Adopting a corporate culture focused on data management is crucial for the controller’s role. Various studies show that data quality and technology integration (with half of organizations using more than five tools) are among the key challenges for today’s and tomorrow’s CFOs and controllers, who are increasingly expected to have strong data analysis and management skills.
Building on these aspects, Assocontroller – the association of management control specialists – organized the webinar “Data Driven Financial Decision Making & AI Evolution”, featuring numerous authoritative insights. Representing Irion were Mario Vellella, Principal Domain Advisor, and Lanfranco Gastaldi, Principal Business Consultant.
Who are the controllers, and what challenges do they face?
What’s the profile of a controller in Italy? The organization has over 400 members: 72% hold a degree in economics, the average age is 41, and 17% work in large companies (42% in medium-sized ones, the rest in small and micro enterprises). The event was opened by Ivo Hristov, Professor of Business Economics at the University of Tor Vergata, who pointed out that non-financial data “always carry a certain degree of subjectivity, making them even harder to govern.”
Since measuring performance is challenging in any context and requires a “complex vision,” various aspects must be considered: “A company is a system with the goal of creating value, and our analysis must take into account all its elements—not just the economic and financial ones.” This means focusing on factors such as customer loyalty, integration across corporate levels, employee motivation, and cultural change. And all the sustainability indicators that—together with digitalization—form the two pillars of the National Recovery and Resilience Plan (PNRR). These elements are also central to the CSRD directive (November 2022), which, starting in 2025, will require listed European companies with more than 500 employees to publish the so-called Taxonomy Disclosure—based on 2024 data—in their annual financial management report. In 2026, the obligation will extend to all large enterprises, and in 2027, to listed SMEs and others.
Valeria Lazzaroli, Chief Risk Officer of ENIA (the National Agency for Artificial Intelligence), highlighted the limitations of the public-private ecosystem and the financial system in supporting AI development and scale-up operations. Meanwhile, according to Massimo Di Virgilio, “companies have ended up creating silos, but from an evolutionary perspective, it’s clear that digital transformation forces a radical change in how they operate. We see many struggling because they resist change.”
Data stewardship between innovation and governance
Also due to new regulatory requirements, controllers today often find themselves saying, “I can no longer do my job as a controller”: complexity has become a key challenge in terms of data management. Together, our two experts explained how the balance between innovation and governance of the information asset—ensuring speed, flexibility, and security—is the key to establishing effective stewardship. On one side, change management requires agility, customization, and timeliness; on the other, the “run” of processes demands efficiency, standardization, automation, reliable outcomes, and compliance.
Seven aspects of state-of-the-art reporting
- There’s no such thing as one-size-fits-all reporting. Reporting is about customization—of analysis, data views, and layout—based on the needs of the specific organization requesting it.
- Yesterday’s reporting is not tomorrow’s. It’s a constantly evolving field, keeping pace with the dynamism of business processes.
- Data sources tend toward infinity. They are typically multiple and non-homogeneous, both in format and frequency. Moreover, unstructured data is often present, and the volumes involved are significant.
- Reporting is like Picasso. We need to adopt a multifaceted perspective to classify, organize, and group data at various levels of detail, depending on the different recipients and users of the reports to be built.
- Reporting and controllers are interdependent. Manual interventions on data are often necessary to integrate, modify, and correct reports.
- A report is forever. Traceability is a must: data must be “justifiable,” and it must be possible to reproduce a specific report over time for internal audits and, if necessary, to comply with external regulations and authorities.
- It’s a time-eating monster.
Reporting is a burdensome set of activities and, to be comprehensive, requires a significant investment of time.
The challenges of enterprise data governance for controllers
By definition, management control follows organizational evolution and business needs, responding to new demands when necessary and presenting data with varying levels of aggregation depending on the stakeholders involved. Its key focus areas lie in the company structure (such as cost and revenue centers), business elements (products, services, projects, etc.), and the various forms of budgeting.
All of this translates into at least seven data management challenges: governing quality and processes, ensuring traceability at every processing step, reducing manual and repetitive tasks to gain efficiency, mitigating operational risks, improving decision-making and change management—with the ultimate goal of freeing up time for analysis and control activities.
Irion EDM: approach and capabilities
In the language of data experts, three key phases are typically identified: Data Capture (acquisition—here, one of the main goals, supported for instance by Irion EDM, is to automate as much as possible); Data Classification & Aggregation (classification, normalization, processing); and the final step, which involves Data Analytics & Reporting (both the finished report to be delivered, for example, to the Board of Directors, and the ability to perform analytics, provide data to other departments, and create dashboards for the controllers themselves).
Throughout the entire data journey, it’s essential to carry out proper data integration and remediation activities to identify and address data issues. Equally valuable is an approach oriented toward the Data Marketplace and Data Products (and more broadly, Data Sharing within the company), because while a piece of data may not have been created with end-user consumption in mind, a Data Product is, by definition, designed with those very characteristics.
Some of the capabilities of Irion, used in the field of management control alongside subject matter specialists for over 20 years, include: operational workflows (where possible, solutions have been developed in which the system automatically acquires data and generates reports), governance management with roles and permissions (responsibility chains), tracking, versioning, and certification, custom-built user interfaces (UIs), operational dashboards with data persistence, and support from the platform’s engines for AI and machine learning—enabled also by the metadata-driven nature of Irion EDM.
UNI 11608: explicit mention of data quality
The UNI 11608:2016 standard (professional requirements for controllers) emphasizes the importance of data quality in management control and defines the competencies needed to ensure that the information asset is accurate, consistent, and complete—an essential foundation for effective business decisions. A direct link is established between data quality and business performance: if data quality is lacking, not only will business analyses be inaccurate, but strategy execution within the organization will also be compromised, ultimately affecting competitiveness.
