score of after-sales maintenance visits is 60 points, if the number of after-sales maintenance visits is between 2 and 5 times, the score of after-sales maintenance visits is 4 0 points; for the proportion of mined customers, if the proportion of mined customers is 0, the score of the proportion of mined customers is 10 points, if the proportion of mined customers is greater than 50%, the score of the proportion of mined customers is 60 points, if the proportion of mined customers is between 0 and 50%, the score of the proportion of mined customers is 40 points; take a weighted average of the scores including the renewal proportion, the score of the number of after-sales maintenance visits and the score of the proportion of mined customers to obtain a third score, among which the weight of the renewal proportion score can be 50%, the weight of the score of the number of after-sales maintenance visits can be 10%, and the weight of the score of the proportion of mined customers can be 40%.

[0045] After obtaining the first score, the second score and the third score, an evaluation score of the data asset is generated by weighted summing or weighted averaging the first score, the second score and the third score, wherein the weights of the first score, the second score and the third score may be 30%, 50% and 20% respectively.

[0046] In one embodiment, determining at least one data asset to be processed based on the evaluation result may include: based on a preset evaluation score threshold, taking data assets whose evaluation scores reach the evaluation score threshold as data assets to be processed.

[0047] Specifically, data assets whose evaluation scores reach an evaluation score threshold (such as 60 points) are marked as high-quality data assets and are subject to a handover process as data assets to be processed.

[0048] In one embodiment, after determining at least one data asset to be processed according to the evaluation results, it may also include: according to the evaluation score threshold, treating data assets whose evaluation scores do not reach the evaluation score threshold as data assets to be optimized; for each data asset to be optimized, optimizing the data asset to be optimized by completing information until the evaluation score of the data asset to be optimized reaches the evaluation score threshold.

[0049] Specifically, data assets whose evaluation scores do not reach the evaluation score threshold (such as 60 points) are marked as low-quality data assets, and are optimized as data assets to be optimized through intelligent information completion until the evaluation score of the data assets to be optimized reaches the evaluation score threshold.

[0050] In another embodiment, data assets whose evaluation scores do not reach a low-quality evaluation score threshold (such as 10 points) are marked as invalid data assets, and the invalid data assets are stored in a smart incubation pool for incubation until the evaluation score reaches the evaluation score threshold.

[0051] Step S102: For each data asset to be processed, business information of the data asset to be processed is obtained, and according to the business information and a preset allocation rule, a target handover person corresponding to the data asset to be processed is determined.

[0052] In one embodiment, based on business information and through preset allocation rules, the target handover personnel corresponding to the data assets to be processed are determined, which may include: based on the business information, determining at least one handover personnel corresponding to the business information; for each handover personnel, evaluating the handover personnel according to preset handover personnel evaluation rules, and generating an evaluation score for the handover personnel; and selecting the handover personnel with the highest evaluation score as the target handover personnel for the data assets to be processed.

[0053] Specifically, business information may include regions, battle zones and business lines. For example, salesperson Zhang San is in the cold chain pharmaceutical line in the Shaanxi battle zone in the Northwest region. After Zhang San leaves his job, the data assets under his control need to be allocated to other sales personnel in the same region, the same battle zone and the same business line. Therefore, it is necessary to obtain all handover personnel in the cold chain pharmaceutical line in the Shaanxi battle zone in the Northwest region, evaluate each handover personnel according to the preset handover personnel evaluation rules, generate an evaluation score for the handover personnel, and select the handover personnel with the highest evaluation score as the target handover personnel for the data assets to be processed.

[0054] In one embodiment, the handover personnel are evaluated according to preset handover personnel evaluation rules to generate an evaluation score for the handover personnel, which may include: obtaining the risk control dimension data, capability dimension data, and load dimension data of the handover personnel within a preset time period (such as 1 month, 1 quarter, 1 year, etc.); according to the evaluation rules corresponding to each dimension data, the risk control dimension data, the capability dimension data, and the load dimension data are evaluated respectively to obtain the risk control dimension score, the capability dimension score, and the load dimension score; and the handover personnel's evaluation score is generated through the risk control dimension score, the capability dimension score, and the load dimension score.

