Rule Set Organization and Maintenance

Introduction

As validation rule sets grow from dozens to hundreds of rules across multiple modules, organization becomes critical for maintainability. Without systematic naming conventions and logical grouping, finding a specific rule can take 30+ minutes of searching through ambiguously named validation sets. Poor organization leads to duplicate rules, inconsistent implementations, and difficulty onboarding new team members.

Effective rule organization requires consistent naming patterns that identify entity, purpose, and scenario at a glance; logical grouping that separates concerns and enables targeted enabling/disabling; comprehensive documentation that explains business context; and maintenance routines that prevent rule sprawl over time.

This guide covers validation set naming conventions following [Entity] - [Purpose] - [Scenario] pattern, logical grouping strategies by module, purpose, scenario, and table, documentation best practices for rules and validation sets, search and categorization techniques, archiving lifecycle, and team collaboration patterns.

Organization strategies:

• Systematic naming conventions for instant identification

• Logical grouping by module, purpose, and scenario

• Documentation templates for validation sets and rules

• Search and categorization approaches

• Archiving and maintenance schedules

• Team ownership and change control

Part 1: Validation Set Naming Conventions

The Problem with Bad Names

Bad validation set names:

• "Sales Rules" (too vague - sales of what? which type of rules?)

• "Validation Set 1" (meaningless)

• "New Rules" (what's new? when?)

• "Test" (is this test or production?)

• "Important Checks" (everything is important)

Good validation set names:

• "Sales Order - Credit Checks - BeforePost"

• "Purchase Invoice - Required Fields - OnValidate"

• "Item Card - Inventory Policies - OnModify"

• "Customer - Data Quality - OnInsert"

Naming Pattern: [Entity] - [Purpose] - [Scenario]

Format:

[Entity/Table] - [Business Purpose] - [Primary Scenario]

Examples:

Sales-related:

Purchase-related:

Master data:

What this naming tells you at a glance:

• Entity: What table/area it affects

• Purpose: What business problem it solves

• Scenario: When it fires

Finding rules becomes easy:

• Need credit checks on sales orders? Look for "Sales Order - Credit"

• Need all BeforePost validations? Filter by "- BeforePost"

• Need customer-related rules? Filter by "Customer -"

Organization by Module

Group validation sets by Business Central module:

Why this works:

• Developers know where to look (by module)

• Each module owner maintains their rules

• Easy to assign permissions by module

• Natural grouping matches BC structure

✓ Checkpoint: Consistent naming means finding rules in seconds, not minutes

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Part 2: Logical Rule Grouping

One Validation Set = One Purpose

Bad grouping (everything together):

Good grouping (separated by purpose):

Benefits:

• Enable/disable by purpose ("Turn off credit checks")

• Troubleshoot by purpose ("Email notifications not working")

• Document by purpose (clear business reason)

• Maintain by purpose (credit team owns credit rules)

Grouping by Scenario

Keep same scenarios together:

Why: Different scenarios have different performance requirements, troubleshooting approaches, and testing needs.

OnValidate validation sets (immediate feedback):

BeforePost validation sets (comprehensive checks):

AfterPost validation sets (notifications):

Benefits:

• Performance tuning (optimize OnValidate separately from BeforePost)

• Testing approach (test all OnValidate rules together)

• Documentation (explain timing differences)

Grouping by Table

Keep rules on same table together:

Don't mix tables in one validation set:

Bad:

Good:

Size Guidelines

Ideal validation set size: 3-10 rules

Too small (1-2 rules):

• Too many validation sets to manage

• Hard to see related rules together

• Administrative overhead

Too large (20+ rules):

• Hard to find specific rule

• Hard to disable specific functionality

• Slow to load and edit

Sweet spot (5-7 rules):

• Related rules grouped

• Easy to scan and understand

• Easy to enable/disable as unit

• One validation set = one business policy

✓ Checkpoint: Logical grouping makes rules understandable and maintainable

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Part 3: Rule Naming and Documentation

Rule Naming Pattern

Good rule names describe what they do:

Bad rule names:

• "Rule 1"

• "Check"

• "Validation"

• "Important"

• "New Rule"

• "Test"

Good rule names:

• "Prevent Negative Inventory for Location MAIN"

• "Require Approval for Discounts Over 10%"

• "Block Posting if Customer Over Credit Limit"

• "Send Email Alert for Orders Over $50,000"

• "Auto-Set Priority to High for Rush Orders"

Pattern: [Action] [What] [Condition/Context]

Examples:

Preventing:

Requiring:

Validating:

Notifying:

Auto-setting:

What this tells you:

• The action (prevent, require, validate, notify, auto-set)

• The target (what's being acted on)

• The condition (when it happens)

Documentation in Description Field

Every rule should have a description:

Example:

Rule Name: "Prevent Posting if Customer Over Credit Limit"

Description:

What to include:

• What it does (plain English)

• How it works (logic summary)

• Exceptions (when it doesn't apply)

• When it fires (scenario)

• Business owner (who requested it, who maintains it)

• History (created date, modifications)

Comment Complex Conditions

In the Rule itself, add internal documentation:

Example validation set note:

This documentation helps:

