The Kenway Guide to Data Governance
We’re well into the era of digital transformation, but many businesses still struggle to leverage data to drive business decision-making and growth. There is an abundance of technology that provides the ability for businesses to operate smarter, faster, and more competitively. Technology and capability alone, however, do not unleash these advantages. Being able to intelligently mine the vast amounts of information available is what differentiates organizations. The challenge is ensuring a good foundation—the quality, integrity, and security of the data being used by those technologies. That’s where data governance comes in.
Data governance defines how your organization manages its data. By taking an intentional approach to data management, you can be sure that reliable, accurate data is available to your employees and technologies when they need it. With standardization and rules in place, you set the foundation for improving your organization’s data maturity and realizing the elusive goal of operating a data-driven organization.
Despite the fact that 67% of executives recognize the value of data governance, only 42% say they have an actual strategy in place. For many businesses, other priorities (like meeting evolving customer needs and staying ahead of the competition) take precedence over data governance. However, failing to implement enterprise data governance in favor of pursuing these projects is counterproductive.
In this guide, we’ll define what data governance is, why it’s critical to digital transformation, highlight its importance across different industries, and outline the steps needed to implement a successful data governance program.
What Is Data Governance?
Data governance is the collection of clearly defined policies, procedures, standards, processes, roles, and responsibilities that ensure the effective and efficient use of data in enabling an organization to achieve its goals. Your data governance strategy defines who can take action on data, the data they can act upon, and the methods they can use. A data governance strategy is made up of the following elements:
- A vision for how data accomplishes and supports the business strategy
- Policies and standards that guide how data is acquired, transformed, and connected
- Procedures required to cleanse historical data, update systems, and deploy operational processes to adhere to policies
- Roles and responsibilities for the people tasked with sponsoring, directing, and providing operational support for data governance procedures
- Education, communication, and data literacy to engage the entire organization in advancing data
The data governance strategy must be defined by business drivers. Without this connection, it has a tendency to be bureaucratic and stifling. For example, the data governance program for a financial institution should focus on protecting the privacy of client data as it flows through the organization. Standardizing key data attributes and defining the policies for interacting with data ensure that sensitive information is handled correctly and consistently throughout the organization. In contrast, a manufacturing company will focus much less on the privacy of client data and would instead focus on standardizing parts and operational metrics.
Why Enterprise Data Governance is Essential for Digital Transformation
As every aspect of society rapidly digitizes, being able to navigate the ever-evolving landscape of digital transformation has become essential for every business in every sector. Success depends on the business’ ability to leverage data effectively. According to many industry experts, data has replaced oil as the world’s most valuable resource. On its own, raw data doesn’t have much value. However, when you learn how to refine it to information or knowledge, it becomes a valuable tool for decision-making, discovering insights, and collaboration.
Achieving these objectives can be easier said than done. Even if you invest in the most innovative analytics platforms and technologies, data silos, quality issues, and inefficiencies will undermine their effectiveness.
Following data governance best practices ensures you take a more deliberate approach to data management so that your organization’s data is used in the right way, by the right people, at the right time. When the people and systems interacting with data across the enterprise work in harmony, you can overcome many of the common hurdles to realizing your digital transformation vision.
1. Improve Reporting and Dashboards
With data readily available, clear to understand, and easy to trust, it’s easier to manipulate and leverage data to perform advanced analytics and generate consolidated, up-to-date reports.
2. Use Resources More Effectively
By promoting a proactive approach to data management, data governance reduces the time spent on data cleanup and other reactive projects. It also supports self-service and automation tools, which frees up IT and data analytics teams to work on more productive tasks.
3. Improve Integrations
Standardizing and mastering data and how it’s handled throughout its lifecycle allows for more seamless system integrations, which supports better collaboration with internal teams and external partners. Additionally, it allows for fluid omnichannel customer experiences.
4. Future-proof Your Data
Technology is changing so rapidly, it’s hard to predict which innovations you’ll implement in the future. Your data governance strategy ensures that you maintain data accessibility and usability so that you can onboard new tools quickly and confidently.
5. Reduce Risk
When your company has solid data governance practices in place, it can reduce the risk of data loss due to human error by ensuring employees follow established procedures for handling sensitive information. Demonstrating effective controls also allows you to reduce the risk of legal action from regulators.
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What Is the Role of Data Governance for Different Industries?
Digital transformation has been top of mind for business leaders for years, but the COVID-19 pandemic sent digitization into overdrive. To pivot their business practices rapidly and leverage digital tools more effectively, businesses across sectors had to step up their data capabilities. Here are some of the unique data challenges that data governance can address for some of today’s largest industries.
The healthcare industry generates 30% of the world’s data volume. A majority of healthcare executives say they can’t trust their data, and that interoperability is a major hurdle to implementing strategic data initiatives. Data governance allows healthcare organizations to take better control of the massive amount of data they manage to improve record-keeping, reduce treatment errors, deliver services more efficiently, and comply with regulations.
