Financial Planning Maturity Model

A financial planning maturity model gives finance teams a structured framework for progressing from reactive number-crunching to genuine business partnership. Rather than offering vague aspirations about improvement, these models define specific, checkable capabilities that a team either has or has not yet developed. The 2024 AFP FP&A Maturity Model and the FP&A Trends Maturity Model (the one used at the 9th Chicago FP&A Board, held March 13, 2025, at the Spaces venue on Michigan Avenue) both accomplish this by breaking maturity into defined stages with concrete criteria. The FP&A Trends model evaluates teams across five levels, assessing dimensions that include data governance, analytics capability, technology integration, cross-functional collaboration, and the degree to which FP&A functions as a strategic partner rather than a reporting function.

The AFP model organizes maturity across three domains: Finance and Financial Processes, Technology and Data, and Personal and Team Effectiveness. These two frameworks approach the problem from complementary angles: the FP&A Trends model provides a stage-by-stage progression map that helps teams locate where they currently sit in relation to best practice, while the AFP model provides a domain-level diagnostic that surfaces which specific capabilities are limiting a team's overall maturity.

Together, they give finance leaders a practical diagnostic for identifying gaps, prioritizing investments in process improvement and technology, and tracking progress over time. Finance teams that apply these models systematically are better positioned to shift from delivering reports to shaping decisions, which is the practical difference between a transactional FP&A function and one that contributes meaningfully to resource allocation and strategic planning. This piece walks through what those stages look like, what the AFP domains require, and what it takes to move between maturity levels.

The Five Maturity Levels Explained

The FP&A Trends Maturity Model runs five levels, from Basic up to Leading, with intermediate stages in between.

Level 1, Basic. No business intelligence tools, no planning models, no cross-team collaboration, and no business partnering. Finance keeps score: data comes in, reports go out, and the analytical focus is purely descriptive, capturing what happened and nothing more.

Level 2, Developing. Processes exist but are applied inconsistently, and collaboration across teams is minimal. A basic planning model and some analytical drivers are present but used unevenly depending on who is running the analysis. Basic BI tools appear at this stage, though most work remains manual. Analytics begin to move beyond simple description.

Level 3, Defined. Processes are documented and followed consistently. Collaboration becomes structured rather than ad hoc. FP&A begins providing analysis and interpretation rather than just delivering data.

Level 4, Advanced. Predictive capability becomes central. Driver-based models, scenario planning, and rolling forecasts replace static annual budgets. Technology integration deepens, and regular engagement with business units becomes routine. Analytics shift toward predicting what will happen next.

Level 5, Leading. Workflows are automated and optimized, and planning and reporting operate in real time through self-service tools. Prescriptive analytics built on "what-if" scenarios and machine learning recommend specific actions rather than simply forecasting outcomes. The static annual budget is replaced by driver-based rolling forecasts developed collaboratively with business units. FP&A analysts concentrate on judgment-intensive work and strategic business support rather than data assembly.

At the Chicago FP&A Board, participants were polled on where their teams currently sit. 46% said Developing. 26% said Defined. Only 2% said Leading. The gap between where most teams operate and where they aspire to be is substantial, and understanding the specific criteria at each level is a prerequisite for closing it.

AFP's Three Domains Define Maturity Stage

AFP's 2024 model organizes maturity across three domains, each with sub-elements a team can score itself on, landing somewhere in foundational, emerging, or optimized.

Finance and Financial Processes covers how well a team applies financial judgment to capital allocation and strategic decisions, calibrated against the organization's risk appetite. Well-run processes support adaptability and continuous improvement. Poorly designed processes actively obstruct sound decision-making and create organizational drag by slowing down the analytical cycles that business units depend on for timely resource decisions.

Technology and Data is where AFP focuses on function rather than tooling. The model specifies what Integrated Planning, Analytics, and Reporting need to accomplish, all resting on Data Management as the underlying foundation. It deliberately avoids naming specific software vendors, keeping the question focused on what the function needs to do rather than which platform delivers it. The Chicago working group on Data and Models reinforced this approach with a specific recommended sequence: build a central chart of accounts, establish data governance, map every data source, consolidate into a data warehouse or lake, and validate data quality before constructing any model on top of it. Teams that skip or reorder these steps produce models that generate unreliable outputs rather than accurate ones.

Personal and Team Effectiveness addresses the human dimension of maturity. As automation handles a growing share of routine analytical work, AFP's framework is direct: the goal is not to compete with technology on computation but to develop the capabilities technology cannot replicate. That means building commercial awareness, business acumen, scenario planning judgment, and the digital fluency required to work effectively within advanced systems.

A team's overall maturity level is only as high as its weakest domain. A finance function running advanced predictive analysis on top of underdeveloped data governance is not operating at an advanced maturity level in any meaningful sense, regardless of the sophistication of its models.

Why Teams Stall at Developing

At the Chicago Board, a large majority of attendees placed themselves at either Developing or Defined. That pattern reflects the broader reality: most finance teams are not held back by a lack of ambition or awareness, but by a specific set of organizational and structural obstacles.

The primary blockers are cultural resistance, unclear role definitions, systems that do not integrate with one another, and data governance that no one has taken clear ownership of. The Chicago session was explicit on this point: fragmented systems and organizational culture stall progress more reliably than any technology limitation does.

