Comprehensive Guide To Financial Forecasting Methods

Finance teams

With the right financial forecasting methods, FP&A teams can accurately analyzing business performance. But which forecasting method works best?

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Priyanka Desai
September 2, 2022
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Comprehensive Guide To Financial Forecasting Methods

Summary

“Previously, FP&A teams would spend their time justifying assumptions. With a powerful set of financial forecasting methods, these teams can now spend more time analyzing the organization’s performance and serve as proactive business partners.” 

The evolution of financial forecasting 

Financial forecasting started when organizations realized that they needed a method to:

  • Evaluate performance
  • Compare budget vs actual spend
  • Identify areas that deviated from expectations
  • Attempt to hedge against the worst-case scenarios

Traditional financial forecasting models involved quarterly business performance checks that led to limited transparency and a reactive state, where outcomes could not be influenced as soon as they were reported. 

Paired with limited access to data, what should have been a value-add activity became a significant process burden. Organizations did not have the bandwidth in terms of tools, resources, flexibility, and interdepartmental collaboration to analyze the results constantly. 

As a result, stagnant and interval-based forecasting became a thing of the past. 

What led to transformations in financial forecasting?

With evolving stakeholder requirements, growing expectations, and global disruptions, financial forecasts need to be constantly refined and optimized.

Organizations have an increasing need to be agile in order to keep pace with competitors. In addition, constantly changing customer behavior in an increasingly crowded market place affects the pace of business, and financial forecasting is no exception. 

Business leaders are expected to maintain a high-quality and efficient financial forecast.

Equipped with accessible and accurate data, resource adaptability, and modern technology, they’re leveraging robust financial forecasting methods for strategic finance business partnerships

The current scenario  

Today, organizations and their FP&A teams are using financial forecasting models for a large set of use cases, including:

  • Evaluate multiple “what-if” scenarios to weather unexpected setbacks
  • Charter the path to profitability
  • Actively engage with cross-functional teams
  • Win trust from leadership
  • Proactively monitor competitors
  • Identify opportunity areas to improve and capitalize

With this context in place, take a look at the financial forecasting process in detail:

What is financial forecasting? 

Financial forecasting analyzes events from the past and present, and collates this information to determine what’s going to happen in the future.

Financial forecasting techniques are used by businesses to plan and adapt to uncertainties the business could encounter. It contains both macroeconomic factors and conditions specific to an organization. 

Businesses can engage in a thorough forecast to generate financial plans. This plan helps estimate projected expenses, income, and other factors that could impact revenues and contingencies that may not currently be necessary. 

Effective financial forecasting models rely on skilled experts, strategic business finance partnerships, and tools like budgeting and forecasting software. 

The good thing about financial forecasting is that it creates a business roadmap to achieve growth and maintain stability. But what happens when significant changes occur either internally or externally? 

It’s fair to say that change never ends. And when things aren’t going as originally planned, it is time to reforecast. 

What is reforecasting? 

Ask any FP&A manager and they would say that reforecasting is a core principle of strategic finance. It is defined as a process of revising the existing annual budget, especially when there is a significant fluctuation in projected income or spending. 

Companies that are looking to enter into a more distinct market or looking for additional ways to grow their revenue income streams use reforecasting throughout the year to ensure that their vision aligns with core principles. 

Who uses financial forecasting? 

Financial forecasting models are made by financial planning and analysis (FP&A) teams or CFOs in close collaboration with the business teams. Forecast reports are used by leadership to establish business goals that are both realistic and feasible, which helps in steering the business in the right direction. 

What is the difference between financial forecasting and budgeting? 

Although budgeting and financial forecasting are used by leadership to check the pulse of the business, these terms are often confused. It's important to note the differences between financial forecasting and budgeting:

Funding Stage Budgeting
Projection of the company’s future direction Outlines spending mapped to goals
Prediction-based Actionable
Covers the future status of the company and the economy at large Highlights the current status of the company
Extremely flexible and can be adjusted to reflect changes in the operating environment Budgets are more static and are only adjusted when there are changes in the initial assumptions
Types of financial forecasting methods:
- Driver-based
- Predictive or prescriptive
- Exception-based
- Moving average
- Simple and multiple linear
Types of budgeting:
- Incremental
- Activity-based
- Value proposition
- Zero-based
- Cash flow
As forecasting methods involve intensive data collection and analysis, they are conducted once per year. Simpler forecasts like sales forecasts might be conducted each quarter. Budgeting is done weekly, monthly, quarterly, or annually depending on the size of the company

A well-constructed forecast informs the budget about which areas to focus on for growth or reduction. An updated and strategic budget helps adjust the financial forecast to reflect both increased savings and mitigated losses.