[0055] Specifically, the risk control dimension data refers to the risk control-related data of the handover personnel, which may include risk control penalty measures such as risk control deductions, performance deductions, demotions, and public criticism of the handover personnel. The evaluation rules of the risk control dimension data may include: obtaining the risk control deduction score through the risk control deduction and the preset risk control deduction threshold, obtaining the performance deduction score through the performance deduction and the preset performance deduction threshold, obtaining the salary reduction and demotion score through the number of salary reductions and demotions and the preset salary reduction and demotion threshold, and obtaining the criticism score through the number of public criticisms and the preset criticism threshold; obtaining the criticism score through the weighted average of the risk control deduction score, performance deduction score, demotion and salary reduction score, and public criticism score to obtain the risk control dimension score of the handover personnel. Among them, the greater the risk control deduction, performance deduction, demotion and salary reduction, and public criticism of the handover personnel, the greater the corresponding score, and thus the greater the risk control dimension score.

[0056] Capability dimension data refers to data related to the business capabilities of the handover personnel, which may include the business opportunity signing rate, lead conversion rate, and customer cooperation rate of the handover personnel. The evaluation rules for capability dimension data may include obtaining the score of the business opportunity signing rate through the business opportunity signing rate and the preset business opportunity signing rate threshold, obtaining the score of the lead conversion rate through the lead conversion rate and the preset lead conversion rate threshold, and obtaining the score of the customer cooperation rate through the customer cooperation rate and the preset customer cooperation rate threshold; and obtaining the capability dimension score of the handover personnel by weighted averaging the scores of the business opportunity signing rate, the lead conversion rate, and the customer cooperation rate. Among them, the greater the business opportunity signing rate, the lead conversion rate, and the customer cooperation rate of the handover personnel, the greater the corresponding score, and thus the greater the capability dimension score.

[0057] The load dimension data refers to the data of the data assets loaded and processed by the handover personnel, which may include the number of customers, business opportunities, visits, and leads of the handover personnel. The evaluation rules of the load dimension data may include: obtaining the score of the number of customers by the number of customers and the preset threshold of the number of customers, obtaining the score of the number of business opportunities by the number of business opportunities and the preset threshold of the number of business opportunities, obtaining the score of the number of visits by the number of visits and the preset threshold of the number of visits, obtaining the score of the number of leads by the number of leads and the preset threshold of the number of leads, and obtaining the score of the number of customers by weighted average, the score of the number of business opportunities, the score of the number of visits, and the score of the number of leads. Among them, the smaller the number of customers, business opportunities, visits, and leads of the handover personnel, the larger the corresponding score, and thus the larger the ability dimension score.

[0058] After obtaining the risk control dimension score, capability dimension score and load dimension score of the handover personnel, the evaluation score of the handover personnel is generated by taking a weighted average of the opposite value of the risk control dimension score, the capability dimension score and the load dimension score.

[0059] Step S103: Allocate each data asset to be processed to a corresponding target handover personnel, and generate a corresponding data asset maintenance plan, so that the corresponding target handover personnel can execute the corresponding data asset maintenance plan.

[0060] Specifically, through scheduled tasks, each data asset to be processed is assigned to the corresponding target handover personnel, ensuring that customer data, business opportunity data, business account data, lead data, visit data, etc. can be automatically assigned to the corresponding target handover personnel, and then a data asset handover document is generated, and the handover process is carried out through the data asset handover document. For each data asset to be processed, a data asset maintenance plan is generated for the target handover personnel to perform visit maintenance based on the data asset to be processed and the target handover personnel.

[0061] Step S104: Complete the handover process of each data asset to be processed by monitoring the execution result of the corresponding data asset maintenance plan.

[0062] In one embodiment, the handover processing of each data asset to be processed is completed by monitoring the execution results of the corresponding data asset maintenance plan, which may include: for each data asset to be processed, monitoring the execution results of the corresponding data asset maintenance plan, and when the execution result is incomplete, re-determining the target handover personnel for the data asset to be processed, and assigning the data asset to be processed to the new target handover personnel, generating a new data asset maintenance plan, and having the new target handover personnel execute the new data asset maintenance plan, and completing the handover processing of the data asset to be processed by monitoring the execution results of the new data asset maintenance plan.

[0063] Specifically, for each data asset to be processed, the target handover personnel's execution results of the data asset maintenance plan are monitored. If it is not completed within 3 days, the target handover personnel will be reminded. If it is still not completed within 7 days, the execution result is confirmed to be incomplete, and the process returns to the step of determining the target handover personnel for the data asset to be processed; if it is completed within 7 days, the data asset to be processed is confirmed to be handed over to the target handover personnel. The embodiment of the present invention realizes the closed loop of the data asset visit plan through system monitoring and automatic tasks, ensures high efficiency and accuracy at the data level, and reduces customer losses at the business level, thereby reducing economic losses caused by customer churn.

[0064] Figure 3 It is a flowchart of a data asset handover processing method according to an embodiment of the present invention.

