Financial Planning & Analysis teams relied on slow, manual workflows: forecasting in spreadsheets, investigating variances across siloed systems, and spending days writing narrative reports for executives. FP&A was reactive, fragmented, and unable to deliver insights with the speed modern businesses required.

As UX Director at Oracle, I led the strategy and design of Planning Agent, a next-generation AI system embedded in Oracle Cloud EPM that transforms how FP&A teams forecast, explain, and simulate financial outcomes. I defined the north-star vision, AI interaction model, trust framework, and cross-product orchestration needed to operationalize AI at enterprise scale.

By reimagining forecasting, variance analysis, scenario modeling, and executive reporting through an AI-first lens, the Planning Agent elevates FP&A from manual data management to strategic decision-making, enabling CFO organizations to move from reactive reporting to proactive insight.

This case study highlights the product strategy, system design, organizational leadership, and cross-functional influence behind Oracle’s AI-driven FP&A platform.

FP&A work was fragmented, reactive, and dependent on manual analysis.

Across enterprises, FP&A teams faced consistent challenges:

• Reactive FP&A Processes

Forecasting, variance analysis, and scenario modeling were slow, manual, and dependent on siloed spreadsheets.

• Hidden Insights
  Analysts lacked clear explanations for forecast changes, making it difficult to identify drivers, correlations, and emerging risks.

• No Strategic “AI Partner”
  FP&A teams needed automated narratives, AI-guided simulations, and proactive recommendations—not just faster math.

• Fragmented Experience
  Disconnected tools and legacy workflows prevented CFOs and analysts from making timely, data-driven decisions with confidence.

Fragmented Experience

Primary Users of FP&A
Planner, Regional Analyst, Corporate Analyst, CFO

My Mandate as UX Director

I was asked to lead the product vision and UX strategy that would transform Oracle EPM from a traditional planning tool into an intelligent, AI-driven enterprise platform.

My mandate included:

• Defining the vision and north star for AI-driven planning.

• Establishing the experience architecture for Planning Agent.

• Creating the trust, explainability, and human-in-the-loop frameworks required for financial adoption.

• Aligning ERP and EPM organizations around shared integration points and AI maturity.

• Building operating mechanisms that allowed multiple teams to deliver cohesive AI value.

• Coaching and directing designers to execute the vision across journeys, workflows, and systems.

This required influencing product strategy, engineering priorities, and organizational behaviors at scale.

Strategy I Defined

North Star: The Planning Agent becomes the “AI Analyst” that supports every FP&A professional.

The strategy centered around four pillars aligned to finance teams’ biggest pain points:

How I Operationalized Planning Agent

Turning a multi-year vision into a unified, AI-driven product experience.

1. Predictive AI — Trust
Builds trust in AI with data-driven forecasts and measurable accuracy gains

Drove Business Impact

Achieved shared goals of Trust, Efficiency, Adoption

“With Oracle Cloud ERP, we have transformed our accounting services by standardizing financial processes across 40+ countries to improve efficiency, reduce cost, and accelerate decision-making.” - Dietrich Franz, Chief Financial Officer, DHL Supply Chain.