Quantitative evaluation method for data asset management value

Abstract

The invention relates to a quantitative evaluation method for a data asset management value. The method comprises the following steps: S1, calculating a business case data asset management income; s2, calculating normalized data asset management income based on the data item single call RTB income and call times; s3, calculating business case data asset management cost and normalized data asset management cost; and S4, calculating a data asset management value, a business case data asset management value and a normalized data asset management value. Compared with the prior art, the method has the advantages of quantizing the data value and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to a quantitative evaluation method for data asset management value. Background Art

[0002] Data assets refer to data resources that are formed by past transactions or events of an enterprise, owned or controlled by the enterprise, and expected to bring economic benefits to the enterprise. Data assets are different from data resources, and "value" is the core attribute of data assets. The current research on data asset value assessment mainly faces the following difficulties.

[0003] Advancedness: As a frontier field at the intersection of contemporary economic management and data science, data asset valuation has attracted extensive participation and in-depth research from universities, research institutes, data exchanges and enterprises, but an authoritative data asset valuation model has not yet been formed.

[0004] Professionalism: Data asset value assessment is highly professional and requires a variety of professional capabilities such as data ownership definition, data cost accounting, data application scenario mining, and data model construction.

[0005] Feasibility: Some leading companies have tried to carry out data asset valuation practices, integrating the cost method, income method, and market method of intangible asset valuation to conduct value assessment on the company's existing data assets. Although these efforts have made significant progress in theoretical construction and model design, they are still insufficient in effectively transforming the evaluation results into practical applications for internal management decisions, resource allocation, and value creation. Most of them are still limited to the scope of academic research and theoretical discussion, and it is urgent to further promote the practical transformation and in-depth application of the evaluation results.

[0006] When enterprises carry out data asset management, they need to invest resources. However, before investing resources, they need to first identify the data with high-value attributes that need to be governed first, and determine the input-output of the data asset management project. The current research on data asset value assessment lacks quantitative analysis of the above data, and does not measure the value of normalized data asset management work. The above problems are urgent problems that need to be solved when data asset value assessment is applied in internal enterprise management. Summary of the invention

[0007] The purpose of the present invention is to provide a quantitative evaluation method for the value of data asset management in order to promote the application of enterprise data asset management and lay the foundation for enterprise data assets to be included in the table or participate in the circulation of data element market. The purpose of the present invention can be achieved through the following technical solutions:

[0008] A quantitative evaluation method for data asset management value, the method comprising the following steps:

[0009] S1. Obtain the data to be evaluated, construct corresponding different business effectiveness evaluation indicators according to the use case type of the business use case, calculate the business effectiveness, obtain the first CTB benefit calculation factor, and calculate the business use case data asset management benefit according to the first CTB benefit calculation factor, the second CTB benefit calculation factor and the third CTB benefit calculation factor;

[0010] S2. Calculate the normalized data asset management benefits based on the RTB benefits of a single call to a data item and the number of calls;

[0011] S3. Calculate the business use case data asset management costs and the normalized data asset management costs;

[0012] S4. Calculate the data asset management value, business use case data asset management value, and normalized data asset management value based on the business use case data asset management benefits, normalized data asset management benefits, business use case data asset management costs, and normalized data asset management costs, and adjust the data priority based on the management value, where the data asset management value is:

[0013]

[0014] Furthermore, the first CTB income calculation factor is specifically:

[0015] When the use case type is marketing enablement, the first CTB benefit calculation factor, that is, the business effect, is the incremental NBV;

[0016] When the use case type is business efficiency, the first CTB benefit calculation factor is the incremental labor cost reduction;

[0017] When the use case type is risk mitigation, the first CTB benefit calculation factor is incremental loss reduction;

[0018] When the use case type is regulatory compliance, the first CTB benefit calculation factor is not calculated.

[0019] Furthermore, the second CTB benefit calculation factor is the overall data contribution, which is obtained by calculating the impact of data application on business results using AB testing, indicator attribution, and business process impact ratio methods, or by referring to the overall data contribution accumulated by the same type of business use cases.

[0020] Furthermore, the third CTB benefit calculation factor is the data asset management contribution. When the data application type is the algorithm model type, the data asset management contribution refers to the data asset management contribution ratio value accumulated by the same type of business use cases, or uses AB testing to analyze the impact of data asset management on the accuracy of the data model as the data asset management contribution;

[0021] When the data application type is data analysis, the data asset management contribution is the ratio of the amount of governance data to the total amount of business use case data;

[0022] When the data application type is data governance type, 100% of the overall data effectiveness will be included in the data asset management contribution.

