Monday Buzz…

Monday Buzz...I’ve been in the profession of Training/Learning/Knowledge Management for corporations – since the late 1970’s.


I never heard the claim that Formal Training was intended to cover 100% of every job. And that we should stop that madness and aim for something more reasonable, like 10%.

I knew that only the most critical of jobs would need that level of coverage.

I knew that most training was intended to simply get someone started on the performance curve – back on the job – where the real learning occurs.

I knew that all Learning starts as Informal … not Formal. And that the situation, the Performance Context, should dictate the need for some sort of Performance Support, including possible Information & Instruction. Not just because you could, should you invest any time and money in formalizing Learning. However…

I knew that incorrect learning – unfortunately – too often results from learners/Performers being left to their own … in sink or swim learning situations … when it’s all Informal Learning.

I knew that Formal Training is an attempt to avoid learning bad habits based on myths and superstitions – where poor performance is too risky and/or the rewards you might forgo are too big to let that happen.

I knew that Formal Training is only good if it teaches one to do the job with authentic training/learning experiences – especially where the job tasks and context are tricky. That might require interactive content. Otherwise, a static but up-to-date PDF might do.

And … I knew that if the Learning is for the Operators of the local nuclear facilities – I am pretty sure that their situation would require something almost the exact opposite from 70-20-10. Or close to it.

Same with Passenger Jet Pilots and Mechanics. Theirs might be closer to the opposite than what 70-20-10 suggests or prescribes.

I know that any Performance Context with extremely high Risks and/or Rewards may require something much different than 70-20-10. Maybe exactly the opposite.

I know that that’s the problem with over-generalizations: One size does not fit all.

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