Grace Period Rule Adjustments Without Side Effects – ICMG in Action

Series: Rethinking Requirements: How the ICMG Enterprise Anatomy Model Makes Systems Change-Ready

Perspectives Covered: Strategy, Business Process, System, Component Specification, Implementation, Operations

Key Variables Impacted: Rule, Data, Event, UI, Function, Network

When a "Simple" Rule Change Breaks the System

It started as an act of empathy:

“Extend the repayment grace period from 5 days to 10 for borrowers in flood-affected areas.”

A humane response.

Regulatory alignment.

A sensible business decision.

But once the rule hit the systems, everything went sideways:

• Auto-debit instructions still triggered on Day 6.

• Notifications warned of late fees—incorrectly.

• Customer support was blindsided.

• Reports were inconsistent—some showing 5 days, others 10.

What should’ve been a minor update turned into a release-day emergency.

Why? Because the architecture wasn’t prepared to absorb a change without side effects.

The rule changed—but the system wasn’t structured to respond coherently.

Why Conventional SDLC Approaches Fail

Common Problems

1. Rule Representation Too Coarse for Grace Period Logic:

The grace period adjustment from 5 to 10 days was documented as a compound statement, without clear understanding of the elements (such as specific customer segments or loan types) across the Team.

2. Hidden Dependencies Across Architectural Elements:

Implementation diagrams for the grace period rule didn't explicitly show all the relationships with

• Data Sub System Components (e.g., regional borrower segmentation),

• Function Sub System Components (auto-debit scheduling logic),

• Network Sub System Components (notification delivery),

• UI Sub System Components (agent and customer displays),

• Event Sub System components (payment reminders) elements.

3. Fragmented Developer Mental Models on Grace Period Changes:

Different developers used their own specialist expertise to interpret the new grace period requirement, leading to inconsistent implementations—such as auto-debit and notifications triggering on outdated schedules.

4. Narrow Stakeholder Focus Limited to Technical Teams:

Grace period adjustment diagrams were created and reviewed only by technical specialists. Business stakeholders, operations teams, and customer service representatives weren’t adequately engaged, causing real-world scenarios to be overlooked.

5. Limited Impact Analysis Ignored Business and Operational Consequences:

Tests focused solely on IT scenarios, failing to simulate real-world operational processes—such as dispute resolution, customer communication, and regulatory reporting—which rely on accurate grace period enforcement.

6. Ambiguous Task Dependencies Prevented Clear Traceability:

Implementation tasks (such as rule adjustments, data updates, and notification scheduling) were purely technical, without clarity on how each task directly impacted customer-facing processes, compliance outcomes, or strategic business objectives.

Root Causes:

• Absence of Granular Rule Models:

  • Rules are not broken down into elemental levels, resulting in coarse modeling and ambiguous impacts.

• Lack of Explicit Dependency Mapping:

  • Dependencies across architecture variables (Rule, Data, Function, Network, UI, Event) are not explicitly modeled, making it difficult to anticipate impacts clearly.

• Reliance on Individual Interpretation:

  • Teams rely on subjective, personal mental models rather than explicit, universally shared architectural models.

• Limited Stakeholder Integration:

  • Diagrams focus only on developer stakeholders, missing strategic and operational viewpoints.

• Reactive Testing Approach:

  • Tests performed are reactionary and technical, without comprehensive scenario-based validation against business and operational objectives.

• Disconnected Change Management:

  • Technical changes are implemented without explicit alignment to strategic intent or cross-variable dependencies.

Applying the ICMG Enterprise Anatomy Model (Project Edition)

The ICMG model transforms chaos into coherence by treating the grace period change as an architectural event—mapped, versioned, and governed across all variables.

Strategy Perspective

Business Driver:

Provide timely relief to disaster-impacted borrowers without unintended financial penalties.

Strategic Intent:

Preserve customer trust and regulatory alignment, minimizing disruptions to operations and reporting.

Business Process Perspective

Processes Impacted:

• Loan Servicing

• Collections & Dunning

• Customer Notification

• Dispute Resolution

Observation: Each process must interpret the new rule consistently, reflecting clear business intent—not assumptions.

System / Subsystem Perspective (by Variable)

Policy changes ripple through multiple architecture variables. Clearly mapping these ensures comprehensive adjustments.

Sub System Type	Subsystems Involved
Rule Sub Systems	Grace Period Rule Engine, Collections Policy Module
Data Sub Systems	Customer Segmentation Store, Region Mapping, Loan Ledger
Function Sub Systems	Dunning Logic, Auto-Debit Processor, Reminder Scheduler
UI Sub Systems	Agent Dashboard, Customer Portal UI
Event Sub Systems	Payment Due Events, SMS Alerts, Auto-Debit Triggers
Network Sub Systems	Batch Orchestrator, Notification Gateway

Observation: This wasn’t simply a Rule update—it affected timing behavior, data segmentation, and user-facing logic. The ICMG model maps these interdependencies clearly.

Component Specification Perspective

Clearly defining component-level impacts—both single-variable and multi-variable—provides comprehensive visibility and prevents unintended side effects.

