Agile R&D Analyzer for Tax Credit Assessment
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Solution Overview
Problem
The current process for claiming research and development (R&D) tax credits is burdensome and inefficient, particularly for entities using Agile software development processes, due to complex eligibility and documentation requirements, lack of formal tracking, and risk of penalties for improper filings.
Innovation Solution
A computer-implemented system and method that extracts and transforms data from various sources to generate an activity nexus matrix, identifies subject matter experts, and creates interview preparation packages and pre-qualified time surveys, facilitating a streamlined R&D credit assessment with improved accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual R&D credit assessment process is used, then flexibility in handling complex cases is maintained, but time consumption and resource requirements increase significantly
Solution Approach 1:
The system performs preliminary data extraction and transformation from multiple sources (project data, human resource data, vendor data) before the actual credit assessment, generating pre-qualified time survey data and activity nexus matrices in advance. This preliminary processing reduces the time required during the actual assessment while maintaining manual review capabilities for complex cases.
Solution Approach 2:
The patent introduces an intermediary automated analysis layer between the raw data and the final credit assessment. This intermediary system processes data through standardized transformations and generates recommendation reports that assist manual assessors, combining the speed of automation with the flexibility of manual judgment for complex R&D credit cases.
2Measurement precision
If comprehensive data collection from multiple sources is performed, then assessment accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the complex data collection process into distinct modules: project data extraction, human resource data extraction, vendor data extraction, and activity nexus matrix generation. Each module handles a specific data source independently, then integrates results through standardized transformations. This segmentation improves assessment accuracy by ensuring comprehensive data collection while reducing system complexity through modular design.
Solution Approach 2:
The patent implements a universal data transformation framework that handles multiple data sources (projects, HR, vendors) through a common processing architecture. The activity nexus matrix and standardized output formats serve as universal interfaces that work across different data types, reducing system complexity while maintaining the ability to collect comprehensive data for accurate assessments.
3Productivity
If standardized output format is implemented, then processing efficiency increases, but adaptability to different data sources decreases
Solution Approach 1:
The system applies local quality by implementing data-source-specific extraction and transformation logic tailored to each type of input (projects, HR data, vendor data). Each data source undergoes customized processing appropriate to its structure and characteristics, then all results converge to a standardized output format. This approach maintains processing efficiency through standardization while preserving adaptability through localized transformation rules.
Data Source
AI summary
An embodiment of the present invention is directed to an Agile Research and Development (R&D) Analyzer that represents a suite of tools that analyze documentation and associated metadata from project management systems such as JIRA, Wiki, and GIT to assist in key stages of a qualitative assessment of an R&D Tax Credit Study. The quantitative assessment may be leveraged across a number of entities and clients that use Agile software development processes or other iterative approach to project management and software development. For example, the Agile R&D Analyzer may be used by Tax engagement team members during a R&D Tax Credit Study.