[0065] like Figure 3 As shown, in one embodiment, the data assets corresponding to the staff members who have changed are saved in the data asset pool, and each data asset in the data asset pool is evaluated according to the preset data asset evaluation rules, and the data assets to be processed and the data assets to be optimized are determined according to the evaluation score threshold. For each data asset to be processed, the target handover personnel corresponding to the data asset to be processed are determined by the preset allocation rules, and the data assets to be processed are allocated to the corresponding target handover personnel, and then a data asset maintenance plan is generated, and the execution result of the data asset maintenance plan by the target handover personnel is monitored. If the execution result is not completed, the step of determining the target handover personnel according to the allocation rules is returned, and if the execution result is completed, the handover processing of the data assets to be processed is completed. For each data asset to be optimized, the data asset to be optimized is optimized by incubation or information completion until the evaluation score of the data asset to be optimized reaches the evaluation score threshold.

[0066] The embodiment of the present invention can evaluate the data assets corresponding to the staff members who have changed, uniformly manage and clean the data, and identify high-quality data assets. Through the algorithm engine, combined with multiple dimensions such as risk control, sales ability, and current load, dynamic calculation and intelligent recommendation of the most suitable handover personnel to visit and maintain data assets can be performed, and a visit plan can be automatically created to ensure that the handover personnel can maintain customers in a timely manner and avoid business loss.

[0067] Figure 4 It is a schematic diagram of main modules of a data asset handover processing device according to an embodiment of the present invention.

[0068] like Figure 4 As shown, a data asset handover processing device 400 according to an embodiment of the present invention mainly includes: a data asset to be processed determination module 401, a target handover personnel determination module 402, a data asset to be processed allocation module 403, and an execution result monitoring module 404.

[0069] The module 401 for determining data assets to be processed is used to respond to a data asset handover request, evaluate each data asset in the data asset pool according to preset data asset evaluation rules, and determine at least one data asset to be processed based on the evaluation results.

[0070] The target handover personnel determination module 402 is used to obtain the business information of each data asset to be processed, and determine the target handover personnel corresponding to the data asset to be processed according to the business information and preset allocation rules.

[0071] The data asset allocation module 403 is used to allocate each data asset to be processed to a corresponding target handover personnel, and generate a corresponding data asset maintenance plan so that the corresponding target handover personnel can execute the corresponding data asset maintenance plan.

[0072] The execution result monitoring module 404 is used to complete the handover processing of each data asset to be processed by monitoring the execution result of the corresponding data asset maintenance plan.

[0073] In one embodiment, data assets may include pre-sales stage data, sales stage data, and post-sales stage data; the module 401 for determining data assets to be processed is specifically used to: obtain the pre-sales stage data, sales stage data, and post-sales stage data corresponding to the data assets; evaluate the pre-sales stage data, sales stage data, and post-sales stage data according to the weight evaluation rules corresponding to the data in each stage, and obtain a first score, a second score, and a third score; and generate an evaluation score for the data asset through the first score, the second score, and the third score.

[0074] In one embodiment, the to-be-processed data asset determination module 401 is specifically used to: according to a preset evaluation score threshold, take data assets whose evaluation scores reach the evaluation score threshold as data assets to be processed.

[0075] In one embodiment, the target handover personnel determination module 402 is specifically used to: determine, based on the business information, at least one handover personnel corresponding to the business information; for each handover personnel, evaluate the handover personnel according to the preset handover personnel evaluation rules to generate an evaluation score for the handover personnel; select the handover personnel with the highest evaluation score as the target handover personnel for the data assets to be processed.

[0076] In one embodiment, the target handover personnel determination module 402 is specifically used to: obtain the risk control dimension data, capability dimension data, and load dimension data of the handover personnel within a preset time period; evaluate the risk control dimension data, capability dimension data, and load dimension data respectively according to the evaluation rules corresponding to each dimension data to obtain the risk control dimension score, capability dimension score, and load dimension score; generate the evaluation score of the handover personnel through the risk control dimension score, capability dimension score, and load dimension score.

[0077] In one embodiment, the execution result monitoring module 404 is specifically used to: for each data asset to be processed, monitor the execution result of the corresponding data asset maintenance plan; if the execution result is incomplete, redetermine the target handover personnel for the data asset to be processed, and assign the data asset to be processed to the new target handover personnel, generate a new data asset maintenance plan, and have the new target handover personnel execute the new data asset maintenance plan; and complete the handover processing of the data asset to be processed by monitoring the execution result of the new data asset maintenance plan.

