Most times, bad data causes confusion at best, or consequences in our immediate lives at worst. Incorrect values, wrong dates, bad inferences, and countless other examples impact people and businesses every day.
However, every so often, bad data does much more than create a mundane problem. When bad data becomes the focal point in an event with global ramifications, the course of world history can change.
Here are 8 jaw-dropping ways bad data changed world history.
China’s Disrupted Search for Rome (97 AD)
In 97 AD, Chinese military ambassador Gan Ying was sent on an expedition by Chinese general Ban Chao to travel to the Roman Empire. But Gan Ying never reached Rome. He travelled as far as modern day Iran, and asked local merchants how long it took to cross the Black Sea to Rome. Wanting to preserve their trading monopolies, the merchants provided Ying with bad data, saying the trip could take up to 2 years. This was too long a wait, so Ying turned back, and China never connected with the Roman Empire.
The Invasion of England (1066 AD)
Harald Sigurdsson, King of Norway, invaded England in 1066. After initial blistering victories, Harald’s army decamped in the defeated town of Fulford. Harald’s reconnaissance team concluded that English troops were nowhere near the town. The team passed this bad data onto Harald, who ordered his men to remove their armor and rest. Then English troops surprised the vulnerable invaders, routed the army, and killed Harald in battle, forcing Norway’s retreat from England.
Trans-Atlantic Voyage of Christopher Columbus (1492)
In 1492, Christopher Columbus sailed across the Atlantic Ocean to find an alternative route to Asia. But Columbus relied on the inferior calculation of Alfranagus, a Persian geographer, to chart his route. Furthermore, Columbus either forgot or did not realize that he had to convert the Arabic miles used by Alfranagus into Roman miles. This bad data caused Columbus and his crew to land in the Americas, rather than in Asia.
Miasma Theory of Disease (100 BC – 1900 AD)
For centuries, miasma theory held that diseases were transmitted by poisonous vapors or mists that contained decomposed matter, rather than by microbes. The theory was used to treat all of Europe’s major plagues. Miasma theory called for medical treatments that eliminated poor smells and bad hygiene. Since scientists had no instruments for measuring real success, they interpreted mild improvements amongst patients as confirmatory data for the theory. Miasma theory, and all the bad data associated with it, blocked physicians from properly treating patients all the way into the 20th century.
V-2 Missile Misinformation (1944)
During World War II, the Germans created the first long-range guided ballistic missile, known as the V-2. The V-2 allowed the Germans to hit Allied targets accurately and rapidly over very long distances. However, a misinformation campaign led by British double agents convinced the Germans that the missiles were off by 10 – 20 miles. The Germans adjusted the missiles based on this bad data, and ended up mostly hitting the sparse areas outside of London.
Revelations of the Pentagon Papers (1971)
By 1971, resistance to America’s war in Vietnam was growing quickly. But there was still a large portion of the country that supported the effort. When the Pentagon Papers were leaked to the New York Times, it became clear that most of the data the US government released about the conflict was false. Without this smokescreen of bad data, support for the war plunged across the American public.
Mars Climate Orbiter (1999)
The Mars Climate Orbiter was a NASA space probe launched in 1998 to study the Martian climate. The probe was expected to generate major breakthroughs, and the scientific community across the world was eagerly awaiting the results. But the Orbiter never performed a single test. The probe flew off track and disintegrated in the atmosphere of Mars because its software was not converting data to the metric system. The bad data may have been a 6th grade science problem, but it led to a $193 million dollar mistake.
2008 World Financial Meltdown (2008)
As one of the worst financial crises in history, the 2008 crash was fueled by bad data that overstated how much mortgage-backed securities, collateralized debt obligations, and other derivatives were actually worth. When the subprime mortgages that formed these derivatives defaulted, and their true value became apparent, key financial institutions such as Lehman Brothers went bankrupt. The collapse led to widespread evictions, foreclosures, and job losses across the world.
Maybe That’s Why Data Quality is So Important?
Not every instance of bad data is going to generate a world altering event. But it is interesting to reflect on how the data we use every day could ever become so randomly consequential. Most of us will never discover a country, or win a war, but we can certainly try our best to make sure that the data we handle and produce is of a high quality.