Authors
Raymond R. Panko
Abstract
Despite strong evidence of widespread errors, spreadsheet developers rarely subject their spreadsheets to post-development testing to reduce errors. This may be because spreadsheet developers are overconfident in the accuracy of their spreadsheets.
This conjecture is plausible because overconfidence is present in a wide variety of human cognitive domains, even among experts.
This paper describes two experiments in overconfidence in spreadsheet development. The first is a pilot study to determine the existence of overconfidence. The second tests a manipulation to reduce overconfidence and errors.
The manipulation is modestly successful, indicating that overconfidence reduction is a promising avenue to pursue.
Sample
Conclusions regarding spreadsheeting.
Although the overconfidence literature is largely empirical and is weak in theory, a number of research results suggest that overconfidence is an important issue for spreadsheet accuracy:
- The broad body of the literature has shown that overconfidence is almost universal, so we should expect to see it in spreadsheeting.
- Overconfidence tends to result in risky behavior, such as not testing for errors.
- Error rates indicate that spreadsheeting is a difficult task, so in accordance with the hard-easy effect, we should expect substantial overconfidence.
- Even experts are poorly calibrated in confidence unless they do consistent and reflective analysis after each task, which is uncommon in spreadsheeting.
- It may be possible to reduce overconfidence by providing feedback.
- Reducing overconfidence may reduce errors, although this link is not demonstrated explicitly in the overconfidence literature.
Publication
2003, EuSpRIG
