Enterprise application digital operation evaluation system

Abstract

The invention relates to an enterprise application digital operation evaluation system, and belongs to the technical field of operation evaluation, and the enterprise application digital operation evaluation system comprises an evaluation model, a data collection module, a quantitative index calculation module and an evaluation report generation module. The evaluation model is more comprehensive, evaluation is carried out from four dimensions of business value, technical specification, demand activeness and operation state, and the cost performance of application operation is evaluated more comprehensively; the evaluation data is more objective, and the data required by the evaluation are automatically acquired and stored by the system, do not need to be provided manually, and are objective and real; the automation degree is high, and the processes of data acquisition, warehousing, storage, evaluation, generation and the like are fully automatically realized; the method is high in digitization degree, the evaluation model, rules, indexes, data and report total elements are visualized, management is generated based on the system, and manual offline maintenance is not needed.

Description

Technical Field

[0001] The present invention belongs to the technical field of operation evaluation, and in particular, relates to an enterprise application digital operation evaluation system. Background Art

[0002] In the context of the overall acceleration of digital economic construction, the digital transformation of enterprises has become a key way for them to transform and upgrade and enhance their competitiveness. Faced with the rapid changes in the market environment, the increasing diversification of consumer needs, and the continuous emergence of technological innovations, enterprises have begun to realize that achieving digital transformation through the construction of applications is an important measure to improve operational efficiency, optimize decision-making processes, accelerate product innovation, promote employee collaboration and communication, and adapt to changes in the external environment. This transformation will help enterprises build digital competitive advantages and achieve sustainable development.

[0003] In order to ensure that application construction meets business needs, improve user experience and satisfaction, optimize performance and efficiency, ensure data security and compliance, guide future development and planning, and promote continuous improvement and optimization, enterprises need a feasible application evaluation system to have a more comprehensive understanding of the actual situation of the application and provide strong support for the development of the enterprise.

[0004] Traditional application evaluation generally focuses on application operation or performance. It determines what types of data need to be collected and designs a data collection plan. Evaluators manually collect and organize data according to the designed plan, and use statistical methods, charts or performance analysis tools to analyze the application. Based on the analysis results and problems found, evaluators will put forward targeted improvement suggestions and optimization plans and write a detailed evaluation report. However, the following problems also arise in the process of using this evaluation method:

[0005] 1. It is highly subjective and relies on the subjective judgment and experience of the evaluator, which may lead to inconsistency and bias in the evaluation results. Different evaluators may evaluate the same application based on different standards, experience, and preferences, and thus come to different conclusions.

[0006] 2. One-sidedness: focusing only on certain aspects of the application, such as operation and performance, while ignoring other equally important aspects, such as business value, technical specifications, and the activity of application requirements. This one-sidedness may result in the evaluation results not fully reflecting the true situation of the application.

[0007] 3. Low efficiency. A large amount of data needs to be manually input or extracted. The manually collected data needs to go through processing steps such as sorting, cleaning, and confirmation. These steps also require manual operation, which increases the processing time and extends the entire evaluation cycle. Delays in data collection and processing will cause the evaluation results to lag behind the actual situation.

[0008] Therefore, it is necessary to provide a new enterprise application digital operation evaluation system to solve the above technical problems. Summary of the invention

[0009] The purpose of the present disclosure is to provide an enterprise application digital operation evaluation system in order to solve the above problems.

[0010] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0011] An enterprise application digital operation evaluation system, comprising an evaluation model, a data collection module, a quantitative index calculation module and an evaluation report generation module;

[0012] The evaluation model is used to define the dimensions and indicators that need to be evaluated and the evaluation rules of each dimension and quantitative indicator;

[0013] The data collection module is used to regularly collect operational data from the data source identified according to the quantitative indicators and store it in a database;

[0014] The quantitative index calculation module is used to calculate the operation data regularly according to the quantitative index defined by the evaluation model by grouping or aggregating in different dimensions using SQL statements to obtain the index value;

[0015] The evaluation report generation module is used to obtain evaluation results of each dimension according to the evaluation model, the evaluation rules, and the indicator values, and to match the recommendation strategy library to generate optimization suggestions, and finally generate an evaluation report.

