It’s no secret that the First World War had almost unimaginable casualty rates amongst both combatants and civilians.
This was mainly due to major advances in weapon technology, especially artillery.
Science had got much better at killing people.
However in 1914, at the beginning of the war, not one army equipped its infantry with steel helmets.
Soldiers stood in trenches wearing cloth or leather caps to cover their heads from exploding shells.
The British War Office were concerned by the high level of head injuries being recorded.
Finally, in 1915, they commissioned a design for a steel infantry helmet .
The now familiar round ‘Brodie helmet’ made an immediate impact on head injury figures.
They went up considerably.
By a factor of 5.
British commanders were horrified and some considered a return to ‘safer’ cloth caps.
The data was clear.
The metal Brodie helmet was causing more soldiers to suffer head injuries.
Except of course it wasn’t.
The problem was with the way the data was recorded and interpreted.
What the data showed was head injuries not fatalities.
Before the Brodie helmet, most head injuries resulted in death.
Deaths were recorded as a separate category.
Those who were lucky enough to survive, were recorded as head injuries.
With the Brodie helmet the survival rates soared and therefore so did the head injury figures.
Fortunately, the true reason for the increase was realised and the helmet remained in service for many years.
It’s all too easy to rely on data to inform strategy.
But unless you look beyond the data, you’re not getting the full story.
On it’s own, data is simply raw indication seeking context.
Correlation is not the same as causality.
Context is everything.
Don’t let dumb data drive decisions.