Modern FP&A Solutions for Agile Business Strategy.
What is Financial Planning and Analysis (FP&A)?
FP&A (Financial Planning and Analysis) is a set of planning, forecasting, budgeting, and analytical activities that support a company's major business decisions and overall financial health.
In today's volatile market, finance professionals must see around corners. FP&A helps combine financial data, operational data, and external market trends to uncover deep insights that guide profitable decision-making.
How FP&A Helps Your Business
- Predictive Insights: Predict the impact of potential decisions on cash flow and profitability.
- Financial Health: Assess and monitor the company's overall investments and health.
- Scenario Planning: Create agile financial plans that account for multiple "what-if" scenarios.
- Budgeting: Collaborate with departments to prepare and consolidate budgets.
- Performance Tracking: Align corporate strategy with execution and track performance in real-time.
The FP&A Process
Data Collection & Consolidation
Collecting financial and operational data from ERP systems and external sources. Consolidating and standardizing this data is the foundation of accurate planning.
Planning & Forecasting
Using prepared data to create financial forecasts (sales, cash flow, etc.) that predict future performance. This includes predictive planning and driver-based planning.
Budgeting
Estimating expenses needed to execute the corporate plan. Allocating budgets to business units and rolling them up into one master corporate budget.
Performance Monitoring & Analytics
Ongoing analysis of financial data (sales, expenses, profit, KPIs) to advise business leaders and support decision-making.
Modern FP&A Technologies
We leverage modern tools to enhance accuracy and efficiency:
- Cloud-Based Solutions: Scalable, cost-effective, and accessible from anywhere for easy collaboration.
- AI & Machine Learning: Uncover hidden trends and improve forecast accuracy by analyzing big data.
- Robotic Process Automation (RPA): Automates manual data aggregation tasks, reducing errors and saving time.