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CN-122022541-A - Performance variation diagnosis method, electronic device and computer program product

CN122022541ACN 122022541 ACN122022541 ACN 122022541ACN-122022541-A

Abstract

The application discloses a performance fluctuation diagnosis method, electronic equipment and a computer program product. The method comprises the steps of obtaining performance statistics information and a plurality of performance statistics dimensions in a target time period, wherein each performance statistics dimension comprises a plurality of categories, the performance statistics information comprises total performance variation and category performance under each performance statistics dimension, the sum of the category performance variation under each performance statistics dimension is identical to the total performance variation in the target time period, determining an imbalance value corresponding to each performance statistics dimension according to the ratio information of each category performance variation to the total performance variation, and determining a first influence factor of performance variation according to the imbalance value of each performance statistics dimension. The embodiment of the application can rapidly and accurately identify the core factors influencing performance variation, and improve the efficiency and accuracy of performance diagnosis.

Inventors

  • FAN TAO
  • JIANG MIANYUE

Assignees

  • 前锦网络信息技术(上海)有限公司

Dates

Publication Date
20260512
Application Date
20251219

Claims (10)

  1. 1. A method of diagnosing performance variations, comprising: Acquiring performance statistical information and a plurality of performance statistical dimensions in a target time period, wherein each performance statistical dimension comprises a plurality of categories, the performance statistical information comprises total performance variation and category performance under each performance statistical dimension, and the sum of the category performance variation under each performance statistical dimension is the same as the total performance variation in the target time period; Corresponding to each performance statistics dimension, determining an imbalance value corresponding to each performance statistics dimension according to the duty ratio information of each performance variation and the total performance variation; and determining a first influencing factor of performance variation according to the magnitude of the imbalance value of each performance statistics dimension.
  2. 2. The method of claim 1, wherein said determining, for each of said performance statistics dimensions, an imbalance value for each of said performance statistics dimensions based on the duty cycle information of each of said categories of performance variation and said total performance variation comprises: And calculating the ratio of the performance of each category to the total performance according to each performance statistics dimension to obtain the performance duty ratio of each category, and calculating the imbalance values of the performance duty ratios of a plurality of categories included in the performance statistics dimension to obtain the imbalance value corresponding to each performance statistics dimension.
  3. 3. The method of claim 2, wherein the determining as the first contributor to performance variation based on the magnitude of the imbalance value for each performance statistics dimension comprises: n performance statistics dimensions with the highest unbalance value are determined, wherein N is a preset positive integer; and extracting the category with the maximum performance ratio under each performance statistics dimension in the N performance statistics dimensions to obtain N categories, and determining the N categories as the first influence factors.
  4. 4. The method according to claim 1 or 2, characterized in that the imbalance value corresponding to the performance statistics dimension represents the degree of dispersion of the respective performance variation in the performance statistics dimension.
  5. 5. The method according to claim 1, wherein the method further comprises: Acquiring a performance participation object of a target performance range, wherein the target performance range comprises at least one category; Extracting statistical performance, the participation number of performance participation objects and the performance average value of the performance participation objects, which correspond to the target performance range at a first time point, and statistical performance, the participation number of the performance participation objects and the performance average value of the performance participation objects, which correspond to a second time point, from the performance statistical information, wherein the first time point is earlier than the second time point; calculating the change times of the performance, the change times of the participation numbers of the performance participation objects and the change times of the performance average values of the performance participation objects from the first time point to the second time point respectively; Determining the influence weight of the participation number of the performance participation object on the performance change amount in the target time period according to the change times of the participation number of the performance participation object and the change times of the statistical performance, and According to the change times of the performance mean values of the performance participation objects and the change times of the statistical performance, determining the influence weight of the performance mean values of the performance participation objects on the performance change amount in the target time period; and determining a second influence factor according to the magnitude of the influence weight corresponding to the participation number of the performance participation object and the influence weight corresponding to the performance average value of the performance participation object.
  6. 6. The method of claim 5, wherein said determining an impact weight of the participation count of the performance participant on the performance change amount in the target time period based on the multiple of the participation count of the performance participant and the multiple of the statistical performance change, comprises: And calculating the ratio of the logarithmic value of the change multiple of the participation number of the performance participation object to the logarithmic value of the change multiple of the statistical performance to obtain the influence weight of the participation number of the performance participation object on the performance change quantity in the target time period.
  7. 7. The method of claim 5, wherein the determining the impact weight of the performance mean of the performance participant on the performance variation in the target time period according to the multiple of the performance mean of the performance participant and the multiple of the statistical performance comprises: And calculating the ratio of the logarithmic value of the change times of the performance mean value of the performance participators to the logarithmic value of the change times of the statistical performance to obtain the influence weight of the performance mean value of the performance participators on the performance change amount in the target time period.
  8. 8. An electronic device comprising a processor and a memory storing computer program instructions, the electronic device implementing the method of any one of claims 1-7 when executing the computer program instructions.
  9. 9. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon computer program instructions which, when executed by a processor, implement the method according to any of claims 1-7.
  10. 10. A computer program product comprising computer program instructions which, when executed by a processor, implement the method of any of claims 1-7.

