Companies spend billions on training programs each year but, unfortunately, the majority do not provide measurable improvement in performance. The reason for this is that there is no way to capture data that demonstrates the effectiveness of the training.
By using data-based training analytics, organisations can demonstrate how training relates to actual business results such as increased productivity, reduced turnover, and increased revenue.
The purpose of this guide is to assist HR and Learning and Development Managers in using analytics to improve their organizations’ Performance; including what analytics are available to measure, the key learning metrics, as well as the four levels of Kirkpatrick, in order to achieve an expected 15-35 percent increase in performance through the use of analytics.
Why Data-Driven Training Analytics Matter
Organizations employing analytics for performance management have 20% less employee turnover and 30% quicker productivity improvement compared to organizations relying on traditional forms of training (completion percentages).
While traditional forms of training primarily track completion percentages, the focus of data-driven training methods is on changes in behavior and performance results, which provide actual return on investment (ROI) to organizations.
Advanced analytics identify skill deficiencies 41% better than traditional methods and create a more effective intervention 37% more frequently.
Key Metrics for Measuring Training Effectiveness
Use all four levels of Kirkpatrick’s model to evaluate training effectiveness and the impact of training on job performance.
Examples of Key Metrics to evaluate training effectiveness:
Advanced: Engagement: Time Spent and Completion: 55% more when personalized
Level 1: Reaction: (NPS or Satisfaction Rating) 80% + positive
Level 2: Learning: Pre-Post Test Score Increase: 20-30% average increase
Level 3: Behavior: Application of Skills (used on job): 50%+
Level 4: Results: ROI = (Gains – Costs)/Costs and increase in productivity: 15-25%
Additional Read:
Employee Training and Engagement: How a WordPress LMS Plugin Binds the Pieces Together?
Metrics Comparison: Traditional vs Data-Driven
Step-by-Step: Implementing Data-Driven Training Analytics
To convert data into improvements in performance, take these steps:
- Create Goals: Create outcomes (e.g. Increase in sales due to training) for each metric.
- Establish a Baseline: Establish a baseline for training performance through KPI Assessment.
- Implement a Tracking Method: Implement for monitoring the learning and/or engagement activity in real-time.
- Evaluate using Kirkpatrick’s Evaluative Levels: Evaluate at each of the four levels (reaction, learning, behavior, results) of Kirkpatrick’s evaluation model.
- Take Action and Continue to Revise: Identify areas that need attention and customize learning pathways for improved outcomes (21% improvement) of those at a lower level of performance.
- Report Outcome of Investment to Stakeholders: To obtain budget increases, illustrate those expected ROI figures visually (250%-450%).
Real-World Case Studies: Analytics in Action
Analytics Drive Results Via Case Studies
- FinTech Manager Training – Analytic results of 312% return on investment (ROI) with Manager-Support (Post Training), versus 209% ROI without Manager-Support (Post Training). Manager Engagement Doubled Result
- AT&T Workforce Retraining – $250 million active Investment resulted in 25% growth in revenues and 45% reduction in Turnover through the Traceable Development of Data.
- Engineering Firm – Elimination of Project Delays with personalized paths to succeed from the skills box used by their Workers decreased delay times by 25% and doubled the satisfaction levels across the Workers that participated
- Implementation of Retail LMS – Onboarding times decreased by 40%. Increase in sales of 18%. Decreased turnover rate of 15%.
- TechCorp – Post-training 35% increase Productivity; 40% increase Revenue.
- Analytics provide the vehicle for the delivery of the right intervention at the right time for maximum Return on Investment (Investment = Potential Financial Gain)
Overcoming Common Challenges in Training Analytics
Data silos and Level 3/4 measurements are challenges for many organizations. Consider integrating your LMS with your HRIS to create a complete view of employee performance; in addition, consider using manager observations of employee behavior to capture this information. Start with a small pilot program to create a more thorough understanding of what is required to gain buy-in before implementing further initiatives.
Predictive modeling can help identify skill gaps and provide organizations with a means to address these issues before they become problems.
Conclusion
SkillTriks offers strong data analytics tools designed for data-based organization training programs, to assist with tracking of Kirkpatrick evaluation levels through ROI calculation, as well as through the personalization of learning pathways leading to a 15-35% increase in employee performance levels.
Additionally, SkillTriks offers real-time dashboards and many integrations, which make it possible to convert unprocessed data into intelligence resulting in a reduction in employee turnover and an increase in employee productivity.
