In today’s data-obsessed business environments, the only thing worse than not having any data is having bad data. Poor quality data undermines all of the potential benefits that trustworthy, actionable information provides, such as enabling intelligent decision making, increasing profitability, and improving analytics.
Due to lifestyle changes and accelerated digital transformations initiated by the COVID-19 pandemic, data is being generated and consumed at a historically high rate. This data could either be an analytics goldmine or a complete waste of time, depending on how well it is governed and managed within your organization.
Data governance is all the processes and policies used to ensure that an organization’s data is accurate, reliable, compliant, and secure. An effective data governance initiative breaks down silos between systems that contribute to errors and prevents personal data from being misused, both maliciously and unintentionally.
A well-crafted data governance strategy eliminates data inconsistencies and errors that can complicate integrations, affect the accuracy of business intelligence, and negatively impact regulatory compliance.
Highly regulated industries—such as finance and healthcare—rely heavily on data governance to maintain compliance requirements. However, businesses in every industry should prioritize data quality and implement a governance framework.
Kicking off a data governance or master data governance initiative can seem daunting if you aren’t sure where to start. That’s why we compiled a high-level look at six widely accepted best practices.
These are the three main factors driving a data governance initiative. Although it’s essential to address all three, they don’t all need to be improved at once. Start with the people, because without a strong team, executing your strategy and deploying the right technology will be even more challenging.
Getting buy-in for master data governance always comes down to the business case. Leadership doesn’t want to hear about “data quality.” Instead, they want to hear that implementing a data governance framework will increase revenue by 20 percent or reduce procurement spend by $1.5 million next year.
Measuring progress and demonstrating success in a data governance strategy requires tracking metrics every step of the way. Set an initial baseline, then measure changes over time to determine whether the plan has a measurable impact on data quality metrics.
Open communication is a crucial part of implementing a data governance strategy. The chief information officer (CIO) or chief digital officer (CDO) should take on this role and keep all stakeholders apprised of the status of the implementation, including both successes and setbacks. This will improve visibility and increase stakeholder engagement in the process.
Data governance is a team effort, requiring clearly defined roles and ownership across the organization. At a minimum, the core data governance team should include the following roles:
Data governance committee: This group is responsible for developing the data governance policies and overseeing the entire strategy.
Data stewards: This group ensures the quality of the data by enforcing data standards and policies.
Data owners: This group’s members are held accountable for a data asset.
Data users: This group uses the data during their day-to-day work.
Before launching a data governance initiative, it’s important to set expectations. This is a long-term endeavor, not a one-off project. There is no start and end date. Data governance should be approached as a policy or cultural change and woven into the fabric of the organization.
In today’s data-driven economy, your organization can’t afford to base critical business decisions and customer satisfaction on sub-standard data. Investing in a robust data governance strategy will provide high-value benefits to your organization, including:
Accurate analytics
Strong regulatory compliance
Improved data quality
Lower data management costs
Easier access to data
Data governance strategies will look different across organizations because they are tailored to specific business objectives, compliance requirements, and data assets. Despite differences in strategy, these six data governance best practices are universally applicable and will help your organization improve its data governance maturity level.
For even more data governance insights from thought leaders in the industry, consider watching our short video about how Syniti can support your business on every step of your data journey!