[0078] In one embodiment, a data asset optimization module (not shown in the figure) may also be included, which is used to: according to the evaluation score threshold, treat data assets whose evaluation scores do not reach the evaluation score threshold as data assets to be optimized; for each data asset to be optimized, optimize the data asset to be optimized by completing information until the evaluation score of the data asset to be optimized reaches the evaluation score threshold.

[0079] In addition, the specific implementation content of the data asset handover processing device in the embodiment of the present invention has been described in detail in the above data asset handover processing method, so the repeated content will not be described here.

[0080] Figure 5 An exemplary system architecture 500 is shown to which the data asset handover processing method or data asset handover processing device according to the embodiment of the present invention can be applied.

[0081] like Figure 5 As shown, system architecture 500 may include terminal devices 501, 502, 503, a network 504 and a server 505. Network 504 is used to provide a medium for communication links between terminal devices 501, 502, 503 and server 505. Network 504 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0082] Users can use terminal devices 501, 502, 503 to interact with server 505 through network 504 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 501, 502, 503, such as data asset handover processing applications, data processing applications, personnel management applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0083] The terminal devices 501 , 502 , and 503 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0084] The server 505 may be a server that provides various services, such as a background management server that provides support for the handover processing websites of data assets browsed by the users using the terminal devices 501, 502, and 503 (for example only). The background management server may respond to the handover processing request of the data assets and other data received, evaluate each data asset in the data asset pool according to the preset data asset evaluation rules, and determine at least one data asset to be processed according to the evaluation results; for each data asset to be processed, obtain the business information of the data asset to be processed, and determine the target handover personnel corresponding to the data asset to be processed according to the business information and the preset allocation rules; assign each data asset to be processed to the corresponding target handover personnel, and generate the corresponding data asset maintenance plan, so that the corresponding target handover personnel can execute the corresponding data asset maintenance plan; complete the handover processing of each data asset to be processed by monitoring the execution result of the corresponding data asset maintenance plan, and feedback the processing result (such as the handover processing result of the data asset - for example only) to the terminal device.

[0085] It should be noted that the data asset handover processing method provided in the embodiment of the present invention is generally executed by the server 505 , and accordingly, the data asset handover processing device is generally set in the server 505 .

[0086] It should be understood that Figure 5 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0087] Reference below Figure 6 , which shows a schematic diagram of the structure of a computer system 600 of a terminal device or a server suitable for implementing an embodiment of the present invention. Figure 6 The terminal device or server shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0088] like Figure 6 As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The CPU 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0089] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage section 608 as needed.

[0090] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the central processing unit (CPU) 601, the above-mentioned functions defined in the system of the present invention are executed.

[0091] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0092] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0093] The modules involved in the embodiments of the present invention may be implemented in software or hardware. The modules described may also be set in a processor. For example, they may be described as: a processor includes a module for determining data assets to be processed, a module for determining target handover personnel, a module for allocating data assets to be processed, and a module for monitoring execution results. The names of these modules do not, in some cases, constitute limitations on the modules themselves. For example, the module for determining data assets to be processed may also be described as "a module for responding to a data asset handover processing request, evaluating each data asset in the data asset pool according to preset data asset evaluation rules, and determining at least one data asset to be processed based on the evaluation results."

[0094] As another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently and not be assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by a device, the device includes: responding to a data asset handover processing request, evaluating each data asset in the data asset pool according to a preset data asset evaluation rule, and determining at least one data asset to be processed according to the evaluation result; for each data asset to be processed, obtaining the business information of the data asset to be processed, and determining the target handover personnel corresponding to the data asset to be processed according to the business information and the preset allocation rules; assigning each data asset to be processed to the corresponding target handover personnel, and generating a corresponding data asset maintenance plan, so that the corresponding target handover personnel can execute the corresponding data asset maintenance plan; completing the handover processing of each data asset to be processed by monitoring the execution result of the corresponding data asset maintenance plan.

[0095] According to the technical solution of the embodiment of the present invention, in response to the handover processing request of the data asset, each data asset in the data asset pool is evaluated according to the preset data asset evaluation rules, and at least one data asset to be processed is determined according to the evaluation results; for each data asset to be processed, the business information of the data asset to be processed is obtained, and according to the business information, the target handover personnel corresponding to the data asset to be processed are determined by the preset allocation rules; each data asset to be processed is allocated to the corresponding target handover personnel, and a corresponding data asset maintenance plan is generated, so that the corresponding target handover personnel can execute the corresponding data asset maintenance plan; by monitoring the execution results of the corresponding data asset maintenance plan, the handover processing of each data asset to be processed is completed. It can realize the unified trusteeship of data asset handover, improve the efficiency of data asset handover processing, evaluate each data asset according to the data asset evaluation rules, dig high-quality data assets from a large number of data assets, give priority to the handover processing of high-quality data assets, and determine the target handover personnel through the allocation rules, improve the adaptability between data assets and target handover personnel, and then improve the processing effect of target handover personnel on data assets, and avoid business loss.

