Today’s ultra-competitive, fast-moving and rapidly evolving business environment means only the smartest, fastest and most innovative enterprises will emerge on top. Such success though is increasingly unachievable in the absence of a robust data governance program. With the average business today capturing massive volumes of internal and external information, there’s a need to leverage this data in order to maximize value, reduce cost and manage risks. Information governance is the discipline that helps enterprises do just that.
For many organizations, there isn’t just one enterprise-wide data repository. Big data, unstructured data, increasing complexity, information diversity and operational intelligence creates a business environment with numerous moving parts that demands a thorough and consistent overarching data handling strategy.
Data governance is the set of policies, processes, standards, metrics and roles that ensure the efficient and effective utilization of information in order to support the organization in the realization of its objectives. In simpler terms, information governance is a framework that helps organizations better manage data assets.
It establishes the responsibilities and process that make certain of the security and quality of data across an entire organization. Data governance clarifies who is mandated to take what action, on what data, under what circumstances and using which techniques. A well-thought-out information governance strategy is crucial for all enterprises including those that work with big data.
For example, businesses must know and understand what the term ‘customer’ means in different contexts and how the understanding of the term in each context implies for the management of customer data.
Data governance delivers a wide range of benefits for the enterprise. These include:
A violation of the quality, security, privacy, integrity, availability and reliability of business data carries significant risks. First, the very operations of the organization are in jeopardy if the information that decisions are founded on is not of the required standard. Second, there’s the threat of regulatory action if the business is found to have violated a key law such as GDPR and HIPAA. Third, the company’s reputation may be shattered as customers and employees start to distrust the data. Data governance lowers risk by systematically addressing the key risks that could endanger the business in the aftermath of poor data handling.
The average organization today captures, stores and manipulates a vast and complex quantity of data. This data is captured through tens, hundreds or thousands of interfaces spread across multiple business units. It’s relatively easy for each business unit to be sucked into a silo and develop its own definition, understanding and classification of the data it uses. This only leads to conflict during data handoffs or inconsistent application of data handling policies.
Data governance harmonizes the understanding of data by developing common terminology that’s applied uniformly across the organization (even though business units may be given some leeway if that is what is needed for them to successfully discharge their responsibilities).
Data drives enterprise decision-making. Poor quality data inevitably leads to poor decisions. For example, think about a business whose primary target is Baby Boomers and is looking at launching a presence in a city it’s not been to before. Some of the data it needs to know that it’s making the right decision is the population of Boomers in the said city. If the data it relies on is incorrect or outdated, then every decision made using it will be inherently flawed.
Data governance creates a working environment that ensures data consistency, completeness and accuracy.
There are so many interfaces through which data is created or received in an organization that over time it can become difficult to have a clear picture of just what information is in the company’s custody.
Information governance gives businesses the ability to map the location of all data. This makes data assets retrievable, usable, easy to integrate and easier to connect to strategic outcomes.
Data governance improves the customer experience, reduces operational costs, increases revenue and enhances efficiency. But for many organizations, the information governance initiative is primarily driven by the need for regulatory compliance. The actual data handling regulations a business is subjected to will vary depending on industry and jurisdiction.
The regulations and standards may include HIPAA, GDPR, SOX and PCI DSS. The penalties for non-compliance can be severe. In cases of repeated violation, non-compliance may even lead to the revocation of a business license.
The terms data governance and data management are often used interchangeably but data management is in fact a subset of data governance. A good information governance framework brings the human touch to a technology-driven and highly automated world.
It establishes best practices and codes of conduct in data management that transcend the traditional excessive focus on system controls. It ensures that the compliance, security and legal areas of data management are applied consistently and comprehensively.
A data governance implementation exercise helps streamline and organize enterprise information. Such organization not only improves the quality of the data itself, but it also leads to better and quicker insights.
Oftentimes, the distributed, irregular, inconsistent and varied nature of business data can make it hard to extract conclusive insights. It’s not unusual for the process of generating a business report to take hours or even days simply because of the formatting and harmonization that must be done before the data can be gainfully utilized.
Information governance forces data consolidation and integration in a way that speeds up the extraction of insights.
A business could have great employees. But having great employees doesn’t necessarily translate into effective departments. And individually effective departments won’t always translate into an effective organization. The better the collaboration between departments, the better the quality of the organization’s overall work output.
Implementing a data governance initiative means breaking down walls between departments and encouraging a coordinated approach toward data handling. Even when the process of rolling out the data governance framework is complete, the established channels of collaboration as well as the camaraderie between departments is likely to linger long after.
In addition, the high data quality and the consistent handling of data across the business will eliminate many of the previously existing points of friction.
It’s only over the last decade or so that businesses have started to appreciate the place of data as a business asset in the same breath as buildings, automobiles, cash and employees. Nevertheless, the value of business data is in its ability to efficiently propel the enterprise toward its strategic goals.
A data governance framework improves the quality of data and thereby makes it more of an asset for the corporation.
Poorly governed and managed data increases business costs in multiple ways. Ill-advised strategy, inter-departmental conflicts, flawed models, misinformed product development, and poor planning are examples of the different ways poor quality data can trigger decisions that end up costing a company dearly.
Information governance improves the quality of business data and thereby eliminates the unnecessary expenses that would otherwise be incurred by the enterprise.
Information governance isn’t all about technology, but it’s virtually impossible to implement data governance in any meaningful way without some dependence on IT systems. After all, the bulk of enterprise data today is held in electronic form. There are many information governance tools one can choose from. Their cost and functionality vary broadly.
Apart from looking at the basic considerations such as your budget, there are several aspects you must pay attention to in order to be certain that you select the most appropriate data governance technology. These include scalability, compatibility with existing systems, quality of customer support and the reviews of previous users.
Implementing a data governance framework isn’t something you can accomplish at one go. Instead, it’s a complex and long-term process. This means there’s a danger of participants and stakeholders losing enthusiasm over time. To make the project more exciting and relatable, it may be advisable for you to apply the agile method of project management.
Ergo, break down the initiative into work stories and then identify the stories that are of highest priority to start on. Run these priority stories through the agile workflow iteratively until they satisfy the expectations of the information governance framework. As you complete some work stories, take on new ones. This way, the governance initiative will feel manageable and finite.
Key business drivers will determine what stories and data needs highest priority. For instance, if one of the drivers of your data governance initiative is to ensure the protection of healthcare information (in compliance with regulations such as HIPAA and GDPR), then one work story would be to protect patient data during capture, storage, transit and use.
The data governance council should make sure it asks all the right questions at the start of the initiative to business unit heads and other stakeholders. This ensures the project takes off on the right footing and with a clear picture of the current status of governance and the end goal of the initiative.
Regulations, data breaches, ransomware, and compliance audits are just some of the many factors that are contributing to the expanding requirements of data governance. The Micro Focus File Governance Suite addresses these and other issues through comprehensive data reporting and analytics, followed by a powerful engine that automates data governance tasks to optimize, secure, and protect your network data while helping you meet your compliance requirements.
Acquire data governance insights, streamline policy implementation, automate compliance monitoring, and protect information from creation to destruction. Keep data safe when in transit and at rest.
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