Know and understand importance, characteristics and uses of verification including visual checking and double data entry to reduce data entry errors

15 Proofing

Objective

Students should be able to:

• Explain why verification (proofing) is essential when handling data.
• Identify the main characteristics of effective verification.
• Describe common verification techniques, especially visual checking and double data entry.
• Apply these techniques to reduce data‑entry errors in real‑world situations.

Why Proofing Matters

Data is the foundation of decisions, reports and analyses. Errors in data can lead to:

• Incorrect conclusions and poor decisions.
• Loss of credibility for individuals and organisations.
• Financial loss, legal issues or safety hazards.
• Wasted time correcting mistakes after they have been used.

Proofing is the process of checking data for accuracy before it is stored, processed or published.

Key Characteristics of Effective \cdot erification

• Systematic: Follow a set procedure each time data is entered.
• Independent: Where possible, the checker should not be the original data entry person.
• Timely: Errors are identified as soon as possible, ideally before the data is used.
• Documented: Record how verification was carried out and any corrections made.
• Appropriate to risk: More critical data receives more rigorous proofing.

Common \cdot erification Techniques

1. Visual Checking (Manual Review)

Involves looking at the data on screen or on paper and comparing it with the source document.

• Simple and inexpensive.
• Effective for small data sets or when the source is a hard copy.
• Relies on the reviewer’s concentration; fatigue can cause missed errors.

2. Double Data Entry

Two separate operators enter the same data independently. The two versions are then compared automatically.

• Reduces random typing errors dramatically.
• Can be automated with software that flags mismatches.
• More time‑consuming and may double labour costs.

3. Automated \cdot alidation Rules

Software checks that entered values meet predefined criteria (e.g., numeric range, mandatory fields).

• Prevents many simple errors at the point of entry.
• Cannot detect errors that are logically correct but factually wrong.

Comparison of Techniques

Step‑by‑Step Double Data Entry Process

1. Prepare two identical data entry screens or forms.
2. Assign two different operators (Operator A and Operator B).
3. Each operator enters the complete data set independently.
4. Run a comparison routine that flags any mismatched fields.
5. For each mismatch, refer back to the original source document and correct the erroneous entry.
6. Record the final, verified data set and keep a log of the verification process.

Practical Example

Suppose a school is entering student exam scores into a spreadsheet. The following table shows how double entry can catch errors.

Tips for Reducing Data‑Entry Errors

• Use clear, well‑structured source documents.
• Train staff on common error types (transposition, omission, duplication).
• Implement field‑level validation (e.g., numeric only, date format).
• Schedule regular breaks to avoid fatigue.
• Keep a log of errors detected and corrective actions taken – this helps improve the process.

Suggested Diagram

Summary

Proofing is a vital quality‑control step in ICT. By understanding the importance of verification and applying techniques such as visual checking and double data entry, students can significantly reduce the risk of data‑entry errors, leading to more reliable information for decision‑making.