Why Quality Matters: The 10 Biggest Data Quality Disasters
In the age of data-driven decision-making, businesses and institutions rely heavily on big data and digital technologies to make informed choices, optimize processes, and gain competitive advantages. But what happens when things go wrong? When the data we count on is incomplete, outdated, and just plain wrong? Data disasters can be unimaginably costly—and they happen more often than you may think. Here, we delve into some of history's most expensive data quality disasters, spanning from simple address mix-ups to billion-dollar catastrophes.
1. Wrong house demolition
Ever tried to drive somewhere only to find out it wasn’t where Google Maps said it was? Annoying, but not the worst thing that can arise from outdated or incorrect GIS data. In numerous instances, demolition crews have arrived at the wrong job site due to inaccurate address data in Google Maps and torn down the wrong house. This led to devastated homeowners, tens of thousands of dollars in property damage, and uphill legal battles for the demolition companies.
2. Zoll Medical defibrillators
Due to data quality issues in their manufacturing process, Zoll Medical’s defibrillators were found to potentially display error messages and even fail during use. The company had to issue a Class 1 recall—the most serious type of recall for situations in which there is a reasonable probability that use of these products will cause serious injury or death. The recall led to a loss of trust and $5.4 million in fines.
3. UK Passport Agency
In 1999, the UK Passport Agency faced severe delays in issuing around 500,000 passports due to data migration errors during a system upgrade. The delays led to public outrage and a massive backlog of passport applications. Addressing the data migration failures and hiring additional staff to handle the mountain of applications waiting to be processed cost the Agency an estimated £12.6 million.
4. Mars Climate Orbiter
The Mars Climate Orbiter was a probe launched to collect data on Mars. Unfortunately, the craft burned up as it entered the planet’s atmosphere, making the mission a total loss and setting back Mars exploration efforts. The reason behind the $327.6-million failure? A unit conversion error between the engineering teams, with one team using metric units and the other using imperial.
5. Knight Capital trading error
In 2012, a flaw in Knight Capital’s new software led to unintended stock trades, with the company purchasing 150 different stocks for $7 billion in just an hour. The consequences of using this untested software included a $440-million loss and bankruptcy.
6. Amazon's AWS outage
During routine AWS maintenance, a typo in a command instead took down a large portion of the internet because the error removed more servers than intended. It took three hours to restore part of the system, and four hours before everything was up and running once again. Companies relying on AWS faced major unplanned downtime, leading to significant financial losses of an estimated $150 million.
7. Hubble space telescope
In 1990, the Hubble's primary mirror was affected by a tiny measurement error; its shape was off by less than 1/50th the thickness of a human hair. The discrepancy was enough to render all images blurry and the telescope effectively useless. To correct the issue, a “contact lens” had to be manufactured and installed—costing $50 million on top of the $2.1 billion the telescope had already cost to develop.
8. Spanish submarine "Isaac Peral" (S-81)
During the submarine’s design, a decimal point error in the displacement calculation resulted in the vessel being 75-100 tons overweight. The magnitude of the error meant that the submarine was too heavy to float and had to be completely redesigned, causing extensive delays and costing over €2 billion.
9. Boeing 737 Max crashes
In 2018 and 2019, two Boeing 737 Max aircrafts fatally crashed, killing 349 people. The aircrafts featured a new automated fight control system, which relied on data from a single angle-of-attack sensor. That faulty sensor data triggered the system and overrode pilot controls, leading to the crashes. All 737 Max planes were then grounded, and Boeing lost over $18 billion.
10. Lehman Brothers
In 2008, poor data quality and risk assessment led Lehman Brothers to take on more risk than it could handle, and the lack of accurate data masked the real value of assets and liabilities. We all know what happened next: $691 billion assets lost and bankruptcy that triggered a global financial crisis affecting economies worldwide.
From simple human errors to complex technological failures, we’ve seen how improper data handling can result in catastrophic outcomes. Each of these costly data errors shows us just how important data accuracy is to safeguarding human life, consumer peace of mind, company profits, and reputations. As we further delve into the digital age, it's vital to prioritize data quality and management to safeguard ourselves from making history for all the wrong reasons. Treat these historical data disasters as lessons about the importance of meticulous data handling and high-quality control measures.
