Your Chief Virtual Learning Architect

Learning to Performance

Read More
Custom Design & Delivery

Read More
Predictive Evaluation

Read More
Enterprise Learning Strategy

Read More

› ‹

1
2
3
4

Dave Basarab Consulting has elevated the training experience, offering an end-to-end comprehensive approach that includes training strategy, instructional design, development, delivery , post program training transfer, and evaluation (via the unique Predictive Evaluation methodology). Virtual Chief Architect Dave Basarab has combined all of these individual training elements with his user-friendly, comprehensive Learning to Performance approach, which significantly increases companies' training ROI.

Why we are different

Innovation: Our primary focus is creating learning programs using a Learning to Performance approach.
Expertise: Dave offers the depth and breadth of his experience, including working internally at prestigious companies (Motorola, Ingersoll Rand and Pitney Bowes) as well as his knowledge and expertise as a highly-respected, sought-after consultant.
Partnership: Basarab collaborates with companies, serving as their own Chief Learning Officer whenever they need to plan, strategize, or implement training initiatives.

Training Services

Enterprise Learning Strategy

Enterprise Learning Strategy

At Dave Basarab Consulting, we're experts in creating Enterprise Learning Plans. We work with you to develop your company's learning strategy and direction.

Custom Design, Development, & Delivery

Custom Design, Development, & Delivery

Custom training is an effective way of developing the capability required to execute your strategy. We are a custom design house that creates programs specific to your business.

Learning Burst Development

Learning Burst Development

We can create and deliver your courses via our unique Learning Burst Method - keeping your employees at their jobs while receiving world-class training.

Predictive Evaluation

Predictive Evaluation

We predict the ROI for your courses and establish success gates. We then evaluate the course against the success gates to show value realized and continually improve results.

Leadership Development

Leadership Development

Turn-key virtual custom leadership development program that combines world-class leadership speakers/educators with post-event personalized coaching to provide you with a cadre of highly skilled leaders.

Predictive Evaluation

How to Use Learner Feedback to Predict Long-Term Adoption

Training feedback is often treated as a satisfaction score collected immediately after a workshop. That snapshot can reveal whether participants enjoyed the experience, but it says little about whether they will apply new skills weeks or months later. A stronger approach treats learner feedback as an early indicator of future behavior.

When feedback is gathered at several points and connected with workplace conditions, it can help learning teams forecast adoption. The goal is to identify the beliefs, barriers, and support needs that influence whether employees use what they learned on the job.

This makes feedback valuable for more than course refinement. It becomes evidence for improving instructional design, manager reinforcement, communication, and the business impact of enterprise learning.

Start with adoption intent

The first useful signal is a learner’s intention to apply a skill. Ask participants what they expect to use, how frequently they anticipate using it, and when they plan to begin. Specific answers are more predictive than broad statements such as “the training was helpful.”

Intent should be measured alongside confidence and perceived relevance. A learner may understand a concept but see no connection to current responsibilities. Another may feel motivated but lack the authority, time, or tools required to act. These distinctions reveal the difference between willingness and realistic adoption potential.

A structured intention evaluation method can help organizations capture these early indicators consistently and compare them across programs, roles, and audiences.

Turn comments into behavioral signals

Open-ended comments contain valuable evidence, but they need to be analyzed for patterns. Look for references to specific behaviors, upcoming opportunities to practice, manager expectations, workflow friction, and perceived usefulness. Comments that describe an intended action are generally more informative than comments focused only on presentation quality.

Use a simple coding framework to classify responses. For example, “I will use this during next week’s client review” indicates opportunity and timing, while “I need access to the reporting system first” identifies an adoption barrier. Repeated mentions of unclear examples may point to an instructional design issue rather than a motivation problem.

Combining qualitative feedback with scaled questions improves predictive accuracy. A low confidence rating paired with a strong intention to apply may signal a need for coaching. High confidence paired with low relevance may indicate that the content is unlikely to transfer into daily work.

