Build Trust in Your Financial Data Through Data Transparency

Financial leaders are constantly under pressure to make well-informed decisions. Many organizations consider themselves data-driven without having full control over their data. The key to success isn’t just easy access to data (although its management is essential) but understanding it—knowing where it comes from, how it’s connected, and whether it’s reliable. Data transparency bridges the gap between mere numbers and actionable insights.

Discrepancies in Data and KPIs?

Imagine this scenario: the controlling team reports a decline in overall profitability, while the sales department shows an increase in sales during the same period, meeting its targets. The question arises: who is right? Or rather, is it possible to understand why these seemingly conflicting results can coexist? This issue might stem from data discrepancies, but it often involves misunderstandings or incorrect interpretations of available information. The key question isn’t about who is wrong but rather how data quality and transparency are maintained and whether there’s a shared understanding of terminology across departments. Misinterpretation and misunderstanding of data are among the most common challenges companies face.

Terminology poses a significant problem in these situations. For employees to truly understand one another and “speak the same language,” clear term definitions are necessary. For instance, a financial analyst might see “profitability” as a specific report with calculated figures like net profit after deducting expenses. In contrast, a salesperson might interpret “profitability” in terms of sales growth or revenue as a success indicator. Both perspectives are valid but differ in focus. Without a centralized terminology, misunderstandings arise. There needs to be a clearly defined concept of “product profitability,” including its description and components, accessible to sales teams as well.

When business reports and financial KPIs (key performance indicators) don’t align, it creates confusion for management. Financial and IT directors face challenges not only in ensuring data consistency but also in making data traceable and connected to other metrics. Without a clear understanding of the data itself, its origin, and how it links to KPIs, it becomes difficult to trust the reported results.

Solution? A Data Catalog for Finance

The answer to this complex issue is implementing a data catalog, which, with the help of AI, lays the groundwork for future transparency across the company’s data landscape. However, this is not a one-time project. It’s essential to recognize that data is a valuable asset that requires ongoing care. For CFOs and senior financial leaders, a data catalog should not just be another technical tool but, if used correctly, a guide that helps finance teams document the data landscape, track the connections between metrics and KPIs, and, most importantly, serve as a communication tool. It provides a single place to standardize, publish, and maintain the terminology used in financial management, linking terms to specific individuals responsible for them.

With clearly defined terminology and content, the catalog serves as a basic “translation dictionary,” enabling employees to “speak the same language.” Even though everyone may speak the same language, terms often mean different things to different people, leading to significant misunderstandings when interpreting report information. For example, “revenue” or “turnover” in sales is not the same as “profit”; to arrive at actual profit, costs—both direct and indirect, and even risk premiums—must be accounted for. Well-described and connected data fosters transparency, enabling a better understanding across the entire company.

Trust in Numbers

This transparency is crucial for controllers and analysts to confidently validate their reports and explain them to colleagues from other departments. Without this unified view, decisions often rely on assumptions, which increases the risk of errors and leads to inconsistencies in data interpretation.

When decisions are based on unverified data, it fosters a poor data culture where teams rely on incomplete information. This practice not only undermines trust in data but also causes hesitation in using it for critical decisions. The result is inaccurate business outcomes (misguided strategies, inappropriate investments, or missed growth opportunities).

Implementing a transparent data catalog minimizes debates over whose data is correct and allows more time for strategic tasks. CFOs and CEOs can rest assured that their reports accurately reflect the organization’s financial performance, while CIOs and data analysts ensure that data flows consistently and without loss of integrity across systems.

Building Trust Through Transparency

Trust in data should be a necessity, not a luxury, for business leaders and all employees alike. Along with a unified data perspective, a data catalog also provides “interpretation dictionaries” that ease communication across the company. Even though we all speak the same language, within a company, we interact with specialists in finance, technology, risk, or business, each needing data for their effective work. To ensure that data is genuinely understandable for everyone, it must be properly and clearly defined in data and business glossaries accessible to all users.

Rather than having data managed by a small group of experts, it’s more effective when the entire data community naturally participates in the process. Whether they’re salespeople, managers, or analysts, everyone can contribute with comments or suggestions for changes in definitions and terms within their specific area. Dawiso, designed for this open approach, enables the creation of a truly live data management system where terminology aligns with the needs and knowledge of all users. The result is a transparent environment that fosters trust in data and mutual understanding.

Data transparency is not just about understanding one’s data in detail but, more importantly, about facilitating mutual understanding across the entire company, saving time and costs on resolving inconsistencies, and ultimately gaining real control over data to become a truly data-driven organization.

Investing in data transparency is a fundamental step towards truly transforming an organization, where numbers aren’t just metrics but are valuable assets leading to growth, opportunity utilization, and long-term success.