Convincing Upper Management it’s Time for Data Governance
Quantifying the Value of Data Governance Efforts
Data is universally accepted as one of the most valuable assets across any industry. Businesses of every size are leveraging data to substantiate every business decision, optimize day-to-day operations, improve the customer experience, enable digital initiatives and eventually gain a competitive advantage. However, with data being collected and deployed at a rapid pace, there is a real danger of data assets becoming liabilities if organizations don’t have a comprehensive data governance program in place.
Data governance serves an important enterprise function by setting parameters for data management, driving data issue resolution processes, and actively measuring for data quality levels and improvement. An effective data governance program empowers business users to make decisions based on trustworthy, reliable data.
Starting a data governance program isn’t easy because it takes a significant amount of time, requires buy-in from diverging departments and needs a significant financial investment from upper management. Acquiring budget for the program is especially difficult because creating a business case with quantifiable monetary benefits is a challenge. The major advantages are typically business confidence in the data because of common definitions, the ability to track data usage and the ability to trust the quality.
To educate executive leadership on the value of data governance and to obtain adequate budget, IT and the business team must prove the program’s value beyond financial gains.
Proving the Value of a Data Governance Program
With data governance, it’s challenging for any organization to put together a comprehensive cost/benefit analysis because the value is largely indirect, but that doesn’t mean there isn’t any. There are a wide variety of other benefits that can be realized from data governance that illustrate its value and can help gain both buy-in and budget from upper management.
For one, data governance can provide a huge advantage for business users attempting to leverage data for business decisions. Data governance helps business users understand what data means, where it resides, who owns it and how to properly consume that data. With it, the data management team is no longer slowed down by requests from business users, allowing them to use their time more efficiently.
Data quality is also a critical component of data governance. Data quality fosters trust in an organization’s data landscape, helping to reinforce the validity of business decisions. Data governance also helps verify the accuracy and completeness of data. When business users modify data sets for their own needs, data can become inconsistent across the enterprise. A proper governance program dictates the authorized sources for data sets and guides users on how to pull information appropriately.
Without properly governed data, organizations can unknowingly make business decisions based on outdated, inaccurate or incomplete data. However, with a comprehensive data governance program in place, organizations can proactively ensure data issues are resolved instead of spending time and energy reacting to emergency data issues or running the risk of potential regulatory noncompliance.
The benefits of a data governance program are endless. Once upper management has been swayed, organizations need the right technologies to ensure successful data governance.
Generating a Successful Data Governance Program
Successful data governance requires an all-inclusive solution suite to maximize both the organization’s data quality and the insights that data can provide. The solution suite should include data governance capabilities to provide business users with a comprehensive view of their data landscape, allowing users to easily define and understand data and associated business terms, facilely track data lineage and readily manage all aspects of their data assets.
In addition, the solution suite should also include data quality capabilities to conduct data quality checks such as data profiling, consistency, conformity, completeness, timeliness, reconciliations, visual data prep and machine learning to verify the quality of data and ensure continued trust among business users. The solution suite should also combine analytics capabilities and apply machine learning algorithms for self-learning to monitor and continuously improve data quality.
The solution should facilitate a broad understanding of an organization’s data landscape, enabling data owners, stewards and business users to effectively manage, share, and utilize data to drive growth and ultimately increase profits. When business users have trust in data integrity and confidence in their data knowledge, leading to increase data utilization and better business insights, executive leadership will know that implementing a data governance program was a smart and savvy investment.
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