Data Governance Best Practices for Business Intelligence

In a world where data-driven decisions are crucial, understanding data governance and implementing data governance best practices is paramount. Building a culture that values data governance allows you to make better decisions. From there, the benefits will ripple across your organisation. 

In this article, we’ll distil the essence of data governance in business intelligence and illustrate how data governance transcends data management and strengthens your decision-making.

What Is Data Governance?

Hariharan KP, Head of Service Operations for solverASSIST, explains that data governance involves three key parts: how the data is being sourced, how the data is being used, and how the data is being transferred. Governance is needed for all areas, and there are legal and security ramifications for these actions, as consent is almost always required for the sourcing, using, and transferring of data.

Why You Need to Implement Data Governance Best Practices for Business Intelligence

Data governance best practices are pivotal in maximising the power of business intelligence – facilitating decisions that propel operational efficiency, business growth, and a competitive edge in the maritime industry. 

Data governance is more than just a backend process – it is a mindset and a strategy that should ultimately guarantee the credibility, security, quality, and accessibility of data, whether your company is consuming data internally or if third parties and customers are handling it, too. Having quality data lets you make better decisions that don’t hurt your business. From a financial perspective, Experian Data Quality reports that bad data costs 12% of a company’s revenue.

Picture a global shipping company managing complex routes and countless goods across international waters. If their data governance is lacking, the resulting dataset might contain discrepancies, duplications, and errors. Another example would be optimising your shipping routes, calculating fuel consumption, or assessing docking schedules when the underlying data is compromised. 

Both scenarios underscore the risks of neglecting data governance best practices.

The Challenges of Implementing Data Governance Best Practices for Business Intelligence

Many companies are slow to implement effective data governance best practices. Hariharan KP has seen these challenges first-hand. Data governance is rarely a priority, and most individuals are unaware of its impact on the organisation as a whole.

The following challenges are common: 

• Lack of Understanding. Many individuals within organisations may not fully comprehend the scope and significance of data governance. The “what is data governance?” question often remains unanswered, leaving individuals unsure of its risks, importance, and benefits.
• Complexity and Time. Creating effective data governance structures and frameworks can be time-consuming and complex. This complexity extends to educating every individual within the organisation on data governance, further straining resources and timelines.
• Indifference towards Data. Often, there is an underlying sentiment that “business is more important than the data being captured”. This results in a disregard for data governance, as its importance in shaping strategic business decisions is undervalued.
• Resource Constraints. Companies operate under limited resources and may prioritise other areas needing assistance over data governance. This challenge is amplified when the organisation does not understand the value that robust data governance can bring to its operations.
• Reluctance to Change. Implementing effective data governance necessitates a culture shift towards a data-driven mindset. It requires collaboration and accountability across all levels of the organisation. However, leadership can often resist, making this transformation a challenging endeavour.
• Lack of Leadership Support. Without the backing of leadership, data governance initiatives are likely to falter. It’s essential that leaders not only understand but also advocate for the importance of data governance, providing the necessary resources and setting a tone of importance throughout the organisation.

Data Governance Best Practices for Establishing a Framework

Implementing data governance best practices is an evolutionary journey that takes time. It requires a holistic approach and continuous refinement. We asked Hariharan KP for data governance best practices:

One: Define Objectives

These objectives should align with your business strategy and be designed to enhance business intelligence. For instance, an objective could be to improve reporting accuracy to support better decision-making.

Two: Educate Stakeholders

Data governance campaigns, for example, can effectively educate stakeholders about the importance and benefits of data governance, their roles, and how to use data responsibly.

Three: Establish Policies and Frameworks

Creating comprehensive data governance policies and guidelines ensures consistency and clarity. This includes everything from how data is collected, stored, and accessed, to how it is shared and disposed of.

Four: Define Roles and Responsibilities

Assigning clear roles and responsibilities is crucial to ensuring accountability. This might include a data governance manager overseeing the initiative, data stewards responsible for data quality and compliance, and data users trained in proper data handling.

