The Problem with Agile Data Governance: Here’s How to Make It Work

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With the demands of today’s global market, companies need to handle vast amounts of data on a daily basis. In the hopes of effectively managing information, many leaders and employers began implementing agile methodologies to govern their data.

Although Agile Data Governance can bring benefits to organizations, there are still many companies that make mistakes in execution. To prevent this, there’s a need to identify the problems, find solutions, and implement them into your own data governing systems.

 

Understanding Agile Data Governance

Agile Data Governance aims to establish and maintain effective organizational data management practices. This method moves away from traditional data governance that follows a top-down model where the highest management level dictates decisions and policies.

Agile Data Management follows a bottom-up approach and actively involves data creators, stakeholders, and users in handling data and their activities. Rather than imposing rigid rules and processes, this approach recognizes that those working directly with data possess invaluable knowledge, making them more suitable to govern and manage data. This strategic collaboration and control allow companies to produce better services and outcomes.

In addition to prioritizing employee engagement, Agile Data Governance also utilizes new technological tools. Through leveraging advanced tech like AI, machine learning, and agile data analytics, companies can automate and improve the way they handle data.

 

Pitfalls in Implementing Agile Data Governance

Agile Data Management started as a response to the challenges organizations face in managing and governing their rapidly growing volumes of data. Although it has proven to be effective, it created problems during implementation. Some think it’s ineffective or that the agile method does not work.

Here are some of the most notable issues of agile methodologies that you need to be aware of:

 

1. Lack of Clear Policies and Frameworks

Without a solid foundation of policies, standards, and guidelines, implementing Agile Data Governance can quickly become disorganized and ineffective. Employees may be left unsure of how to proceed with their roles and responsibilities, making the execution even more damaging.

Moreover, the absence of a comprehensive agile governance framework, such as in IT, can lead to different practices across teams and departments, making the process convoluted. Instead of a successful and collaborative environment, companies may face inconsistencies and accidental non-compliance in specific parts of their workforce.

 

2. Inadequate Data Literacy and Training

Agile Data Management relies heavily on stakeholders’ active participation and engagement, including data creators, users, and decision-makers. However, implementing Agile Data Management can be significantly hindered if these individuals lack sufficient data literacy and understanding of governance principles.

Without proper training and education programs, stakeholders may struggle to comprehend the importance of data governance. This can impact their ability to understand, interpret, and utilize data they’re given access to.

Suppose stakeholders are not equipped with the necessary knowledge and skills. They may misinterpret governance policies and practices, which can undermine the overall effectiveness of the Agile Data Governance approach.

 

3. Streamlining over Collaboration

One of the core principles of Agile Data Governance is fostering collaboration and open communication among stakeholders. Unfortunately, some companies ignore these for the sake of streamlining their processes. This becomes a counterproductive state, redirecting efforts back to the traditional data management methods.

When organizations focus excessively on efficiency, they tend to undervalue the input and contributions of data creators, users, and decision-makers. This leads them to implement a top-down decision-making process, where policies and practices are dictated without adequate stakeholder involvement or feedback.

This can lead to a disconnect between the governance strategies and the practical realities faced by those working with data. Without considering the diverse perspectives and insights of stakeholders, governance decisions may fail to address real-world challenges or align with the unique needs of different teams and departments.

 

4. Technology Limitations

Agile Data Management leverages modern technologies and tools to monitor, enforce, and streamline governance practices. However, organizations may encounter challenges if their existing technology infrastructure is outdated or incompatible with the requirements of Agile Data Management.

Limitations in data management platforms, governance tools, or integration capabilities can hinder an organization’s ability to implement and automate processes effectively. Manual processes or workarounds may become necessary, increasing the risk of errors, inconsistencies, and inefficiencies.

Additionally, if the chosen technologies lack scalability or cannot handle the increasing volume and complexity of data, the organization may struggle to maintain effective governance as data environments evolve.

 

5. Resistance to Cultural Shift

One of the reasons why agile doesn’t work for companies is that they implement strategies and methods solely without adopting the proper mindset.

Implementing data management with agile methods often requires a significant cultural shift within the organization. This involves embracing a more collaborative, decentralized, and data-driven culture.

Resisting this cultural shift may cause unsuccessful implementation of Agile Data Governance. This usually stems from:

  • Fear of change or complacency with existing processes and methods.
  • Skepticism about the benefits of Agile Data Management.
  • The perceived threat to established power structures and decision-making processes.

 

Tips for Effective Implementation of Agile Data Management

To successfully implement agile strategies to your data governance and processes, Strategic Systems created these tips for employers like you to achieve quality data governance using agile methodologies:

 

1. Establish detailed policies and frameworks.

Before you can begin implementation, investing time, effort, and resources in developing concrete policies and frameworks is necessary. This should outline specific details such as:

  • Governance objectives
  • Principles and processes
  • Guidelines for your stakeholders

Moreover, you must establish clear changes and adjustments in everyone’s roles and responsibilities. This will guide everyone on how to handle data properly and how they can participate in the process.

Once you’ve established comprehensive frameworks and policies, effectively communicate these across the organization. If needed, review and update them to align with your growing business needs and objectives.

 

2. Invest in employee training and advancement.

To execute and sustain Agile Data Governance frameworks, consider providing ongoing training programs for your workforce. Help them understand data governance concepts, tools, and methodologies.

Investing in employee training and advancement is crucial for building a skilled workforce capable of implementing and sustaining Agile Data Governance practices. Moreover, a thorough understanding of Agile Data Management can help employees be less skeptical about its implementation and adequately apply the new method you want to implement.

 

3. Prioritize agile values.

Employers should prioritize agile values over promised benefits. For example, leaders should strive for adaptability, collaboration, and continuous improvement aside from focusing on sales and KPIs.

  • Pay more attention to the methods rather than the outcomes.
  • Create a space where people feel comfortable to discuss their ideas.
  • View mistakes as fuel for improvement instead of something that should be punished.
  • Encourage experimentation and iteration even if it causes brief stagnation in profits.

 

4. Improve your technology and tools.

To improve data quality, enable automation and allow scalability. This is necessary to ensure your technology and tools are capable and updated. First, you need to assess and optimize your existing technological infrastructure. Find ways to fill the gaps so your organization can support agile practices.

  • Are there any gaps or limitations that may hinder governance efforts?
  • Are your tools scalable and capable for your use-case?
  • Will your workforce quickly adapt to a new technology?

 

5. Start small and iterate.

The biggest problem with Agile Data Governance is that leaders and employers rush its implementation. They focus on which agile methodologies they should use and adopt immediately without considering how it would affect their stakeholders.

To improve your data quality and governance, adopt an iterative approach, beginning with small, manageable projects or pilot programs. Then, gradually expand your scope over time. This allows your organization to demonstrate value, gather stakeholder feedback, and adjust based on what you’ll learn.

Since you’re not forcing abrupt change to stakeholders, you can better mitigate risks, build momentum, and scale governance efforts to address broader organizational challenges.

 

HIRE EXPERTS TO GUIDE YOUR AGILE APPROACH TO DATA GOVERNANCE

It’s undeniable that agile data governance can be complicated to implement. If you’re still unsure how to proceed in your organization, hiring an expert who knows what to do is best. This is where we at Strategic Systems can help you!

With our network of professionals and rigorous vetting process, we can help you find the people who can drive your agile efforts.

Reach out to us today to learn more!