What is Data Governance and why businesses lose money without it
Oleksandr Perkhun
Head of the Data Management Center at Metinvest Digital
In more than ten years of working with corporate data, I have seen dozens of definitions of the term «Data Governance»:
• for an analyst — reports and dashboards,
• for security teams — access and protection,
• for data engineers — pipelines and integrations,
• for infrastructure specialists — role models and permissions.
Each of them is partly correct. But when a company focuses on only one aspect, gaps appear:
• dashboards look convincing but are based on inconsistent data;
• security systems work, but there is no transparent reporting;
• integrations are implemented but bring no business value.
Data Governance is not a technical tool but a business necessity. It defines whether executives can trust the numbers and make decisions quickly. Without it, even large companies fall back to intuition-based decisions — and lose millions.
When data chaos turns into financial losses
In large companies, data comes from everywhere: finance, marketing, sales, production, logistics. Without common rules — chaos begins.
A typical situation: the finance department shows one sales volume, the commercial department another, and top management gets a third.
Who is right? Nobody knows. Meanwhile, the business suffers losses:
• decision-making is delayed,
• accounts receivable grow unnoticed,
• demand forecasts diverge from reality,
• supply chain disruptions undermine client and partner trust.
Such problems are measured in millions. For example, in an accounts receivable management project we identified potential risks of $60M in annual losses. The reason — lack of dynamic control and transparent data rules.
What effective Data Governance covers
To avoid chaos, Data Governance must cover all key business processes. In Metinvest Digital practice, this means four pillars we implement in our platforms:
1. Data Lake and Data Warehouse
• A single architecture based on the one source of truth principle.
• Less time spent searching and processing data.
• Reduced human factor impact → greater trust in numbers.
• Foundation for mathematical models and artificial intelligence.
Impact: all departments rely on the same data, reducing conflicting reports and accelerating decision-making.
2. Security and access control
• Access only for authorized users.
• Secure processes that are hard to hack or steal.
• Transparent logs and audits for internal control.
Impact: the company minimizes leakage risks and ensures data is used according to the rules.
3. Reporting and dashboards
• Integration with most data sources.
• Delivery into BI environments and accounting systems.
• Interactive dashboards in real time.
• Visualizations and charts instead of “dry” tables.
• Business management in AS IS mode, without delays.
Impact: executives see the current business picture “here and now,” not a week later.
4. Data Science and AI
• Predictive models: demand, prices, equipment load, production volumes.
• Optimization models: supporting business process management.
• Computer vision: reading data from cameras and turning it into practical insights.
Impact: the company moves from “analyzing the past” to “predicting the future” and automating operations.
Behind Data Governance architecture there are always not only systems but also people capable of building and scaling them. At Metinvest Digital this is the team of our experts:
• Yevhenii Cherkesov — Program Manager
• Vitalii Svyrydenko — Head of Data Engineering
• Anton Kudriavtsev — Head of Data Science
• Andrii Serdiukov — Head of Business Analytics
What’s next?
Our current goal is to combine all data into a single space where reports, dashboards, and models are available not only to executives but also to analysts and teams.
The next step is developing tools for automated process optimization. This means management decisions will become even faster and more accurate, and the business will get maximum value from data.
Conclusions
Data Governance is not a set of rules or technical settings. It is a business practice that determines whether a company makes decisions based on facts or assumptions.
What happens without Data Governance:
• Conflicting figures across departments.
• Accounts receivable growth without a clear picture.
• Inaccurate forecasts that break supply chains.
• Losses measured in millions.
What changes with it:
• Transparent AR control → saving tens of millions.
• Optimized logistics → planning in seconds, saving millions.
• Financial and legal processes without chaos → unified rules, fewer errors.
• Executives see a consistent business picture → no delays, no dependency on IT.
In our practice, Data Governance has proven: it is not about data itself, but about ROI, speed, and business resilience. The next step is automation and optimization at company scale, where decisions are made not just based on data, but in real time.
👉 Learn more about our solutions in the Data Management section on the Metinvest Digital website.
👉 I regularly share insights on Data Governance and digital transformation — join me on LinkedIn to exchange experiences.
👉 If you are interested in a business consultation or want to discuss solutions for your department or company — fill out the form via the link.
