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 Conduct a Predictive Evaluation of Your Current Learning Programs

Learning teams are under pressure to show that training changes behavior, improves performance, and supports strategic priorities. Attendance figures and satisfaction scores provide useful context, but they rarely predict whether employees will apply new skills or whether the organization will see measurable value.

A predictive evaluation looks forward as well as backward. It combines existing program data, stakeholder judgment, learner behavior, workplace conditions, and business measures to estimate adoption, impact, and return on investment before resources are committed to expansion.

This approach helps organizations decide which learning initiatives deserve investment, which need redesign, and which should be retired. It also gives learning leaders a practical way to connect instructional design with operational results.

Start with the business decision

The first step is to clarify what decision the evaluation must support. You may need to determine whether to scale a leadership program, redesign onboarding, replace a compliance course, or increase support for a sales enablement initiative. Each decision requires different evidence and different definitions of success.

Write a concise evaluation statement that connects the program to a business outcome. For example, a manager development program might be expected to improve retention among first-year employees, while technical training may aim to reduce production errors. A precise outcome prevents the review from becoming a general opinion survey.

Identify the executives, operational leaders, learning professionals, and frontline managers who influence the decision. Their perspectives reveal competing priorities and help establish what evidence will be credible across the organization.

Map the current learning portfolio

Create a simple inventory of current learning programs, including target audiences, delivery formats, completion rates, costs, facilitators, learning objectives, and related performance measures. Include formal courses, coaching, learning bursts, job aids, peer learning, and manager reinforcement.

Review the learner experience from enrollment through workplace application. Check whether employees can access the content when needed, whether managers reinforce the expected behaviors, and whether systems or workloads make application difficult. A program can have excellent content and still produce limited value if the surrounding environment discourages use.

Workforce differences also matter. Employees across generations may have different preferences for practice, feedback, technology, and collaboration. This multigenerational workforce guidance can help teams examine whether the learning experience is accessible and relevant to varied employee groups.

Build an evidence model

A predictive evaluation should use several evidence categories rather than relying on a single score. Start with participation and completion data, then add knowledge checks, skill demonstrations, manager observations, workflow metrics, and business indicators. The goal is to understand the chain from exposure to learning, from learning to behavior, and from behavior to results.

For each program, document the assumptions behind that chain. If a customer service course is expected to improve first-contact resolution, specify which behaviors should change, how quickly they should change, and what other factors could affect the metric. These assumptions become testable points in the evaluation.

Separate leading indicators from lagging indicators. Leading indicators might include practice frequency, manager coaching, tool usage, or early confidence. Lagging indicators could include sales growth, quality improvements, reduced incidents, or increased retention. Leading signals are especially valuable when business results take months to appear.

Estimate adoption and impact

Adoption is more than attendance. Estimate the percentage of the intended audience that will use the learning, the frequency of application, and the degree to which managers and systems reinforce it. Interviews, pulse surveys, observation, platform data, and manager ratings can produce a realistic adoption estimate.

Next, assess likely impact by examining the strength of the learning intervention and the conditions around it. Consider whether employees have opportunities to practice, whether expectations are clear, and whether tools, incentives, and processes support the target behavior. A low adoption forecast may indicate an implementation problem rather than a content problem.

Account for the cost of inaction. Poor training adoption can create rework, inconsistent customer experiences, safety exposure, and wasted development budgets. Reviewing the hidden costs of poor adoption helps leaders include these risks when comparing investment options.

Compare signals before making a forecast

Use a consistent scoring model so programs can be compared fairly. A useful model rates strategic alignment, learner readiness, manager support, application opportunity, measurement quality, expected business impact, and total cost. Scores should be supported by evidence and confidence ratings rather than presented as false precision.

The example below shows how a learning team might summarize predictive findings. The numbers are illustrative; each organization should define its own scales, thresholds, and weighting rules.

Program	Adoption forecast	Impact confidence	Business alignment	Recommended decision
New manager development	High	Medium	High	Scale with manager reinforcement
Sales enablement	Medium	High	High	Improve field coaching
Annual compliance course	High	Low	Medium	Redesign for application
Technical onboarding	Medium	Medium	High	Add practice and job aids

Look for patterns across programs. High participation with low application suggests weak transfer support. Strong manager advocacy with poor learner access points to a delivery or scheduling issue. High expected impact with low measurement confidence signals a need for better baseline data before expansion.

Turn findings into action

A predictive evaluation has value only when it changes portfolio decisions, design choices, or implementation plans. Convert findings into a small number of funded actions, assign owners, and establish review dates. Avoid producing a report that describes problems without specifying what will happen next.

Useful actions may include:

Redesigning activities around realistic workplace decisions
Adding manager prompts, coaching guides, or peer practice
Segmenting learning paths by role, experience, or performance need
Replacing completion targets with application and business measures
Piloting a program with a defined adoption threshold before scaling

Set a follow-up cycle that compares the forecast with actual results. Record which assumptions proved accurate, where adoption fell short, and which interventions improved performance. Over time, this creates an internal evidence base that makes future learning investments faster and more reliable.

A disciplined predictive evaluation gives learning leaders a stronger basis for prioritization. It reveals where capability building is likely to produce value, where implementation risks must be addressed, and where resources may be better directed elsewhere. To apply this approach to your learning portfolio, contact Dave Basarab Consulting to connect evaluation strategy with measurable organizational results.

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.