Data Governance: Quality and Security of Marketing Data

Introduction

We live in a digital world filled with nuances and challenges. In this context, marketing faces enormous obstacles. The competition? Absolutely fierce. Brands constantly battle for consumer attention. And the fragmentation of communication channels? A labyrinth that makes reaching the right audience a true feat. But it doesn’t stop there. Data privacy and security? Under intense inspection. More informed consumers demand transparency and protection.

Consider the speed of changes. It’s overwhelming. Marketing has no choice but to adapt to this frenetic pace. Consumer expectations? Constantly rising. They crave personalized and relevant experiences. Here enters the effective management of data, a crucial element to meet these growing demands.

In this storm of challenges, the need for a structured and robust approach is clear. Without a good governance strategy, data becomes a liability, not an asset.

What is Data Governance?

Data governance is the process of managing access, quality, and security of data, including collecting and organizing data from various sources and using it to make critical business decisions.

The goal of marketing data governance is to ensure that the right people have access to the correct and consistent data they can use to make decisions. Additionally, good data governance protects your data against unauthorized access and security breaches.

A solid data governance strategy is vital for any organization that uses data to drive business growth, make more accurate decisions, and ensure success in a competitive market. When collecting vast amounts of internal and external data, it is essential to develop a strategy that preserves this information, optimizes expenses, and achieves business objectives efficiently.

A significant part of data governance lies in creating a program that deconstruct data silos, or information islands, that form when an organization has various computerized systems, spreadsheets, and disconnected apps, creating an illogical isolation of data, duplication of the same, and even inconsistency of information (by generating numerous sources of truth).

This usually involves collaborative engagement with stakeholders from isolated business segments. The data governance solution must take primary responsibility for ensuring that meticulously organized data is employed appropriately and integrated accurately into systems.

Adopting a resilient data governance strategy helps ensure your information is:

• Cleanly audited;
• Evaluated;
• Documented;
• Managed;
• Protected;
• Reliable.

What are the benefits of good data governance?

Data governance is not just a best practice, but a critical necessity for modern organizations. It offers a range of benefits beyond simple organization and security of data, such as:

• Better data quality: Your team avoids uncertainties regarding the completeness, consistency, and security of all data available for use.
• Enhanced data management: Helps establish a code of conduct and best practices to ensure your team addresses organizational needs and concerns promptly and consistently.
• Faster and more consistent compliance: Having clean data management throughout your governance process means that procedures generate, handle, and protect your data correctly to keep it compliant.
• Reduced costs and better profit margins: Eliminating decisions based on outdated information results in efficient daily operations, easier audits, and reduced waste.
• A single source of truth: All decision-makers work with the same sets of data, terminology, and vision. With the same terminology, it becomes easier to converse in a common language, making the communication process more agile. Additionally, costs can be reduced by eliminating possible redundancies of information.

What are the challenges of data governance?

While data governance offers significant benefits, it also faces various challenges that organizations need to overcome to implement and maintain an effective strategy. These challenges can range from technical issues to organizational and cultural issues, such as:

• Data Complexity: With the increasing variety and volume of data required with ever-greater speed, managing and organizing it becomes increasingly complex.
• Lack of Awareness and Education: A lack of understanding of the importance of data governance and how to implement it correctly can be a significant obstacle.
• Organizational Resistance: Changing organizational culture and obtaining the commitment of all stakeholders can be challenging. As data spans multiple departments, clear top-down leadership is required, along with multifunctional collaboration.
• High Costs: Implementing and maintaining an effective data governance strategy may require significant investments in technology, training, and human resources.
• Security and Privacy Issues: Protecting data against unauthorized access, leaks, and cyberattacks is a continuing necessity and becomes a challenge as new forms of attack are developed.
• Constant Regulatory Changes: Data protection regulations are constantly evolving, requiring organizations to adapt quickly and continuously.
• Data Integration: Integrating data from different sources and systems can be complicated and requires consistent standards and protocols.
• Risk Management: Identifying, assessing, and mitigating risks associated with security, privacy, and data integrity is an ongoing and challenging task.
• Poor data management: If your data management is structured from an incomplete data governance solution, the data will be insecure and isolated, in addition to having undisciplined processes — possibly leading to massive data breaches and non-compliance.
• Standardization: Organizations need to find the right balance between governance standards and flexibility.

What is the relevance of a Data Governance Solution for Marketing?

A data governance strategy is fundamental for modern marketing. The best practices of data governance are a formal set of policies, processes, and procedures that determine how data is handled as it flows through the organization. A strong data governance strategy should seek to break down data silos, create standards for data format, storage, and handling, and ideally create that single source of truth that marketing professionals dream of.