One recurring failure pattern involves deploying a new planning tool before addressing underlying data quality issues. Teams invest in sophisticated platforms and then find that the outputs remain unreliable because the input data is inconsistent, duplicated, or poorly reconciled. The tool performs as designed; the problem is the foundation it is built on.

The Chicago working groups identified several additional obstacles on the people side: insufficient intellectual curiosity as a team habit, a mismatch between the roles people hold and the skills that higher maturity levels actually require, and underinvestment in developing the business partnering capabilities that distinguish advanced FP&A from transactional reporting.

On the systems side, recurring issues include scope creep during technology implementations, rollout approaches that are too uniform to account for variation across business units, unaddressed security risks, and inadequate training that prevents new tools from being used effectively. Compounding all of this is a persistent perception problem: many business units continue to view FP&A as a reporting function rather than a strategic partner. Until that perception shifts, FP&A teams will continue to be engaged as information providers rather than as contributors to decision-making.

Concrete Steps to Advance Maturity Stages

The model is designed for teams to assess where each domain actually sits before directing resources toward improvement. Without that assessment, investments are poorly targeted.

Basic to Developing means establishing foundational infrastructure where none exists: basic planning models, some consistent use of analytical drivers, and introductory BI tooling. The objective at this stage is to create a baseline rather than achieve sophistication.

Developing to Defined means standardizing processes that are currently informal and inconsistent, and establishing structured, repeatable collaboration with business units as a minimum threshold for genuine progress.

Defined to Advanced means building predictive capability and treating scenario planning as an ongoing discipline embedded in the planning cycle rather than a periodic exercise triggered by external requests.

Advanced to Leading means automating high-volume repetitive tasks, building out machine learning and "what-if" analytical capability, and reorienting analyst time from data assembly toward interpretation and strategic input. Matt Poleski, CFO for the Northeast and Mid-Atlantic Region at Arthur J. Gallagher and Co., described at the Chicago Board how his team aligned finance principles directly with the FP&A Maturity Model, pairing digital tools with structured leadership development, using technology to expand margin without proportionally expanding headcount, and connecting career development and compensation decisions systematically to business outcomes.

Every stage transition requires two parallel changes: a structural one covering process, data, and tools, and a behavioral one covering roles, skills, and leadership. Addressing systems without addressing culture produces stalled progress. Addressing culture without addressing systems produces good intentions constrained by bad data. The Chicago working group on People and Culture identified specific behavioral capabilities worth building into formal development plans: servant leadership orientation and intellectual curiosity. These are not aspirational descriptors but observable behaviors that can be assessed and developed deliberately.

What Advanced Maturity Demands from Talent

At lower maturity levels, FP&A is evaluated on speed and accuracy: whether reports are delivered on time and whether the numbers are correct. At higher maturity levels, the evaluation criteria shift substantially. The relevant questions become whether the analysis generated meaningful insight and whether that insight influenced decisions.

AFP's model addresses this directly. As automation absorbs more routine analytical work, the appropriate response is not to replicate what technology does more efficiently, but to invest in the capabilities technology cannot provide. These include commercial awareness, business acumen, scenario planning judgment, and digital proficiency oriented toward interpretation and strategic partnership rather than computation.

The Chicago session described the senior FP&A professional as occupying two roles simultaneously: communicator of complex financial narratives and architect of strategic planning frameworks. Both roles require distinct skill sets, and both require deliberate development. The FP&A Club's characterization of advanced maturity stages includes a formal talent improvement plan as a specific element, which suggests that maturity planning and talent planning should be integrated rather than managed as separate workstreams.

Poleski's experience at Arthur J. Gallagher also highlighted the importance of maintaining balance between creative leadership and operational discipline. Finance functions operating at the leading stage manage that balance intentionally, and building that capacity requires planned effort rather than emerging as a byproduct of reaching a certain level of technical capability.

Use the Model as a Recurring Diagnostic

AFP designed this model for ongoing self-evaluation rather than a one-time assessment. Teams score themselves across the domains, establish a baseline, and track movement over time. The purpose is to identify a starting point and measure progress from there, not to generate a static rating.

The broader conclusion from the Chicago Board session is that maturity is not a fixed label but a continuously evolving condition. That means the model should be revisited whenever significant organizational changes occur: a new CFO joins, a major platform is deployed, a reorganization takes place, or a new strategic planning cycle begins. Running the assessment on a fixed calendar schedule regardless of whether anything has changed reduces its value as a diagnostic tool.

The model's primary utility is in directing resources toward the domains that are constraining overall maturity, not in assigning grades. A domain that lags behind the others is a signal about where investment in process, data, or people development is most needed. The specific interventions the Chicago working groups identified, including data governance improvements, process documentation, and building organizational buy-in for change, are not completed once and then resolved. They require ongoing maintenance as the organization evolves.

The distance between Developing, where 46% of the Chicago room placed themselves, and Leading, where only 2% operate, is real and significant. But it is traversable through sequential, defined steps, and that is the core value of a maturity model: making each step visible and concrete so that progress can be planned and measured rather than hoped for.