[0016] As a further optimization solution of the present disclosure, the dimensions that need to be evaluated include four main dimensions, namely business value, technical specifications, demand activity and operating status.

[0017] As a further optimization scheme of the present disclosure, the four main dimensions include seven sub-dimensions; the business value includes business operations; the technical specifications include regular audits; the demand activity includes three sub-dimensions: online release, code changes, and team stability; the operating status includes two sub-dimensions: application availability and service availability.

[0018] As a further optimization scheme of the present disclosure, the seven sub-dimensions are reflected by ten quantitative indicators; the ten quantitative indicators are application visits, application message subscriptions, application API calls, shared data queries, application audit compliance rate, application online release times, application code changes, application team changes, application availability, and application API availability;

[0019] The business operation is reflected by four quantitative indicators: the application visits, the application message subscriptions, the application API calls and the shared data queries; the routine audit is reflected by the application audit compliance rate; the online release is reflected by the number of online releases of the application, the code change is reflected by the number of application code changes, and the team stability is reflected by the number of application team changes; the application availability is reflected by the application availability rate, and the service availability is reflected by the application API availability rate.

[0020] As a further optimization scheme of the present disclosure, the evaluation rules include:

[0021] The results of the quantitative indicators generate evaluation results of the sub-dimensions according to the sub-dimensions to which they belong and the defined rules, and the evaluation results of the sub-dimensions are merged into the evaluation results of the main dimension according to the main dimension to which they belong.

[0022] As a further optimization scheme of the present disclosure, the data collection module identifies the data source that needs to be collected according to the quantitative indicators defined by the evaluation model. The data source provides a data view, collects operational data in the data source and synchronizes the operational data to the database through a timer.

[0023] As a further optimization scheme of the present disclosure, the quantitative indicator calculation module adds quantitative indicators in the indicator center according to the quantitative indicators defined by the evaluation model, writes SQL for the indicator quantitative calculation, sets the fields of the calculation result table, which are divided into dimension fields and indicator fields, associates the indicator fields of the calculation result table with the indicator business created when the evaluation model is established, configures the quantitative indicator execution timer and saves it.

[0024] As a further optimization plan of the present disclosure, the optimization suggestions include technical transformation, offline, business transformation, regular audit, technical transformation, confirmation of whether the changes are effective, strengthening the team's technical reserves and strengthening monitoring.

[0025] The beneficial effects of the present disclosure are:

[0026] The present disclosure can automatically collect application operation data and automatically evaluate the application operation status according to the defined evaluation model and rules. The evaluation model of the present disclosure is more comprehensive, and it evaluates from four dimensions, including business value, technical specifications, demand activity, and operation status, to more comprehensively evaluate the cost-effectiveness of application operation; the evaluation data is more objective, and the data required for the evaluation are all collected and stored by the system automatically, without manual provision, and are objective and true; the present disclosure has a high degree of automation, and the processes of data collection, warehousing, storage, evaluation, and generation are fully automated; the present disclosure has a high degree of digitization, and all elements of the evaluation model, rules, indicators, data, and reports are visualized, relying on system generation and management, without the need for manual offline maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a schematic diagram of the system structure in an embodiment of the present disclosure;

[0028] Figure 2 It is a schematic diagram of the evaluation model structure in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0029] The present application is further described in detail below in conjunction with the accompanying drawings. It is necessary to point out here that the following specific implementation methods are only used to further illustrate the present application and cannot be understood as limiting the scope of protection of the present application. Technical personnel in this field can make some non-essential improvements and adjustments to the present application based on the above application content.

[0030] like Figure 1 As shown, an enterprise application digital operation evaluation system includes an evaluation model, a data collection module, a quantitative indicator calculation module and an evaluation report generation module.

