Your Chief Virtual Learning Architect

Learning to Performance

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Custom Design & Delivery

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Predictive Evaluation

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Enterprise Learning Strategy

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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 Forecast Training Impact Using Predictive Analytics

Training investment is easier to defend when leaders can see how learning is expected to influence business performance before a program launches. Predictive analytics provides a practical way to estimate adoption, behavior change, operational outcomes, and financial value using evidence from employees, workflows, and past initiatives.

This approach moves evaluation beyond attendance, completion rates, and post-course satisfaction. It connects learning activity with measurable indicators such as productivity, quality, sales conversion, customer retention, safety, or time to proficiency.

A reliable forecast does not require perfect data or a complex artificial intelligence system. It requires a clear business goal, relevant baseline measures, sensible assumptions, and a method for updating predictions as new evidence becomes available.

Define The Business Outcome First

The strongest training forecast begins with the result the organization wants to improve. “Build leadership capability” is a worthwhile aim, but it is difficult to model. A more useful objective might be reducing regrettable turnover among new managers, shortening project delays, or increasing the percentage of sales opportunities that reach a defined stage.

Once the target is clear, identify the behaviors that should influence it. For example, improved coaching frequency may affect employee performance, while better discovery questioning may affect sales conversion. These links create a causal chain between the learning experience and the business metric.

Assemble Evidence For The Forecast

Predictive evaluation draws on several types of evidence. Historical training data can show who participated, how quickly employees completed activities, and whether previous programs were associated with improved performance. Operational data can reveal workload, manager support, employee tenure, location, role, and other factors that influence adoption.

Qualitative evidence also matters. Interviews, focus groups, manager observations, and workflow analysis help explain why a skill is or is not being used. Combining quantitative and qualitative inputs produces a more realistic learning impact model than relying on learner surveys alone. Published perspectives on evaluation practice, including these reader perspectives, can also help organizations frame the measurement challenge.

Build An Adoption And Impact Model

A forecast should estimate more than whether employees will attend. It should consider the conditions that make application likely: relevance to the role, ease of access, manager reinforcement, practice opportunities, confidence, and consequences for using the new behavior.

A simple model can assign expected probabilities to each stage. For example, an organization might estimate the proportion of employees who will access a resource, complete it, demonstrate the skill, apply it on the job, and sustain the behavior. Those estimates can then be connected to expected changes in operational performance.

Forecast Stage	Useful Evidence	Example Indicator
Reach	Enrollment and access data	Percentage of target employees reached
Engagement	Completion and practice activity	Practice tasks completed
Capability	Assessments and demonstrations	Proficiency score
Adoption	Workflow or manager evidence	New behavior used on the job
Business impact	Operational performance data	Fewer errors or faster cycle time
Financial value	Cost and benefit assumptions	Estimated return on investment

Quantify Uncertainty And Scenarios

A credible forecast should show a range rather than one overly precise number. Create conservative, expected, and optimistic scenarios by changing assumptions such as participation, skill transfer, manager reinforcement, and the size of the expected business improvement.

Sensitivity analysis reveals which assumptions deserve the most attention. If the forecast changes dramatically when manager follow-up rises from 40% to 60%, reinforcement is a critical risk factor. If results remain stable across a wide range of assumptions, the business case is more resilient.

Financial estimates should include program costs, employee time, technology, delivery, reinforcement, and evaluation. Benefits may include avoided costs, increased revenue, reduced rework, improved retention, or faster productivity. Stating assumptions openly makes the forecast easier to review and revise.

Use Learning Design To Improve The Prediction

Analytics cannot compensate for a learning solution that is difficult to use in the flow of work. Short practice activities, realistic scenarios, manager tools, job aids, and targeted reminders can increase the likelihood that capability becomes behavior.

Learning bursts are especially useful when employees need frequent reinforcement rather than a single event. Reviewing learning burst examples can help teams visualize how focused, accessible interventions may support adoption between larger training experiences.

Design data collection into the program from the beginning. A short check-in after application, a manager observation, or a workflow metric can provide stronger evidence than a satisfaction survey collected immediately after training.

Track Leading And Lagging Indicators

Lagging indicators such as revenue, turnover, quality, and customer satisfaction are valuable, but they may take months to change. Leading indicators provide earlier signals that the program is progressing. These may include practice completion, confidence, manager coaching, use of a checklist, or observed behavior.

Set measurement points before launch, during early adoption, and after the expected business effect should appear. Compare results with a baseline, a similar group, or the organization’s previous performance where possible. This creates a stronger basis for separating training effects from unrelated business changes.

Use the results to update the forecast. If access is high but application is low, the issue may involve workflow friction or insufficient manager support. If behavior changes but business performance does not, the original causal assumption may need to be reconsidered.

Practical Steps For A Defensible Forecast

A repeatable process helps learning teams move from general expectations to evidence-based decisions. Use these actions to establish a useful predictive evaluation cycle:

Define one primary business outcome and the behaviors expected to influence it.
Establish baseline performance before designing the intervention.
Combine learning, workforce, operational, and qualitative data.
Model conservative, expected, and optimistic adoption scenarios.
Assign owners to each leading and lagging indicator.
Review actual results and revise assumptions after launch.

Forecasting training impact is a disciplined way to connect enterprise learning strategy with organizational priorities. It helps leaders decide where to invest, where risks may limit adoption, and which evidence will demonstrate value.

Dave Basarab Consulting can help organizations design the learning strategy, measurement architecture, custom content, and predictive evaluation approach needed to link employee capability with business results. Build a forecast around your next critical performance goal and turn training data into a clearer business decision.

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.