Preventing Data Entry Errors: Validation Best Practices

Introduction

Data quality is the foundation of reliable business systems. A single data entry error can cascade through your organization—incorrect pricing leads to revenue loss, wrong customer information causes shipping delays, invalid GL codes create accounting nightmares, and bad inventory data results in stockouts or overstock.

Traditional approaches to preventing data entry errors rely on user training, manual verification, and hoping people catch mistakes before they cause problems. This approach is expensive, inconsistent, and ultimately ineffective—humans make mistakes, especially when entering repetitive data under time pressure.

Business rules provide a better solution: Automated, real-time validation that catches errors at the point of entry, provides immediate feedback with specific guidance, and prevents bad data from entering your system in the first place.

This comprehensive guide covers validation best practices, common validation patterns, techniques for effective error messages, handling complex data relationships, balancing strictness with usability, and real-world examples across sales, purchasing, inventory, and finance.

The Cost of Data Entry Errors

Understanding the business impact of data errors makes the case for investment in validation.

Direct Financial Impact

Pricing errors:

Quantity errors:

Account coding errors:

Indirect Business Impact

Customer satisfaction:

• Wrong shipping address → Delivery delays → Unhappy customers

• Incorrect pricing → Customer disputes → Relationship damage

• Invalid order → Processing delays → Lost sales

Operational efficiency:

• Errors discovered later require rework (10x more expensive than prevention)

• Support tickets from error-related issues

• Management time spent investigating and correcting

Compliance and audit:

• Invalid data fails regulatory reporting

• Audit findings from data quality issues

• Remediation costs and reputation risk

Estimated cost: Industry studies suggest data errors cost organizations 15-25% of revenue. For a $10M company, that's $1.5-2.5M annually.

Validation Design Principles

Principle 1: Validate Early and Often

Catch errors at the earliest possible point:

Implementation with QUALIA:

• Use Before Insert for validating new records

• Use Before Modify for validating changes

• Validate as early in transaction lifecycle as possible

Principle 2: Provide Specific, Actionable Feedback

Poor error message:

Better error message:

Best error message:

Message components:

1. What's wrong: Clear statement of the problem

2. Relevant data: Specific values showing the issue

3. Why it's wrong: Context (limits, rules, policies)

4. How to fix: Specific resolution steps

5. Who to contact: Escalation path if needed

Principle 3: Balance Strictness with Usability

Too strict:

Too lenient:

Appropriate:

Guideline:

• Error (blocking): For violations that would cause serious problems

• Warning (non-blocking): For unusual but potentially valid situations

• No validation: For subjective or flexible fields

Principle 4: Understand User Context

Consider the user's situation:

Implementation:

• Distinguish between required (must have) and recommended (should have)

• Use warnings for recommendations, errors for requirements

• Consider rule groups to reduce validation for experienced users

Principle 5: Validate Related Data Consistency

Single-field validation is insufficient:

Cross-field validation:

Implementation: Use conditions that reference multiple fields and linked tables

Principle 6: Provide Positive Reinforcement

Not all validation is about errors:

Positive validation:
Message: "Order for loyal customer [CustomerName]. Consider offering 
loyalty discount of [DiscountPercent]

Informational messages:

Message: "Customer [CustomerName] typically orders [TypicalQuantity] units. 
This order is for [OrderQuantity]

Common Validation Patterns

Pattern 1: Required Field Validation

Purpose: Ensure critical fields are filled before saving

Implementation:

Rule Set: SALES-REQUIRED-FIELDS
Trigger Table: 36 (Sales Header)
Trigger Event: Before Insert
Scenarios: [36:1] is 'Order'

Rule 1: Customer Required
Condition: [36:2] is ''
Action: Error - "Customer No. is required for all sales orders."

Rule 2: Salesperson Required
Condition: [36:43] is ''
Action: Error - "Salesperson Code is required. Please assign a salesperson."

Rule 3: Order Date Required
Condition: [36:99] is ''
Action: Error - "Order Date is required."

