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

Estimating training payback periods with predictive evaluation

Learning leaders across Sydney, Melbourne, and Brisbane routinely face the same budget question: when does a training program begin paying for itself? Traditional ROI calculations only tell you what already happened, leaving executive sponsors to guess about future returns.

Predictive Evaluation fills that gap. The methodology forecasts adoption, behaviour change, and business impact before the first learning session is delivered, allowing organisations to project a payback window with measurable confidence. It uses historical benchmarks, organisational baselines, and adoption proxies to model likely outcomes rather than waiting a year to measure them.

For Australian enterprises navigating Fair Work Act obligations, persistent ANZSCO skill shortages, and the realities of a federated training market, this forward-looking method turns learning investment from a leap of faith into a defensible line item.

What predictive evaluation measures before launch

The methodology tracks four interconnected dimensions before any program rolls out. Adoption forecasting estimates how many learners will apply the new skills on the job, how quickly, and how often. Performance lift projects the behavioural change expected across the cohort. Business contribution translates that lift into measurable outcomes such as reduced rework or faster onboarding. Confidence intervals wrap around every estimate, giving decision-makers a clear sense of how much margin to apply when the numbers reach the boardroom.

These dimensions let a learning leader walk into a steering committee meeting with a projected payback range rather than a hopeful guess. The shift from retrospective reporting to prospective modelling is what separates Predictive Evaluation from older evaluation frameworks.

Comparing traditional and predictive payback approaches

Method	Timing	Data inputs	Confidence profile
Traditional post-program ROI	After delivery	Actual financial and performance data	High retrospective accuracy, no foresight
Predictive Evaluation	Before delivery	Adoption proxies, historical benchmarks, business baselines	Forecasted with explicit confidence intervals
Hybrid Phillips model	Mixed	Combines both approaches	Strong on impact, weaker on adoption timing
Vendor-provided estimates	Pre-contract	Mostly anecdotal or aspirational	Lowest reliability, often optimistic

Traditional ROI tells a clean story once a program is finished, but offers no guidance while contracts are still being negotiated. The hybrid Phillips model blends forecast and actual data, which works well for mature learning functions with rich archives. Vendor-provided estimates, often produced during sales conversations, rarely survive contact with finance scrutiny.

Side-by-side, the comparison shows why more organisations are shifting to Predictive Evaluation as their default planning instrument.

The payback equation step by step

The arithmetic behind a forecasted payback period is straightforward. Divide the fully loaded program cost by the projected annual financial benefit to arrive at the number of years required to break even. The methodology supplies the inputs that make this equation credible before the program runs.

Start with program cost, including design, delivery, platform licences, and participant time. Then model annual benefit using three levers: the proportion of learners expected to adopt new behaviours, the average performance lift per adopter, and the monetary value of that lift in operational terms. Apply a confidence discount to reflect uncertainty, and the resulting range becomes the forecasted payback window. A leadership program costing AUD 350,000 that projects AUD 140,000 in annual benefit points toward a payback period of roughly two and a half years before adjustments.

Aligning the model with Australian workforce realities

A forecast built from overseas benchmarks rarely holds up under local scrutiny. The country's skills shortage in trades, healthcare, and digital roles means capability gains often show up faster than in markets with deeper talent pools. Apprenticeship completions in regional centres like Newcastle or Geelong can lift productivity within months, while metro programs in financial services may take longer to surface measurable results.

The Fair Work Act and modern award structures influence how quickly productivity gains convert into payroll savings, and the Australian Skills Quality Authority's expectations shape what counts as evidence of competency. Pairing Predictive Evaluation with enterprise learning strategy work ensures forecasts account for these local conditions rather than borrowing assumptions from generic global models.

Forecasts earn trust when they reach decision-makers in language they recognise. The strongest business cases convert the projected payback range into a short narrative covering what will change, by when, and how the organisation will know. Pairing the forecast with leading indicators such as a 30-day adoption rate gives executives a way to track whether reality is tracking the model. Listing the organisations Dave has supported reassures sponsors that the methodology has been tested across industries rather than improvised for a single pitch.

Recommendations for applying predictive evaluation

Applying Predictive Evaluation well requires a few disciplined habits. The practices below consistently produce reliable forecasts and credible payback periods across Australian organisations.

Start with a clear, single business outcome that the program is meant to influence, and trace every forecast back to it.
Use Australian industry benchmarks where available rather than importing assumptions from overseas studies.
Build adoption estimates from observable proxies such as manager check-ins or system usage.
Apply a confidence discount of 15 to 25 percent to reflect slippage between training and on-the-job transfer.
Revisit the forecast at 30, 90, and 180 days post-launch to compare projected payback against emerging evidence.
Document the assumptions openly so finance partners can stress-test the model alongside you.

These habits are most powerful when written down, reviewed at each steering committee meeting, and updated as new evidence emerges.

A forecasted payback period earns its keep only when it travels with the program, not when it sits in a forgotten business case. Learning leaders who combine disciplined forecasting with local context, credible benchmarks, and ongoing review will consistently produce payback projections that survive boardroom scrutiny and outperform the underlying reality of the rollout.

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.