Spreadsheet Errors
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This document discusses common spreadsheet errors. It notes that research shows 20-40% of spreadsheets contain errors, with an average cell error rate of 1-2%. Errors can be qualitative, quantitative, structural, visible, hidden or temporal. The document outlines the spreadsheet lifecycle and common causes of errors like human error, logic errors, omissions, over-familiarity, and lack of testing or development guidelines. Finally, it lists five common spreadsheet risks such as unskilled users, lack of preparation guidelines, data entry issues, complacent attitudes, and potential for fraud or lost data.
Spreadsheet Errors
- 1. SPREADSHEET ERRORS“ Remember it can happen to the best of us”Fannie Mae Discovers $1.3 Billion "Honest" Mistake"There were honest mistakes made in a spreadsheet used in the implementation of a new accounting standard."The $24 Million "Clerical Error" at TransAltaThe snafu was "literally a cut-and-paste error in an Excel spreadsheet that we did not detect when we did our final sorting and ranking bids prior to submission,"
- 2. Basics of Spreadsheet ErrorsResearch shows that 20 – 40% of spreadsheets have errors Average cell error rate of 1-2%Error rates depend on situation, complexity & skillsApproximate bottom line error rate:E = 1 – (1-e)^n e = task error rate; n = number of task steps)Errors cascade through the spreadsheet
- 3. Types of ErrorsDifferent ways to classify errors‘Purser & Chadwick’ developed commonly used taxonomy of errorsQualitative ErrorsQuantitative ErrorsStructural
- 4. Visible
- 5. Hidden
- 6. Temporal
- 7. Reasoning
- 10. Accidental
- 11. Insertion
- 12. UpdateSpreadsheet Lifecycle & Causes of ErrorsCell EntryHuman Error“To err is human”Logic ErrorBehavioralWrong reasoning
- 13. Omission
- 14. Over-familiarity
- 15. Over confidence
- 16. LaxityEnd of DevelopmentCorporate shortcomingsCode InspectionNo formal spreadsheet development guidelines
- 17. Lack of formal testing5 Common Spreadsheet RisksUnskilled usersLack of guidelines for spreadsheet preparationData Entry & RecyclingPersonnel’s behaviourComplacence, casual attitudeFraudLoss of data