Description

Performance variation diagnosis method, electronic device and computer program product Technical Field The present application relates to the field of data processing technologies, and in particular, to a performance change diagnosis method, an electronic device, and a computer program product. Background With the refinement and data development of enterprise business activities, attention and analysis of key performance indicators (Key Performance Indicator, KPIs) have become a part of enterprise daily management. For example, sales and other data capable of reflecting performance indexes can directly reflect the business state of an enterprise, and the change situation of the sales and other data has important reference value for enterprise decision making. Therefore, when the performance index fluctuates, the fluctuation cause is timely and accurately judged, and the method has important significance for enterprises to adjust the operation strategy and reduce the operation risk. In the existing scheme for analyzing performance indexes, an enterprise is required to be provided with a special analysis team, and the analysis staff splits and compares data to find out reasons of performance fluctuation. However, this approach requires the expertise and experience of the analyst. For small and medium enterprises, due to the limitation of cost and manpower resource conditions, professional and stable analysis teams are often difficult to construct, and the reasons for performance fluctuation are difficult to find out timely and accurately after the performance fluctuation occurs. In addition, even if the staff with the profession is used for processing, the staff can be limited by the manpower processing speed and energy, and at least the core cause can be found after a few hours or even more, so that the operation adjustment time is missed, and the response efficiency of enterprises to performance risks is reduced. Therefore, how to quickly and accurately identify the core factors influencing performance fluctuation when performance fluctuation occurs and improve efficiency and accuracy of performance diagnosis has become a technical problem to be solved in the field of enterprise operation management. Disclosure of Invention In view of this, embodiments of the present application provide a performance fluctuation diagnosis method, an electronic device, and a computer program product, which can quickly and accurately identify core factors affecting performance fluctuation, and improve efficiency and accuracy of performance diagnosis. The embodiment of the application provides a performance change diagnosis method, which comprises the steps of obtaining performance statistical information and a plurality of performance statistical dimensions in a target time period, wherein each performance statistical dimension comprises a plurality of categories, the performance statistical information comprises total performance variation and category performance under each performance statistical dimension, the sum of the category performance variation under each performance statistical dimension is identical to the total performance variation in the target time period, corresponding to each performance statistical dimension, determining an imbalance value corresponding to each performance statistical dimension according to the ratio information of each category performance variation to the total performance variation, and determining a first influence factor of performance change according to the imbalance value of each performance statistical dimension. According to some embodiments of the present application, optionally, corresponding to each performance statistics dimension, determining an imbalance value corresponding to each performance statistics dimension according to the duty ratio information of the performance variation of each category and the total performance variation includes: and calculating the ratio of each category of performance to the total performance according to each performance statistics dimension to obtain the performance duty ratio of each category, and calculating the imbalance values of the performance duty ratios of a plurality of categories included in the performance statistics dimension to obtain the imbalance value corresponding to each performance statistics dimension. According to some embodiments of the application, optionally, according to the magnitude of the imbalance value of each performance statistics dimension, determining the first influence factor of performance variation comprises determining N performance statistics dimensions with the highest imbalance value, wherein N is a preset positive integer, extracting the category with the largest performance ratio under each performance statistics dimension in the N performance statistics dimensions to obtain N categories, and determining the N categories as the first influence factor. According to some embodiments of the applicat