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Unlocking the Hidden Value in Your Current GRC Platform
Most organisations use less than 30% of their GRC platform capabilities. Learn how to extract maximum value through GRC engineering fundamentals.
Ayoub Fandi
May 08, 2025
GRC Engineering doesn't always require fancy new tools or complete platform overhauls.
Sometimes, the most impactful changes come from reimagining how you use the investments you've already made.
Your current GRC platform likely contains untapped potential that could transform your program's effectiveness - if approached with an engineering mindset.
Let's explore how to unlock this hidden value through data optimisation, strategic integrations, and workflow redesign.
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Why It Matters 🔍
The why: the core problem this solves and why you should care
Most organisations use less than 30% (free guesstimation) of their GRC platform's capabilities. This represents an enormous waste of both financial investment and potential security improvement.
The reasons are familiar:
Initial implementation focused on basic compliance needs
Limited understanding of advanced capabilities
Lack of technical expertise on GRC teams
Siloed operations between GRC and technical teams
This underutilisation creates a dangerous spiral: you're paying for powerful tools but using them as glorified spreadsheets. When these tools inevitably fall short of expectations, the solution becomes "buy something new" rather than "use what we have effectively."
Random self-help image that gets my point across
The impacts of this pattern can be huge:
Security risks go unaddressed while documented
Engineering teams develop shadow GRC processes
Budget gets wasted on overlapping tools (all-purpose GRC, GRC automation, security automation tool, security scoring tool, etc.)
Integration opportunities are missed
By applying engineering principles to your existing platform, you can break this cycle and deliver significantly more value without additional major investments. As we discussed in previous entries, thinking of your GRC program as a product rather than a project creates the right mindset for continuous improvement.
# The typical GRC platform utilisation pattern
class GRCPlatform:
def __init__(self):
self.capabilities = {
"data_collection": True, # Used ✓
"workflow_automation": True, # Barely used ✗
"integration_apis": True, # Unused ✗
"reporting": True, # Basic use only ⚠️
"analytics": True, # Unused ✗
"risk_modeling": True # Unused ✗
}
def typical_usage(self):
return "Expensive spreadsheet replacement"
def potential_usage(self):
return "Security automation hub"
Strategic Framework 🧩
The what: The conceptual approach broken down into 3 main principles
Reconceptualise Your GRC Platform as an Integration Hub
Stop thinking of your GRC platform as merely a storage repository for compliance documentation. Instead, view it as a central integration hub that connects security data across your organisation, we dug deep on this in From Silos to Systems: GRC Architecture.
Most platforms, even older ones, offer capabilities to exchange data with other systems through APIs, file imports, or scheduled jobs. These connections form the foundation of a truly effective GRC architecture.
By focusing on these integration points rather than just the user interface, you transform your platform from a passive documentation tool into an active component of your security ecosystem.
Prioritise Data Model Optimisation
The most powerful engineering improvement you can make to any GRC platform is optimising your data model. How you structure relationships between controls, risks, assets, and evidence fundamentally determines what's possible with your system.
Many organisations adopt default data structures without considering how they'll support automation, reporting, or decision-making. By deliberately designing your data taxonomy, hierarchies, and relationships, you can enable capabilities that seemed impossible with your current platform.
As we discussed in the Central Data Layer piece, this foundation is critical to effective GRC, regardless of which tools you use. Even basic tools can deliver significant value with a well-designed data model behind them.
Engineer Workflows, Not Just Processes
Most GRC implementations focus on documenting processes rather than engineering workflows. The difference is crucial:
Process documentation describes what should happen
Workflow engineering makes it happen automatically
By approaching your GRC platform as a workflow engine rather than a documentation tool, you can create automated sequences that drive consistent execution rather than just describing ideal scenarios.
This shift from documentation to orchestration fundamentally changes how controls are implemented and evidence is collected. As you know, the goal is to create systems that drive action, not just document risks.
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Execution Blueprint 🛠️
The how: 3 practical steps to put this strategy into action at your organisation
1. Conduct a Platform Capability Assessment
Before you can optimise your current platform, you need to understand what it's truly capable of, beyond what you're currently using.
Start by creating an inventory of:
Unused modules or features you've already licensed
Integration capabilities including APIs, webhooks, import/export features
Workflow automation options like conditional rules, notifications, and approvals
Reporting and visualisation tools beyond standard dashboards
Data model customisation options available to administrators
Don't rely solely on vendor documentation. Talk to other users through communities, user groups, and discord/slack rooms . Engage directly with your vendor's professional services team—they often have insights about advanced use cases that aren't obvious.
Focus especially on identifying capabilities that could reduce manual effort in your most time-consuming GRC activities. For most organisations, these typically include evidence collection, control testing, and risk assessment processes—the core activities we discussed in Control Orchestration.
2. Optimise Your Data Structure for Integration
Even within the constraints of your current platform, you can likely make significant improvements to your data model:
Standardise naming conventions across all GRC data elements
Create consistent taxonomy for classifying risks, controls, and assets
Implement detailed metadata that enables filtering and automation
Design hierarchical relationships that support roll-up reporting
Map connections between risks, controls, assets, and business processes
The goal is to create a data structure that enables meaningful connections rather than isolated records. This often requires some initial cleanup of existing data but pays enormous dividends in enabling automation and intelligent reporting.
Focus on establishing a core set of standard fields that serve as "universal identifiers" across systems. For example, ensure asset identifiers in your GRC platform match those in your CMDB or vulnerability scanner to enable future integration. This approach directly supports building a Central Data Layer for your organisation.
3. Build Low-Effort, High-Value Automation
With an optimised data model, you can now create automations that deliver immediate value:
Evidence collection workflows that trigger reminder emails and escalations
Control testing schedules with automated task assignment and tracking
Status update processes that notify stakeholders of changes
Approval workflows that capture decisions and responsible parties
Reporting jobs that generate and distribute key metrics
Start with simple automations that address your team's most painful manual tasks. Success with these initial projects builds momentum for more sophisticated workflows, similar to what we’ve dove deeper into the control orchestration entry.
Don't overlook the power of even basic automation. A simple scheduled report or notification workflow can save hours of manual effort each month, gradually freeing your team to focus on higher-value security activities rather than administrative tasks.
Did this help you better leverage your current GRC Tool?Send an email back with your feedback, might include it next week! |
Content Queue 📖
The learn: This week's resource to dive deeper on the topic
This week, if you haven’t read the first Edition of the GRC Market Pulse, I really recommend you do. We dig deep on Anecdotes while also giving mental models and frameworks to assess your vendor and make better buying decisions.
This also relates to this week’s entry as better understanding your current tool, its capabilities, its advantages and shortcomings can help you determine where you need workarounds, additional work and some plumbing.
That’s all for this week’s issue, folks!
If you enjoyed it, you might also enjoy:
My spicier takes on LinkedIn [/in/ayoubfandi]
Listening to the GRC Engineering Podcast
See you next week!
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