[0023] Furthermore, the benefits of business use case data asset management are:

[0024]

[0025] Furthermore, the benefits of normalized data asset management are:

[0026]

[0027] Among them, when the data items of normalized data asset management have been covered in the past business use cases, the CTB revenue of a single call of the data item is used as the RTB revenue of a single call of the data item;

[0028] When the data items of normalized data asset management are not covered in previous business use cases, the average single-call CTB revenue of the business use case data items or the single-call price of external similar data will be used as the single-call RTB revenue of the data items.

[0029] Furthermore, the CTB benefit of a single call of the data item is specifically:

[0030] For data items that have been covered by previous business use cases and are single business use cases, the revenue from a single CTB call for the data item is:

[0031]

[0032] For data items that have been covered by previous business use cases and support multiple business use cases, the revenue from a single CTB call for the data item is:

[0033]

[0034] Furthermore, for data items not covered in previous business use cases, the average single-call CTB benefit of the business use case data item is:

[0035]

[0036] Furthermore, the business use case data asset management cost is the data asset management investment of each participant in the business use case.

[0037] Furthermore, the normalized data asset management cost is:

[0038] Normalized data asset management cost (RTB cost) = fixed cost of a single data item 1×Number of data items covered 2 +Variable costs 3

[0039] The fixed cost of a single data item is calculated by evenly allocating the fixed cost of data asset management to a single data item. The number of data items covered is equal to the number of data items covered by normalized data asset management minus the number of data items covered by business use cases. The variable cost includes the normalized data asset management investment of each participant except for special data asset management work in the enterprise, starting from the data items covered by normalized data asset management, including manpower, software, hardware and other cost investments.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] (1) The present invention solves the problem of the difficulty in quantifying the value of data asset management projects within enterprises through the "Business Use Case Data Asset Management ROI". Under the condition of limited resources, it identifies the key points of data asset management and guides the external data procurement of enterprises. It encourages all departments of the enterprise to actively participate in data asset management, and accumulates and promotes excellent data asset management applications.

[0042] (2) The traditional data asset management value assessment is limited to a single data asset management project. The "normalized data asset management ROI" of the present invention innovatively adds the value assessment of normalized data asset management, realizing the explicit display of this part of invisible value. It enables enterprises to fully and clearly understand the overall scale of their own data asset management, providing data support for the subsequent formulation of data asset management strategies.

[0043] (3) The "CTB revenue of a single data item per call" accumulated through business use cases and the "cost of a single data item" accumulated through business use cases and normalized data asset management lay the foundation for the pricing and cost measurement of data assets that are included in the balance sheet of the enterprise data assets and participate in the circulation of data element markets. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The figure is a schematic diagram of the system structure corresponding to the method of the present invention. DETAILED DESCRIPTION

[0045] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0046] The present invention proposes a quantitative evaluation method for data asset management value. The system structure diagram corresponding to the method of the present invention is as follows: Figure 1 The method comprises the following steps:

[0047] S1. Obtain the data to be evaluated, construct corresponding different business effectiveness evaluation indicators according to the use case type of the business use case, calculate the business effectiveness, obtain the first CTB benefit calculation factor, and calculate the business use case data asset management benefit according to the first CTB benefit calculation factor, the second CTB benefit calculation factor and the third CTB benefit calculation factor;

[0048] S2. Calculate the normalized data asset management benefits based on the RTB benefits of a single call to a data item and the number of calls;

[0049] S3. Calculate the business use case data asset management costs and the normalized data asset management costs;

[0050] S4. Calculate the data asset management value, business use case data asset management value, and normalized data asset management value based on the business use case data asset management benefits, normalized data asset management benefits, business use case data asset management costs, and normalized data asset management costs, and adjust the data priority based on the management value, where the data asset management value is:

[0051]

[0052] The specific steps of the overall calculation formula of data asset management value proposed in the present invention are:

[0053] Data asset management supports company operations and business revenue creation in two ways:

[0054] Business use case driven data asset management (Change the business, CTB): Serving enterprise transformation projects and incremental value creation by supporting the data asset management needs of business use cases.

[0055] Regular data asset management (Run the business, RTB): Under the current business process and management model of the enterprise, regular data asset management is used to support the enterprise's regular business development and meet regulatory compliance requirements.