Five: Ensure Security

From a security perspective, it’s important to implement measures that comply with regulatory requirements. Not all data is relevant or appropriate for everyone in the organisation, so proper security frameworks should be in place to protect sensitive data.

Six: Implement Processes and Quality Standards 

Processes should be established to monitor and manage data quality. This includes defining what metrics will be monitored, implementing data cleansing procedures, and identifying the tools needed for these tasks. 

Manual processes can lead to errors and inconsistencies, so automation and digital tools are crucial.

Key Roles and Responsibilities when Implementing Data Governance Best Practices

Effective data governance and following data governance best practices are a team effort. Each role, from the Data Governance Manager to the business’ suppliers and customers, is critical in ensuring data quality and compliance. 

But remember: all parties involved in data governance must regularly review policies, ensuring they continue to align with business objectives, industry standards, and legal regulations.

“If all parties work together, data quality and compliance will be achieved.”

 – Hariharan KP.

• Data Governance Manager. The Data Governance Manager, or a similar executive role, is responsible for devising the overall strategy for data governance. This strategy is crucial as it underpins any actions. Alarmingly, Forrester reports that 60-73% of data in an organisation is never successfully used for any strategic purpose.
  
  A Data Governance Manager must establish and communicate the vision, objectives, and expected outcomes, ensuring that the data governance strategy aligns with broader business goals. 
• Data Stewards. Often described as the ‘watchdogs’ or ‘monitors’ of data governance, data stewards are tasked with executing the established strategy. They understand the specific business objectives to ensure alignment and provide guidance.
  
  Data stewards are responsible for establishing frameworks, ensuring quality control, and guiding the use of data. Their role necessitates cross-functional decision-making.
• Data Architects. Data architects are pivotal in capturing data and defining the information flow within your organisation. They design and manage the data infrastructure, ensuring it supports the organisation’s needs and aligns with the data governance strategy.
• Compliance and Legal Teams. These teams ensure the data governance strategy and practices align with regulatory requirements. They help navigate the complex legal landscape of data use, privacy, and security, providing guidance to prevent regulatory breaches.
• Business Users and Data Consumers. The individuals who use the data for business operations, analytics, and decision-making also have crucial roles. They must adhere to established standards and protocols for data use, ensuring that their practices support the data governance strategy.

Trends Impacting Data Governance Best Practices

In the world of data governance, the rising trends of data ethics and responsibility and data privacy concerns, especially within cloud computing, are reshaping the landscape. Their impact on data governance can be highlighted as follows:

Data Ethics and Responsibility

Your organisation must ensure it collects, processes, and uses data ethically. You must ensure these ethical protocols to build trust with stakeholders, investors, and customers and maintain a reputable and sustainable business.

Data Privacy

In cloud computing, specifically, data is often distributed across multiple servers or locations. This presents unique challenges for data privacy, requiring data governance to be more agile and comprehensive.

There are also compliance regulations to consider. With the complex nature of cloud storage, data governance strategies must adhere to various data protection regulations. This involves creating privacy policies and practices that specifically address cloud-related vulnerabilities.

Allow Data Governance Best Practices to Transform Your Business Intelligence

Business intelligence requires a strong and intentional data governance culture, a culture where data quality, accuracy, and security are not just lofty ideals but a daily practice. Well-designed tools and systems also play a critical role in data governance. 

Manual processes will be disastrous – McKinsey highlights this by revealing that the average user spends 2 hours a day looking for the right data. Therefore tools and systems must be designed and utilised to support your data governance processes today and tomorrow. 

This harmonious blend of culture and technology sets the stage for robust data governance. Only then can data governance will empower your company to sail forward in a data-driven world.

solverASSIST can support your data governance efforts. We take care of your technology, applications and processes, leveraging deep industry knowledge and technical expertise. Our services can enhance your business intelligence and enable informed decision-making.