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Financial planning and analysis business meeting

What is FP&A?

Over the past few years, CFOs and their teams have been under increased pressure to evolve from record- and scorekeepers into strategic business partners. They are being asked to deliver meaningful business intelligence to the C-suite, provide rapid decision support across the enterprise, and steer the ship in a profitable – and sustainable – direction. That’s where FP&A comes in.

FP&A definition

Financial planning and analysis (FP&A) is a set of planning, forecasting, budgeting, and analytical activities that support a company’s major business decisions and overall financial health. With a corporate FP&A system, finance teams can combine financial data, operational data, and external data (like market trends) in one place. Finance can analyze it all – and uncover the in-depth insights they need to plan for the future and guide more profitable decision-making.


FP&A tools can help finance professionals:

  • Provide fast and accurate financial analysis and advice to business leaders
  • Predict the impact of potential decisions on cash flow and the bottom line
  • Assess and monitor the company’s overall financial health and investments
  • Build and maintain detailed financial models and forecasts
  • Create agile, integrated financial plans that account for multiple scenarios
  • Collaborate with departments to prepare and consolidate budgets
  • Align corporate strategy with execution and track performance
  • Identify and assess new revenue opportunities and risk
  • And much more

Financial planning and analysis is typically part of a broader financial management system – which also includes functionality for accounting, revenue and cash flow management, governance, risk, and compliance (GRC), and other core financial processes. Alternatively, FP&A can be part of a standalone analytics solution that integrates with other business systems, like ERP. Either way, FP&A has grown from basic spreadsheets and manual calculations into modern, cloud-based solutions that use artificial intelligence (AI), automation, and advanced analytics to meet the financial challenges of a rapidly changing world.


The emergence of xP&A

In 2020, Gartner introduced the concept of xP&A – which stands for extended planning and analysis. xP&A takes the best of financial planning and analysis and extends it across the enterprise, breaking down silos between departments and syncing plans across the business in real time. These continuous plans include everything from finance, sales, and marketing to HR and supply chain. And by linking them, businesses can become much more agile and able to plan for – and adapt to – changing scenarios.


The concept of xP&A is not new – it was just known by many different names: connected planning, integrated business planning, integrated financial planning, collaborative enterprise planning, and others. But now we have a name we can all rally behind – xP&A. This silo-busting, synchronized functionality has been around for years (offered by leading software vendors), and it’s never been more important than right now, when we’re all trying to plan for the unexpected and pivot on a dime.

Basic steps in the FP&A process

The FP&A process is a continuous cycle of data collection and analysis. As businesses grow and expand into new markets, and in times of market volatility and rapid change, the process becomes more complex. More data needs to be collected and more analysis needs to be done – which is why many large and midsize companies have formed dedicated FP&A branches within their finance departments. But despite increasing complexity, at its core the FP&A process includes the same four basic steps:

  1. Data collection, consolidation, and verification
    The first step in the FP&A process involves collecting financial and operational data from ERP systems, data warehouses, and other business solutions. In addition, data from outside the enterprise – such as broader demographic, economic, and market data – may also be collected.

    Once all the necessary data is collected, it needs to be consolidated, standardized, and verified. Accurate plans, forecasts, budgets, and analysis all depend on the quality and completeness of the data they use – so this step is absolutely essential. It’s also very time-consuming, so businesses are now turning to AI-powered solutions that can automate many of these tasks.
  2. Planning and forecasting
    In this step, FP&A analysts use the prepared data to create financial forecasts that predict how the business will perform in the future and if it is headed in the right direction. Financial forecasts include sales forecasts, cash flow projections, and more. Financial forecast models are also used to test out different scenarios, simulate the impact of different variables, and determine the best course of action to drive the right outcomes.

    The most commonly used financial planning methods include:

    Predictive planning: With predictive planning, FP&A professionals create a model on large data sets of past performance. Then this time-series forecasting model is used to predict future performance. Predictive analytics supercharges planning tools, especially when it’s integrated in a single solution and augmented with AI and machine learning.

    Driver-based planning: In driver-based planning, analysts identify a company’s key business drivers (aka the things that are most important to its success) – and then create a series of plans that mathematically show how the business drivers would be affected by different variables.

    Multi-scenario planning: Scenario planning and analysis is the planning method used increasingly by businesses today. In multi-scenario planning, analysts make assumptions about what might happen in the future. They anticipate consequences and then create a plan for responding to each plausible scenario.

    These models and financial forecasts are used to create the financial and operational plans needed to achieve the business’ overarching strategic goals. Developed by senior management with input from FP&A, the strategic plan includes high-level targets like revenue and net income over the short- and long-term.

