10 data governance challenges that can sink data operations

Data governance challenges

Governance presents more challenges than any one list can capture. The 10 challenges here are ones that organizations across all industries encounter. These examples provide a foundation for understanding what companies might be up against when trying to protect and understand their data assets.

1. Data quality and consistency

Data quality is one of the biggest challenges for every data-driven operation. It can be a significant undertaking, depending on the amount and type of data, its location and what resources are available to manage it. It also depends on what current efforts and tools are in place to use the data. Substandard data might be inaccurate, inconsistent, irrelevant or redundant.

Several factors can contribute to data quality issues. Unstructured data can come from a wide range of sources, including edge systems, mobile devices and IoT devices. Organizations might not have a data management strategy in place, or they might not have inventoried or cataloged their data. They might also lack the proper tools for managing their data at scale.

When an organization fails to maintain data quality, users cannot trust the data. Users also have a harder time finding the data they need or using it effectively. Unreliable data can also lead to poor insights and decision-making, operational inefficiencies and unnecessary expenditures.

To improve data quality, organizations should implement a data management strategy that includes data profiling and classification. The process requires tools and technologies that provide full lifecycle data management, with an eye toward automating and improving their operations wherever possible. They should also monitor their data systems and perform regular data audits, with quality as a key strategic goal.

2. People don't understand their role in governance

Organizations are often overwhelmed by the amount of data they collect and generate. The individuals who work with the data often don't know who owns and manages it or what the owners' specific roles and responsibilities are. Many people assume that IT owns the data and is responsible for its governance, but data governance should be an organization-wide effort that relies on many players.

Multiple factors contribute to the lack of ownership and sense of shared responsibility. One of the main issues is the absence of assigned data stewards who are accountable for its upkeep. Another factor is the lack of clear communication and documentation that specifies how to work with the data, as well as a lack of cross-functional collaboration across departments and teams. In addition, an organization might not provide people with the training and education they need to work with the data effectively.

Many of these issues occur because the organization has no governance program in place or has failed to establish a culture of governance. In such an environment, it's no surprise that people don't understand their roles and responsibilities or how they fit into the larger governance scheme. As a result, the data is often mismanaged or misunderstood, which can lead to further confusion, miscommunication and an overall mistrust of the data.

To address these issues, organizations must move governance back to the business groups that generate, collect and use the data. They must make it clear that governance is a shared responsibility, not an IT-only operation. The appropriate groups must take ownership of their data and assign the necessary data stewards.

Organizations must also create a culture of governance that emphasizes its importance, fosters communication and collaboration, and clearly defines roles and responsibilities. They must provide employees the education and training necessary to ensure that everyone who works with the data understands the importance and implementation of governance.

3. Lack of leadership

A data governance strategy is destined to fail if it is not backed by strong support and leadership from the top. Lack of executive support -- or just lackadaisical support -- is common. Governance proponents must often contend with inadequate resources and funds, making it difficult to move forward with an effective governance strategy.

The lack of support is often the result of leadership failing to see the importance of data governance and the role it plays in ensuring the integrity, availability, security and usability of the data. They don't understand the consequences of not carefully defining and implementing a governance strategy, including substandard data, missed opportunities and security risks. Without this understanding, they see governance as a low-priority initiative that doesn't justify the commitment in time and resources, making it difficult to launch a meaningful governance effort.

Governance proponents must convince leadership that the lack of a comprehensive governance strategy could potentially cost the organization more than it takes to implement and maintain one. Explaining the risks of failing to implement such a strategy, including data errors, integration issues and operational overhead, shows leadership what they can lose without governance. The lack of a strategy also increases the risks for compromised data and compliance violations.

4. Unclear policies and procedures

An effective data governance strategy relies on clearly defined policies and procedures. In many cases, however, policies are not carefully planned, documented or distributed to the people who need to see and understand them. The people who own and work with the data might find the policies and procedures confusing, incomplete, contradictory or in other ways less than useful -- assuming they see them at all.

