Data is one of the most valuable assets of any organization. Still, the effective management of data assets can also be one of the most challenging aspects of your strategy. A successful data governance program ensures that your data is high quality, secure, and accessible for your business objectives and needs. Complying with internal policies and external regulations is critical now more than ever as businesses gather massive amounts of data from different sources.
Comprehensive data governance programs are core components and critical aspects that can help you improve your Business Strategy. They enable better information-related processes and accurate analytics, which enhance user satisfaction and customer service, reduce costs, and comply with industry regulations. But how do you implement data governance in your organization? And how can you measure its impact on your business performance? In this post, we will answer these questions and help you take control of your data.
What is Data Governance?
Data governance initiatives focus on the best management practices to ensure your data's quality, security, and usability throughout its lifecycle. Governance efforts involve defining the governance roles, business rules, policies, standards, and procedures for collecting, storing, accessing, sharing, and using data in your organization. Data governance activities provide lineage visualization, which lets you illustrate data flows. Lineage tracking activities also help ensure that your data is accurate, consistent, reliable, and compliant with the rules and regulations that apply to your business operations and domain. It also helps you leverage data as a strategic asset supporting your business data goals and objectives. Data governance is how you control your data and make it work for you.
How Does Data Governance Work?
You need to establish a comprehensive data governance framework for managing and using data in your organization. The framework consists of four main essential elements: data strategy, data architecture, data policies, and data roles. Let's take a look at each of them in more detail.
1. Data Strategy
Data strategy defines the vision, goals, and objectives for your data. It helps you align your data governance roadmap with your business strategy and create value from your data. For example, you may want to use data governance to improve user satisfaction, reduce costs, or innovate new products or services.
2. Data Architecture
Data architecture defines the structure, design, and integration of your data. It helps you ensure the quality and consistency of your data and optimize your data processes and workflows. For example, you may want to use data architecture in the data governance implementation process to store and organize your data securely, access your data easily and quickly, or integrate your data from different sources or systems.
3. Data Policies
Data policies define quality rules, standards, and procedures for collecting, processing, distributing, and consuming data. It helps you protect and respect your data and comply with the regulations and ethics that apply to your data. For example, you may want to use data policies to secure your data from unauthorized access or use, comply with the General Data Protection Regulation (GDPR) or other laws that affect your data, or monitor and audit your data activities and performance.
4. Data Roles
Data roles define the responsibilities, accountabilities, compliance requirements, and decision rights of the people involved in the data governance practices. This collaborative process helps you communicate with your data stakeholders and users and ensure everyone follows the data governance framework. For example, you may want to hire subject matter experts to work on different functions and tasks in your data governance teams, such as Chief Data Officer, Data Scientists, Data Analysts, or Data Engineers.
How Can You Measure the Impact of Data Governance?
The data governance process is also a performance. It is important to measure the impact of data governance on your organization and evaluate its effectiveness and efficiency. But how can you measure the impact of data governance? Here are some steps that you can follow:
● Metric Definition: Before you start measuring the impact of data governance, you need to define what you want to achieve and how you want to measure it. You need to align your data governance objectives with your business goals and identify the Key Performance Indicators (KPIs) that can help you track your progress and results.
● Data Collection: Once you have defined your data governance objectives and metrics, you must collect and analyze your data to see how well you perform. You must use reliable and consistent data sources and methods to gather and process your data. You must also use appropriate data governance software, tools, and techniques to analyze and visualize data. For example, common data governance solutions and techniques are surveys, audits, reports, dashboards, or charts. Among the Open-Source data governance software you can use are Collibra and Microsoft Purview. Remember to choose one that fits your business requirements.
● Data Benchmarking: After you have collected and analyzed your data, you need to compare and benchmark your data to see how well you are doing. You must match your current data with your previous or target data to know if you have improved or achieved your objectives. You must also benchmark your data with your peers or competitors to see where you stand in the market or industry.
● Data Reporting: You must communicate and write your data to share your findings and recommendations with stakeholders, business units, and users. You must use clear, concise language and formats to present your data meaningfully and actionable. You must foster a culture of collaboration by using improved data-driven insights and suggestions to boost the performance and strategy of your data governance model. For example, some common data communication and reporting formats are presentations, newsletters, blogs, or infographics.
What are the Benefits of Data Governance?
The data governance journey may sound tedious, but it benefits your business by avoiding poor data quality. Hence, it helps you avoid bad decisions. Here are some of the benefits of data governance that you should know.
A data governance plan can help you master effective data management accurately, consistently, and reliably; in other words, you can trust it to level up your data-related decisions to boost business benefits. Data governance enables access control and analysis of your data more easily, gaining valuable insights and making data-driven decisions faster and more effectively.
2. Reduced Costs
A data governance strategy prevents data duplication, errors, and breaches, saving time and money on data maintenance and repair. Data governance enables optimizing your data processes and workflows, improving operational efficiency and productivity.
3. Regulation Compliance
Data governance allows you to comply with the compliance regulations that apply to your industry and domain, such as the General Data Protection Regulation (GDPR), the Health Insurance Portability and Accountability Act (HIPAA), or the Sarbanes-Oxley Act (SOX).
4. Competitive Advantage
Data governance enables you to leverage data as a strategic asset supporting your business goals and objectives. Data governance allows you to create value from your data, such as new products, services, or innovations. Data governance also helps you differentiate yourself from competitors and gain a competitive edge in the market.
When Should You Start Data Governance in Your Organization?
You cannot postpone or ignore the data governance ongoing process. The sooner you start an effective data governance program within your business, the better. Doing so can avoid confusion and chaos and ensure data clarity and confidence. Furthermore, it helps prevent data errors and breaches, guaranteeing secure and high-quality data, which could be especially important for some lines of business, like Artificial Intelligence (AI) and Machine Learning (ML). By implementing data governance policies at a strategic level, you can reduce data costs and risks and, at the same time, increase data value and collaboration among teams. With the help of your data, you'll be able to achieve your business goals and objectives more efficiently and effectively.
Data governance is an ongoing management concept and a core feature for using data effectively and efficiently in your business process. It can help you improve your business performance, user satisfaction, cost reduction, business outcomes, regulatory compliance, and regulatory requirements.
However, remember that the data governance strategy won't work without business ownership, as it involves defining your data strategy, architecture, bi-directional integration policies, and analytics systems. It also requires measuring their impact through control measurements.
Data governance is not boring but a smart way to leverage key insights and strategic assets of your business context to maintain customer trust. Are you ready to take control of critical data elements and level up the enforcement of governance policies?