Rule 4: Requested Delivery Date Required
Condition: [36:76]

Placeholders Used in This Pattern:

• [36:1] - Sales Header (Table 36): Document Type (Field 1) - Type of sales document

• [36:2] - Sales Header (Table 36): Sell-to Customer No. (Field 2) - Customer number

• [36:43] - Sales Header (Table 36): Salesperson Code (Field 43) - Assigned salesperson

• [36:99] - Sales Header (Table 36): Order Date (Field 99) - Date of order

• [36:76] - Sales Header (Table 36): Requested Delivery Date (Field 76) - Customer's requested delivery date

Variations:

• Conditional required: Field required only in certain situations

• Dependent required: If field A filled, then field B required

Example: Conditional required:

Condition: [36:CustomInternationalOrder] is true AND [36:CustomExportLicense]

Pattern 2: Format Validation

Purpose: Ensure data follows expected format or pattern

Implementation:

Rule Set: CONTACT-FORMAT-VALIDATION
Trigger Table: 5050 (Contact)
Trigger Event: Before Insert, Before Modify

Rule 1: Email Format
Condition: [5050:102] is <>'*@*.*'
// Email must contain @ and . (basic check)
Action: Error - "Email '[5050:102]' appears invalid. Must be format: 
user@domain.com"

Rule 2: Phone Number Format
Condition: [5050:103] is <>'*-*-*'
// Phone must contain dashes (basic format check)
Action: Warning - "Phone number '[5050:103]' doesn't match standard format 
XXX-XXX-XXXX. Confirm this is correct."

Rule 3: Postal Code Format (US)
Scenario 1: [5050:Country] is 'US'
Scenario 2: [5050:PostCode] is <>'#####'
// US postal codes are 5 digits
Action: Error - "US postal codes must be 5 digits. '[5050:PostCode]

Placeholders Used in This Pattern:

• [5050:102] - Contact (Table 5050): E-Mail (Field 102) - Contact's email address

• [5050:103] - Contact (Table 5050): Phone No. (Field 103) - Contact's phone number

• [5050:Country] - Contact (Table 5050): Country/Region Code - Contact's country

• [5050:PostCode] - Contact (Table 5050): Post Code - Postal/ZIP code

Note: BC filter syntax has limited pattern matching. For complex patterns, consider custom validation or external validation.

Pattern 3: Range Validation

Purpose: Ensure numeric values fall within acceptable ranges

Implementation:

Rule Set: SALES-RANGE-VALIDATION
Trigger Table: 37 (Sales Line)
Trigger Event: Before Insert, Before Modify

Rule 1: Quantity Reasonable Range
Condition: [37:15] is >10000
// Quantity exceeds 10,000
Action: Warning - "Quantity [37:15] is unusually high. Average order for 
this item is [AvgQuantity] units. Confirm this quantity is correct."

Rule 2: Unit Price Cannot Be Zero
Condition: [37:22] is 0
Action: Error - "Unit Price cannot be zero. Enter valid price."

Rule 3: Unit Price Maximum Check
Condition: [37:22] is >1000000
Action: Warning - "Unit Price $[37:22] is extremely high. Confirm this 
is correct or adjust decimal placement."

Rule 4: Discount Percentage Limit (Hard)
Condition: [37:11] is >100
Action: Error - "Discount percentage [37:11]% cannot exceed 100%."

Rule 5: Discount Percentage Limit (Soft)
Condition: [37:11] is >50
Action: Warning - "Discount [37:11]

Placeholders Used in This Pattern:

• [37:15] - Sales Line (Table 37): Quantity (Field 15) - Quantity ordered

• [37:22] - Sales Line (Table 37): Unit Price (Field 22) - Price per unit

• [37:11] - Sales Line (Table 37): Line Discount % (Field 11) - Discount percentageRule 2: Unit Price Not Zero Condition: [37:22] is 0 Action: Error - "Unit Price cannot be zero. Please enter valid price."

Rule 3: Unit Price Reasonable Range Condition: [37:22] is >1000000 Action: Warning - "Unit Price $[37:22] is extremely high. Confirm this pricing is correct."

Rule 4: Discount Percentage Range Condition: [37:11] is >100 // Discount % over 100% Action: Error - "Discount percentage [37:11]% cannot exceed 100%."

Rule 5: Line Discount Maximum Condition: [37:11] is >50 Action: Warning - "Discount [37:11]% exceeds typical maximum of 50%. Manager approval may be required."

