Making decisions based on empirical evidence is increasingly recognized as essential to the success of today's businesses. Large amounts of information, including PII, are handled by insurance companies every day making data management extremely difficult. However, a good data governance strategy reduces overhead costs by enhancing data quality and streamlining access to critical information for teams. To that end, let's investigate the topic of data governance and how implementing best practices contributes to the success of a given strategy.
Information entering a system must adhere to specific standards and rules established by the business. Data governance is the process that ensures compliance with these rules. It gives organizations command over their data assets and their management. Now, let’s take a look at the three facets of data governance that ensure data is valid, accessible, and appropriate for its intended purpose:
Having a solid data governance strategy is crucial in industries requiring strict adherence to rules and regulations, such as banking and insurance. Organizations need formal data management processes to govern their data throughout its lifecycle and show they comply with regulations.
Practical data governance breaks down data silos in insurance ecosystems and boosts trust in the collected information. In this way, actuarial professionals can rest assured that they have access to the most recent and reliable information for their daily work needs.
By implementing a practical data governance framework, you can improve data consistency in generation, security, and handling. This is useful for passing data audits and complying with legal and industry regulations.
Many insurance companies need help to develop a data governance strategy and data management plan. The following methods and recommendations will help lessen the pressure:
Get the details right before you tackle the big picture
People, processes, and technologies all play integral roles in data governance. It's best to begin on a small scale and expand to the complete picture. Assemble the team first, establish the procedure, and implement the technology. A comprehensive data governance strategy should be constructed, with each part building on the previous ones.
Also Read: Data Governance & Integration in Insurance: Unlocking Value & Benefits
Consider the present condition of data governance
Get a handle on where things stand with current data governance initiatives and their success so far. Find out where you're falling short regarding data stewardship, data quality, data management, or master data management, and which parts of governance require improvement. The insights gained here will shape the overall approach to data governance.
Connect data governance with business objectives
First and foremost, your company needs to know what it hopes to achieve through its data governance process. Data that aids in risk reduction, data that provides insights, and data that guide operational decisions are the three crucial objectives for the insurance sector. This is typically broken down into these three groups within the insurance industry.
Design a data governance framework
Ideally, you should build a data governance framework that lays the groundwork for data management and preserves the value of data. The management of data storage is improved by having robust data governance policies, tools, and techniques in place. However, it is just as crucial to educate staff on the importance of adhering to the policies in place to keep sensitive information secure.
Besides these primary pillars, a data governance framework also needs:
Engage stakeholders on three fronts
Aligning stakeholders at the strategic (executive management), operational (product development, planning, etc.), and tactical levels of the organization are the next step (including data management and data science).
Success or failure is typically measured in unique ways by various communities. To increase involvement from all three layers of management, the data governance process must cater to the specific requirements of each stakeholder group.
Put together a set of guidelines, manuals, and metrics
Data governance guidelines and procedures ensure that appropriate controls are in place and data is well-protected. So, it is critical that data governance policies are procedures are firmly established, informed, and reinforced through appropriate training to all those involved in handling data. Ensure that your documentation has details of every approach and will serve as a reference point for any changes or enhancements that may be made in the future. Finally, come up with a list of metrics to track. This will provide actionable insights into the success of governance systems in your firm and helps you determine if your business is aligned with your data governance objectives.
Embrace technology and use it to your advantage
With the right technology, your company can collect, manage, and secure data according to its governance goals. Automation is a valuable tool when it comes to improving and ensuring the ongoing efficacy of the data governance program. As a bonus, technology, and software can be used for:
Keep adapting the framework
Constantly adapt your framework to the evolving needs of your company. A well-executed data governance initiative will smooth out stakeholder processes, making it easier for them to carry out their duties and produce the desired results.
Parting thoughts
Considering regulatory and auditing concerns while developing a data governance plan can be daunting. However, having better visibility into data risk and regulatory compliance is invaluable when it comes to managing data governance programs. Therefore, organizations can significantly boost the efficacy of data governance processes by adopting these best practices. Implementing these best practices will become a seamless process with our professionals from Trueloader in your corner. Give us a call today!
