Normalized Earning Code Classification for Payroll Data Analysis

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Solution Overview

Problem

Existing human resources data, particularly earning codes, are not normalized and utilized effectively for business operations, leading to inefficiencies in payroll transactions and resource allocation.

Innovation Solution

A computer-implemented method using statistical machine learning to classify and normalize employee transaction data into human resources-related attributes, enabling the adjustment of organizational operating procedures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If employee transaction data is not normalized, then data storage is simple, but data analysis and evaluation capabilities are poor

Engineering Contradiction:

Improvedata analysis capabilityVSAvoiddata processing complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system performs preliminary normalization and classification of employee transaction data before analysis. By pre-processing the heterogeneous data into standardized earning codes and HR attributes, the system enables subsequent analytical operations without requiring complex processing during query execution.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary classification layer that translates raw transaction data into standardized earning codes and HR attributes. This intermediary representation serves as a bridge between raw data and analytical operations, enabling efficient evaluation while maintaining data fidelity.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If heterogeneous transaction data is used directly, then data collection is straightforward, but evaluation and refinement of business operations is difficult

Engineering Contradiction:

Improvebusiness operation evaluation efficiencyVSAvoiddata standardization level

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system transforms heterogeneous transaction data by changing its parameters into standardized earning codes and HR attributes. This parameter transformation enables consistent measurement and evaluation across different data sources while maintaining the essential information needed for business operation analysis.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The normalized earning codes and HR attributes serve as universal descriptors that can be applied across multiple business operations and analytical contexts. This universal representation enables the same data structure to support various evaluation and refinement activities.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Reliability

If payroll data is not classified into normalized codes, then data processing is simpler, but resource allocation and benchmarking are ineffective

Engineering Contradiction:

Improveresource allocation accuracyVSAvoidclassification system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments payroll data into distinct normalized earning codes and HR attributes. By dividing the heterogeneous data into categorized segments, the system enables precise resource allocation and benchmarking while keeping the classification structure manageable through standardized codes.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20260080365A1Earning code classification

Publication Date: 2026.03.19 ADP INC

AI summary

Managing and applying human resources data comprising aggregating employee transaction data for an organization. A number of human resources-related attributes are evaluated across heterogeneous transaction data. The employee transaction data is classified via statistical machine learning into a number of normalized codes according to the human resources-related attributes, a user interface is presented to adjust a number of organizational operating procedures according to the normalized codes.