### Pattern 4: Cross-Field Consistency Validation

**Purpose**: Ensure related fields have consistent values

**Implementation**

Rule Set: SALES-CONSISTENCY-VALIDATION Trigger Table: 36 (Sales Header) Trigger Event: Before Insert, Before Modify Linked Tables: Customer (18)

Rule 1: Bill-to vs. Sell-to Scenario 1: [36:13] is <>[36:2] Scenario 2: [36:CustomBillToReason] is '' // Bill-to differs from Sell-to but no reason specified Action: Warning - "Bill-to Customer [36:13] differs from Sell-to Customer [36:2]. Confirm this is intentional."

Rule 2: Payment Terms vs. Customer Default Condition: [36:64] is <>[18:27] // Payment terms differ from customer default Action: Warning - "Payment Terms '[36:64]' differ from customer default '[18:27]'. Confirm this is correct."

Rule 3: Currency Consistency Condition: [36:CustomCurrency] is <>[18:CustomDefaultCurrency] Action: Warning - "Order currency [36:CustomCurrency] differs from customer's default [18:CustomDefaultCurrency]. Exchange rate will apply."

Rule 4: Shipment Date vs. Order Date Condition: [36:CustomShipmentDate] is <[36:99] // Shipment date before order date (impossible) Action: Error - "Shipment Date [36:CustomShipmentDate] cannot be before Order Date [36:99]. Please correct dates."

Rule 5: Requested Delivery Before Shipment Condition: [36:76] is <[36:CustomShipmentDate] Action: Error - "Requested Delivery Date [36:76] cannot be before Shipment Date [36:CustomShipmentDate]. Please correct dates."

**Placeholders Used in This Pattern:**
- `[36:13]` - Sales Header (Table 36): Bill-to Customer No. (Field 13) - Who gets billed
- `[36:2]` - Sales Header (Table 36): Sell-to Customer No. (Field 2) - Who is buying
- `[36:64]` - Sales Header (Table 36): Payment Terms Code (Field 64) - Payment terms for this order
- `[18:27]` - Customer (Table 18): Payment Terms Code (Field 27) - Customer's default payment terms
- `[36:99]` - Sales Header (Table 36): Order Date (Field 99) - Date order was created
- `[36:76]` - Sales Header (Table 36): Requested Delivery Date (Field 76) - When customer wants delivery

### Pattern 5: Business Logic Validation

**Purpose**: Enforce business policies and rules

**Implementation**

Rule Set: ITEM-BUSINESS-RULES Trigger Table: 37 (Sales Line) Trigger Event: Before Insert Linked Tables: Item (27), Customer (18)

Rule 1: Minimum Order Quantity Condition: [37:15] is <[27:CustomMinOrderQty] // Quantity less than item's minimum order quantity Action: Error - "Item [27:3] has minimum order quantity of [27:CustomMinOrderQty] units. Order quantity [37:15] is too low. Increase quantity or select different item."

Rule 2: Maximum Order Quantity Condition: [37:15] is >[27:CustomMaxOrderQty] Action: Warning - "Order quantity [37:15] exceeds recommended maximum of [27:CustomMaxOrderQty] units. Confirm quantity is correct."

Rule 3: Price Below Cost Linked Tables: Item (27) Condition: [37:22] is <[27:22] // Unit Price < Unit Cost Action: Warning - "Unit Price $[37:22] is below cost of $[27:22]. Loss per unit: $([27:22] - [37:22]). Total line loss: $(([27:22] - [37:22]) * [37:15]). Manager approval required."

Rule 4: Restricted Item for Customer Type Scenario 1: [27:CustomRestricted] is true Scenario 2: [18:CustomCustomerType] is <>'Enterprise' Action: Error - "Item [27:3] is restricted to Enterprise customers only. Customer [18:2] is type '[18:CustomCustomerType]'. Select different item or upgrade customer type."

Rule 5: Incompatible Item Combinations Condition: [Checking if incompatible items exist in order] Action: Error - "Item [27:3] is incompatible with item [OtherItem] already on this order. Remove one of these items to proceed."