[0031] like Figure 2 As shown in the figure, the evaluation model defines the dimensions and indicators that need to be evaluated, including 4 main dimensions, 7 sub-dimensions, 10 quantitative indicators (quantitative indicators are an important analysis tool and methodology. They describe and measure a phenomenon, process or result in a digital way. These indicators can be based on any subject or object, which is equivalent to a certain attribute of the subject or object. It can provide objective and comparable data support, which is helpful for analysis and decision-making), as well as the evaluation rules of each indicator and dimension.

[0032] Definition of main dimensions: The evaluation model is divided into four main dimensions: business value, technical specifications, demand activity, and operating status according to the value of the application to the enterprise, the technology used by the application, application changes, and application runtime.

[0033] Definition of sub-dimensions: Business value mainly reflects the use of application functions and the use of application shared services and data, that is, the business operation sub-dimension; technical specifications mainly reflect the technical specification audit of the entire life cycle of the application, that is, the regular audit sub-dimension; demand activity is divided into three sub-dimensions: online release, code change, and team stability, which respectively reflect the three aspects of application release frequency, change frequency and team change, and comprehensively reflect whether the stability of the application development team can meet demand changes; the operating status is divided into two sub-dimensions: application availability and service availability, which respectively reflect the two aspects of application functions and open services, and reflect the stability of the application during runtime.

[0034] Definition of quantitative indicators: Business value in terms of functional value is mainly reflected through the application access volume indicator; in terms of shared services and data, it is mainly reflected by three quantitative indicators: application message subscription volume, application api (Application Programming Interface) call volume, and shared data query volume; technical specifications are reflected by one quantitative indicator, the application audit compliance rate; the online release sub-dimension can be reflected by one quantitative indicator, the number of online releases of applications, the code change sub-dimension can be reflected by one quantitative indicator, the number of application code changes, the team stability sub-dimension can be reflected by one quantitative indicator, the number of application team changes, the application availability sub-dimension can be reflected by one quantitative indicator, the application availability rate, and the service availability sub-dimension can be reflected by one quantitative indicator, the application api availability rate.

[0035] Define evaluation rules: The evaluation results are based on the evaluation model and are given according to each quantitative indicator. Since the quantitative indicators of each dimension have different meanings, the evaluation rules and conclusions of each sub-dimension are set separately. The results of the indicators generate sub-dimension evaluation results according to the sub-dimensions to which they belong and the defined rules, and the sub-dimension evaluation results are merged into the main dimension evaluation results according to the main dimension to which they belong.

[0036] Data collection module: Based on the data source identified by the indicators, the operation data is collected regularly and stored in the database. Specifically, according to the 10 quantitative indicators defined by the evaluation model, the data source to be collected is identified, the data source provides a data view, and the operation data is synchronized with the database through a timer.

[0037] Quantitative indicator calculation module: According to the quantitative indicators defined in the evaluation model, the operation data is grouped or aggregated according to different dimensions using SQL (Structured Query Language) statements to periodically calculate and obtain the indicator value. Specifically, according to the quantitative indicators in the evaluation model, new indicators are added to the indicator center, SQL for quantitative calculation of indicators is written, and the fields of the calculation result table are set, which are divided into dimension fields and indicator fields. The indicator fields of the result table are associated with the indicator business created when the evaluation model is established, and the quantitative indicator execution timer is configured and saved.

[0038] Evaluation report generation module: Obtain evaluation results of each dimension based on evaluation models, rules, and indicator values, and match the recommended strategy library (an important management tool that stores and manages a series of strategies or solutions that can be selected and used. Users can quickly find effective suggestions based on the evaluation results. By continuously updating and improving the strategy library, the correctness of the evaluation suggestions can be improved.) to generate optimization suggestions and finally generate an evaluation report. Optimization suggestions include technical transformation, offline, business transformation, regular audits, technical transformation, confirming whether the changes are effective, strengthening the team's technical reserves, and strengthening monitoring.

