What is FP&A?

What is FP&A?

In recent years, senior finance managers and their teams have been under pressure to transform their function from record keepers into strategic business partners. The C-suite needs them to produce meaningful business intelligence, supporting rapid decision-making across the whole business and guiding the company in a profitable direction – as well as being sustainable. FP&A (Financial Planning & Analysis) enables them to do this.

Defining FP&A

FP&A can be defined as a set of planning, forecasting, budgeting or analytical activities which supports a company’s decisions and protects their financial health. Corporate FP&A systems allow finance teams to collate operational, financial and external data (such as market activity or trends) in one place. The aim is to uncover detailed insights through the analysis of this data. The business can then plan for its future more effectively, ensuring profitability.

Financial professionals are helped by FP&A tools to do many things, such as:

  • Produce quick, accurate financial analysis and advice for senior managers and leadership teams,
  • Prepare and consolidate budgets in collaboration with other departments,
  • Monitor and predict how cash flow and profitability will be impacted by certain decisions,
  • Assess the organisation’s overall financial position,
  • Allow the creation of detailed financial forecasts and models,
  • Ensure corporate strategy is aligned with execution and monitor performance,
  • Find and analyse new opportunities for revenue generation and associated risks,
  • Take into account multiple scenarios when creating agile, integrated financial plans.

FP&A has developed from simple spreadsheets or manual calculations to advanced, cloud-based solutions, drawing on automation and artificial intelligence (AI) to overcome financial issues that our rapidly changing world creates. Financial planning and analysis is commonly part of a wider system designed to manage finances which itself may be responsible for managing accounting, cash flow, governance, risk and compliance. On the other hand, FP&A may form part of a self-contained analytics solution that integrates with other systems in the organisation, such as Enterprise Resource Planning (ERP).

Overview of the FP&A process

FP&A requires continuous processing of data collection and analysis. When markets are volatile and change rapidly, and as businesses themselves expand and change, FP&A becomes increasingly complex. It’s this increased demand for data handling that leads many larger organisations to create specialised FP&A teams within their finance departments.

Underpinning all Financial Planning Analysis are four basic steps, which remain broadly the same however complex the process becomes:

(1) Data gathering, consolidation and verification

Before any planning or analysis can happen, data needs to be collected. The data may be financial or operational in nature and come from ERP systems, data warehouses or other place within the business. External data – such as economic, market or demographic data may also be gathered.

After collection, there is one more step to go through before the data can be used to make business decisions: it must be standardised, consolidated and verified. This is critical, as the forecasts, plans and budgets that are made using the data rely on it being complete and of high quality. This step may take significant time, but nowadays more and more businesses are harnessing the power of Artificial Intelligence to speed up this process.

(2) Planning and forecasting

In step 2, FP&A analysts create forecasts using the data, to predict the future performance of the business and assess the direction the business is heading in. Financial forecast models can be used to workshop scenarios, or simulate the impact of many moving parts and variables on the business. They may also include projections around cash-flow and sales. There are several methods of financial planning, the most common being:

  • Predictive planning: this is where a large dataset of past performance data is used to create a model, which is used to predict future performance. Planning tools can be supercharged by using predictive analysis, which is particularly powerful when integrated in a single system and boosted with machine learning or AI.
  • Driver-based planning: here, the factors most crucial to a business’s success are analysed, and a series of plans are created. They use maths to show how these key drivers might be affected by different variables.
  • Multi-scenario planning: this is where analysts create several scenarios about what might happen in the future, and then identify the consequences of these events and a plan of response. This sort of planning is used increasingly by businesses today.

The developers of these plans are the Senior Management team, using input from FP&A, and they’ll include high-level targets like revenue and net income, over both the long- and short term. They will be used ultimately to achieve the business’s high-level strategic goals.

Inter-departmental collaboration is important when it comes to planning, so that all expertise is used and all variables and data sources are considered. This brings greater accuracy and engagement. When the process is collaborative, validity is brought to plans and a consensus can be built around them. Extended Planning and Analysis (xP&A – see below) also plays its part here, to synchronize plans across sections of the business and thus break down silos and increase operational efficiency.

