What FP&A Leaders Must Prioritize Now to Drive Value

Compressed planning horizons. Boards demanding faster insights. Technology is changing every month, reshaping what’s possible. In these ways and more, financial planning and analysis (FP&A) is changing quicker than you can say “scenario planning.” Yet ambition is outpacing execution.

According to recent research, only 2% of FP&A teams describe themselves as “fully optimized,” while nearly half of their time is still spent on data collection and validation. That’s at the highest level in five years. Strategic partnering? Analysis? Who has time for that?

Moving forward, FP&A must evolve from reactive reporting to proactive, trusted decision-making.

Here are five priorities shaping the future of FP&A and how to act on them:

1. Establishing Joint Finance–IT Councils

Governance is the backbone of transformation. Today, FP&A leaders increasingly recognize that definitions, master data, lineage, and access cannot be managed in isolation. While finance owns assumptions and usage, IT ensures infrastructure, security, and performance. Together, the two create a foundation for consistency and trust.

Why It Matters:

Without joint stewardship, data chaos undermines credibility and slows decision-making. Governance gaps derail transformation and create conflicting metrics. In fact, finance transformation programs often fail because governance is treated as an afterthought. Unclear decision rights also lead to conflicting metrics and wasted effort.

What Good Looks Like:

• Consistent definitions across the enterprise to eliminate debates over “what counts.”
• Persistent lineage tags for drill-back to source systems, ensuring transparency.
• Role-based access and artificial intelligence (AI) guardrails to maintain compliance and prevent misuse.

Practical Tip:

Form a finance–IT council with a clear charter for governance and accountability. Embed governance into transformation programs early to prevent costly rework. Through this partnership, technology amplifies well-defined processes rather than compensating for broken ones.

2. Making Scenario Planning a Muscle Memory

Now that uncertainty is the new normal, scenario planning has become a core competency, not a crisis response. Assumptions can shift overnight — whether due to supply chain disruptions, regulatory changes, or geopolitical shocks. To make scenario planning iterative rather than episodic, organizations must institutionalize foresight.

Why It Matters:

Organizations that can pivot quickly with scenario planning gain a significant edge in decision-making. However, many still struggle to embed this capability into their daily rhythm. For most organizations, scenarios remain an occasional exercise rather than a core part of integrated planning. And even when insights are generated, they often fail to translate into timely action.

What Good Looks Like:

• Refreshing assumptions weekly or daily, not just annually.
• Leveraging AI to seed forecasts automatically.
• Maintaining transparent assumption catalogs.

Practical Tip:

Treat flash forecasts as obsolete. Unified, governed data enables automatic seeding of forecasts, with collaborative adjustments in a shared user experience (UX). Make scenario planning a core competency, not a crisis response. When able to stand up credible what-ifs “on the fly,” finance moves from historian to navigator.

3. Aggregating Source Systems into Trusted Data Marts

AI magnifies the cost of poor data, so trusted data marts are essential for speed and accuracy. Today, organizations are increasingly adopting modern architectures, such as data fabric and data mesh, to unify fragmented sources and create a single, governed environment. Companies with strong data foundations reliably demonstrate greater agility and better decision-making due to being able to access accurate, timely information when it matters most.

Why It Matters:

Compared to low-quality teams, high-quality data teams spend twice as much time on insights. Trusted data marts enable the following:

• Faster refresh cycles aligned to planning SLAs.
• Reduced risk of hallucinations in AI models.
• A single, governed environment for planning and analysis.

What Good Looks Like:

• Aggregating ERP, HCM, CRM, and supply chain data into curated, auditable data marts.
• Enforcing data borders so models stay within curated contexts.
• Setting refresh SLAs aligned to planning cadence.

Practical Tip:

Invest in modern data integration tools, and master data management practices. To ensure data is accurate, auditable, and timely, establish joint stewardship between finance and IT. This trust dividend compresses cycles and green-lights the next wave of AI use cases.

4. Owning a Shared Source of Truth and Producing Credible Scenarios on Demand

Influence starts with trust, and FP&A leaders want one version of the truth that supports instant scenario modeling. According to McKinsey, this “next-level FP&A” means teams that build speed and flexibility into processes become trusted partners to the business.

Why It Matters:

When able to deliver credible what-ifs on the fly, finance moves from historian to navigator. A shared source of truth eliminates definitional debates and accelerates decision-making. Having one source of truth also strengthens FP&A’s role as a strategic advisor rather than a reporting function.

What Good Looks Like:

• Unified platforms (like OneStream!) that reconcile actuals, plans, and scenarios in real time.
• Extensible dimensions for granular modeling and instant roll-ups.
• Collaborative UX for business owners to plan with finance, not just consume reports.

Practical Tip:

Adopt platforms that enable continuous planning and scenario modeling. Align technology investments with governance to ensure consistency and auditability. By owning the data and the process, FP&A earns a seat at the strategy table.

5. Overcoming Political Blockers

Technology alone won’t fix siloed ownership or legacy guardrails. Functional silos make organizations slow and bureaucratic. According to HBR, 67% of collaboration failures stem from silos. Breaking these barriers requires cultural change, governance, and clear accountability.

Why It Matters:

Political blockers delay transformation and keep FP&A stuck in reactive mode. They manifest as departmental turf wars, conflicting priorities, and resistance to shared platforms.

What Good Looks Like:

• Moving from departmental control to shared stewardship.
• Defining decision rights upfront and aligning incentives to enterprise outcomes.
• Appointing global process owners to drive end-to-end visibility.

Practical Tip:

Frame unification as a business imperative, not just a technology upgrade. Show how faster answers and fewer definitional debates translate into strategic agility. Use metrics (cycle time reduction, forecast accuracy, decision speed) to build the case for change.

Conclusion

The future belongs to FP&A teams that unify platforms and data, embed scenario planning into daily rhythms, enforce data trust, scale auditable AI, and retool roles for influence. What does that mean for you? First, fix the process. Then let technology amplify it. Treat trusted data as a strategic asset, and make scenario speed an everyday reality.

Boards are also watching. They expect AI programs to prove return on investment, cost savings, and productivity on a recurring cadence. By acting now, FP&A leaders will not only meet those expectations but also redefine what finance means to the business.

Curious about what other trends are driving FP&A leaders? Read our eBook titled “The Future of FP&A: Trends, Challenges, and the Rise of AI in 2026.”