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We keep making the same mistakes with spreadsheets, despite bad consequences

Accepted submission by Freeman at 2024-01-29 18:34:07 from the peering into the abyss dept.
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https://arstechnica.com/science/2024/01/we-keep-making-the-same-mistakes-with-spreadsheets-despite-bad-consequences/ [arstechnica.com]

Spreadsheet blunders aren’t just frustrating personal inconveniences. They can have serious consequences. And in the last few years alone, there have been a myriad of spreadsheet horror stories.

In August 2023, the Police Service of Northern Ireland apologized [bbc.co.uk] for a data leak of “monumental proportions” when a spreadsheet that contained statistics on the number of officers it had and their rank was shared online in response to a freedom of information request.

There was a second overlooked tab on the spreadsheet that contained the personal details of 10,000 serving police officers.
[...]
In 2021, Crypto.com, an online provider of cryptocurrency, accidentally transferred [theguardian.com] $10.5 million (£8.3 million) instead of $100 into the account of an Australian customer due to an incorrect number being entered on a spreadsheet.

The clerk who processed the refund for the Australian customer had wrongly entered her bank account number in the refund field in a spreadsheet. It was seven months before the mistake was spotted. The recipient attempted to flee to Malaysia but was stopped at an Australian airport carrying a large amount of cash.
[...]
Industry studies show that 90 percent of spreadsheets containing more than 150 rows have at least one major mistake.

This is understandable because spreadsheet errors are easy to make but difficult to spot. My own research [aisnet.org] has shown that inspecting the spreadsheet’s code is the most effective way of debugging them, but this approach still only catches between 60 and 80 percent of all errors.
[...]
Finally, fostering a culture of critical thinking toward spreadsheets is vital. This would mean encouraging users to continually question calculations, validate their data sources, and double-check their work.


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