[0039] Users can display detailed data of quantitative indicators under each dimension on the system according to the evaluation model and the selected time range, automatically generate evaluation results of each dimension through SQL according to the evaluation rules and quantitative indicator values ​​of the evaluation model, manually generate evaluation suggestions for each dimension according to the recommended strategy library and quantitative indicator values, and finally generate an enterprise application digital operation report on the system and export it as a PDF file.

[0040] The above-mentioned embodiments only express several implementation methods of the present disclosure, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present disclosure. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present disclosure, and these all belong to the protection scope of the present disclosure.

Claims

1. An enterprise application digital operation evaluation system, characterized in that: It includes evaluation model, data collection module, quantitative index calculation module and evaluation report generation module; The evaluation model is used to define the dimensions and quantitative indicators that need to be evaluated and the evaluation rules of each dimension and quantitative indicator; The data collection module is used to regularly collect operational data from the data source identified according to the quantitative indicators and store it in a database; The quantitative index calculation module is used to calculate the operation data regularly according to the quantitative index defined by the evaluation model by grouping or aggregating in different dimensions using SQL statements to obtain the index value; The evaluation report generation module is used to obtain evaluation results of each dimension according to the evaluation model, the evaluation rules, and the indicator values, and to match the recommendation strategy library to generate optimization suggestions, and finally generate an evaluation report.

2. According to claim 1, the enterprise application digital operation evaluation system is characterized in that: The dimensions that need to be evaluated include four main dimensions, namely business value, technical specifications, demand activity and operating status.

3. According to claim 2, the enterprise application digital operation evaluation system is characterized in that: The four main dimensions include seven sub-dimensions; the business value includes business operations; the technical specifications include routine audits; The demand activity includes three sub-dimensions: online release, code change and team stability; the operating status includes two sub-dimensions: application availability and service availability.

4. The enterprise application digital operation evaluation system according to claim 3 is characterized in that: The seven sub-dimensions are reflected by ten quantitative indicators; the ten quantitative indicators are application visits, application message subscriptions, application API calls, shared data queries, application audit compliance rate, application online release times, application code changes, application team changes, application availability, and application API availability. The business operation is reflected by four quantitative indicators: the application visits, the application message subscriptions, the application API calls and the shared data queries; the routine audit is reflected by the application audit compliance rate; the online release is reflected by the number of online releases of the application, the code change is reflected by the number of application code changes, and the team stability is reflected by the number of application team changes; the application availability is reflected by the application availability rate, and the service availability is reflected by the application API availability rate.

5. The enterprise application digital operation evaluation system according to claim 1, characterized in that: The evaluation rules include: The results of the quantitative indicators generate evaluation results of the sub-dimensions according to the sub-dimensions to which they belong and the defined rules, and the evaluation results of the sub-dimensions are merged into the evaluation results of the main dimension according to the main dimension to which they belong.

6. The enterprise application digital operation evaluation system according to claim 1, characterized in that: The data collection module identifies the data source that needs to be collected according to the quantitative indicators defined by the evaluation model. The data source provides a data view, collects operation data from the data source, and synchronizes the operation data to the database through a timer.

7. The enterprise application digital operation evaluation system according to claim 1, characterized in that: The quantitative indicator calculation module adds quantitative indicators to the indicator center according to the quantitative indicators defined by the evaluation model, writes SQL for indicator quantitative calculation, sets the fields of the calculation result table, which are divided into dimension fields and indicator fields, associates the indicator fields of the calculation result table with the indicator business created when the evaluation model is established, configures the quantitative indicator execution timer and saves it.

8. The enterprise application digital operation evaluation system according to claim 1, characterized in that: The optimization suggestions include technical transformation, offline, business transformation, regular audit, technical transformation, confirming whether the changes are effective, strengthening the team's technical reserves and strengthening monitoring.

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