Why Is Bad Data Dangerous? Why Does Bad Data Lead to Bad Outcomes: Real-Life Example

In this video, Christian Briggs explains why bad data is dangerous through a compelling example of a hiking trip in the Grand Canyon. In October 2000, six employees of an interactive agency embarked on a three-day hike with reliable maps, gear, and teamwork. However, one piece of bad data almost led to a disaster. Despite checking the daily weather and water report that indicated plenty of water, the team faced record high temperatures and dryness. As a result, the water sources they relied on began to dry up.
By the end of the third day, with only one liter of water left between them, the team had to make a grueling 3,000 ft vertical climb back to the canyon rim. Two members managed to crawl to the top that night, two more arrived by morning, and the last two had to be helicoptered out due to severe dehydration. Fortunately, everyone recovered once they had food and water. This incident underscores the critical importance of accurate data and thorough research. This example vividly illustrates how bad data can lead to bad outcomes and potentially ruin an entire experience. In the context of journey mapping in UX design, accurate data is equally crucial. Bad data can misinform decisions, leading to poor design choices and a flawed user experience. Understanding why data is important, why research is important, and how bad data can lead to bad outcomes is essential for successful journey mapping.
Explore why data analysis is important and how ensuring good data can prevent dangerous situations and enhance user experience design. Learn from the Interaction Design Foundation (IxDF) about the importance of data research and journey mapping in UX design.
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