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 Use Predictive Evaluation to Identify High-Potential Employees

Identifying high-potential employees requires more than reviewing performance ratings or asking managers who appears ready for promotion. Predictive Evaluation connects learning behaviour, capability growth and business outcomes to estimate which employees are most likely to apply new skills effectively in future roles. Learn more about Maximize Your Training Value.html.

For Australian organisations, this approach is useful across dispersed teams, regulated industries and competitive talent markets. A learning program may serve employees in Sydney, Melbourne and regional sites, while leaders still need a consistent way to recognise emerging capability and invest in the right development opportunities.

From Learning Data to Talent Signals

Predictive Evaluation examines the conditions that influence training adoption, performance improvement and business impact. It can combine participation data with manager observations, assessment results, workflow evidence and operational measures. The purpose is not to create a mysterious score; it is to produce a defensible forecast about future capability.

High-potential employees often show patterns before promotion is considered. They may complete learning early, seek feedback, practise skills in live work and help colleagues apply new methods. These behaviours become more meaningful when they are linked to outcomes such as faster project delivery, improved customer service or safer work practices.

A useful model distinguishes potential from current seniority. An employee in a Brisbane contact centre, a Perth resources operation or a Melbourne professional-services team may demonstrate strong learning agility without having access to the same projects or visibility as established leaders.

Define the Evidence Before Scoring

Start by defining what “high potential” means for the organisation. It might include the capacity to lead through change, learn complex systems, influence without formal authority or transfer expertise across teams. The definition should reflect business priorities rather than generic personality traits.

Next, identify leading and lagging indicators. Leading indicators show likely adoption, such as practice frequency, peer coaching or assessment improvement. Lagging indicators show realised value, such as reduced rework, stronger retention or improved sales conversion. A training adoption scorecard can help organise these measures before data collection begins.

Avoid treating attendance, completion or a single manager nomination as proof of potential. Those measures may reflect access, workload, confidence or manager visibility rather than capability. Use several evidence sources and document why each one matters.

Signals Worth Tracking

The strongest predictive models use a balanced set of behavioural, learning and operational signals. They also account for opportunity: an employee cannot demonstrate a skill that their role never allows them to practise.

Useful leading indicators include:

Voluntary participation in practice sessions or learning bursts
Improvement between diagnostic and follow-up assessments
Frequency of applying a new skill in real work
Quality of peer support, coaching or knowledge sharing
Speed of responding to feedback and correcting errors

Useful outcome indicators include:

Increased productivity, quality or customer satisfaction
Successful performance in stretch assignments
Greater consistency during process or technology changes
Reduced supervision required after development
Evidence of capability transfer across teams or locations

The aim is to identify patterns over time, not to reward the employee who clicks through content fastest. For example, a FIFO worker in Western Australia may have fewer synchronous learning opportunities than an office-based colleague, yet show stronger application and problem-solving in operational settings.

Read Signals Responsibly

Predictive analytics can reinforce existing workplace inequalities if historical data is treated as objective truth. Employees from smaller regional offices, part-time workers, people with disability or staff returning from parental leave may have different access to learning and visibility. Those differences need to be examined before a score influences succession planning.

Transparency matters. Explain what information is used, how forecasts are generated and how employees can correct inaccurate records. Managers should treat the output as a prompt for a structured conversation, not as an automatic label. The ethical predictive analytics guidance is particularly relevant when models affect development access or career progression.

Governance should include privacy controls, role-based access and regular checks for disparate outcomes. In Australia, organisations should also consider their obligations under privacy requirements, workplace consultation practices and internal policies governing employee data. A forecast should support fair opportunity, not replace human judgement.

Turn Forecasts Into Development Moves

A useful forecast leads to a specific development decision. Employees with strong learning adoption but limited business exposure might receive a cross-functional project. Those with strong results but low confidence could receive coaching, mentoring or guided practice. Employees showing low adoption may need better manager support, clearer relevance or protected time rather than exclusion from future opportunities.

A practical decision framework can look like this:

Predictive pattern	Likely interpretation	Development response
High adoption and high performance impact	Strong readiness for broader responsibility	Stretch assignment or succession pathway
High adoption and low current impact	Skill is developing but barriers remain	Coaching, tools or workflow support
Low adoption and high baseline performance	Existing expertise may mask learning need	Targeted challenge and peer contribution
Low adoption and low impact	Risk of capability gap or access problem	Diagnostic conversation and tailored support

Review forecasts at agreed intervals, such as quarterly, and compare them with actual performance and employee experience. This improves the model while preventing one assessment cycle from defining a person’s career.

To put the approach into practice, select one priority capability, define three observable adoption measures, link them to two business outcomes, and pilot the model with a representative Australian team before using it in broader talent decisions.

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.