[0056] The overall calculation formula for data asset management value is as follows:

[0057]

[0058] Can be further broken down into:

[0059]

[0060] 1. Business use case data asset management benefits (CTB benefits):

[0061]

[0062] Among them, CTB revenue calculation factor 1 "business effectiveness" corresponds to different business effectiveness evaluation indicators according to the use case type of business use case

[0063] Marketing empowerment: Enable business opportunity discovery and product innovation, improve customer experience, and create incremental revenue. The business effectiveness evaluation indicator is incremental NBV.

[0064] Operational efficiency type: assisting business operation decision-making and improving operational efficiency, improving operation and management efficiency and reducing management costs. For report dashboard type, the business effectiveness evaluation indicator is incremental labor cost reduction; for special data analysis type, it is only used for decision support and does not require profit calculation.

[0065] Risk reduction: Identify and control risks in advance and reduce losses through data analysis and mining and function settings. The business effectiveness evaluation indicator is the reduction of incremental losses.

[0066] Regulatory compliance: Reduce regulatory violations and penalties by managing regulatory data quality, optimizing reporting data caliber and platform functions. Strong regulatory requirements, no need for ROI calculation.

[0067] CTB revenue calculation factor 2 "overall data contribution %" evaluates the proportion of overall data contribution of data applications to business results. Use AB testing, indicator attribution, business process impact ratio and other methods to calculate the impact of data applications on business results, or refer to the overall data contribution % of the same type of business use cases.

[0068] CTB revenue calculation factor 3 "Data asset management contribution %" evaluates the proportion of data asset management contribution to the overall data effectiveness based on the data application type, or refers to the data asset management contribution % accumulated by the same type of data application. The data application type and the corresponding data asset management contribution calculation method are as follows

[0069] Algorithm model type: Algorithms or rule models are used as the main data application investment. The data asset management contribution can refer to the data asset management contribution ratio value accumulated by the same type of business use cases, or use AB testing to analyze the impact of data asset management on the accuracy of the data model as the data asset management contribution.

[0070] Data analysis type: The main data application investment is report dashboard or special data analysis. The contribution of data asset management is the ratio of the amount of governance data to the total amount of business use case data.

[0071] Data governance only: 100% of overall data effectiveness is counted as data asset management contribution.

[0072] Sedimentation of CTB benefit factor for a single call of a single data item: Calculate the CTB benefit of a single call of a single data item used in a business use case as the input factor reference value of the normalized data asset management benefit (RTB benefit).

[0073] Data items for a single business use case: CTB revenue is distributed to each data item by simple average or weighted average to calculate the revenue of a single call. The "weight of revenue of a single data item" is derived from the data item importance factor in the algorithm model or from the expert scoring method.

[0074]

[0075] Data items that support multiple business use cases: Calculate the average revenue of a data item based on the percentage of times the data item is called in each business use case.

[0076]

[0077] i = number of business use cases.

[0078] 2. Regularized data asset management benefits (RTB benefits):

[0079]

[0080] j = the number of data items covered by normalized data asset management.

[0081] Among them: RTB revenue calculation factor 1 "RTB revenue of a single call to a data item". If the data items of normalized data asset management have been covered in past business use cases, the "CTB revenue of a single data item single call" accumulated from past business use cases will be used as a reference value for the "RTB revenue of a single data item single call".

[0082] If the data items of normalized data asset management are not covered by past business use cases, you can refer to the single call price of similar external data (such as the single call price of similar data items from external data suppliers and data exchanges), or use the past "average single call CTB revenue of business use case data items" as a reference value for "single call RTB revenue of data items".

[0083]

[0084] As the scope of business use cases continues to expand, the "CTB revenue per call of a single data item" based on business use cases will gradually increase, and the single call price of similar external data that needs to be referenced or the "average CTB revenue per call of business use case data items" data items that need to be used will gradually decrease.

[0085] RTB benefit calculation factor 2 "Number of calls" counts the number of calls made by the source system and the data middle platform to the data items of normalized data asset management, which is equal to the total number of calls made to the data items by the source system and the data middle platform minus the total number of calls made to the data items of the business use case.

[0086] 3. Business use case data asset management costs (CTB costs):

[0087] Data asset management investment of all parties involved in the statistical business use case, including human resources, software and hardware and other cost investment. Data asset management investment refers to the investment generated by data quality rule formulation, data quality verification, data quality problem analysis, data governance plan formulation, data quality problem governance, data quality problem tracking and other data asset management-related work.

[0088] The means of managing data quality issues include but are not limited to: system collection control, system batch cleaning, system transmission control, adding internal tracking points, external data access, offline management actions, data standard implementation, etc.

