Unlocking Data Governance: 3 Proven Strategies from Top Czech Managers

Managing data governance within organizations and among stakeholders can be an overwhelming task for CIOs, CDOs, or data strategists. The implementation and sustained adherence to established processes pose similar challenges. Why is this the case, especially when various surveys indicate that 10-30% of an organization's revenue is spent on addressing data quality issues?


10-30%

The percentage of an organization’s revenues spent on resolving data quality issues

35%

C-level management has a high level of trust in the use of data and analytics in their organization

34%

C-level executives claim that data is managed with the same standards as other assets

Every Company Faces the Challenge, But Who’s Solving It?

Discrepancies in data – be it sales, financial, or marketing figures – are a common headache in companies. Requests to ‘tweak’ these numbers to align them are all too familiar, often accompanied by the urgent query: “How quickly can this be fixed?” Answers like “in a month or two” are hardly ever what business colleagues want to hear.

The real question then is: How can your organization establish a single, accurate version of the truth and effectively implement a data governance program that touches every aspect of your business? The journey begins with understanding where your company stands within the five developmental phases of data governance. This initial step is crucial to pave the way for a streamlined, efficient approach to managing your data, ensuring that it not only serves your immediate needs but also aligns with your long-term strategic goals.

The Overlooked Necessity

Clients often miss the strategic value of implementing data governance, sticking to traditional practices. This oversight neglects the efficiency and insights a formal system can provide. The absence of a Data Office, standardized processes, and Data Governance platforms limits the full utilization of data as a key organizational asset. Addressing these gaps is crucial for enhancing data management and accuracy.

Emerging Awareness in Data Governance

There’s an increasing acknowledgment of the need for Data Governance within the company, originating from different levels. However, clients often face uncertainty about how to proceed and where to start.

Key elements still missing include a dedicated Data Office, established data governance processes, and the implementation of Data Governance platforms.

Strategic Data Governance Initiative

The company is actively investing in a strategic data governance solution, with the Data Governance framework currently in development.

The creation of a Data Office is progressing, alongside the definition of essential governance processes.

Selection of specific Data Governance platforms is also underway, tailored to the company’s needs.

Data Governance Implementation in Progress

With the design and conceptualization complete, the client is now implementing data governance, often starting with an MVP or POC. The formation of a Data Office and the implementation of key processes are underway. Data Governance platforms are being actively utilized to support these efforts.

Full-Scale Data Governance Deployment

The company is advancing from the successful MVP phase to a full-scale implementation of data governance. The operational Data Office is leading this effort, with key processes being integrated across the organization and supported by specialized technical platforms.

Assessing the State of Data Governance in Czech Businesses

The October 2023 survey, targeting leading Czech companies and conducted during an Adastra-hosted workshop on data governance, reveals insightful trends. It’s clear that data governance (DG) isn’t a novel concept for these organizations.

  • A notable 20% of these companies acknowledge the necessity of DG but are uncertain about its implementation strategy.
  • A significant 40% are actively developing DG frameworks.
  • Impressively, 30% are ahead of the curve, currently integrating DG practices into their organizational fabric, showcasing a proactive approach to modern data management.

To effectively introduce data governance to management, subtlety trumps directness. Success hinges on two key strategies: leveraging the stringent regulations integral to our industry and developing compelling, management-focused use-cases. These approaches not only underscore the necessity of data governance but also highlight its practical benefits, ensuring it's seen as a vital, relatable solution for the organization.

Martin Novak, Data Director in Allwynu, international company specializing in lottery and betting games

1. Bet on Progressive Managers – They Know DG Makes Life Easier

At the forefront of embracing data governance is Alena Rozsypalova, both a board member and CFO at E.ON. Her tenure began amid an energy crisis, swiftly followed by the conflict in Ukraine, pushing her to seek innovative solutions from day one. Rozsypalova’s experience underscores the vital role of data in critical decision-making, sometimes under high pressure, or as she describes, “a matter of utmost urgency.”

Data stands as the cornerstone of our organization’s digital transformation and process automation, especially in finance,” Rozsypalova asserts. “Reliable and accurate data is essential for swift and effective decision-making, eliminating the need for constant verification.”

In collaboration with David Jez, E.ON’s Chief Data Officer, Rozsypalova embarked on a comprehensive assessment of the company’s data storage practices. This initiative revealed several areas ripe for improvement, culminating in a strategic decision to develop a new, state-of-the-art data warehouse. This development was paired with the introduction and rigorous application of data governance principles, reflecting a proactive approach to modern data management.

Jez highlights the synergy between the finance department and IT under this new initiative. “We have robust backing from our business leaders, particularly in finance, who are instrumental in driving our data governance strategy,” he says. Jez also emphasizes the importance of foundational elements in successfully implementing data governance, outlining “three critical prerequisites for its establishment.”

