FP&A teams now work with larger data volumes, connected models and more frequent forecasting cycles. This evolution is driving the emergence of hybrid professionals who understand finance, data and technology.
Why traditional skills are no longer enough
Strong financial expertise remains essential. But time spent extracting, cleaning and reconciling data reduces analytical capacity. Teams must understand how information flows between ERP systems, data platforms and EPM solutions.
The finance and data profile
This person is not necessarily a data scientist. A hybrid professional can:
- formalize a business rule;
- query and validate data;
- understand a multidimensional model;
- automate a simple task;
- visualize a result;
- turn analysis into a decision.
A bridge between business and technology
These professionals reduce misunderstandings between finance, IT and operations. They can challenge an architecture without losing sight of the accounting or economic meaning of the data.
The impact of AI
Generative AI makes tools and programming more accessible, but it also increases the need for control. Knowing how to formulate a request, verify an answer and understand its sources is becoming a key skill.
How to develop teams
- train finance professionals in data fundamentals;
- provide access to test environments;
- create finance and technology pairs;
- recognize automation and documentation work;
- build cross-functional career paths;
- recruit for learning ability as much as for proficiency in a specific tool.
Avoid creating an isolated specialist
The hybrid specialist must not become the only person capable of operating the model. Solutions must be documented, reviewed and incorporated into team governance.
A new role for FP&A
By reducing manual production, these professionals allow FP&A to focus on scenarios, risks and decision support. They also help connect actuals, forecasts and operational data.
Priority skills to develop
- financial modeling;
- data quality and governance;
- EPM and BI tools;
- automation;
- storytelling and business partnering;
- governance of AI use.
The hybrid profile does not signal the disappearance of specialist expertise. It creates the capacity for dialogue and integration that has become essential for turning data into operational decisions.