Excel Mistake Leads to Thousands of Unrecorded COVID-19 Cases

The accounting world knows how detrimental an Excel mistake can be – but it was never life-threatening.  Enter 2020 and welcome to a world where an Excel mistake led to the wrong reporting of 16,000 new cases of COVID-19.

Excel Mistake Leads to Thousands of Unrecorded COVID-19 Cases

Yes, you read that correctly. The United Kingdom has admitted to the misreporting of thousands of positive Corona Virus carriers. Adding insult to injury, those in contact with positive carriers were not informed, leaving approximately 50,000 people unknowingly exposed.  

So how did such a large mistake occur? Well, the labs conducting COVID-19 tests exported their findings using CSV files. Public Health England (PHE) imported these limitless CSV files into Excel, which has a row and a column cap – and the labs’ files evidently exceeded these. 

The extraordinary meltdown was caused by an Excel spreadsheet containing lab results reaching its maximum size, and failing to update. Some 15,841 cases between September 25 and October 2 were not uploaded to the government dashboard.

The problems are believed to have arisen when labs sent in their results using CSV files, which have no limits on size. But PHE then imported the results into Excel, where documents have a limit of just over a million lines.

The technical issue has now been resolved by splitting the Excel files into batches.

Source: The Daily Mail

Now a blame game is occurring trying to get to the bottom of this potentially fatal fiasco – but the results of this particular blunder are not a game, many citizens are now at risk. 

Excel Mistake Leads to Thousands of Unrecorded COVID-19 Cases

This is not the first time an Excel issue has led to large consequences but, regardless of the proof being in the British pudding, companies are still hesitant to take the necessary steps ensuring mistakes such as this won’t happen again. 

In finance, the importance of data accuracy and where the origin of error occurred, is a time tested phenomenon. Finance professionals face these issues religiously and yet the majority of which still rely on their seemingly reliable Excel spreadsheets. Now, what if it was possible to avoid these fatal gaffes without needing to adapt to something entirely new?

What if there was a software that allowed you to upload CSV and Excel files into a database – ridding the issue of Excel limitations, as the database has none. What if it allowed you to see everything with a clear dashboard, a dashboard that follows trends, so a large portion of data missing is instantly red-flagged? What if version comparisons and their mismatches were automatically revealed? How about a data-basing submission platform that would have avoided this fiasco in its entirety? 

Using Excel on its own is irresponsible, but what if the PHE had used a financial analytics platform like DataRails? They probably wouldn’t have been in the headlines this morning, to say the least. PHE has already admitted they will continue using Excel but will merely ‘split the files into batches.’ So have they learned their lesson? Or just come across the DataRails’ website? 

DataRails was created as a Financial Analytics Platform to rid professionals of the limitations within Excel spreadsheets by providing a unified, smart interface that consolidates and analyzes imported data. Their platform allows professionals to derive actionable insights by doing all the aforementioned and more – guaranteeing an inaccuracy, such as the one plaguing the United Kingdom, never occurs. 

Many people are at risk, many could get very sick and for some this mistake may be fatal – but a simple-to-use dashboard that works with an institution’s current processes would have made a world of difference, literally.  You’ve heard this before, and now you’re hearing it again – it’s time for a change. Contact DataRails and learn more about how to catapult your operations into the future and avoid a catastrophic event occurring within your business now, and in the years to come.