Describe a decision you have made in the past that you later understood was influenced by bad data. If you cannot recall such a decision, then look for an example of a public official who has done so.
What was the result of the decision informed by bad data?
What were the reasons bad data was used to make the decision?
How might good data have been obtained to make a better data-driven decision?
Full Answer Section
The Result:
The bridge collapsed less than four months after opening, due to a combination of factors, including the unpredictable nature of the wind and the bridge's unique design that amplified these forces. The collapse was a major engineering disaster, costing the state millions of dollars and creating a tragic loss of public confidence.
Reasons for Bad Data:
- Incomplete Data:The wind tunnel tests were conducted with a scaled-down model, and the data collected did not adequately reflect the real-world conditions of the bridge's location.
- Limited Understanding:At the time, there was limited understanding of the aerodynamic forces that could impact a long, narrow suspension bridge like the Tacoma Narrows.
- Overconfidence:The engineers involved in the project may have been overconfident in the accuracy of the wind tunnel tests, failing to account for potential uncertainties and limitations.
How to Obtain Good Data:
- Real-World Data:Collecting data from the actual bridge site, using instruments to measure wind speed and direction, would have provided a more accurate understanding of the forces the bridge would face.
- Advanced Modeling:Employing sophisticated computer modeling techniques to simulate the interaction of wind and structure would have helped predict the bridge's behavior under different conditions.
- Multiple Perspectives:Consulting with experts in different fields, such as aerodynamics, structural engineering, and meteorology, could have provided a more comprehensive understanding of the potential risks.
Lessons Learned:
The Tacoma Narrows Bridge collapse serves as a powerful reminder of the importance of using good data in decision-making. The project highlighted the risks of relying solely on laboratory-based data and failing to account for real-world complexities. It emphasizes the need for:
- Data Quality:Ensuring that data is accurate, relevant, and comprehensive for the task at hand.
- Contextual Understanding:Considering the context of the data and its potential limitations.
- Openness to New Information:Being willing to revise decisions based on new evidence and analysis.
By embracing these principles, we can strive to make better, more informed decisions that minimize risk and optimize outcomes.
Sample Answer
The Case of the Misguided Bridge Project: A Lesson in Data-Driven Decision Making
One of the most prominent examples of a decision informed by bad data is the construction of the Tacoma Narrows Bridge in Washington state, which famously collapsed in 1940.
The Decision:
The bridge was designed and built based on data collected from wind tunnel tests, but these tests failed to capture the unique aerodynamic forces that the bridge would experience in its real-world location.