Separate enthusiasm from readiness

Positive reactions can create a misleading picture of training success. Learners may rate a session highly because the facilitator was engaging, the topic was interesting, or the event offered a welcome break from routine. None of these factors guarantees sustained behavior change.

To assess readiness, ask about practical conditions: access to tools, supervisor support, peer norms, time to practice, and the consequences of using the new approach. Feedback should also distinguish between knowledge acquisition and performance application.

Feedback signal	What it may indicate	Follow-up measure
High relevance rating	Strong connection to job needs	Observation of task use
Clear intention to apply	Potential early adoption	Check-in after two to four weeks
Low confidence	Need for practice or coaching	Skill demonstration
Limited manager support	Environmental adoption risk	Manager reinforcement review
Requests for job aids	Need for performance support	Resource usage and task accuracy

This interpretation helps learning leaders avoid treating satisfaction as a proxy for return on investment. It also creates a clearer bridge between learner experience data and operational outcomes.

Segment feedback by context

The same course can produce very different adoption patterns across departments, locations, levels of experience, and manager groups. Aggregated feedback may hide these differences. Segmenting responses allows teams to identify where adoption is likely to flourish and where additional intervention is needed.

For example, experienced employees may understand the rationale for a new process but resist changing established habits. New employees may be enthusiastic yet lack the confidence to perform independently. Remote teams may need digital practice tools, while frontline teams may need short learning bursts that fit between operational demands.

Contextual analysis should include the learner’s role, workflow, manager relationship, and access to resources. These variables turn general feedback into actionable adoption forecasts and help organizations target reinforcement instead of applying the same solution to everyone.

Track the path from intention to use

Learner feedback is most powerful when collected throughout the learning journey. A useful sequence can include a pre-training expectation survey, an immediate post-session response, a short-term application check, and a later performance review. Each stage answers a different question.

Before training, feedback reveals perceived needs and motivation. Immediately afterward, it shows confidence and intended use. Two to four weeks later, learners can report what they attempted, what worked, and what prevented application. Later evidence should include manager observations, work samples, productivity measures, quality indicators, or customer outcomes where appropriate.

This progression exposes the gap between intention and behavior. A large gap may signal weak reinforcement, competing priorities, poor system design, or insufficient practice. Organizations can then adjust the learning experience and its surrounding conditions before adoption declines.

Build a predictive feedback loop

A predictive feedback process should end with decisions, not simply dashboards. Establish thresholds that trigger action, such as low application intent among a critical population, repeated reports of manager resistance, or declining use of a job aid. Assign ownership for responding to each signal.

Learning teams should also compare forecasts with later results. If high intention consistently leads to low application, the measurement model may be overvaluing motivation and undervaluing workplace barriers. If moderate confidence still produces strong performance, practical support may be compensating for uncertainty.

This disciplined cycle strengthens future forecasting. A broader view of training ROI measurement can help connect learner evidence with adoption, performance, and business results rather than stopping at reaction scores.

Practical ways to improve prediction

Use feedback as an operating system for learning decisions by making each measure specific, time-bound, and connected to observable work.

Ask learners to name the exact behavior they intend to use.
Collect feedback before training, immediately afterward, and during workplace application.
Segment responses by role, manager support, access to tools, and work environment.
Combine learner reports with manager observations and operational performance data.
Review prediction accuracy and revise questions when forecasts miss actual adoption.

When learner voice is connected to behavior and business context, training teams can see adoption risks before they become performance problems. Start with one priority program, define the behaviors that matter, and build a feedback cycle that shows whether learning is becoming routine.

Learning to Performance

Learning to Performance, a complete training approach, gives companies world-class training to drive significant return. This approach includes upfront work (Impact Mapping, design), training (for staff and company executives), and post-training efforts to ensure training transfer. This unique recipe - the key for successful training and adoption - is changing the way companies implement training. This methodology could work with any content for organizations in any industry.