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The Human Capital Return On Investment

A paper from Global Learning Alliance and Knowledge Advisors

Part 11 - Best Practices, Concluding Thoughts

Remember, when compiling an approach for ROI in learning, keep these best practices concluding thoughts top of mind:

Best Practice #1: Plan your metrics before writing survey questions.

First and foremost, never ask a question on a data collection instrument unless it ties to a metric you will utilize. As simple as this sounds, often is the case where organizations create questions with no purpose in mind.

Best Practice #2: Ensure the measurement process is replicable and scaleable.

Organizations tend to spend thousands of dollars on one-off projects to measure a training program in detail. This information is collected over many months with exhaustive use of consultants and internal resources. Although the data is powerful and compelling, management often comes back with a response such as 'great work, now do the same thing for all the training.' Unfortunately such one-off measurement projects are rarely replicable on a large-scale basis. So don't box yourself into that corner.

Best Practice #3: Ensure measurements are internally and externally comparable.

Related to best practice #2 is the concept of comparability. It is a significantly less powerful endeavor to do a one-off exercise when you have no base line of comparability. If you spend several months calculating out a 300% ROI on your latest program how do you know if that is good or bad? Surely a 300% ROI is a positive return but what if the average ROI on training programs is 1000%?

Best Practice #4: Use industry-accepted measurement approaches.

Management is looking to the training group to lead the way in training measurement. It is the job of the training group to convince management that their approach to measurement is reasonable. This is not unlike a finance department that must convince management of the way it values assets. In both cases, the group must ensure the approach is based on industry accepted principles that have proof of concept externally and merit internally.

Best Practice #5: Define value in the eyes of your stakeholders.

If you ask people what they mean by 'return on investment' you are likely to get more than one answer. In fact, odds are you'll get several. Return on investment is in the eyes of the beholder. To some it could mean a quantitative number and to others it could be a warm and fuzzy feeling.

Best Practice #6: Manage the change associated with measurement.

As you can likely see from some of the best practices, they might be doomed for failure if you fail to manage the change with your stakeholders. Successful organizations will spend considerable time and energy planning for the change. Assess the culture and the readiness for change. Plan for change or plan to fail.

Best Practice #7: Ensure the metrics are well balanced.

Although you want to understand the needs of your stakeholders and have them define how they perceive value, you also need to be proactive in ensuring that your final 'measurement scorecard' is well balanced.

Best Practice #8: Leverage automation and technology.

Although this goes hand and hand with a measurement process that is replicable and scaleable it is worthy of separate mention. Your measurement process must leverage technology and automation to do the heavy lifting in areas such as data collection, data storage, data processing and data reporting.

Best Practice #9: Crawl, walk, run.

When designing a learning measurement strategy it is nice to have a long term vision, but don't attempt to put your entire vision in place right out of the blocks. The best approach is to start with the low hanging fruit that c an be done in a reasonable time frame to prove the concept, demonstrate a 'win' and build a jumping off point to advance it to the next level.

Best Practice #10: Ensure your metrics have flexibility.

The last thing you want to do is rollout a measurement process that is inflexible. You will likely have people who want to view the same data but in many different ways. You need to have architected your database to accommodate this important issue thereby creating measurement flexibility.

Reference Sources

Donald L. Kirkpatrick, Evaluating Training Programs: The Four Levels, 2nd Edition, Berrett-Koehler Publishers, Inc, San Francisco

Jack J. Phillips, Return on Investment in Training and Performance Improvement Programs , Gulf Publishing, Houston, Texas

Barney, M, Measuring ROI in Corporate Universities, Death of Student Day and Birth of Human Capital

Interview with TVA University, Lane Fitzgerald

Part 10 < Back to Top   

© 2004 Global Learning Alliance and Knowledge Advisors. Reproduced with permission. Any opinions or views contained in this article are solely those of the author and do not necessarily represent those of Training Reference.

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