Transforming L&D Strategy with Advanced Analytics: Insights from a Global Mandatory Training Program

Executive Summary

A global financial institution partnered with The Learning Data Agency (LDA) to analyse the results of their Global Mandatory Training (GMT). The institution had recently adopted a test-out approach and needed to understand its effectiveness and identify areas requiring additional training and attention. The LDA provided insights into employee performance, identifying areas for improvement and supporting data-driven decision-making.

Introduction

The financial institution administers quarterly mandatory training to ensure employees are up-to-date with critical knowledge and skills, covering topics such as financial crime prevention and regulatory compliance. The institution had recently adopted a test-out approach and sought to understand the effectiveness of this approach and identify opportunities for improvement.

The Problem

The institution faced challenges in interpreting GMT results effectively. While the business has an internal data team, this resource is shared across multiple L&D teams and predominantly specialises in deriving completion and learning hours metrics. The institution lacked advanced analytics resources to conduct a detailed analysis of the GMT results. They required analysis to determine which questions employees answered incorrectly, the specific answer choices selected, and any patterns or trends in the data. The institution also wanted to explore alternative analyses to gain deeper insights into employee performance.

The Solution

The Learning Data Agency developed a comprehensive analysis plan to address the institution's requirements. The solution included question-level analysis, performance comparison, time-series analysis, difficulty analysis, and learning gap analysis.

The Outcome

The analysis provided insights into employee performance on the GMT:

  • Question-level analysis identified specific questions and topics where employees struggled, enabling targeted training interventions.

  • Performance comparison revealed variations in test scores across employee groups, helping the institution allocate resources and support.

  • Difficulty analysis identified questions that were too easy or too difficult, prompting a review of test content and design.

  • Learning gap analysis uncovered common misconceptions and knowledge gaps, guiding the development of targeted training materials.

The analysis produced was critical in assisting the institution in making their decisions for the next round of training, for example demonstrating that not all topics needed to be mandatory in 2024.

The Feedback

“…the analysis carried out has been useful not just for the Mandatory training team, but the Financial Conduct team too. It has helped them decide which areas they need to focus on in 2025 when they refresh their training”

“Having the data to support the approach in 2023 has meant we can carry this forward in to 2024. The analysis carried out on 2023 has meant the Programme Specialist has evidence to support that not all topics need to be mandatory”

How can the Learning Data Agency help your team make data-driven strategic decisions?

Previous
Previous

Enhancing Data Reliability and Efficiency in L&D: A Journey from Manual Errors to Automated Insights