Learning Management System for Performance- and Weather-Aware Training

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Solution Overview

Problem

Conventional employee training systems fail to provide timely and personalized training recommendations based on individual and business performance metrics, seasonal weather conditions, and geographical variations, leading to inefficiencies and suboptimal skill development.

Innovation Solution

A Learning Management System (LMS) that utilizes operational performance data, sales metrics, and geographical and meteorological information to customize training programs, integrates coaching options, social media tools, and gamification to enhance engagement, and allows associates to create and share content.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional employee training systems are used, then training can be provided, but training recommendations are not timely or personalized enough

Engineering Contradiction:

Improvetraining recommendation precisionVSAvoidtraining delivery timing

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary actions by proactively identifying training needs before they become critical issues. It continuously monitors performance metrics, weather conditions, and operational data to predict when training will be needed, then schedules and delivers training recommendations in advance, ensuring timely intervention before performance degradation occurs.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements continuous feedback loops by monitoring employee performance metrics, weather conditions, and training completion status. This feedback enables the system to dynamically adjust training recommendations based on real-time data, improving both the timeliness and personalization of training delivery.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If conventional training systems are used, then training can be delivered, but training is not personalized to individual or business performance metrics

Engineering Contradiction:

Improvetraining personalizationVSAvoidperformance data utilization

Core Design Contradiction:

Adaptability or versatilityVSLoss of information

Solution Approach 1:

The system applies local quality by tailoring training recommendations to specific individuals, departments, or locations based on their unique performance characteristics. It analyzes local performance metrics, weather conditions, and operational data to create customized training plans that address specific needs rather than applying a one-size-fits-all approach.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system utilizes parameter changes by adjusting training recommendations based on varying performance metrics, weather conditions, and operational parameters. It dynamically modifies training content, timing, and delivery methods according to changing business conditions and individual performance data.

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If conventional training systems are used, then training can be provided, but training does not account for seasonal weather conditions or geographical variations

Engineering Contradiction:

Improveenvironmental adaptabilityVSAvoidtraining relevance

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system implements dynamics by making training recommendations adaptive to changing environmental conditions. It continuously updates training schedules based on seasonal weather patterns, geographical location, and operational demands, ensuring training remains relevant and effective regardless of external environmental changes.

Inventive Principle:

Principle #15Dynamics

4Measurement precision

If more data is collected for personalized training, then training recommendations improve, but system complexity increases

Engineering Contradiction:

Improvetraining recommendation accuracyVSAvoidsystem data processing complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system achieves universality by designing a multi-functional platform that handles diverse data types (performance metrics, weather data, operational data) through a unified processing architecture. This allows the system to manage complex data collection and analysis while maintaining a consistent, scalable approach that reduces overall system complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250252401A1Learning management system

Publication Date: 2025.08.07 TRANSFORM SR BRANDS LLC

AI summary

Systems and methods that support the creation and timely electronic scheduling and delivery of course materials for training of individuals in an organization, in which course recommendations, scheduling, and rollout are based upon a number of factors including, for example, specific individual and/or business day-to-day operational performance measures, sales performance, and seasonal weather conditions by geographical region.