N=1
In case you missed it so far, the Global War on Error is a new way of looking at a very old problem – the disease of human error and its Grim Reaper’s toll.
For the past four decades, the cure for the disease of human error has been approached indirectly (if at all) in most of the industrialized world through a variety of efforts that can broadly lumped into the following five categories:
- Blame and punish the individual
- Emphasize leadership (then blame and punish the leader for failures that occur under his or her command)
- Teamwork strategies to capture or contain errors through better communication
- Systemic approaches that put multiple layers of protection in place to avoid or respond to errors, and most recently
- Cultural approaches that focus on social factors such as trust and fairness to create a so called “just culture.”
To some extent all approaches have been effective in the short run, many are still useful, but even in a combination have only been marginally effective in addressing the challenge of human error. Experts cite the randomness and wide variability of human error present even in relatively small groups, as the reason for these meager results. These are compelling arguments made by bright and well meaning people. Every year, millions of dollars are expended to provide education and training on these subjects – and every year we look at the statistics and continue to see less than desireable results. Some small successes are reported, but on the whole, human error remains culpable for nearly 80% of failures in high risk, high reward industries.
Human performance experts continue to struggle to find a broad spectrum antibiotic to cure the human error disease. If we extend this metaphor another step, we can shed some light on why it is not working. Human error is not an infection that can be fought with a broad spectrum antibiotic – it is more like a virus that the immune system must handle from within. Although the antibiotics can help, when you’re fighting a mutating virus, every battle is an inside job, won or lost at the individual level. As we continue to search for a more effective remedy against human error – the sample size – or “N” – must eventually equal 1.


