Implement IT governance. Covers COBIT, ITIL, governance structure, IT portfolio management, risk assessment, vendor management, and aligning IT strategy with business objectives.
Enterprise IT Governance Frameworks define the policies, processes, roles, and controls that ensure IT systems align with business strategy, deliver consistent value, and remain sustainable at scale. This reference applies when an organisation must standardise IT operations across multiple teams, systems, and locations—especially when adopting or scaling ERP platforms like Dynamics 365 Finance & Operations, SAP, or Oracle Cloud. It matters during major system rollouts, post-implementation reviews, or when resolving recurring issues like inconsistent data, duplicated efforts, or unapproved changes.
Governance begins with defining who owns what across the IT landscape. The most common failure is role overlap without clear boundaries. The key is to define a canonical structure of roles, each with a defined scope, input, output, and decision authority.
Each role is formally documented in a shared governance playbook, stored in a version-controlled repository. The playbook includes:
roles.yml file defining role metadata and responsibilities: roles:
- id: cio
title: Chief Information Officer
responsibilities:
- "Approve annual IT budget"
- "Oversee IT strategy alignment"
- "Approve major project initiatives"
decision-making:
- type: "Final approval"
- threshold: "Approval by 60% of steering committee"
required_inputs:
- "Budget proposal"
- "Project roadmap"
- "Risk assessment report"governance-calendar.json with recurring meetings, deadlines, and owners: {
"meetings": [
{
"name": "IT Steering Committee",
"frequency": "quarterly",
"due": "2024-09-15",
"owner": "cio",
"agenda": [
"Review project portfolio",
"Approve budget reallocations",
"Evaluate EA compliance"
],
"required_documents": [
"Project status report",
"Risk register",
"Change request log"
]
}
]
}Failure occurs when the Application Owner fails to submit a change request before a release, causing a delay. The EA team validates all new integrations using a validate-architecture.sh script that checks for conformance to a set of standards:
#!/bin/bash
set -euo pipefail
INPUT_DIR="$1"
OUTPUT_DIR="$2"
for service in $(find "$INPUT_DIR" -name "*.json" | xargs basename -s .json); do
if ! jq -e '.type == "integration"' "$INPUT_DIR/$service.json" >/dev/null; then
echo "Error: $service.json is not an integration service" >&2
exit 1
fi
# Check required fields
required_fields=("name" "endpoint" "authMethod" "dataModel")
for field in "${required_fields[@]}"; do
if ! jq -e --arg f "$field" '. | has($f)' "$INPUT_DIR/$service.json" >/dev/null; then
echo "Missing required field: $field in $service.json" >&2
exit 1
fi
done
# Validate data model reference
model_ref=$(jq -r '.dataModel' "$INPUT_DIR/$service.json")
if ! [ -f "$OUTPUT_DIR/models/$model_ref.json" ]; then
echo "Data model $model_ref not found in $OUTPUT_DIR/models/" >&2
exit 1
fi
mv "$INPUT_DIR/$service.json" "$OUTPUT_DIR/validated/"
doneThis script is run as part of a CI pipeline and fails on any non-conformant service, blocking deployment.
Changes to systems must follow a consistent lifecycle. The most common failure is ad hoc change requests with no tracking or approval trail.
A change request (CR) is a standard change-request.json object submitted via an HTTP POST to /api/changes:
{
"id": "CR-2024-001",
"title": "Enable cost center tracking in purchase orders",
"requested_by": "[email protected]",
"project": "D365-Finance-2024",
"description": "Add cost center field to PO lines and integrate with GL.",
"impact": {
"system": "D365-Finance",
"users": 120,
"data_volume": "200MB/month"
},
"dependencies": [
"GL-Integration-API",
"Vendor-Management-Module"
],
"risk_assessment": {
"likelihood": "medium",
"impact": "high",
"mitigations": [
"Backup before deployment",
"Rollback procedure documented"
]
},
"status": "draft",
"submitted_at": "2024-05-10T14:30:00Z"
}The change is reviewed by the Application Owner and the EA. Approval requires a minimum of two approvals and a status update via PUT:
PUT /api/changes/CR-2024-001 HTTP/1.1
Host: governance.company.com
Content-Type: application/json
{
"status": "approved",
"approved_by": "[email protected]",
"approval_date": "2024-05-17T11:22:00Z",
"notes": "Approved after review of integration with GL-Integration-API"
}When a change is approved, the system triggers a deployment pipeline. The deployment is tracked in a deployment-plan.json file:
{
"change_id": "CR-2024-001",
"deployment_id": "DEP-2024-001",
"environment": "staging",
"planned_start": "2024-05-20T08:00:00Z",
"actual_start": "2024-05-20T08:02:15Z",
"status": "in-progress",
"steps": [
{
"step": 1,
"task": "Deploy new D365 F&O extension",
"duration": "1200s",
"status": "completed",
"log_url": "https://ci.company.com/logs/DEP-2024-001/1"
},
{
"step": 2,
"task": "Run data migration script",
"duration": "1800s",
"status": "failed",
"error": "SQLSTATE[42P01]: Undefined table: 7 ERROR: relation \"purchase_order_cost_center\" does not exist"
}
]
}The failure in step 2 reveals a common mistake: the migration script assumes a table exists, but it was not created in the deploy-extensions.sh script. The cause is an undocumented dependency: the purchase_order_cost_center table must be created via a schema-migration.sql file that is not part of the deployment package.
Data governance ensures consistency, accuracy, and trust across systems. The most silent failure is data that is correct in one system but inconsistent in another, with no ownership or lineage.
