Broad Oak: your emotional support animal

Saturday, September 28, 2013

Errors in the field

Some years ago I investigated errors generated by people collecting environmental data while out in the field. In those days we had computers and databases back at the lab, but field data was collected manually.

I’d written a range of error-trapping routines to pick up errors during data input at the lab so all I had to do was link errors to people. The survey included several hundred field workers and hundreds of thousands of items of data. These were not major errors by the way, but they had to be corrected.

Findings
I suppose I was most surprised at how many errors were being made and how consistent each person’s error rates were.

Firstly, line managers working in the field to keep their hand in. They tended to generate more errors than anyone else. Many should have been locked in their offices and never allowed into the field under any circumstances.

Secondly, there were a few people who were extremely meticulous, making a very small number of errors day in day out, but there were not many like that – maybe five or six at most.

Thirdly, there were people at the other end of the spectrum who routinely made a large number of errors.

So – not particularly surprising really, but what did strike me was the difference between the best and the worst. The worst field workers regularly made at least twenty times as many errors as the best.

Yet that did not mean that the worst couldn’t care less about the work – far from it as far as I could see. People doing environmental field work tend to be interested and conscientious.

I don’t know what became of the survey in the longer term, because I moved on. My reports were greeted with surprise and not a great deal of enthusiasm, but I always remember just how consistent people are when it comes to making mistakes in largely routine work.

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2 comments:

Sackerson said...

Knowing the error rate, would you have been able to correct for it?

A K Haart said...

Sackers - not usually. Some of it was simply missing data but where data was obviously wrong we had to go back to the field worker.

What we couldn't detect at all was data which was wrong but plausible.