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Using L&D data to control retention

In today’s fast-paced work environment, learning and development (L&D) plays a crucial role in employee retention. In fact, 45% of workers are more likely to stay in their roles if they receive some form of training or a development plan.

How does L&D enhance employee retention? And how do we measure this?

By analyzing various types of L&D data, organizations gain valuable insights into employee engagement, skill development, and career progression, which are all key indicators for improving employee retention.

Let’s dive into the types of L&D data that provide the indicators you need to improve employee retention:

 

Engagement metrics

Monitoring the progress of employees’ skill development through L&D data helps organizations understand which skills are being effectively acquired and which areas may need additional focus. Tracking metrics such as course completion rates, time spent on learning platforms, and participation in training sessions can indicate how engaged employees are with their professional development. By addressing skill gaps and reinforcing strengths, companies can ensure their workforce remains competent and confident, which is crucial for job satisfaction and retention.

 

Skill advancement tracking

L&D data can highlight the career paths that employees are most interested in and the training they need to advance. Keeping tabs on the skills employees are developing helps organizations identify growth opportunities and career pathways. This data should be used to tailor individual development plans that align with both employee aspirations and business needs. This not only helps in retaining talent but also in preparing future leaders within the organization.

 

Feedback and assessment results

Regular feedback and assessments provide a window into employee performance and areas for improvement. By analyzing participation rates, feedback scores, and completion rates, organizations can identify the types of content and delivery methods that resonate best with their workforce. This insight allows companies to tailor their L&D offerings to better meet employee preferences, thereby increasing overall engagement.

 

Learning Pathways and Progression

Analyzing employees’ progression through various learning pathways reveals the effectiveness of L&D programs. The higher the growth, the better the program. It also highlights the need for additional resources or changes in the curriculum to better support employee growth. By closely analyzing employees’ progression through learning pathways, organizations can ensure their L&D programs are not only effective but also continuously evolving to meet the needs of their workforce. This proactive approach helps in creating a culture of continuous improvement and lifelong learning.

 

Correlation with Performance Data

Integrating L&D data with performance metrics reveals how learning initiatives impact job performance, validating the investment in L&D. A positive correlation can encourage further investment and promote a culture of continuous learning. Regular analysis helps identify areas for improvement and ensures alignment with business objectives.

 

Predicting Turnover Risks

Advanced analytics can be used to predict which employees might be at risk of leaving based on their engagement with L&D programs. For example, a sudden drop in participation or a lack of progress in skill development could be indicators of disengagement. By proactively addressing these signs, organizations can use targeted support to keep employees engaged and, therefore, at a lower risk of leaving.

 

L&D data offers a treasure trove of insights that, when analyzed and acted upon, can significantly enhance employee retention strategies. By understanding what drives engagement, skill development, and career progression, organizations can create a more fulfilling work environment that encourages employees to stay and thrive.

 

Find out how Kallidus Learn LMS can support you with its new reporting and analytics features.

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Written by Dawn Baron

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