Telecom providers are at the forefront of many digital innovations, and they’re under immense pressure to optimize networks, protect data security, and deliver personalized customer experiences. To address these challenges, it’s important to be able to analyze complex data sets and create a 360-degree profile of your customers. By centralizing and standardizing data, you can ensure that analytics platforms receive reliable, up-to-date data. You can also develop a holistic view of your customers to deliver a customized experience.
Financial institutions face an ever-changing slate of regulations, ranging from Know Your Client (KYC) standards to cybersecurity rules. Maintaining compliance has become a significant challenge. With data management practices backed by a data governance strategy, financial services firms can maintain and access the records needed to meet regulatory requirements and adapt as regulations change in the future.
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How Data Governance Supports Data Privacy
Regulators and consumers have grown increasingly concerned with data privacy. Each year, new data privacy laws are enacted or refined, and managing data privacy will continue to be a key focal point for all businesses in the years ahead. Data governance, especially data governance at an enterprise level, can help organizations avoid the legal consequences and public fallout of non-compliance and data privacy incidents.
Data governance also helps to prevent the mishandling of protected information. When employees clearly understand data policies and can easily access the data they need, you can reduce the likelihood that they implement workarounds that may expose sensitive data.
As part of your data governance program, you can identify high-risk, high-value data so you can ensure that it’s properly protected according to its level of sensitivity. This allows you to implement data privacy tools like OneTrust more effectively. Data must be inventoried, classified, and follow well-defined workflows to ensure your data privacy solution is truly compliant.
How to Build a Data Governance Program
Once an organization recognizes the need for a data governance strategy, it’s time to create a plan. Whether you are starting from scratch or revamping your enterprise data governance strategy, these steps will help you craft a well-defined plan.
1. Define your goals.
What are the key business drivers (such as compliance, customer satisfaction, or innovation) for your organization? Defining your desired outcomes up front will impact the decisions you make about policies, procedures, and responsibilities as you create your program.
2. Establish a clear business case.
Because data governance can take a backseat to other priorities, establishing the business case helps to align stakeholders on its worthiness as a project. Be prepared to demonstrate how data governance can help ensure the success of strategic initiatives and address current data frustrations.
3. Choose your data governance model.
There’s no one-size-fits-all approach to data governance. However, there are three common frameworks used to implement data governance: centralized, hybrid, and decentralized. Your organization’s data governance model will depend on your company’s needs, objectives, and resources.
4. Establish an invested team of senior-level stakeholders who have authority and credibility to ensure these rules are followed.
To be effective, data governance adoption requires buy-in and engagement from senior leaders. They help guide the data governance strategy so that it aligns with the overall corporate vision. Also, data governance needs to be ingrained into the business culture or it will undoubtedly fail. Leadership plays a vital role in ensuring that everyone, at every level of the organization, understands their role in data governance, is engaged with the program, and has the data literacy needed to use information effectively.
5. Determine which team members will be involved in developing and enforcing the data governance plan.
This can include subject matter experts (SMEs) with knowledge of specific areas, like human resources, or widely used tools, like Salesforce. They should also be supported by people with general expertise in areas such as IT or data management. You’ll want to include representation from across departments so that everyone has a stake in ensuring compliance throughout the organization’s data environment.
6. Define the scope of your data.
Where does your business generate, ingest, or share data? Before diving into policies, procedures, and roles, it’s important to understand your data sources and outputs.
7. Determine the rules for your data.
Create policies defining how data will be managed. Policies should be set at both the organizational and data element levels. Organizational policies may include mandates for the creation of data dictionaries that include metadata, lineage, and data quality rules for all company data. Lower-level policies may include rules around the appropriate use of data fields, such as whether a field is required and what determines completeness.
8. Determine which tools and resources are necessary for implementing policies and procedures.
Create and implement technical tools (such as front-end entry screens, required fields, and drop-down lists) employees will need to adhere to data governance policies. Technology is only part of the picture. Training, communication, and data reviews are also necessary to ensure that policies are executed and enforced.
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Build Your Data Governance Program with Help from the Experts
By taking the time to implement and refine your data governance program, you can lay the foundation for successful digital transformation. As you invest in advanced technologies and offer more digitally based services, your data governance strategy ensures that your most valuable asset—data—is always available and accurate. It removes many of the barriers to effective reporting, integration, and analytics so you can reduce risk and maximize your technology investments.
The key is to use best practices and a proven, methodical process that is customized to your unique organization. If you are unsure of where to start and need support in developing, revamping, or integrating data governance best practices into your business processes, Kenway can help. We work with complex organizations, from startups to those in highly regulated industries, to implement data governance throughout the enterprise. With the right foundation set by data governance, they’re able to reap the full rewards of digital transformation and promote data-driven processes across the business.
Schedule a consultation to learn how we can help you do the same.