**Placeholders Used in This Pattern:**
- `[37:15]` - Sales Line (Table 37): Quantity (Field 15) - Quantity ordered
- `[27:3]` - Item (Table 27): Description (Field 3) - Item description
- `[27:CustomMinOrderQty]` - Item (Table 27): Custom field for minimum order quantity
- `[27:CustomMaxOrderQty]` - Item (Table 27): Custom field for maximum order quantity
- `[37:22]` - Sales Line (Table 37): Unit Price (Field 22) - Selling price
- `[27:22]` - Item (Table 27): Unit Cost (Field 22) - Cost of the item
- `[18:2]` - Customer (Table 18): Name (Field 2) - Customer name
- `[18:CustomCustomerType]` - Customer (Table 18): Custom field for customer type
- `{[27:22] - [37:22]}` - Calculated expression: Loss per unit
- `{([27:22] - [37:22]) * [37:15]}` - Calculated expression: Total loss

### Pattern 6: Temporal Validation (Date/Time)

**Purpose**: Validate date and time fields

**Implementation**

Rule Set: DATE-VALIDATION Trigger Table: 36 (Sales Header) Trigger Event: Before Insert, Before Modify

Rule 1: Order Date Not Future Condition: [36:99] is >[TODAY] // Order Date in the future Action: Error - "Order Date [36:99] cannot be in the future. Today is [TODAY]."

Rule 2: Order Date Not Too Old Condition: [36:99] is <[TODAY-90D] // Order Date more than 90 days ago Action: Warning - "Order Date [36:99] is more than 90 days ago. Confirm this is not a data entry error."

Rule 3: Posting Date Within Period Condition 1: [36:CustomPostingDate] is <[PERIOD_START] Action: Error - "Posting Date must be within current open period ([PERIOD_START] to [PERIOD_END]). Date [36:CustomPostingDate] is before period start."

Condition 2: [36:CustomPostingDate] is >[PERIOD_END] Action: Error - "Posting Date must be within current open period ([PERIOD_START] to [PERIOD_END]). Date [36:CustomPostingDate] is after period end."

Rule 4: Delivery Date Reasonable Condition: [36:76] is <[TODAY+1D] // Requested delivery less than 1 day away Action: Warning - "Requested Delivery Date [36:76] is less than 1 day away. Standard lead time is [LeadTime] days. Expedited shipping may be required."

Rule 5: Weekend Delivery Warning Condition: [36:76 is Saturday or Sunday]

**Placeholders Used in This Pattern:**
- `[36:99]` - Sales Header (Table 36): Order Date (Field 99) - Date order was created
- `[36:76]` - Sales Header (Table 36): Requested Delivery Date (Field 76) - When customer wants delivery
- `[TODAY]` - System placeholder: Current date
- `[TODAY-90D]` - Calculated expression: 90 days ago
- `[TODAY+1D]` - Calculated expression: Tomorrow
- `[PERIOD_START]` - System placeholder: Start of current accounting period
- `[PERIOD_END]` - System placeholder: End of current accounting period
Action: Warning - "Requested Delivery Date [36:76]

Note: Date comparison syntax depends on BC version and QUALIA Rule Engine capabilities.

Pattern 7: Lookup/Reference Validation

Purpose: Ensure referenced records exist and are valid

Implementation:

Rule Set: REFERENCE-VALIDATION
Trigger Table: 36 (Sales Header)
Trigger Event: Before Insert
Linked Tables: Customer (18), Salesperson (13), Location (14)

Rule 1: Customer Exists and Active
Condition: [18:39] is true
// Customer is blocked
Action: Error - "Customer [18:2] ([18:1]) is blocked for reason: [18:40]. 
Cannot create orders. Contact customer service."

Rule 2: Salesperson Active
Condition: [13:CustomInactive] is true
Action: Error - "Salesperson [13:3] is inactive. Please select active 
salesperson."

Rule 3: Location Allows Sales
Condition: [14:CustomSalesAllowed] is false
Action: Error - "Location [14:1] does not allow sales orders. Select 
different location or change order type."

Rule 4: Customer Credit Hold
Condition: [18:CustomCreditHold] is true
Action: Error - "Customer [18:2]

Pattern 8: Duplicate Detection

Purpose: Prevent creating duplicate records

Implementation:

Rule Set: DUPLICATE-PREVENTION
Trigger Table: 18 (Customer)
Trigger Event: Before Insert

Rule 1: Duplicate Customer Name
Condition: [Check if customer with same name exists]
// Complex - may require custom function
Action: Warning - "Customer with name '[18:2]' already exists (No. [ExistingNo]). 
Confirm you want to create another customer with same name."