[0089] 4. Normalized data asset management costs (RTB costs):

[0090] Calculate the normalized data asset management costs, including manpower, software, hardware, and other cost investments:

[0091] Normalized data asset management cost (RTB cost) = fixed cost of a single data item 1 ×Number of data items covered 2 +Variable costs 3 in:

[0092] The "fixed cost of a single data item" is calculated by evenly allocating the "fixed cost of data asset management" to a single data item. The "fixed cost of data asset management" mainly refers to the costs related to special data asset management work in an enterprise.

[0093]

[0094] The “number of data items covered” is equal to the number of data items covered by normalized data asset management minus the number of data items covered by business use cases.

[0095] "Variable costs" start from the data items covered by routine data asset management, and include the routine data asset management investment of each participant except for the special data asset management work in the enterprise, including manpower, software, hardware and other cost investments.

[0096] The improvements of the present invention are:

[0097] Through "Business Use Case Data Asset Management ROI", we can solve the problem of the difficulty in quantifying the value of internal data asset management investment. Under the condition of limited resources, we can identify the key points of data asset management and guide the external data procurement of enterprises. We can encourage all departments of the enterprise to actively participate in data asset management and accumulate and promote excellent data asset management applications.

[0098] The traditional data asset management value assessment is limited to a single data asset management project. The "Normalized Data Asset Management ROI" innovatively adds the value assessment of normalized data asset management, and realizes the explicit display of this part of invisible value. It allows enterprises to fully and clearly understand the overall scale of their own data asset management, and provides data support for the subsequent formulation of data asset management strategies.

[0099] New requirements have been put forward for the management of enterprise technology costs. In addition to conventional technology cost items such as development, testing, UI, operation and maintenance, hardware, and software, a new data asset management cost item has been added to achieve refined management and operation of technology costs.

[0100] Data asset management is a strategic investment for enterprises. How can management better understand and distinguish the value of different data and invest in data asset management projects? Compared with complex algorithm models, the above calculation formula is more intuitive and easy to understand, which is convenient for enterprise management to understand and apply. It helps to apply the value assessment results to internal management decisions, resource allocation and value creation practices of the enterprise.

[0101] The "CTB revenue of a single data item per call" accumulated through business use case data asset management and the "cost of a single data item" accumulated through business use cases and normalized data asset management lay the foundation for the pricing and cost measurement of data assets when the enterprise data assets are included in the balance sheet and participate in the circulation of data element markets.

[0102] The process of the present invention in specific application is as follows:

[0103] 1. Business Use Case Data Asset Management ROI

[0104] 1. Data Acquisition

[0105] Business effectiveness: Calculate business effectiveness (incremental NBV / incremental labor cost savings / incremental loss reduction) based on the type of business use case (marketing enablement / operational efficiency / risk mitigation / regulatory compliance).

[0106] Overall data contribution %: Use AB testing, indicator attribution, business process impact ratio and other methods to calculate the impact of data application on business performance, or refer to the overall data contribution % accumulated by the same type of business use cases.

[0107] Data asset management contribution %: Based on the type of data application (algorithm model / data analysis / data governance), use A / B testing to estimate the improvement in algorithm model accuracy / estimate the proportion of data governance, or refer to the data asset management contribution % accumulated by the same type of data applications.

[0108] CTB cost: Each participant records the data governance cost, including manpower, software and hardware, and other cost inputs. (ii) Formula calculation: Calculate the ROI of data asset management for business use cases based on the acquired data.

[0109] (III) On-site application: Based on the ROI value of the business use case, determine whether the enterprise should invest in data asset management resources for the business use case, or adjust the priority of investment in data asset management resources for the business use case.

[0110] 2. Regular Data Asset Management ROI

[0111] 1. Data Acquisition

[0112] RTB revenue of a single call to a data item: Match the "CTB revenue of a single data item single call" according to the data items governed in the enterprise's normalized data governance tasks, or refer to the single call price of similar external data, or use the past "average CTB revenue of a single call of a business use case data item".

[0113] Number of calls: Count the number of calls of the data items governed in the routine data governance tasks in the source system and the data middle platform, and exclude the parts that overlap with the business use cases.

[0114] Fixed cost of a single data item: Count the costs related to the enterprise's special data asset management work, excluding the parts that overlap with business use cases.

[0115] Number of data items covered: Count the number of data items covered by the company's routine data governance tasks.

[0116] Variable costs: All participants in the statistical enterprise, except for special data asset management work, invest in regular data asset management, including manpower, software, hardware and other costs.

