Modernizing FP&A: How CFOs can transform finance into a strategic powerhouse
Finance has been a forward-looking function responsible for planning, budgeting, forecasting and overall financial management. Today’s accelerated business pace demands faster decision-making capabilities. Hence, the financial planning and analysis (FP&A) function is becoming strategy-focused, helping leadership make timely, informed decisions. When properly configured with the right mix of people, organizational interfaces and technology solutions, FP&A becomes a strategic growth engine, enabling intelligent and quick decision-making.
A recent webinar discussion with Baker Tilly’s Christopher Annand, Principal; Dave DuVarney, Principal; Colt Meraw, Director and Sunil Kumar, Senior Manager revealed insights about the evolution of FP&A from a traditional planning and reporting function to a strategic business engine. The conversation highlighted the challenges organizations face with disconnected systems, the importance of data readiness and the transformative potential of artificial intelligence (AI) integration in financial processes. Below are the key takeaways:
Key challenges in modern FP&A facing CFOs
Disconnected systems and processes: Organizations continue to struggle with fragmented data infrastructure, where systems don’t integrate effectively. This creates unreliable real-time information, leading some businesses to view FP&A as a “luxury function” rather than a strategic necessity. Many organizations still rely heavily on Excel for planning processes, even when they have implemented FP&A tools.
Talent gap: As technology advances and systems become more integrated, there’s an emerging shortage of finance talent with analytical and technological literacy. Traditional finance roles are evolving beyond report building toward more strategic, analytical functions that require different skill sets. Finance professionals spending time on report creation should adapt to becoming more analytical and leveraging dashboards, predictive analytics, machine learning (ML) and AI.
Finance talent must evolve alongside technology, becoming more tech-savvy and learning to leverage modern tools. This shift allows them to focus less on manual tasks and more on analytics, deep insights and driving strategic change as true partners to the business.
Colt Meraw, Director, Baker Tilly’s Digital Solutions practice
FP&A transformation approach and maturity framework
The finance transformation or FP&A technology implementation approach prioritizes understanding client needs before tool selection, considering the organization’s size and budget, existing technology ecosystem, data infrastructure capabilities and unique functional requirements. Transformation begins with the evaluation of the current FP&A team structure and skill sets, capability gaps, existing planning processes and reporting cadence. The panel outlined five levels of FP&A maturity:
Level 1
Heavy reliance on spreadsheets including manual consolidation with less control and reactive approach
Level 2
Some processes and tools integrated and in place, but business units work in silos
Level 3
Standardization and repeatable processes, but limited use of advanced technology
Level 4
Optimization state where analysis takes precedence because data and report compilation is more automated
Level 5
Integration of artificial intelligence (AI) and predictive analytics capabilities
A strong data foundation is crucial for FP&A success. As organizations grapple with fragmented systems, messy master data and over-reliance on Excel, enterprise data lakes and warehouses can serve as game-changers. They can help in integrating raw data, enabling smart modeling and powering both FP&A and enterprise-wide analytics.
Dave DuVarney, Principal, Baker Tilly’s Digital Solutions practice
AI integration in FP&A
There are three major categories of AI in finance. Predictive analytics focus on statistical models for forecasting, while machine learning follows a no-code environment, enabling time-series forecasting. Generative AI, which is mostly used, provides conversational interfaces and autonomous decision support. Advanced platforms are introducing AI agents that can provide natural language querying of financial data, generate real-time analysis and visualizations, search across enterprise documents and unstructured data and process large document volumes for complex analysis.
Organizations require three key elements for AI readiness:
- Data foundation: Clean, integrated data infrastructure
- Innovation process: Systematic approach to identifying appropriate use cases
- Adoption planning: Training and change management for user comfort
Strategic implications in finance
- Shift from reporting to influencing: Modern FP&A should focus on influencing future outcomes rather than just reporting historical results and plan variances. This requires alignment of financial goals with strategic objectives through carefully selected key performance indicators (KPIs).
- Leading versus lagging indicators: Organizations should prioritize leading indicators that drive performance (sales pipeline velocity, customer retention, operational efficiency) rather than focusing solely on lagging indicators like revenue growth and financial results.
- Finance as a strategic partner: The finance function is evolving toward a strategy-focused role that helps leadership make informed, timely decisions. This transformation requires both technological advancement and talent development.
FP&A success requires integrated approaches combining advanced technology platforms, clean data infrastructure, evolved talent capabilities and thoughtful AI implementation. The evolution from Excel-based processes to AI-driven strategic functions represents both challenge and opportunity. Companies that embrace this transformation will emerge as leaders in their respective markets.
Source: BakerTilly
