How Predictive Evaluation Differs From Other Approaches
The Predictive Evaluation Model is a practical step-by-step process that begins where most other evaluation methods stop. It’s unique because it:
- Adds the element of prediction to evaluation training, and is the first training evaluation model to do so.
- Requires student participation, making employees feel invested and engaged throughout the process.
- Can be used with existing or new courses and works equally well with classroom-based training, on-the-job training, on-line learning, workshops, etc.
- Is appropriate for content across all industries and departments.
- Is suitable for staff at all levels.
- Provides recommendations for continuous improvement.
- Predicts the quantifiable impact of training to forecast training investments, results and ROI.
Following outlines how Predictive Evaluation compares to traditional approaches
Typical Approach
Focus on costs and numbers, not on forecasting financial return.
Training groups rarely predict the value-add of their training to the company before the training is undertaken. At best, they provide information about costs, who and how many will be trained, and the training schedule. As a result, management views training in cost and activity terms, not in terms of its financial value to the organization.
Evaluation is after-the-fact with no measures of success.
Most training functions rely on the “Levels” approach. Although most do an end-of-course evaluation (“Happy Sheet”), relatively few evaluate transfer or impact on business results. Those that do, perform evaluation at the completion of training, thus leaving little or no opportunity to improve the results.
ROI and/or Cost-Benefit evaluation. ROI evaluation, when it is attempted by trainers, often over-relies on subjective estimates of the percentage of return.
An ROI figure has little value for making decisions about the program. Cost-benefit evaluation requires significant use of statistics to provide useful data. Both types of evaluation are conducted well after training has concluded and do not provide data that can be used to improve the program in real time.
Existing approaches work after-the-fact with one-off programs.
Data are not collected until program completion, allowing no opportunity for mid-course correction or feedback.
Predictive Evaluation
Focuses on the predicted impact and its value-add to the organization.
Integrated with instruction design activities, PE enables the training function to forecast (predict) the quantifiable impact of training. This allows management to judge potential training investments in terms of predicted business results and value returned.
Employs repeated measures that mirror employees path to improved performance with predicted Success Gates.
PE provides management with high-value training data, including (1) predictions of success in the three areas of Intention, Adoption, and Impact; (2) leading indicators of future adoption (transfer of learning); (3) business dashboards showing Impact (return on investment in the form of business results); and (4) recommendations for continuous improvement while training is being delivered.
Provides concrete, business-focused and evidence-based data on return on investment.
Data collection is robust and rigorous, and management finds the data far more compelling, convincing, and useful.
Works well with programs that have repeated deliveries over time.
PE offers a carefully determined prediction of the extent of transfer and impact. PE identifies the expected outcomes, assesses progress against those at regular intervals during the delivery time frame, and provides feedback that can be used to make changes, mid-course corrections, etc., both in relation to the program and to the application environment.
In the case of a one-off program, PE is similar to other approaches - data are not collected until program completion, allowing no opportunity for mid-course correction or feedback.