Adapt to Change with Flexible Data Models

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Written by: Chris Clarke

Reviewed by:
Updated: June 06, 2023

Table of contents

Being operationally resilient is no longer an option for most organizations—it’s a survival technique. Agile organizations must build in the flexibility needed to pivot as a result of internal or external market changes. Whether navigating changing market conditions, adopting new regulatory requirements, confronting a pandemic, or integrating a strategic acquisition, companies must adapt how they do business, and their supporting governance, risk, and compliance functions have to follow suit. 

When market conditions dictate new business requirements, the data model an organization relies on must also be reconfigured to optimize decision-making. A data model documents the way data is stored and retrieved, as well as the web of interrelationships and communications between different data elements. As your requirements change, companies with a more flexible approach to managing data can quickly make adjustments and adopt new ways of working.

LogicGate Director of Customer Success Szuyin Leow shares how organizations can adapt to change with flexible data models and the importance of flexibility in tracking and managing data relationships in the LogicGate podcast, GRC & Me

Szuyin shared, “When we have new requirements or new impacts from external factors like COVID-19 impacting a business, we need to be able to react quickly and make sure that these very critical processes that GRC functions are responsible for can adapt and address them as quickly as possible.”

In a dynamic market, companies employing rigid data models designed for specific use cases and market conditions will find themselves falling behind as they invest time and money to adapt that inflexible model to changing market conditions. It may take months or years to be able to introduce a new data control set or workflow, which means losing out on market opportunity and potentially ceding market share to more nimble competitors. 

Advantages of a Flexible Data Model

One key advantage of a flexible data model is an iterative approach that allows companies to assess what works best for you. When considering use cases, companies across an industry will have similar requirements for GRC functions. However, your data hierarchy or methodology for risk assessment will be specific to your needs. A flexible data model allows you to meet your distinct needs while also having the ability to integrate new requirements so you can react and adapt quickly to changes in a manner consistent with existing practices and workflows. 

Flexible data models adjust based on how your company grows and changes over time. LogicGate’s customizable and extensible model enables companies to start with a single workflow, assess its efficacy, and iterate until the model meets your needs. Companies can start with an industry-standard data structure for a GRC process, adjust it to your organizational context, and innovate as business requirements evolve. When ready, the model can expand to include additional processes and functions. 

How A Flexible Data Model Can Help Your Company Adapt

A flexible data model helps your company respond and quickly adapt to internal or external market changes.

Using the COVID-19 pandemic as an example, a flexible data model can quickly incorporate new health and safety protocols into your company’s control repository in order to adopt new processes, compliance assessments, or workflows. A data model with a rigid framework would be unable to pivot as quickly. 

A flexible data model can help companies adapt to internal changes, too. This is particularly important when integrating two companies that may employ two distinct data models and processes. Rather than taking months to integrate, a flexible data model can connect, realign, or redraw lines and workflows in order to mold to a new post-transaction structure. Easy access to and identification of risk owners, mitigations, and tasks will avoid any GRC lapses through the integration process. 

Incorporating a Flexible Data Model

As Szuyin notes, to successfully adopt a flexible data model in your organization, it’s important to:

  1. Start with the end in mind 
  2. Engage the necessary stakeholders 

Starting with the end in mind means agreeing on what insights and outcomes your company is hoping to achieve so they can effectively be incorporated into the reporting requirements, whether that is for senior management, the board, or any other stakeholder. On engagement, this model works best when the stakeholders that will use the platform align on their needs and requirements before diving into the design. LogicGate’s visual representation of the flexible data model helps facilitate that discussion to successfully engage all stakeholders. 

How LogicGate Can Help

Flexible data models help companies stay agile and responsive to changing demands and ready to pivot to new opportunities. It’s time for you to build the risk program based on your organization’s needs and not based on the limitations of your technology or platform. Explore LogicGate’s Risk Cloud™ platform for customized GRC solutions.

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