Data Mapping System for Business Question Alignment
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Solution Overview
Problem
Calculating return on investment for business activities like employee training is speculative due to difficulties in obtaining accurate and complete data sets, which are often costly and do not reflect the correct indicators for measuring human resource activities.
Innovation Solution
A data mapping system that structures and programs hierarchical data structures to align business questions with relevant data elements, prioritizing value driver data to optimize the assessment of business requirements and questions, such as recruiting and training effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive data sets are collected to answer business questions, then measurement precision is improved, but loss of time and loss of energy increase due to the costly and difficult data acquisition process
Solution Approach 1:
The system pre-identifies and pre-maps relevant data elements to business questions before actual analysis is needed. By establishing the mapping framework in advance, the system eliminates the need for time-consuming data collection and processing when business questions arise, as the relevant data elements are already identified and structured for immediate use
Solution Approach 2:
The patent introduces an intermediary mapping system that connects business questions to data elements without requiring direct data collection. This mapping layer acts as a mediator that translates business questions into specific data element requirements, eliminating the need for organizations to directly acquire and process comprehensive data sets
2Measurement precision
If comprehensive data sets are collected to answer business questions, then measurement precision is improved, but loss of energy and financial resources increase due to costly data acquisition
Solution Approach 1:
The system extracts only the specific data elements that are directly relevant to answering particular business questions, rather than collecting comprehensive data sets. The mapping framework enables organizations to extract precisely the data needed for specific analyses, eliminating waste of financial resources on unnecessary data acquisition
Solution Approach 2:
The patent changes the parameter of data selection from comprehensive to targeted by using the mapping system. Instead of acquiring all possible data, the system transforms the approach to select only data elements that map to specific business questions, thereby reducing financial expenditure while maintaining measurement precision
3Ease of operation
If data are collected in digestible format, then ease of operation is improved, but measurement precision deteriorates because the data may not reflect the correct indicators for measuring human resource activities
Solution Approach 1:
The mapping system serves as an intermediary layer between raw data elements and business questions. It translates business questions into specific data element requirements without requiring data to be pre-formatted or pre-processed, thereby maintaining both ease of operation and measurement precision through the mapping framework
4Productivity
If hierarchical data structures are implemented to map business questions to data elements, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent segments the data mapping system into hierarchical levels (business questions, data factors, data elements, source systems) that can be independently developed and maintained. This segmentation allows the complex mapping functionality to be broken down into manageable components, improving productivity while controlling system complexity through modular architecture
Data Source
AI summary
Various embodiments of the invention can be used to organize and prioritize data to optimize the ability to answer business questions and address business needs. A data mapping system may be used to map value driver data elements to business questions to assess which data sets or sources of data are more important than others when assessing the business questions. This can assist in the process of identifying the most useful and accurate data for assessing a business question.