The process of defining clear and concise policies and procedures is a daunting task because of the complexity of the data and the different ways it is distributed, managed and used across the organization. Policies and procedures must integrate smoothly into existing business processes, which is why they often require buy-in from the various key stakeholders. After they accept the policies, it can be a challenge to get everyone to adhere to them, especially in a culture where governance is treated more as an inconvenience than a priority.

Confusion around the policies and procedures can put data at risk, increase operational overhead and result in substandard data. The poorer the data quality, the more difficult it becomes to gain meaningful insights from the data or make informed business decisions.

Defining and properly communicating the policies and procedures is essential to the success of a governance program. Key stakeholders should participate in the process of creating a program that everyone who works with the data should receive and thoroughly understand. They must also understand that integrating the policies into existing operations is an ongoing effort that takes time. After implementation, the policies and procedures should undergo regular reviews and receive updates as necessary to meet changing business requirements.

5. Siloed data operations

Siloed data is a common problem in many organizations, especially larger ones. Departments and teams often manage their own data; each one might take a different approach to storing and maintaining data. Individual groups might attempt to implement their own governance strategies. They're seldom consistent with each other and do little to support an organization-wide strategy.

Multiple factors can contribute to data silos. It's difficult to track and maintain the massive amount of data that organizations generate and collect. The data is largely unstructured and comes from a wide range of sources. The ecosystems built to collect, store and manage the data are larger and more complex, and they might rely on legacy technologies. In many cases, the data isn't properly maintained, often because administrators lack the tools they need to do their jobs properly. The situation is exacerbated by a lack of effective communication and cross-functional collaboration between teams.

It's more difficult for people to use data or make informed decisions when they lack a comprehensive view of all the data. Data sets might include significant amounts of duplicate, inconsistent or incorrect data, causing people to view the data as untrustworthy. Organizations also face greater challenges in trying to protect their data, which can lead to potential security and compliance risks.

Any organization that hopes to implement a comprehensive governance strategy must tackle its siloed data. Standardized policies and procedures should be clearly defined and distributed with a mechanism for evaluating and updating them as needed. The governance team should also develop a detailed plan that specifies how they'll roll out the strategy and measure the success of each stage. At the same time, leadership should foster a governance culture that encourages communication and collaboration and provides the training and education needed to nurture that culture.

6. Budget and resource constraints

Stakeholder support doesn't guarantee successful data governance if the budget and resources aren't available. Some organizations are reluctant to invest resources in governance because they fail to see the long-term advantages or the risks of not implementing a strategy. The total costs of such an endeavor can also be difficult to forecast, especially if the data variables are still unknown. It requires a significant investment in the time, tools, technologies and people to make it work.

If an organization has limited resources, allocating some to a governance initiative might be beyond their means. It might be difficult to acquire the personnel or tools they need to implement a strategy. Many organizations also face a shortage of skills and struggle to find the talent they need to take on governance. In many cases, employees are already overburdened and have little time to learn new skills or take on additional responsibilities. An organization might also consider other issues to be more pressing and must allocate their resources to address them instead of governance.

Budget and resource constraints can lead to a half-hearted attempt at governance or no attempt at all, resulting in the type of challenges caused by poorly managed data. An organization might need to move slowly to carry out a governance program, taking small steps as part of a larger, carefully orchestrated effort. Leadership must be willing to prioritize governance when allocating resources. Automating as many operations as possible, cross-training personnel where practical and implementing self-service capabilities that help to share responsibilities among the data users can maximize efficiency. The governance team should carefully track and analyze resource usage and produce detailed reports on a regular basis. Some cases might warrant the hiring of temporary consultants.

7. Slow adjustments

Organizations also face the challenge of trying to implement and maintain a governance program over the long term. Circumstances inevitably change, requiring program adjustments. New technologies, shifts in business strategies and market fluctuations can all affect the environments an organization operates under. Governance teams should be able to adapt to such changes quickly and efficiently; otherwise, it is difficult to sustain governance in a meaningful way.

A lack of timely responsiveness can occur for several reasons. The types and amounts of data or number of users might increase at unprecedented rates. The organization might lack a comprehensive change management plan that can address unusual circumstances and accommodate new technologies or changing operations. An organization might not have the infrastructure and systems in place to scale adequately to meet shifting demands.

