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

Measuring coaching impact with predictive analytics

Coaching programs can strengthen leadership, improve performance, and support behavior change, but their value is often difficult to demonstrate. Attendance counts and satisfaction surveys show participation and perception; they do not reliably show whether employees applied new skills or whether the business benefited.

Predictive analytics gives learning leaders a stronger way to evaluate coaching. By combining baseline data, participation signals, manager observations, and business metrics, organizations can estimate the likelihood of adoption and identify where coaching is most likely to produce measurable results.

The objective is not to reduce human development to a single score. It is to create credible evidence that helps decision-makers improve coaching design, focus resources, and connect individual growth with organizational priorities.

Why coaching measurement needs prediction

Traditional evaluation usually happens after a program ends. Participants complete a survey, managers may provide anecdotal feedback, and the learning team compares a few performance indicators. This approach can reveal what happened, but it rarely explains what is likely to happen next.

Predictive evaluation changes the timing and purpose of measurement. It uses early indicators to forecast coaching adoption, skill application, and potential business impact. For example, low practice frequency may signal weak transfer before performance data begins to decline.

This forward-looking view supports timely intervention. A coach may need to adjust the practice format, a manager may need a structured reinforcement conversation, or the organization may need to clarify how the new behavior supports operational goals.

Define outcomes before coaching begins

A measurable coaching initiative starts with a clear business need. “Improve leadership” is too broad to evaluate effectively. A stronger objective might be reducing regrettable turnover among frontline teams, increasing sales conversion, or improving the speed and quality of project decisions.

The next step is to identify observable behaviors connected to that objective. If the desired outcome is stronger delegation, evaluation might track the quality of goal setting, assignment clarity, follow-up routines, and employee ownership. These behaviors provide a bridge between coaching activity and business performance.

Baseline data matters as well. Establishing current performance, manager confidence, employee engagement, or retention rates makes it possible to distinguish meaningful movement from normal variation. It also helps predictive models identify which participants or teams may need additional support.

Build an evidence model that people can use

A practical measurement framework combines several types of evidence instead of relying on one metric. Participation data shows exposure, practice data indicates application, manager feedback reveals observed change, and operational measures show whether the change matters to the organization.

The model should remain understandable to coaches, managers, and executives. A complex algorithm that cannot inform a practical decision has limited value. Use a manageable set of indicators, define how each one is collected, and establish who is responsible for reviewing the signals.

Evidence area	Useful indicators	Predictive question
Participation	Session attendance, coaching completion, response rates	Who may be at risk of disengaging?
Practice	Action completion, reflection quality, skill demonstrations	Who is likely to apply the behavior?
Reinforcement	Manager check-ins, peer feedback, follow-up activities	Where is transfer being supported?
Performance	Productivity, quality, retention, sales, engagement	Which changes may affect business results?
Context	Workload, role changes, team conditions	What factors may influence adoption?

Privacy and fairness must be built into the approach. Employees should understand what is being measured, why the data is collected, and how it will be used. Predictive analytics should guide support and program improvement, not label individuals permanently or replace professional judgment.

Connect coaching signals to business performance

A coaching program creates value when new capabilities appear in daily work. That makes transfer measurement essential. Look for evidence that participants are using the targeted behavior in real situations, such as improved one-to-one conversations, more effective prioritization, or better customer interactions.

Short reinforcement activities can make this evidence easier to capture. For example, learning bursts for product launches can provide brief practice and reflection opportunities between formal coaching sessions. Similar techniques can prompt participants to record examples of application while those examples are still recent.

Business metrics should be interpreted carefully. A rise in revenue, engagement, or productivity may have several causes, including market conditions, staffing changes, or a new technology rollout. Comparing coached and non-coached groups, reviewing trends over time, and gathering manager evidence can produce a more defensible attribution story.

Use evaluation when attendance is uneven

Coaching programs often include optional sessions, distributed teams, shift workers, and participants with changing schedules. If measurement only considers live attendance, the organization may confuse access with learning and overlook people who engage through other channels.

A broader evaluation design can include recordings, practice tasks, digital reflections, manager observations, and performance evidence. Guidance on measuring learning without live attendance is especially useful when coaching is delivered across time zones or through blended formats.

Predictive models can also reveal whether alternative participation paths produce comparable outcomes. If employees who complete asynchronous practice show strong behavior adoption, the program may be able to expand access without weakening impact. If their results lag, the learning team can improve support rather than simply requiring attendance.

Turn findings into better coaching decisions

The value of analytics appears when findings lead to action. A dashboard might show that participants understand a concept but rarely practice it, indicating a need for job aids or manager reinforcement. It might also reveal that one business unit has stronger adoption because its leaders create more opportunities to use the skill.

Review results at multiple levels. Coaches need individual or cohort signals, program owners need patterns across delivery methods, and executives need a concise view of business contribution. Each audience should see information that supports a decision rather than an abundance of disconnected measures.

Practical recommendations:

Define two or three target behaviors before selecting evaluation metrics.
Capture baseline performance and contextual factors before coaching starts.
Combine participation, practice, reinforcement, and business data.
Set review points early enough to correct adoption problems.
Protect employee privacy and explain the purpose of predictive measures.

A well-designed measurement system makes coaching more credible and more adaptable. Dave Basarab Consulting can help organizations connect coaching strategy, learning evidence, and business outcomes through Predictive Evaluation. Build an evaluation approach that forecasts adoption, demonstrates impact, and gives leaders clear evidence for their next investment.

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.