From the course: Executive Decision-Making
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Quality of data
- Large executive decisions require a lot of data. The problem is that data isn't always right. There are biases involved in the way you gather information. Sometimes there are structural issues with the way the data is structured. And there are quality problems. The data is always suspect. Understanding the data's limitations and then accounting for them is going to help you make better decisions. The way you account for it is, first, clearly articulate the assumptions you're making. Second, identify gaps in the data or questions about data accuracy. Third, put errors ranges around that suspect data and assess how much that could change the decision you're trying to make. Lastly, try to triangulate in and confirm the decision using different data sets. You may have one data set that says it's a bad idea and two others that say it's a good idea. So looking at it from multiple views can give you a higher degree of…
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