Your Chief Virtual Learning Architect

Learning to Performance

Read More
Custom Design & Delivery

Read More
Predictive Evaluation

Read More
Enterprise Learning Strategy

Read More

› ‹

1
2
3
4

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 Predictive Analytics Can Identify Training Redundancies

How to Use Predictive Analytics to Identify Training Redundancies starts with a practical question: which learning activities improve capability, and which simply repeat content employees already know? By combining participation records, assessment results, workplace performance and learner feedback, organisations can find overlap before investing in another course.

For Australian employers, this matters across large cities, regional operations and distributed teams. A workforce may move between classroom workshops in Melbourne, mobile learning on a Sydney commute and compliance modules required across Queensland or Western Australia. Predictive analysis helps learning teams connect those different experiences to measurable business needs.

Approach	What it reveals	Best use
Course catalogue review	Similar titles, topics and learning objectives	Initial screening
Learner feedback	Perceived repetition and low relevance	Experience diagnosis
Performance data	Whether learning changes workplace behaviour	Impact validation
Predictive modelling	Likely adoption, overlap and business value	Investment decisions

Define Redundancy In Business Terms

Training redundancy is more than two courses with similar names. It may involve repeated explanations, duplicate assessments, overlapping compliance content or several programmes teaching the same skill at different levels. A course can also become redundant when the role, technology or regulation it supports has changed.

Begin by defining the outcome that matters. For example, a customer service programme might aim to reduce complaints, while a safety module might target fewer incidents. If two learning products address the same outcome for the same audience, predictive analytics can test whether both are necessary.

Useful indicators include:

Similar learning objectives or assessment questions
High enrolment overlap among the same employees
Repeated low ratings for relevance
Little change in operational performance after completion
Long completion times without stronger capability

Assemble Evidence From The Learning Ecosystem

A useful model combines data from the learning management system with human resources, workforce scheduling, performance dashboards and operational platforms. Relevant variables can include role, location, tenure, previous course completion, assessment scores, manager support and time between learning events.

Data quality needs attention before modelling begins. Duplicate employee records, inconsistent course names and missing completion dates can create false patterns. In Australia, privacy obligations under the Privacy Act 1988 also mean organisations should limit personal data to a legitimate purpose and explain how employee information is being used.

Predictive analytics should support informed decisions rather than label individuals. Aggregate reporting is often sufficient for identifying duplicated content, while access to person-level records should be restricted and governed.

Map Content Against Capability Needs

Create a capability map that links each course to specific behaviours, knowledge areas, job families and business measures. This exposes duplication that a catalogue search may miss. For instance, separate programmes on difficult conversations, performance feedback and frontline leadership may share the same communication practice.

Natural language processing can compare course descriptions, facilitator guides, transcripts and assessment items. Similarity scores are useful screening signals, but subject matter experts must check whether apparently similar content serves a different context or skill level.

A course should be considered for consolidation when its content overlaps substantially, its audience is the same and its distinct contribution is weak. Keeping separate versions may still be justified where a requirement differs by industry, risk profile or work environment.

Predict Adoption And Business Value

Historical data can estimate whether a proposed programme will be used and applied. Models may consider manager reinforcement, delivery format, workload, role relevance and the learner’s previous experience with similar training. This helps identify initiatives likely to attract enrolments but produce limited workplace transfer.

Evaluation should examine more than attendance. Compare predicted and actual completion, confidence, behaviour change and operational outcomes. A short learning burst may outperform a longer course when employees need a targeted reminder, while a complex leadership capability may require practice, coaching and follow-up.

Dave Basarab Consulting’s Predictive Evaluation dashboards provide a practical way to monitor adoption, impact and return on investment as evidence accumulates.

Account For Australian Workforce Conditions

Australian learning portfolios often span office staff in Brisbane, field workers in the Pilbara, healthcare teams in Adelaide and hybrid employees moving between home and shared workplaces. Predictive models should therefore include delivery location, roster patterns, connectivity and access to devices. A module that appears redundant in head-office data may remain essential for a regional team.

Everyday learning habits also affect results. Employees may complete a short module during a train journey, while shift workers need protected time rather than an assumption that learning can happen after hours. Fair Work requirements around working time, consultation and employee conditions should be considered when scheduling mandatory programmes.

Leadership content may need cultural and personality-aware design, especially when organisations expect quieter employees to participate in visible development activities. Resources on introverted leadership can help distinguish genuine capability gaps from delivery methods that favour highly vocal participants.

Decide Whether To Retire, Merge Or Rebuild

The analysis should produce a decision for every overlapping learning asset. Some courses can be retired, while others should be merged into a clearer pathway. A third group may need redesign because the problem is not duplication but weak sequencing, outdated examples or poor transfer to the job.

Use a simple decision logic:

Retire content with low relevance and no unique outcome
Merge modules that teach the same behaviour to the same audience
Sequence courses when foundational and advanced needs are distinct
Refresh examples when legislation, systems or work practices have changed
Retain specialist content where the risk or audience genuinely differs

Custom design should preserve useful evidence rather than reproduce familiar material. A custom training solution can combine existing assets, remove repeated explanations and add practice tied to real Australian workplace scenarios.

Govern The Portfolio As A Living System

Redundancy analysis should become a regular portfolio discipline, not a one-off catalogue clean-up. Review learning assets when new systems are introduced, roles change, legislation is updated or performance data shows that a capability remains weak.

Assign ownership for each programme, define review dates and record the evidence behind retirement or consolidation decisions. A learning council can include people from human resources, operations, compliance, technology and frontline management so that course decisions reflect business reality.

The next step is to export the last 12 months of course completions, objectives, assessment results and performance measures, then flag programmes sharing the same audience and target outcome for expert review.

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.