(3) Budgeting

The third step is to estimate the expense needed to carry out the corporate plan based on the revenue from the strategic plan. An expense budget will then be given to each business unit, alongside figures for the revenue and cash flow they will be required to generate. These departmental budgets will then form a master budget.

Corporate budgets are usually made annually, with quarterly updates as trading conditions change. But many businesses now use continuous budgeting cycles to cope better with volatile commercial conditions, which are often updated with rolling forecasts and projections. Zero-based budgeting is used sometimes, which is designed to avoid overspend and bloat by keeping an eye on necessary expenses and eliminating non-essential spend.

(4) Performance monitoring and analytics

FP&A teams have to give business advice and support decision making, which they do continually by analysing financial data and monitoring performance, such as cash flow, profit, expenses, working capital and other key performance indicators. Decision makers may also require them to answer ad hoc queries and create a narrative from the numbers – also known as a ‘data story’ – to help them understand situations and take appropriate action.

Other duties of FP&A analysts may include creating data visualisations, reports and analysis of profitability. They may answer questions around which products or services will be most profitable the following year, or whether production should be in-house or outsourced.

The evolution of xP&A

xP&A stands for ‘extended planning and analysis’, a concept which was introduced by research and advisory firm Gartner in 2020.  It breaks down inter-departmental silos and aligns business plans in real time, by using the best financial planning and analysis and extending these across the whole organisation. Continuous plans such as these may be for sales, finance, marketing, HR and supply chain. When they are linked, a business can become far more agile, and be able to plan and adapt to a variety of changeable scenarios.

The emergence of xP&A means there is a new term to get behind and a new goal to aim for. But it isn’t an entirely new concept – it’s been known by many names, from collaborative enterprise planning, to integrated financial planning, connected planning or variations of these. The functionality to break down silos and synchronise systems has existed for a while, but today it’s more crucial than ever. Uncertain business conditions necessitate planning for every eventuality, however unexpected, and the ability to be agile and change direction at a moment’s notice is crucial.

Modern FP&A technologies

Companies which use the latest technology in their FP&A activities have better prediction and planning skills compared to competitors, giving them a significant advantage. In recent years, CFOs and finance leaders have prioritised FP&A because they see how the financial planning sphere – and the technology associated with it – is becoming more powerful.  Some of the most powerful technologies are:

Machine learning and AI

FP&A analysts benefit hugely from tools that are enhanced with AI and machine learning. In addition to enabling the analysis of Big Data of many types and from more sources, they also spot patterns, trends and insights that would otherwise go unseen. Financial forecasts become much more accurate when AI and machine learning tools are used, and predictive analytics, reports and multi-scenario planning are supercharged in their effectiveness.

Cloud

Nowadays, cloud-based solutions bring a multitude of opportunities, in contrast to traditional on-premise FP&A software. Cloud systems access more sources of Big Data, offer access from anywhere, wider collaboration and are also more cost effective and scalable. In addition, compared to on-premise storage of data, cloud solutions now have much improved security.

Embedded collaboration tools

In-built collaboration and planning helps drive accuracy, engagement and efficiency in the planning process. It can happen through automated task scheduling, discussion and commenting tools like Teams and Slack, or mobile display on a phone or digital boardroom.

Summary

As businesses realise the advancements in insight and planning confidence that it brings, FP&A will continue to grow in popularity. Business will also become more and more complex, so we are likely to see FP&A solutions developing too, in order to meet this challenge. For example:

  • AI solutions will allow FP&A processes to become faster, more accurate and operate with greater efficiency,
  • Barriers to collaboration will be removed by virtue of extended planning and analysis (xP&A), both inside and outside of an organisation,
  • Even more business systems and sources of data will become seamlessly integrated with FP&A tools,
  • The delivery method of choice to FP&A software will become cloud-based platforms.