Rule 2: Duplicate Email
Condition: [Check if email already used]
Action: Error - "Email '[18:102]' is already registered to customer [ExistingCustomer]. 
Each customer must have unique email."

Rule 3: Duplicate Phone
Condition: [Check if phone already used]
Action: Warning - "Phone number '[18:103]' matches existing customer [ExistingCustomer]

Note: Duplicate detection typically requires aggregation or lookup that may need custom implementation or integration.

Pattern 9: Inventory Availability Validation

Purpose: Warn about insufficient inventory

Implementation:

Rule Set: INVENTORY-AVAILABILITY
Trigger Table: 37 (Sales Line)
Trigger Event: Before Insert, After Modify
Linked Tables: Item (27)

Rule 1: Negative Inventory Warning
Condition: [37:15] is >[27:18]
// Order quantity > Inventory
Action: Warning - "Inventory for item [27:3] is [27:18] units, but order 
requests [37:15] units. Backorder of ([37:15] - [27:18]) units will be created. 
Estimated fulfillment: [EstDate]."

Rule 2: Below Reorder Point
Condition: [27:18] is <[27:22]
// Inventory below reorder point (after this order)
Action: Message - "Item [27:3] inventory will be below reorder point after 
this order. Automatic replenishment will be triggered."

Rule 3: Out of Stock
Condition: [27:18] is 0
Action: Error - "Item [27:3]

Pattern 10: Data Completeness Validation

Purpose: Ensure sufficient data exists before proceeding

Implementation:

Rule Set: ORDER-COMPLETENESS
Trigger Table: 36 (Sales Header)
Trigger Event: Before Release/Posting

Rule 1: Has Lines
Condition: [Count of lines = 0]
Action: Error - "Order has no lines. Add at least one line item before posting."

Rule 2: All Lines Have Quantity
Condition: [Any line has zero quantity]
Action: Error - "One or more order lines have zero quantity. Update quantities 
or remove lines."

Rule 3: All Required Dimensions
Condition 1: [CustomDimension1] is ''
Action: Error - "Dimension 1 is required before posting. Please complete all dimension fields."

Condition 2: [CustomDimension2] is ''
Action: Error - "Dimension 2 is required before posting. Please complete all dimension fields."

Rule 4: Shipping Information Complete
Condition 1: [36:CustomShipToAddress] is ''
Action: Error - "Ship-to Address is required. Complete shipping information before proceeding."

Condition 2: [36:CustomShipToCity]

Effective Error Message Design

Message Structure Template

"[PROBLEM STATEMENT]. [RELEVANT DATA]. [EXPLANATION/CONTEXT]. 

[SOLUTION OPTIONS]:
- Option 1: [Specific action]
- Option 2: [Alternative action]
- Option 3: [Escalation path with contact]

Example: Credit Limit

"Credit limit exceeded. Customer [Name] has credit limit $[Limit] but current 
balance $[Balance] plus this order $[Amount] would total $[Total], exceeding 
the limit by $[Overage].

To proceed:
- Reduce order amount to $[MaxAllowed]

Message Best Practices

1. Use active voice:

2. Be specific:

Poor: "Invalid quantity"
Better: "Quantity is too high"
Best: "Quantity [Value] exceeds maximum order quantity of [Max]

3. Explain why:

4. Provide context with data:

Poor: "Price too low"
Better: "Price is below cost"
Best: "Unit Price $[Price] is below cost of $[Cost], creating loss of $[Loss]

5. Offer solutions:

6. Use appropriate tone:

7. Avoid jargon:

Technical: "Referential integrity violation on FK_Customer"
User-friendly: "Customer [CustomerNo]

Balancing Validation Strictness

When to Use Errors (Blocking)

Use Error action (blocks transaction) for:

✓ Data integrity violations (referential integrity, required fields) ✓ Business rule violations that would cause serious problems ✓ Compliance requirements (regulatory, audit, legal) ✓ Financial accuracy (credit limits, pricing rules) ✓ Data consistency (invalid combinations, conflicting values)

Examples:

