2 Comments

  1. Excellent observations, which get back to the question “Why should a company engage in learning and development?” We founded Zoomi to address the same question. From our own previous corporate L&D experiences, and having spoken to dozens of L&D executives across the globe and in myriad industries, the author’s realizations ring true — unless you know the operational metric that the learning intervention is intended to address, you need to go back to the drawing board.
    There are ample systems in place to measure these metrics, and the effect upon them of learning intervention. The problem then becomes one of confounding factors. Did sales improve due to economic factors, rather than the intervention? Is it a coincidence that customer satisfaction improved? Although the metric was flat, can we still see some impact of the intervention?
    Because these variables have a multitude of inputs which can affect them, the challenge is one of analytics. Designing proper experimental conditions and gathering as much data as possible on the factors that may confound our results is key. Using analytics to filter the set of factors down to the ones that are really impacting outcomes, so that organizations can focus on what will drive success.

  2. Excellent observations, which get back to the question “Why should a company engage in learning and development?” We founded Zoomi to address the same question. From our own previous corporate L&D experiences, and having spoken to dozens of L&D executives across the globe and in myriad industries, the author’s realizations ring true — unless you know the operational metric that the learning intervention is intended to address, you need to go back to the drawing board.
    There are ample systems in place to measure these metrics, and the effect upon them of learning intervention. The problem then becomes one of confounding factors. Did sales improve due to economic factors, rather than the intervention? Is it a coincidence that customer satisfaction improved? Although the metric was flat, can we still see some impact of the intervention?
    Because these variables have a multitude of inputs which can affect them, the challenge is one of analytics. Designing proper experimental conditions and gathering as much data as possible on the factors that may confound our results is key. Using analytics to filter the set of factors down to the ones that are really impacting outcomes, so that organizations can focus on what will drive success.


Add a Comment

Your email address will not be published. Required fields are marked *

Comment *
Name *
Email *
Website