• New developers understand why rules exist

• Business users verify correct behavior

• Auditors see compliance controls

• Future you remember what you did

✓ Checkpoint: Clear names and documentation make rules self-explanatory

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Part 4: Finding Rules Quickly

Search Strategies

By name pattern:

By table:

By scenario:

By business purpose:

Categorization Tags

Add tags in description for cross-cutting concerns:

Example:

Now you can search:

• #compliance - All compliance-related rules

• #audit - All rules auditors care about

• #high-priority - Critical rules that must work

• #performance - Rules to monitor for slowness

Inventory Spreadsheet

For large rule sets, maintain an inventory:

Excel/SharePoint list:

Benefits:

• See all rules at a glance

• Filter by status (Active, Testing, Archived)

• Track review dates (ensure rules stay current)

• Identify owners quickly

• Export for auditors or documentation

✓ Checkpoint: Good organization means finding any rule in under 2 minutes

⏱️

Part 5: Archiving and Maintenance

Rule Lifecycle

Rules go through stages:

When to Archive

Archive validation sets when:

• Replaced by newer rules

• Business process changed (rules no longer needed)

• Regulatory requirement ended

• System customization removed

Archiving process:

1. Disable all rules in validation set

2. Add "ARCHIVE -" prefix to validation set name

3. Document why archived and when in description

4. Keep for 1 year (for rollback if needed)

5. Delete after 1 year (or per compliance requirements)

Example:

Regular Maintenance Schedule

Monthly:

• Review Validation Log for errors

• Check performance of top 10 slowest rules

• Update documentation for any rules modified

Quarterly:

• Review all active rules (still needed?)

• Test critical rules (still working correctly?)

• Update rule inventory spreadsheet

• Clean up test/development rules

Annually:

• Full rule set audit

• Archive unused rules

• Update naming conventions if needed

• Train new team members on organization system

✓ Checkpoint: Regular maintenance prevents rule sprawl and chaos

⏱️

Part 6: Team Collaboration

Ownership Model

Assign owners to validation sets:

Each owner responsible for:

• Maintaining their rules

• Testing changes

• Documenting updates

• Performance monitoring

• Compliance verification

Change Control

For critical rules, implement change control:

1. Request: Business owner requests change

2. Review: IT reviews technical feasibility

3. Test: Change tested in development

4. Approve: Business owner approves test results

5. Deploy: IT deploys to production

6. Verify: Business owner verifies in production

7. Document: Update documentation

Track changes in validation set description:

✓ Checkpoint: Clear ownership and change control prevent rule chaos

⏱️

Wrap-Up and Next Steps

What you've learned:

• ✓ Validation set naming: [Entity] - [Purpose] - [Scenario]

• ✓ Logical grouping by purpose, scenario, and table

• ✓ Rule naming: [Action] [What] [Condition]

• ✓ Documentation in description fields

• ✓ Search strategies and tagging

• ✓ Rule lifecycle: Development → Production → Archived

• ✓ Maintenance schedules (monthly, quarterly, annually)

• ✓ Team ownership model

What you can do now:

• Rename validation sets to follow naming convention

• Group related rules into focused validation sets

• Document each rule with clear descriptions

• Create rule inventory spreadsheet

• Archive unused validation sets

• Assign ownership to business teams

• Implement regular review schedule

Quick organization wins:

1. Rename top 10 most-used validation sets (follow naming pattern)

2. Document top 5 most complex rules (add descriptions)

3. Archive any "Test" or "Old" validation sets

4. Create rule inventory (even simple Excel sheet)

5. Schedule quarterly review meeting

Before organization:

• 127 validation sets, no pattern

• Finding rules: 30+ minutes

• No documentation

• No ownership

After organization:

• Validation sets named consistently

• Finding rules: <2 minutes

• Every rule documented

• Clear ownership per area

Next blog: Rule Versioning and Change Management

Implementation exercise: Organize one module of rules:

1. Choose a module (Sales, Purchase, Inventory)

2. List all validation sets in that module

3. Rename following [Entity] - [Purpose] - [Scenario]

4. Group rules logically (split or merge sets if needed)

5. Document each validation set and rule

6. Test that all rules still work after reorganization Goal: Find any rule in that module in under 2 minutes

Pro Tips:

💡 Start with most-used rules: Organize Sales Order rules first (highest impact)

💡 Use prefixes for quick sorting: "AAA - Critical" sorts to top

💡 Date stamp archived rules: Easy to know when safe to delete

💡 Keep rule inventory in SharePoint: Team can access, multiple people can update

💡 Screenshot complex rules: Include in documentation (picture worth 1000 words)

💡 Review rules when process changes: Business process change = rules need review

💡 New validation set = new documentation: Don't defer, document as you create

Related Resources:

• Blog 032: Testing and Debugging (Validation Log for monitoring)

• Blog 033: Performance Optimization (monitoring slow rules)

• Blog 030: Understanding Scenarios (organizing by scenario)

• Microsoft Dynamics 365 Business Central Customization Best Practices

• QUALIA Rule Engine Administration Guide

Questions? Take 30 minutes today to rename your top 10 validation sets. You'll save hours of searching over the next month. Organization is an investment that pays daily dividends.

This blog is part of the QUALIA Rule Engine series for Microsoft Dynamics 365 Business Central. Follow along as we explore progressively advanced features.