• Customer doesn't exist → Error

• Credit limit exceeded → Error

• Price below cost (strict policy) → Error

• Posting to closed period → Error

• Required field blank → Error

When to Use Warnings (Non-Blocking)

Use Warning action (allows override) for:

✓ Best practices that can be overridden ✓ Unusual patterns that might be errors ✓ Recommendations, not requirements ✓ Situations requiring judgment ✓ Alerts about potential issues

Examples:

• Payment terms differ from default → Warning

• Unusually high quantity → Warning

• Weekend delivery → Warning

• Price below cost (flexible policy) → Warning

• Discount higher than typical → Warning

When to Use Messages (Informational)

Use Message action (no interruption) for:

✓ Helpful information ✓ Suggestions ✓ Confirmations ✓ Positive reinforcement ✓ FYI notifications

Examples:

• "Customer is VIP - consider special handling"

• "Item will be automatically reordered"

• "Order qualifies for free shipping"

• "Customer's typical order size is [X] units"

Decision Matrix

Validation Performance Optimization

Use Scenarios Effectively

Poor (slow):

Rule Set: SALES-VALIDATION
Scenarios: (none)
Condition: [36:1]

Better (fast):

Rule Set: SALES-VALIDATION
Scenarios:
  1. [36:1] is 'Order'              // Filters 80% immediately
  2. [36:109] is >50000             // Filters another 15%
  3. [18:39] is false               // Filters another 4%
Condition: [Detailed business logic]

Minimize Linked Tables

Poor (many lookups):

Better (minimal lookups):

Simplify Complex Validations

Complex (slow):

Condition: {([37:15] * [37:22] * (1 + [37:27]/100) * [CustomFactor1] * 
[CustomFactor2])} is >{([18:59] - [18:61]) * [CustomMultiplier] / [CustomDivisor]

Simpler (faster):

Condition 1: {[37:15] * [37:22]} is >[Threshold1]
Condition 2: [CustomCalculation] > [Threshold2]

Testing Validation Rules

Test Case Categories

1. Happy path (should pass):

2. Boundary conditions:

3. Invalid data:

4. Edge cases:

5. Cross-field scenarios:

Test Checklist

For each validation rule:

• Test with valid data (should pass)

• Test with invalid data (should fail with appropriate message)

• Test boundary values (at limits)

• Test with blank/null values

• Test with extreme values (very large, very small)

• Verify error message is clear and helpful

• Verify placeholders resolve correctly

• Check performance (rule doesn't slow system)

• Test with different user permissions

• Verify audit logging (if applicable)

Real-World Examples

Example 1: Purchase Order Validation

Rule Set: PURCHASE-ORDER-VALIDATION
Trigger Table: 38 (Purchase Header)
Trigger Event: Before Insert
Linked Tables: Vendor (23), Purchaser (13)

Rule 1: Vendor Not Blocked
Condition: [23:39] is true
Action: Error - "Vendor [23:2] is blocked. Cannot create purchase orders. 
Contact purchasing manager."

Rule 2: Vendor Payment Terms Valid
Condition: [38:64] is ''
Action: Error - "Payment Terms required for all purchase orders."

Rule 3: Budget Approval Required
Condition: [38:109] is >25000
Action: Email to purchasing.manager@company.com
  "Purchase order [38:3] for $[38:109] requires budget approval."
  
Rule 4: Preferred Vendor Compliance
Condition: [27:CustomPreferredVendor] is <>[38:2] AND [27:CustomPreferredVendor] is <>''
Action: Warning - "Item [27:3] has preferred vendor [27:CustomPreferredVendor], 
but you're ordering from [23:2]. Confirm this is intentional."

Rule 5: Minimum Order Value
Condition: [38:109] is <100
Action: Warning - "Order total $[38:109] is below vendor's minimum order 
value of $[23:CustomMinOrderValue]

Example 2: General Journal Validation

Rule Set: JOURNAL-VALIDATION
Trigger Table: 81 (Gen. Journal Line)
Trigger Event: Before Insert
Linked Tables: G/L Account (15)

Rule 1: Account Not Blocked
Condition: [15:34] is true
Action: Error - "G/L Account [15:3] ([15:1]) is blocked. Select different account."

Rule 2: Balanced Entry Required
Condition: [81:13] is 0
Action: Error - "Amount cannot be zero. Enter debit or credit amount."