Each critical data entity (e.g., Customer, Product, Vendor) has a data-governance.json file in the central metadata repository:
{
"entity": "Customer",
"domain": "Sales",
"owner": "[email protected]",
"source_system": "D365-Sales",
"target_systems": [
"D365-Finance",
"CRM-Platform",
"Data Warehouse"
],
"data_quality_rules": [
{
"rule": "Primary contact must be defined",
"condition": "customer.primary_contact_id IS NOT NULL",
"threshold": "98%",
"last_run": "2024-05-18T04:00:00Z",
"status": "passed"
},
{
"rule": "Customer name must be unique",
"condition": "COUNT(*) > 1 WHERE name = customer.name",
"threshold": "95%",
"last_run": "2024-05-17T12:00:00Z",
"status": "failed",
"details": [
"Duplicate entry for 'Acme Corp'",
"Duplicate entry for 'Global Solutions Inc'"
]
}
],
"data_lineage": [
{
"source": "D365-Sales",
"field": "Name",
"target": "D365-Finance",
"mapping": "UPPER(TRIM(name))",
"transformations": [
"Trim whitespace",
"Convert to uppercase"
]
}
]
}The data steward runs a periodic validate-data-quality.sh script that checks all rules:
#!/bin/bash
set -euo pipefail
DATABASE="enterprise_data"
RULES_FILE="/etc/data-governance/rules.json"
OUTPUT_DIR="/var/reports/data-quality"
for rule in $(jq -r '.data_quality_rules[].rule' "$RULES_FILE"); do
query=$(jq -r --arg r "$rule" '.data_quality_rules[] | select(.rule == $r) | .condition' "$RULES_FILE")
threshold=$(jq -r --arg r "$rule" '.data_quality_rules[] | select(.rule == $r) | .threshold' "$RULES_FILE")
result=$(psql -d "$DATABASE" -c "$query" -t -A)
if (( $(echo "$result" | wc -l) < $(echo "$threshold" | cut -d'%' -f1) )); then
echo "FAILED: $rule - $result" >&2
exit 1
else
echo "PASSED: $rule - $result"
fi
doneThis script is run daily by cron and fails when a rule’s threshold is not met. The error output is parsed by a monitoring system and alerts the Data Steward via email.
Integration governance ensures that systems interoperate reliably and evolve together. The most common failure is integrations that break without trace, with no ownership or monitoring.
Each integration is described in an integration.yaml file:
integration:
id: "po-to-gl"
source: "D365-Finance"
target: "GL-Integration-API"
frequency: "hourly"
data_format: "json"
schema: "https://schemas.company.com/integration/po-to-gl/v1.2.json"
endpoint: "https://api.company.com/integration/po-to-gl"
authentication:
method: "oauth2"
client_id: "po-gl-integration-client"
scopes:
- "purchase-orders:read"
- "general-ledger:write"
monitoring:
health_check:
endpoint: "/health"
interval: "5m"
threshold: "200ms"
error_logs:
retention: "30 days"
alert_on_failure: true
change_policy:
versioning: "semantic"
backward_compatible: true
breaking_change_threshold: "3 months"The integration is monitored via a health check endpoint:
GET /health HTTP/1.1
Host: api.company.com
Authorization: Bearer <token>Response:
{
"status": "ok",
"uptime": "1423h",
"last_sync": "2024-05-18T10:15:00Z",
"queue_size": 127,
"error_rate": 0.018,
"dependencies": [
{
"service": "D365-Finance",
"status": "healthy",
"latency": 124,
"last_updated": "2024-05-18T10:14:00Z"
},
{
"service": "GL-Integration-API",
"status": "degraded",
"latency": 312,
"last_updated": "2024-05-18T10:13:00Z"
}
]
}When the integration health check fails (status != 200 or latency > threshold), a ticket is created in the central issue tracker. The most common failure is a missing schema-version header in the request:
POST /integration/po-to-gl HTTP/1.1
Host: api.company.com
Content-Type: application/json
Authorization: Bearer <token>
Schema-Version: 1.2
{
"purchase_orders": [
{
"id": "PO-1001",
"vendor": "V100",
"lines": [ ... ]
}
]
}Without the Schema-Version: 1.2 header, the target system defaults to 1.0, causing fields to be ignored or misinterpreted. This leads to a silent data loss: a new cost_center field is sent but not used, because the schema version is not explicitly communicated.
All governance artifacts are stored in a central Git repository. The root directory contains:
roles/ — YAML files for each rolechanges/ — JSON files for each change requestintegrations/ — YAML files for each integrationdata-governance/ — JSON files for each data entitypolicies/ — Markdown files describing governance policiesA governance.yml file at the root defines the rules for the entire system:
governance:
version: 1.0
policies:
- name: "Change Request Approval"
description: "All changes must be reviewed and approved before deployment."
required_approvals: 2
approval_timeout: "72h"
review_template: "https://templates.company.com/CR-Review"
status_transitions:
- from: "draft"
to: "review"
trigger: "submitted"
- from: "review"
to: "approved"
trigger: "approved_by >= 2"
- from: "approved"
to: "deployed"
trigger: "deployment_plan.status == 'completed'"
workflows:
- name: "Data Quality Review"
trigger: "daily"
steps:
- "Run validate-data-quality.sh"
- "Publish report to /reports/data-quality/latest.html"
- "Notify [email protected] if any rule failed"This configuration is used by a central governance orchestrator service that:
changes/ directory for new change requestsgovernance.ymldeployment-plan.jsonThe most common failure is a stale governance.yml file that is not updated after a policy change. The orchestrator uses the version field to detect updates and triggers a rebuild only when governance.yml changes. This prevents outdated workflows from being applied to new changes.
This page was rewritten on 18 October 2026. It replaced a templated version that was not specific to its own title. How these pages are written and checked. If anything here is wrong, tell us at [email protected] and we will correct it.
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