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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

Full article

Reducing overconfidence in spreadsheet development