Training Effectiveness Agent
Measure L&D impact - beyond satisfaction scores.
Measures training impact across multiple levels: satisfaction, knowledge transfer, behavioural change, and business outcomes.
Analyse your process
Assessment
What This Agent Does
Most organisations measure training effectiveness at the first level only: participant satisfaction (‘How did you like the course?’). The Training Effectiveness Agent goes deeper, implementing a multi-level evaluation framework that measures reaction (satisfaction), learning (knowledge gained), behaviour (application on the job), and results (business impact).
The agent collects evaluation data at each level: post-training surveys for reaction, assessments for learning, follow-up surveys and manager observations for behaviour change, and performance or business metrics for results. It correlates this data across programmes to identify which training investments deliver measurable value and which do not.
This analysis enables a fundamental shift in L&D strategy: from spending based on perceived need or popularity to investing based on demonstrated effectiveness. Programmes that consistently fail to produce behaviour change can be redesigned or discontinued. Programmes that correlate with performance improvement can be scaled.
Micro-Decision Table
Collect reaction data Distribute and aggregate post-training satisfaction surveys AI Agent
Automated survey distribution and response collection
Decision Record
Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.
Collect learning data Aggregate assessment results and certification outcomes AI Agent
Automated data collection from LMS and assessment systems
Decision Record
Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.
Collect behaviour data Gather follow-up observations and manager feedback AI Agent
Automated survey and feedback collection at defined intervals
Decision Record
Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.
Correlate with performance metrics Analyse relationship between training completion and outcomes AI Agent
Statistical correlation analysis controlling for confounding factors
Decision Record
Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.
Generate effectiveness report Produce multi-level evaluation per programme AI Agent
Automated report generation with statistical summaries
Decision Record
Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.
Decision Record and Right to Challenge
Every decision this agent makes or prepares is documented in a complete decision record. Affected employees can review, understand, and challenge every individual decision.
Prerequisites
- Learning management system with completion and assessment data
- Post-training survey infrastructure
- Follow-up observation or feedback collection capability
- Performance metrics accessible for correlation analysis
- Multi-level evaluation framework definition
- Statistical analysis capability for correlation and significance testing
Governance Notes
Infrastructure Contribution
Does this agent fit your process?
We analyse your specific HR process and show how this agent fits into your system landscape. 30 minutes, no preparation needed.
Analyse your processWhat this assessment contains: 9 slides for your leadership team
Personalised with your numbers. Generated in 2 minutes directly in your browser. No upload, no login.
- 1
Title slide - Process name, decision points, automation potential
- 2
Executive summary - FTE freed, cost per transaction before/after, break-even date, cost of waiting
- 3
Current state - Transaction volume, error costs, growth scenario with FTE comparison
- 4
Solution architecture - Human - rules engine - AI agent with specific decision points
- 5
Governance - EU AI Act, works council, audit trail - with traffic light status
- 6
Risk analysis - 5 risks with likelihood, impact and mitigation
- 7
Roadmap - 3-phase plan with concrete calendar dates and Go/No-Go
- 8
Business case - 3-scenario comparison (do nothing/hire/automate) plus 3×3 sensitivity matrix
- 9
Discussion proposal - Concrete next steps with timeline and responsibilities
Includes: 3-scenario comparison
Do nothing vs. new hire vs. automation - with your salary level, your error rate and your growth plan. The one slide your CFO wants to see first.
Show calculation methodology
Hourly rate: Annual salary (your input) × 1.3 employer burden ÷ 1,720 annual work hours
Savings: Transactions × 12 × automation rate × minutes/transaction × hourly rate × economic factor
Quality ROI: Error reduction × transactions × 12 × EUR 260/error (APQC Open Standards Benchmarking)
FTE: Saved hours ÷ 1,720 annual work hours
Break-Even: Benchmark investment ÷ monthly combined savings (efficiency + quality)
New hire: Annual salary × 1.3 + EUR 12,000 recruiting per FTE
All data stays in your browser. Nothing is transmitted to any server.
Training Effectiveness Agent
Initial assessment for your leadership team
A thorough initial assessment in 2 minutes - with your numbers, your risk profile and industry benchmarks. No vendor logo, no sales pitch.
All data stays in your browser. Nothing is transmitted.
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Frequently Asked Questions
How does the agent measure 'behaviour change' after training?
Through a combination of follow-up surveys (asking participants and managers about application on the job), observable metric changes (where applicable), and longitudinal tracking. Behaviour measurement is imperfect - but even imperfect measurement is better than no measurement.
Can the agent prove causation between training and performance improvement?
The agent measures correlation, not causation. However, by controlling for confounding factors and comparing trained vs. untrained groups where possible, it provides the closest approximation to causal inference that is feasible in a workplace context.
What Happens Next?
30 minutes
Initial call
We analyse your process and identify the optimal starting point.
1 week
Discover
Mapping your decision logic. Rule sets documented, Decision Layer designed.
3-4 weeks
Build
Production agent in your infrastructure. Governance, audit trail, cert-ready from day 1.
12-18 months
Self-sufficient
Full access to source code, prompts and rule versions. No vendor lock-in.
Implement This Agent?
We assess your process landscape and show how this agent fits into your infrastructure.