Predicting Training’s Value

When we predict training’s value, we use a form of business forecasting—estimating what training will deliver in terms of increased organizational and business results. These predictions come in the form of participant Intentions, Adoption in the workplace, resulting Impact on the business, and the costs to deliver the value. These predictions enable decision makers to make highly informed, proactive decisions.

As with any business forecasting method, predicting training’s value has benefits and drawbacks that need to be weighed before proceeding.

The benefits of predicting training’s value include:

  • It aids in decision making (whether a business should move forward with training).
  • It provides input, allowing for smarter, more strategic decisions about planning and resource allocation (people and budgets).
  • If data is high quality, it can create an accurate picture of the future.


Its drawbacks are:

  • Data is not always reliable or accurate.
  • Data may be outdated.
  • Qualitative data may be influenced by peer pressure.
  • External factors may be out of the business’s control (e.g., economic policy, competition, and political developments).

  
The Impact Matrix - the Output of Predicting Training's Value

The Impact Matrix is a rectangular array of Intention goals & beliefs, Adoptive behavior examples, business results, and external contribution factors that, when combined using certain rules, predict the Impact from training. It’s usually created by a Steering Committee of subject matter experts and key decision makers, drawing a direct link from training to business impact.  Watch the What is Predictive Evaluation? archived webinar on how the Impact Matrix is created and used.

Sample Impact Matrix for a Business Acumen Training Course

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ROI of Training

Predictive Evaluation

Success Stories

What's distinctive and noteworthy about Predictive Evaluation is that it does take training evaluation to the "next level" that even Donald and James Kirkpatrick acknowledge in the Foreword of the book. For example, it adds the element of prediction and how to determine and make future training and evaluation investments. PE moves training evaluation from "activity based measures" to "value driven continuous improvement efforts" that ensure training investments provide their predicted value. It also involves training participants rather than leaving the training and evaluation planning to training and business leaders.

I particularly like how Dave strives to run training and evaluation like any other business function, and adhere to sound business practices. Training in PE, for example collects evaluation data to judge progress toward meeting business objectives and plans, and predicts (forecasts) training's contribution to those objectives and plans. Data is collected early and often according to defined success goals, and corrections are made at any point to improve or strengthen training.

Randy Bennet EdD.