[0096] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data asset handover processing method, characterized in that: include: In response to a data asset handover request, each data asset in the data asset pool is evaluated according to a preset data asset evaluation rule, and at least one data asset to be processed is determined based on the evaluation result; For each of the data assets to be processed, business information of the data assets to be processed is obtained, and according to the business information and a preset allocation rule, a target handover person corresponding to the data asset to be processed is determined; Allocate each of the data assets to be processed to a corresponding target handover personnel, and generate a corresponding data asset maintenance plan, so that the corresponding target handover personnel can execute the corresponding data asset maintenance plan; By monitoring the execution result of the corresponding data asset maintenance plan, the handover processing of each of the data assets to be processed is completed.

2. The method according to claim 1, characterized in that The data assets include pre-sale stage data, sale stage data and post-sale stage data; The step of evaluating each data asset in the data asset pool according to the preset data asset evaluation rules includes: Obtain pre-sale stage data, sale stage data, and post-sale stage data corresponding to the data asset; According to the weight evaluation rules corresponding to the data of each stage, the pre-sale stage data, the sale stage data and the post-sale stage data are evaluated respectively to obtain a first score of the pre-sale stage, a second score of the sale stage and a third score of the post-sale stage; An evaluation score of the data asset is determined by using the first score, the second score, and the third score.

3. The method according to claim 2, characterized in that The determination of at least one data asset to be processed based on the evaluation results includes: According to a preset evaluation score threshold, data assets whose evaluation scores reach the evaluation score threshold are used as the data assets to be processed.

4. The method according to claim 1, characterized in that: Determining the target handover personnel corresponding to the data asset to be processed according to the business information and through a preset allocation rule includes: According to the business information, determining at least one handover person corresponding to the business information; For each of the handover personnel, the handover personnel are evaluated according to the preset handover personnel evaluation rules to generate an evaluation score for the handover personnel; The handover personnel with the highest evaluation score is selected as the target handover personnel for the data assets to be processed.

5. The method according to claim 4, characterized in that The step of evaluating the handover personnel according to the preset handover personnel evaluation rules and generating the evaluation score of the handover personnel includes: Obtaining risk control dimension data, capability dimension data, and load dimension data of the handover personnel within a preset time period; According to the evaluation rules corresponding to each dimension data, the risk control dimension data, the capability dimension data and the load dimension data are evaluated respectively to obtain a risk control dimension score, a capability dimension score and a load dimension score; An evaluation score of the handover personnel is generated through the risk control dimension score, the capability dimension score and the load dimension score.

6. The method according to claim 1, characterized in that The step of completing the handover process of each of the to-be-processed data assets by monitoring the execution result of the corresponding data asset maintenance plan includes: For each of the data assets to be processed, the execution result of the corresponding data asset maintenance plan is monitored. If the execution result is incomplete, the target handover personnel for the data assets to be processed are re-determined, and the data assets to be processed are assigned to the new target handover personnel. A new data asset maintenance plan is generated, and the new target handover personnel executes the new data asset maintenance plan. By monitoring the execution result of the new data asset maintenance plan, the handover processing of the data assets to be processed is completed.

7. The method according to claim 3, characterized in that After determining at least one data asset to be processed according to the evaluation results, the following steps are also included: According to the evaluation score threshold, the data assets whose evaluation scores do not reach the evaluation score threshold are regarded as data assets to be optimized; For each of the data assets to be optimized, the data assets to be optimized are optimized by completing information until the evaluation score of the data assets to be optimized reaches the evaluation score threshold.

8. A data asset handover processing device, characterized in that: include: A module for determining data assets to be processed, for responding to a data asset handover processing request, evaluating each data asset in the data asset pool according to a preset data asset evaluation rule, and determining at least one data asset to be processed according to the evaluation result; A target handover personnel determination module is used to obtain the business information of each data asset to be processed, and determine the target handover personnel corresponding to the data asset to be processed according to the business information and a preset allocation rule; A data asset allocation module to be processed, used to allocate each of the data assets to be processed to a corresponding target handover personnel, and generate a corresponding data asset maintenance plan, so that the corresponding target handover personnel can execute the corresponding data asset maintenance plan; The execution result monitoring module is used to complete the handover processing of each of the to-be-processed data assets by monitoring the execution result of the corresponding data asset maintenance plan.

9. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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