The inability to adapt to changing circumstances can undermine a governance effort and lead to poor data quality or put that data at risk. To address the issue, an organization should implement a change management strategy that is flexible enough to adapt to new circumstances. They should address scalability limitations and adopt modern technologies that can withstand operational shifts. The governance strategy should incorporate ongoing monitoring and reporting capabilities that enable the organization to take corrective actions as new circumstances arise.

8. Regulatory needs change

Organizations must comply with the applicable regulations in the regions where they do business. Regulations such as the European Union's GDPR and the California Consumer Privacy Act define strict rules for handling data. Navigating regulations can be a daunting task, no matter what size the organization, because of the constant updates to existing regulations or the creation of new ones.

It's not uncommon for organizations to fall out of compliance because of the complexity and intricacy of the regulations themselves, which can be difficult to apply when managing a large and diverse data ecosystem. In some instances, organizations must navigate multiple regulations.

When regulations change, the process of implementing the changes into an organization's systems can be a considerable undertaking. In some cases, an organization doesn't have the resources readily available to handle these changes. Although sweeping changes are often announced far in advance, it's still up to the organization to stay abreast of the regulatory landscape. If an organization does not have full control over its data, ensuring compliance as regulations change is extremely difficult.

Failing to comply with applicable regulations can result in hefty penalties and legal consequences. If sensitive data is compromised, an organization could face lawsuits, exorbitant costs, a hit to the bottom line and a tarnished reputation from which it might never recover.

Organizations must ensure that their data governance programs adhere to applicable regulations and are adaptable enough to accommodate any changes. The more thorough and concise the governance strategy, the better it can ensure compliance, especially with well-defined policies and procedures. They should perform regular compliance checks and provide those who work with the data the training and education they need to maintain compliance as regulations change.

Convincing leadership and data stakeholders of the importance of a comprehensive data governance program is not enough to guarantee success.

9. Privacy and security

Data protection is one of the fundamental components of a governance strategy. Organizations must safeguard their sensitive and private data from internal and external threats. Governance brings the control needed to fully understand what data assets to protect and how to protect them.

Compromised data occurs for a variety of reasons. For example, an organization might not implement proper access controls -- exposing sensitive data -- or users might lack the training and education needed to exercise caution and maintain awareness. An organization that works with outside vendors has additional risks. In some cases, an organization might fail to properly monitor its systems, making it difficult to detect and respond to current threats.

Protecting sensitive data is a difficult undertaking, especially when supporting complex operations and workflows. It can be challenging for IT and security teams, who are already overcommitted, to dedicate the resources necessary to ensure proper protection. Compromised data disrupts operations and leads to heavy penalties, legal issues, loss of business and enormous costs.

To protect their data, organizations should deploy governance plans that cover all aspects of security and privacy. For example, implementing proper access controls ensures that only authorized users can access the data they need. Organizations should implement basic security measures, such as inventorying their data assets, encrypting the data, implementing multifactor authentication, and regularly patching and updating their systems. They should continuously monitor their systems and perform regular audits. Success requires investing in the right tools and ensuring that everyone who works with data receives the necessary training in security and privacy.

10. Failing to understand the importance of governance

Convincing leadership and data stakeholders of the importance of a comprehensive data governance program is not enough to guarantee success. Anyone who works with the data daily, even if only to create the occasional Excel spreadsheet, must understand governance policies. Convincing the skeptics has never been more important.

In many cases, people simply don't understand the long-term business value of a comprehensive data governance strategy. It's a common problem when there is an overall lack of strategic vision that recognizes data as an asset. Governance proponents might also be up against a resistance to change that permeates the organization at every level. When people lack the will to commit to a comprehensive governance program, data is vulnerable and its potential unrealized.

Establishing a data governance team empowers a specific group to educate decision-makers and those working with the data about the importance of governance and the value of protecting the data. The team needs to provide realistic goals and timelines so stakeholders know what to expect. A successful governance program requires the cooperation and willingness of everyone involved.

Robert Sheldon is a freelance technology writer. He has written numerous books, articles and training materials on a wide range of topics, including big data, generative AI, 5D memory crystals, the dark web and the 11th dimension.