[0117] (ii) Formula calculation: complete the calculation of normalized data asset management ROI based on the acquired data.

[0118] (III) Implement applications, make public announcements regularly, and make the value of data asset management explicit and normalized, so that enterprises can fully and clearly understand the overall value scale of their own data asset management, and lay the foundation for the pricing and cost measurement of data assets when the enterprise's data assets are included in the balance sheet and participate in the circulation of data elements in the market.

[0119] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A quantitative evaluation method for data asset management value, comprising the following steps: S1. Obtain the data to be evaluated, construct corresponding different business effectiveness evaluation indicators according to the use case type of the business use case, calculate the business effectiveness, obtain the first CTB benefit calculation factor, and calculate the business use case data asset management benefit according to the first CTB benefit calculation factor, the second CTB benefit calculation factor and the third CTB benefit calculation factor; S2. Calculate the normalized data asset management benefits based on the RTB benefits of a single call to a data item and the number of calls; S3. Calculate the business use case data asset management costs and the normalized data asset management costs; S4. Calculate the data asset management value, business use case data asset management value, and normalized data asset management value based on the business use case data asset management benefits, normalized data asset management benefits, business use case data asset management costs, and normalized data asset management costs, and adjust the data priority based on the management value, where the data asset management value is:

2. A quantitative evaluation method for data asset management value according to claim 1, characterized in that: The first CTB income calculation factor is as follows: When the use case type is marketing enablement, the first CTB benefit calculation factor, that is, the business effect, is the incremental NBV; When the use case type is business efficiency, the first CTB benefit calculation factor is the incremental labor cost reduction; When the use case type is risk mitigation, the first CTB benefit calculation factor is incremental loss reduction; When the use case type is regulatory compliance, the first CTB benefit calculation factor is not calculated.

3. A quantitative evaluation method for data asset management value according to claim 2, characterized in that: The second CTB benefit calculation factor is the overall data contribution, which is obtained by calculating the impact of data application on business performance using methods such as AB testing, indicator attribution, and business process impact ratio, or by referring to the overall data contribution accumulated by the same type of business use cases.

4. A quantitative evaluation method for data asset management value according to claim 3, characterized in that: The third CTB benefit calculation factor is the data asset management contribution. When the data application type is the algorithm model type, the data asset management contribution refers to the data asset management contribution ratio value accumulated by the same type of business use cases, or uses AB testing to analyze the impact of data asset management on the accuracy of the data model as the data asset management contribution; When the data application type is data analysis, the data asset management contribution is the ratio of the amount of governance data to the total amount of business use case data; When the data application type is data governance type, 100% of the overall data effectiveness will be included in the data asset management contribution.

5. A quantitative evaluation method for data asset management value according to claim 4, characterized in that: The business use case data asset management benefits are:

6. A quantitative evaluation method for data asset management value according to claim 1, characterized in that: The benefits of regular data asset management are: Among them, when the data items of normalized data asset management have been covered in the past business use cases, the CTB revenue of a single call of the data item is used as the RTB revenue of a single call of the data item; When the data items of normalized data asset management are not covered in previous business use cases, the average single-call CTB revenue of the business use case data items or the single-call price of external similar data will be used as the single-call RTB revenue of the data items.

7. A quantitative evaluation method for data asset management value according to claim 6, characterized in that: The CTB benefit of a single call of the data item is specifically: For data items that have been covered by previous business use cases and are single business use cases, the benefit of a single CTB call for the data item is: For data items that have been covered by previous business use cases and support multiple business use cases, the benefit of a single CTB call for the data item is:

8. A quantitative evaluation method for data asset management value according to claim 6, characterized in that: The average CTB benefit of a single call of a business use case data item is: Average single call of business use case data items 9. A quantitative evaluation method for data asset management value according to claim 1, characterized in that: The business use case data asset management cost refers to the data asset management investment of each party involved in the business use case.

10. A quantitative evaluation method for data asset management value according to claim 1, characterized in that: The normalized data asset management cost is: Normalized data asset management cost (RTB cost) = fixed cost of a single data item 1 ×Number of data items covered 2 +Variable costs 3 The fixed cost of a single data item is calculated by evenly allocating the fixed cost of data asset management to a single data item. The number of data items covered is equal to the number of data items covered by normalized data asset management minus the number of data items covered by business use cases. The variable cost includes the normalized data asset management investment of each participant except for special data asset management work in the enterprise, starting from the data items covered by normalized data asset management, including manpower, software, hardware and other cost investments.

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