  1. Management support:
    Our financial backbone, Alena, stands as a pivotal stakeholder. The Digital Transformation (DG) is an endeavor rendered possible only through unwavering business support.
  2. Adaptation of corporate culture to changes:
    It’s essential to explain everything within the company and constantly educate on why we’re doing it and what the end result will be.
  3. Properly set expectations:
    The key is to avoid exaggerated expectations. First, establish the foundation, and only then introduce “sexy” terms like machine learning (ML), artificial intelligence (AI), and so on.

Similar challenges are present at GasNet.

“We’ve successfully implemented a data warehouse, and now we’re focused on establishing rules for data management and cascading these practices throughout the entire company,” shared Eva Netušilová, Senior Manager, Strategic Asset Management at GasNet. “I don’t want my colleagues spending hours on end acquiring and cleaning data; we need their added value in the form of interpreting already discovered information. Swiftly analyzing vast amounts of data is crucial for us,” she emphasized.

We've discovered that our colleagues are spending 40-50% of their time, which could be dedicated to actual analysis and interpretation, on acquiring and cleaning data. It was a common occurrence that data from one system couldn't be matched with another. Alternatively, the same query would yield two different answers from two different individuals.

Eva Netusilova, Senior Manager, Strategic Asset Management, GasNet

In response to this situation, the company’s management has come to the realization that the previous data warehouse solution lacked their support, prompting the need for a change in approach. They are now embarking on the creation of a new data warehouse while concurrently implementing data governance, ensuring that the entire company takes ownership of it. “We understand that creating a solution for just one department won’t be sustainable in the long run,” says Eva Netusilova.

 

2. Harness Data Governance Frameworks and Tools

There’s an array of procedures, frameworks, and tools available to approach data governance and implement it within an organization. Notable independent international organizations in this realm include DAMA International and EDMCounsil. How do their approaches differ, and where do they converge?

DAMA FRAMEWORK (DMBOK)

  • Framework developed by Data Management International Association (DAMA)
  • Focuses on concepts and practices of data management
  • Structured into 11 domains: data management, data architecture, metadata management, reference and master data management, data security, data quality, data modeling and other essential foundational elements for data programs
  • Provides a comprehensive overview of best practices and standards
  • Designed for planning, implementing, and administering data assets

DCAM

  • Framework developed by the Enterprise Data Management Council
  • Focuses on the capabilities and maturity of data management function within an organization
  • Comprises 8 components, 38 capabilities, and 136 sub-capabilities
  • Basic components are further categorized into three levels: foundational, execution, and collaborative
  • Primarily used for assessing the maturity of data management in an organization
  • Identifies areas for improvement in the data management function

When embarking on the journey of data governance, the choice of approach becomes a nuanced decision, shaped by the intricacies of your IT ecosystem and operational processes. Whether through careful consideration or seeking counsel from those with substantial experience in the field, the key is to tailor the selected approach to the unique needs and dynamics of your organization.

Subsequently, the focus shifts to the array of data governance tools available, crafted by leading technological giants such as Ataccama, Collibra, Alteryx, SAS, Talend and others.

In the Czech Republic, products from Ataccama have gained notable popularity, consistently securing successful positions in Gartner’s Magic Quadrants for several years in the realms of data governance, master data management, and data quality. Notably, there’s a high degree of automation, particularly in areas like data quality, code lists, and the definition of the golden record.

3. Transform Corporate Culture

Once the data governance tools are in place, the challenge shifts to “adhering to data governance.” This is a demanding task that involves people from various departments across the entire organization. It necessitates changes not only in technology and processes but also in the organizational culture. People play a crucial role in aligning with these changes. Cultural transformation doesn’t happen on its own; it requires explanation and won’t be accomplished within a month. It’s probably not surprising that the sooner you start working on it, the better. How do different perspectives approach it?

Miroslav Umlauf, a Data Strategist with extensive experience in implementing and developing data governance solutions at the technological giant Avast, emphasizes a critical aspect of its implementation: “When anything, including data governance, is addressed separately – us as technology and them as business – it doesn’t work. Business and technology need to work together. Therefore, I spend more and more time with people from the business side, connecting departments. I build and work with a network of individuals who can and want to make a change, regardless of their position in the company’s organizational structure.”

David Jez shares a similar view. For him, efficient collaboration with colleagues from various departments and their willingness to work with IT are keys to success. “I encounter several types of people: one group is okay with changes and wants to cooperate. Another group needs education, thorough explanation of what data governance is, and what benefits it brings. They appreciate when we come up with a small, team-specific solution, and they gain firsthand experience of the benefits of data governance. Quick wins work here. And then there’s always a portion of people who are afraid of change and resist it.”

Data Governance Brings a Single Version of Truth

The conversation around data stewardship has been ongoing for decades. “Data management has always been here; it just had a different form than data governance,” adds Martin Novák, Data Director at Allwyn, an international company focused on lottery and betting games. If organizations don’t handle data carefully, treating it as one of their assets, they risk drowning in a sea of low-quality, outdated data, in a data swamp, in chaos.

Data governance reduces the level of uncertainty – you know where to look and what the data means,” concludes Miroslav Umlauf.

When data governance is more than just words, it can significantly help organizations find the one correct version of truth.

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