Rule 3: Posting Date Valid
Condition 1: [81:5] is <[PERIOD_START]
Action: Error - "Posting Date [81:5] is before allowed period start ([PERIOD_START]). 
Adjust date or request period opening."

Condition 2: [81:5] is >[PERIOD_END]
Action: Error - "Posting Date [81:5] is after allowed period end ([PERIOD_END]). 
Adjust date or request period opening."

Rule 4: Dimension Required for Department Accounts
Scenario 1: [15:CustomRequiresDepartment] is true
Scenario 2: [81:CustomDepartment] is ''
Action: Error - "Account [15:3] requires Department dimension. Select department."

Rule 5: Large Journal Entry Review
Condition 1: [81:13] is >100000
Action: Email to controller@company.com
  "Large journal entry requires review: Account [15:3], Amount $[81:13], 
   User [USERID], Description [81:7]"

Condition 2: [81:13] is <-100000
Action: Email to controller@company.com
  "Large journal entry requires review: Account [15:3], Amount $[81:13], 
   User [USERID], Description [81:7]

Example 3: Customer Master Data Validation

Rule Set: CUSTOMER-DATA-VALIDATION
Trigger Table: 18 (Customer)
Trigger Field: [18:39]  // Blocked field - validate when customer being activated
Trigger Event: Before Modify

Scenarios:
1. {18:39} is <>[18:39]  // Blocked field changing
2. [18:39] is ' '        // Being unblocked (activated)

Rule 1: Required Contact Information
Condition 1: [18:102] is ''  // Email blank
Condition 2: [18:103] is ''  // Phone blank
// Both conditions must be true (AND logic) = both are blank
Action: Error - "Customer must have either email or phone number before activation.

This customer is being unblocked for use in transactions. Contact information 
is essential for order confirmations and communication. Enter at least one contact 
method before removing block."

Rule 2: Credit Limit Reasonable
Condition: [18:59] is >1000000
Action: Warning - "Credit limit $[18:59] exceeds $1,000,000. Executive 
approval required for high credit limits."

Rule 3: Payment Terms Standard
Condition: [18:27] is <>'NET30'|'NET60'|'NET90'
Action: Warning - "Payment Terms '[18:27]' is non-standard. Confirm this is approved."

Rule 4: Duplicate Customer Check
Condition: [Existing customer with same name]
Action: Warning - "Customer '[18:2]' may already exist. Check for duplicates."

Rule 5: Address Validation
Condition 1: [18:CustomPostalCode] is ''
Action: Error - "Complete address required before activation. Postal Code is mandatory."

Condition 2: [18:CustomCity]

Note: This example validates required fields at customer activation (when Blocked field cleared). For format validation or data quality checks that don't require complete data, you could use Trigger Field [18:0] (any field) to validate immediately when fields are changed.

Conclusion

Preventing data entry errors through automated validation delivers measurable business value: reduced rework, improved data quality, better customer service, regulatory compliance, and operational efficiency. QUALIA Rule Engine makes implementing comprehensive validation straightforward and maintainable.

Key principles:

Validate early: Catch errors at point of entry, not during posting Be specific: Clear messages with relevant data and actionable guidance Balance strictness: Errors for critical issues, warnings for recommendations Consider context: Understand user workflow and pressure points Validate relationships: Cross-field and cross-table consistency Test thoroughly: Boundary conditions, edge cases, real-world scenarios Optimize performance: Use scenarios, minimize linked tables

Implementation approach:

1. Identify high-impact validation opportunities

2. Design clear business rules with specific criteria

3. Craft helpful error messages with placeholders

4. Implement using appropriate action types (Error, Warning, Message)

5. Test with real users and real data

6. Monitor and refine based on feedback

7. Expand validation coverage iteratively

Validation effectiveness formula:

By implementing thoughtful validation rules, you transform data entry from error-prone guesswork into guided, reliable process—protecting your business from costly mistakes while helping users work efficiently and confidently.

Related Reading:

• How to Implement Credit Limit Validation in 10 Minutes

• Writing Effective Error Messages: User Experience Best Practices

• The Complete Guide to Placeholders in Business Rules

• Performance Tuning Your Business Rules: Optimization Strategies