Single-Variable Component Impact:

Variable Type	Components Affected	Impact
Rule Components	Grace Period Rule Evaluator	Update rule logic from 5-day to 10-day.
Data Components	Borrower Segmentation Engine	Segment borrowers based on updated grace-period criteria.
UI Components	Agent Dashboard Widget	Clearly reflect updated grace periods for agents.
Event Components	Payment Due Event Scheduler	Adjust event scheduling logic to match the new rule.
Function Components	Auto-Debit Processor	Align debit initiation logic with extended grace period.
Network Components	Notification Gateway	Schedule notifications consistent with updated grace rule.

Multi-Variable Component Impact:

Variables Combined	Components Affected	Impact
Rule Component + Data Component	Eligibility Assessment Module	Update data inputs to reflect new segmentation, ensuring accurate rule execution.
Rule Component + UI Component	Customer Notification Widget	Dynamically update UI alerts and messages consistent with the new grace period rule.
Event Component + Function Component	Auto-Debit Trigger Module	Adjust triggering events and related debit functions simultaneously to reflect the new rule accurately.
Network Component + Event Component	Batch Job Scheduler	Adjust network-triggered batch processes to synchronize precisely with the event logic update.

Observation: Explicit multi-variable modeling ensures complex interactions are governed, not guessed.

Implementation Perspective (Mapped by Component)

Architectural insights translate into precise implementation tasks, clarifying ownership and intended outcomes.

Component	Implementation Task
Grace Period Rule Evaluator	Update configuration; deploy new rule version
Borrower Segmentation Engine	Validate accounts segmentation and filtering logic
Notification Scheduler	Modify timing triggers; validate new schedules
Auto-Debit Initiator	Link to updated rule logic; test transaction timing
Late Fee Calculator	Revise logic; ensure compliance to new rule
Support Agent UI Widget	Update UI logic; ensure accurate messaging

Observation: Clearly defined tasks reduce risk and ambiguity—making implementation deliberate, not reactive.

Operations Perspective (Linked to Business Processes)

Operational validation ensures system behaviors align with strategic intent pre- and post-deployment.

Business Process	Operational Validation Activities
Collections	Test dunning behaviors for varying grace periods
Customer Notification	Simulate SMS/email alert flows
Dispute Resolution	Validate complaint resolution timelines and data flows

Observation: Teams simulate real-world scenarios confidently, as the architecture was coherent before deployment.

Cascading Impact of the Change

Rule changes, even seemingly minor, have cascading effects across multiple architectural perspectives and variables. Clearly modeling these impacts upfront prevents release-day surprises and disruptions.

Level	Impact
Strategy	Ensures alignment with regulatory changes and strategic business intent.
Process	Adjusts processes such as collections, notifications, and dispute management coherently.
System / Subsystem	Integrates updates across all affected subsystems (Rule, Data, UI, Event, Function, Network).
Component Specification	Clearly identifies and updates multiple components (both single and multi-variable impacts).
Implementation	Provides precise, traceable tasks for component updates.
Operations	Validates behavior proactively through scenario-driven testing.
Cross-Variable Effects	Maintains synchronization between rule changes and related architectural elements.

Traditional SDLC vs. ICMG Enterprise Anatomy Model (Project Edition)

Area	Traditional SDLC Problem	ICMG Solution
Scope of Analysis	Limited to IT-focused implementation diagrams.	Comprehensive analysis across all six perspectives (Strategy to Operations).
Rule Representation	Coarse, compound-level rule representation.	Granular rule-element modeling, clearly identifying dependencies.
Dependency Management	Dependencies hidden or implicit.	Explicitly modeled, visible cross-variable dependencies.
Stakeholder Involvement	Developer-centric, limited business visibility.	Explicit involvement across business, operational, and technical stakeholders.
Testing and Validation	Reactive, IT-centric testing.	Proactive, business-aligned, and scenario-driven validation.
Change Management	Technical and isolated tasks, ambiguous business impact.	Clearly mapped tasks linked directly to business objectives and architectural integrity.

Observation: ICMG’s structured, explicit, and integrated approach ensures that rule changes are implemented predictably, strategically, and comprehensively—far superior to traditional SDLC practices.

A Rule Change Shouldn’t Be a Risky Change

Rule changes—no matter how minor—often become high-risk events because traditional SDLC methods lack architectural coherence, visibility, and explicit dependency mapping.

In conventional approaches:

• Dependencies remain hidden or implicit.

• Testing and validation are narrow and reactive.

• Changes are managed without clear architectural context.

ICMG’s Enterprise Anatomy Model (Project Edition) directly addresses these flaws by:

• Clearly modeling each architectural element at the most granular level.

• Explicitly mapping dependencies across all variables (Rule, Data, Function, UI, Event, Network).

• Proactively aligning changes with business and strategic intent through a structured, multi-perspective model.

• Providing precise implementation tasks linked directly to modeled impacts, eliminating ambiguity and guesswork.

• Enabling scenario-driven operational validation to confirm that implemented changes match the intended business and regulatory outcomes.

With ICMG, rule changes transition from risky, reactive events into strategically governed updates that preserve business continuity, operational coherence, and customer trust.

Call to Action

If rule changes are still causing system chaos, consider shifting to architecture-driven governance.

Explore the ICMG Fast Track Rating and Enterprise Select Program, and learn how to deliver predictable, low-risk system changes through architectural precision.

Because even simple rule changes deserve the rigor and governance of a clearly modeled architecture.