Data is a vital asset for modern organizations, providing insights that drive strategic decision making. And the amount of data created, consumed and stored is only increasing. Without proper management, the information gathered can become unwieldy and unusable, compromising analytics and insights and threatening operational efficiency and business performance.
Here's how businesses can maximize their data’s potential.
The value of data
Data governance is essential for effective data management. It establishes a framework for structuring and organizing information—including how it’s defined, cataloged, stored and accessed—and the rules, policies and processes for handling it. This framework creates a unified reference point for quickly identifying what data is collected, where it comes from and how to access and use it.
Data governance defines the purpose, vision and goals underpinning a company’s data practices and builds trust in the quality and integrity of data to advance strategic objectives. Rather than viewing data governance merely as a set of security and compliance procedures, treating it as an enabler unlocks its power to transform data into business strategy by producing consistently high-quality, trusted information for qualified, fact-based decisions.
The dangers of bad data
Executives often question the quality of their data when making data-driven decisions. Bad or poor quality is not just incorrect; it is irrelevant, disorganized, inaccessible, duplicative, inconsistent or contradictory. Bad data can stem from a lack of vision, strategy and controls around data management. In organizations that don’t prioritize governance, valuable information is often inaccessible and untrustworthy due to the absence of a unified source of truth. Disorganized and disparate sources across multiple systems and applications trap data in silos, hindering its quality and potential.
Bad data is a significant business liability. It can cause errors and inefficiencies, reducing productivity. Employees waste approximately two hours daily on non-value-added activities, primarily tracking down or validating information. Making important business decisions based on incorrect data or misleading insights can steer an organization down the wrong path, endangering its market share, reputation and consumer trust.
How to create a data governance plan
When developing your data governance plan, you'll need to define the scope, objectives, stakeholders and risks, as well as determine how the plan aligns with the overall strategic goals of the organization. Building out a robust plan may require months of pre-planning with involvement from a multitude of departments, including executive leadership, IT, legal and the data management teams. Depending on the complexity and structure of your organization, timelines will vary dramatically, but here are a few steps to help you get started.
Define your goal
The primary purpose of collecting data is to gain intelligence—you want to learn something about the company or its environment to develop strategies and initiatives that improve the business. However, many executives I know admit to not using all their data effectively. Developing data as an asset with a defined purpose and future goals helps clarify the problems a company needs data to solve, such as increasing operational efficiency, reducing costs, driving innovation or enhancing customer experiences. This approach also changes the vision and philosophy around data practices by applying a “customer” lens to understand and meet user needs.
Investing in data as an asset plans for an unknown future by designing an extensible data governance model that can evolve with the business' needs. This allows organizations to scale data operations with a strategy and roadmap for growth and transformation. Purpose-driven data governance provides a centralized, structured approach to embedding data capabilities that maximize data quality and usefulness throughout its lifecycle. It also facilitates continuous improvement with a structure for refining and enhancing data quality and usefulness.
Prioritize high-quality data
High-quality data is essential for making informed business decisions and developing reliable analytics. Good data is accurate, consistent, complete, timely and relevant. Feeding good data into business models helps organizations identify market trends, customer preferences and innovation opportunities, as well as predict outcomes, solve business challenges and drive performance and profitability.
Data governance builds a system for cultivating high-quality data from the point of creation. It enhances the quality and reliability of business insights derived from data by ensuring only the best, most useful information is presented for analysis through multidimensional collection, categorization and filtering. These factors turn data into business strategy by eradicating bad data and creating consistently high-quality, trusted information organizations can use to navigate complexities and opportunities, improve decision making and foster innovation with confidence and agility.
Educate your team
For an organization to become truly data-driven, data management must be holistic and centralized, with everyone responsible for understanding and applying best practices. Before expending resources on data governance, companies should understand how data impacts the business, including the value of their existing data, how its volume is predicted to grow over time and how they plan to use it to advance business objectives.
Education is the key. It should be engrained into the foundation principles of the organization starting with the onboarding process. All new employees should understand the importance of data integrity from the day of hire. Continual reinforcement via presentations or town halls can be implemented to ensure the message is being delivered to existing employees. Seek to inform employees about the importance of quality data and the ramifications of poor quality data.
With a tailored strategy and a measured approach, organizations can design a scalable governance program that enables data to evolve in the right direction to deliver continuous value.
Written by Cory McNeley. Originally published by Forbes.
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