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Design an Evaluation Plan to Measure End Results and Your Return on Investment

We’ve already discussed selecting an intervention strategy to reduce the performance gap between the needed performance to bring the desired end results and the actual workplace performance. Now we will discuss designing an evaluation measurement strategy so that you know when the desired performance has been met. This section briefly discusses scientific methods to evaluate the results of the intervention and to measure the ROI. Let’s start with a brief review of the origins of measuring the ROI for performance interventions.

In the beginning, intervention evaluation was most prominent in the training classroom when evaluation was desired. Unfortunately, most training evaluation encompassed and still encompasses what performance professionals call “smiley face evaluation.” This is a brief questionnaire at the end of the training session that asks the participants if they liked the course, if they liked the facility, if they liked the instructor, and if the coffee and donuts were good. In other words, did they have fun, and do they want to do it again? From a measurement perspective, such a questionnaire tells us if we have workers who like to take time away from their jobs and sit in a classroom enjoying the presentation, facility, coffee, and donuts. What we do not know is if the training intervention had a positive impact on the desired end results.

Interest is growing in results-based performance improvement interventions that are linked to the organization’s strategic plan. This is visible through the interest in going beyond the traditional four steps for evaluating training programs (assessing the reaction, learning, behavior, and results) and calculating the ROI for training (Kirkpatrick, 2006; Phillips, 1997, 2011). See Figure 1.6.

Figure 1.6

Figure 1.6. Evaluating and measuring training

We argue that an ROI strategy should always be employed before the design, development, and deployment of a performance intervention. Doing so ensures that the best intervention was selected and that the intervention is designed to bring the desired end results. Indeed, as Covey (2004) maintained that you should always begin with the end in mind, we too have always considered the desired end result before initiating any performance intervention. So to begin with the end in mind, we will walk through our five-step ROI process (see Figure 1.7).

Figure 1.7

Figure 1.7. Five-step ROI process

Our ROI model involves five basic steps that seem simple yet are often complex. The following list discusses the steps and how to overcome barriers to conducting an ROI process:

  1. Collect, evaluate, and isolate tangible and intangible data concerning the effects of a performance intervention.
  2. Convert the isolated effects of a performance intervention into a monetary value.
  3. Calculate the total cost of a performance intervention.
  4. Calculate the net benefit of a performance intervention by subtracting the total performance intervention costs from the total performance intervention benefits.
  5. Calculate the ROI by dividing the net performance intervention benefits from step 4 by the training program costs from step 3 and then multiplying the product by 100.

Figure 1.8 mathematically depicts the ROI process. We take the monetary value of the effects of performance intervention and subtract the cost of performance intervention to get the net benefit of performance intervention. Then we divide the net benefit of performance intervention by the total cost of performance intervention to calculate the ROI. Because we are used to looking at the ROI in percentages, we multiply the ROI by 100 to calculate the return-on-investment percentage, which we call ROI %.

Figure 1.8

Figure 1.8. ROI model

The literature provides numerous case studies and detailed descriptions of the ROI process for determining the effectiveness of a performance intervention. As you can see from our model, the math and five-step ROI process appear linear and simple. However, sometimes distinct peculiarities hinder an organization’s data collection for an ROI process. To overcome these barriers to data collection, we employ the scientific method of hypothetical-deductive reasoning to evaluate the effectiveness of the intervention. Appendix A provides more details on the methods we use to determine the program costs and to measure the effects of the performance intervention that may be used by organizations with similar issues. After we have a strategy in place to measure the desired end results, we can design, develop, and deploy the performance intervention.

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