    Collaboration across departments is critical for all types of planning. It ensures plans take all data, variables, and expertise into account – and it helps increase both accuracy and engagement. Collaboration brings more validity to plans – and helps build consensus around them. This is also where xP&A comes in, linking and synchronizing plans across departments so the business can eliminate silos and move as one well-oiled machine.
  3. Budgeting
    In the budgeting step, FP&A professionals estimate the expenses needed to execute the corporate plan based on the revenue from the strategic plan. They then allocate an expense budget to each business unit or function – as well as the revenue and cash flow they are expected to generate. Corporate collaborates with every department and then rolls up the agreed upon budgets into one master budget.

    The corporate budget is usually created annually, and updates are made quarterly as financial conditions change. However, to better cope with volatile market conditions, many businesses have now adopted continuous budgeting cycles that are frequently updated with rolling forecasts and projections. Some organizations have also adopted zero-based budgeting, which avoids bloat and overspending by continually evaluating which expenses are necessary and which are not.
  4. Performance monitoring and analytics
    To advise the business and provide decision support, FP&A teams analyze financial data and monitor performance – including sales, expenses, profit, working capital, cash flow, and other KPIs – on an ongoing basis. They answer ad hoc queries and translate numbers into a narrative – or data story – to help decision-makers understand a situation and take considered action.

FP&A analysts also generate regular reports and data visualizations, and conduct activities like profitability analysis – which includes future profit projections and can answer questions like “Which products and services will be most profitable next year and now?” or “Should we outsource production or keep it in-house?”.

Modern technologies for FP&A

FP&A was a top priority for CFOs and finance leaders in 2020, and it’s easy to see why. Automation, artificial intelligence, and the cloud are changing the game – making plans, budgets, and forecasts more accurate and financial analytics more powerful. Companies that use these technologies in their FP&A activities have a much better crystal ball than their competitors. It’s an incredible advantage. 


Cloud: Traditionally, FP&A software was deployed on premise, but cloud-based solutions offer a lot of opportunity. They can connect to more Big Data sources than their on-premise counterparts, they can be accessed from anywhere, they offer easy collaboration, and they are scalable and cost-effective. Recent advancements in cloud security have also made data more secure, in many cases, than if it were to be stored on premise.


AI and machine learning: Financial planning and analysis tools that are augmented with AI and machine learning are hugely beneficial to FP&A analysts. Not only can they help users analyze more types of Big Data from more sources, they can also uncover trends, patterns, correlations, and insights that might otherwise go unnoticed. AI and machine learning dramatically improve the accuracy of financial forecasts – and supercharge predictive analytics, self-service reporting, and multi-scenario planning.


Embedded collaboration tools: Built-in collaboration and planning orchestration – through discussion and commenting tools (similar to Slack and Teams), automated task scheduling within a calendar, and mobile display across phone, tablet, and digital boardroom – can help drive engagement, accuracy, and efficiency in the planning process and FP&A organization.

FP&A and COVID-19

Even before the coronavirus hit, finance leaders had begun the process of digitizing finance and adopting new technologies – but progress was slow. By February 2020, only 2% of FP&A functions had adopted AI, even though the benefits were widely known and highly sought after. The biggest barrier was that many finance departments lacked the data quality and “single source of truth” needed for AI analytics to produce meaningful results.


Now, in the COVID-19 era, there is an increased urgency to implement AI-powered FP&A tools. Many companies are facing immediate cash flow challenges and extreme financial stress as a result of virus-related shutdowns, disruptions, and change. They need more accurate forecasts and more realistic budgets. They need to find new and creative ways to make money, save money, and ensure business continuity. And they need to create long-term, integrated plans for adapting to – and surviving in – the new normal.


Modern, AI-powered FP&A solutions can help companies meet these challenges and goals. And as a result, finance leaders around the world are working hard to knock down barriers to adoption – implementing distributed data governance strategies and establishing “sufficient versions of the truth” to get up and running as quickly as possible.

In the wake of the recent economic uncertainty and market volatility, it will become even more important for finance functions to explore advanced analytics and automation. Finance teams will need these techniques to turbocharge their forecasting capabilities. 



Bringing insight and confidence to corporate decision-making, FP&A is growing within businesses as a trusted source of guidance and support. As businesses become even more competitive and complex, expect FP&A solutions to evolve to meet new challenges:

  • FP&A tools will seamlessly integrate with even more data sources and business systems.
  • Cloud-based platforms will become the delivery method of choice for FP&A software.
  • AI solutions will bring greater speed, accuracy, and efficiency to FP&A processes.
  • Extended planning and analysis (xP&A) will help to remove the barriers to collaboration – both inside and outside the enterprise.

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