Good marketing data governance helps your company improve marketing efficiency, for example:

Compliance

Laws like the EU’s General Data Protection Regulation and the General Data Protection Law (LGPD) require organizations to closely meet consumer preferences regarding data. Penalties for violations can be enormous. Managing permissions and privacy is nearly impossible in an organization with isolated data. Customers might express their preferences to the customer service department, for example, and marketing might continue using their data, unaware that the customer has opted out using another system.

Customer Trust

Customer relationships are built on trust, and customers increasingly expect transparency about how their data is used and whether it is to their ultimate benefit. A good data governance strategy can help gain and reward that trust, allowing companies to make strong statements about privacy and data use. Additionally, data governance can provide proof that customer requests are being met throughout the organization.

Consistent Customer Experience

Data governance can also actively improve the quality of your marketing and its relevance to customers. In an organization with isolated data, for example, a customer might buy a product in your store, be dissatisfied with the purchase, complain to customer service, receive a refund, and then receive a voucher by email to buy the same product. A good data governance strategy that unifies and standardizes data across the organization creates a working memory of each interaction with an individual customer, both online and offline.

Customization Capability

All of the above are primarily concerned with data governance from the customer’s perspective. From a marketing standpoint, there are also clear advantages. With a centralized and standardized data source available, analysts can apply machine learning to identify trends, identify buying signals and customers at risk of churn, among others. Intelligent algorithms can even create audience segments based on the behavior of customers who have chosen to remain anonymous.

With all these benefits in mind, it is undeniable that having a data governance solution is essential for Marketing. Let’s explore the best practices now in developing a strategy.

Best Practices in Developing a Data Governance Strategy for Marketing

Despite the consensus that we should get rid of the previously mentioned Data Silos, there is no single way to develop a data governance strategy. Each company has its own reality, its systems, data, managers, and peculiarities.

For this reason, the first step in developing a more intelligent data governance strategy is to map the data landscape of your organization. It’s important to understand where different types of information are stored, who has access, and where data is being duplicated or connected to other systems. To aid this understanding, diagrams of flows, systems, and databases are very important and serve as a true map.

It is doubly important to distinguish where personally identifiable information is stored and who has access. This type of data is extremely important for legal compliance and customer permission management.

Once this map is defined, you can begin implementing the governance journey. Remember these best practices:

• Centralize policies: It is important to define your strategy for the entire organization, with a minimum of exceptions. This will make it easier to manage change, as well as monitor and ensure compliance. Centralization also reduces the IT overhead required for governance.
• Standardize data formatting: If your marketing department uses the dd/mm/yyyy format, but customer service uses mm/dd/yyyy, combining your records can cause confusion. Standardization is a crucial part of centralization. Automated tools can make data cleaning a less time-consuming manual process.
• Think about the future: Your organization will absorb more data over time, not less. Any data governance strategy should take future growth into account. This should include practical considerations like storage and access control, as well as concerns with processes and people. Your data governance plan should also take into account possible future privacy regulations. While it is not possible to predict the future, the processes and systems you implement should have the flexibility to meet new guidelines and restrictions.

The start of a data governance program often looks messy, with new processes and policies crossing many layers of the organization. While no one can be responsible for managing your data, it is important to create an ordered structure that defines each layer:

• IT administration is the lower layer, governing direct access to various tools and technologies. When setting up a data governance system, you want to avoid creating a tangled web where each department or team uses its own set of tools. For consistency, it’s best to implement the same linear flow throughout the organization.
• A data engineering layer is usually responsible for ensuring that data is accurate and consistent and that everyone is using the same set of definitions. Each person should have some view of business performance to inform their day-to-day decisions. While people may not always look through the same “window,” they should see things that are compatible. Otherwise, everyone will start questioning what they see, undermining trust and organizational alignment.
• The human layer is often the most difficult to manage. In the end, the tools, technologies, and systems that IT and data engineering teams set up only work if they are used and maintained as intended. Therefore, simply establishing clear governance processes and conventions is not enough; people also need to adopt them. If everyone understands how and why you are trying to manage your data, and there is an established path to get what they need, they will likely try to follow it. But if they do not understand the logic, do not know where to go, or if the requirements are too burdensome or annoying, they will likely revert to old habits to find information. This will undermine even the best governance systems.

Conclusion

In the end, effective marketing data governance requires people to adhere to the system and maintain the processes. If you keep things simple, you are more likely to create something that is used consistently. And the more your organization trusts the data you provide, the faster and better everyone’s decisions will be.

To overcome the challenges of digital marketing and ensure effective data governance, count on DP6. We offer innovative solutions that organize, protect, and optimize your data, helping you make smart decisions and maintain competitiveness. Talk to us and discover how we can transform data into a powerful asset for your business.

Profile of the Author: Marcos Paulo Paolino| Father of Azura, Nina, and an orange cat named Maktub, pursuing a degree in Data Science at UFMS, Data Engineer at DP6, apprentice in gardening, woodworking, and photography, but a professional in Jenga.

Originally published at https://www.dp6.com.br.