What are the financial forecasting models? 

At this stage, you should know that financial forecasting is not a straightforward task. There are different types of financial forecasting models you can use depending on the information you have and the insights you are looking to generate.

Broadly, they are categorized into quantitative and qualitative methods with a few key differences between each:

Quantitative financial forecasting Qualitative financial forecasting
Most commonly used to analyze business performance, quantitative financial forecasting relies on real data (bank balance, financial statements, and sales) Qualitative forecasting models are used when you don’t have access to complete information and need to make estimates especially when the values are a little vague
Helpful when you have a good record of historic data Helpful when the values are ambiguous
Example - In the SaaS industry, you would use a quantitative forecasting model to predict the average value of each customer Example - If your retail business is looking to expand to new geography, qualitative forecasting would show you how long it would take to break even
More accurate since the forecast is derived from hard numbers Less reliable and used when you need to make predictions about minor aspects of your business

Five key financial forecasting methods for accurate predictions 

Driver-based forecasting 

Driver-based financial forecasting approach to FP&A models business performance based on key levers most impactful to your organization. 

This model answers two main questions: 

  • How are we planning to grow as a business? 
  • How is that growth going to produce desired results? 

Driver-based forecasting uses assumptions to build a comprehensive financial picture. This in turn allows the FP&A team to arrive at a point of view used to hold cross-functional departments accountable. 

How to build a driver-based forecast? 

  1. Define the qualitative business goals 
  2. Identify the quantitative KPIs to measure those goals 
  3. Break down these KPIs into assumptions, drivers, and results 

Predictive and prescriptive forecasting 

It’s common for organizations to accumulate enormous amounts of data. Due to this, it becomes essential to augment analysis by harnessing machine learning and artificial intelligence. This surfaces more robust insights through recognizing patterns in data from both external and internal sources. 

When elucidating data about consumer demand, macroeconomic factors, and beyond, predictive and prescriptive financial forecasting provides intelligent operational forecasts for strategic decision-making.

Exception-based forecasting 

Considering the speed at which the world is progressing, historic business cycles are becoming outdated. During unforeseen events, exception-based financial forecasting models are adaptable enough to cater to these events to mitigate risks and leverage rising opportunities. 

Moving average forecasting 

The moving average forecasting report uses historical data to predict future numbers and allows organizations to project future results. This type of financial modeling is used for budgets and expenses. 

Formula to calculate moving average forecasting: The number of prices within a time period divided by the number of total periods. 

Simple and linear regression 

Simple linear regression forecasts are dependent on the relationship between two variables: dependent and independent. 

Here, the dependent variable signifies the forecasted amount. 

The independent variable is the factor influencing the dependent variable. 

Formula: Y = BX + A 

Y = Dependent variable 

B = Regression line slope 

X = Independent variable 

A = Y - intercept 

When two or more variables directly impact a company’s performance, multiple linear regression gives a more accurate forecast as it takes into consideration several variables that ultimately influence performance.

What are the key benefits of financial forecasting? 

Financial forecasting models allow you to make more informed decisions as they are rooted in facts and data. They enable companies to plan the next steps in relation to funding, operations, and budgeting. 

Historical data helps you glean insights into which factors had the most significant impact on sales and revenue. Alongside, data from financial forecasting offers insights into annual budget planning and informs major financial decisions on whether to seek external funding, fund a capital project or hire more staff. 

Advanced financial forecasts help organizations maintain a real-time understanding of the company’s financial trajectory and produce predictable results. They are equally critical in investor relationships and when seeking loans as banks and funders weigh forecasts in their decision-making process.

The future of financial forecasting 

Data integrity, accuracy and timeliness 

Inaccurate and unreliable financial predictions are caused by solely relying on past financial data. Instead, a better approach would be to curate both internal and external data and market trends to build the forecast. 

Financial forecasting by scenario analysis should take into consideration unexpected and worst-case market scenarios to enable finance teams to proactively address potential problems when things derail from the plan. 

Access to multiple data sources 

Fast-scaling companies or enterprise organizations source data from multiple departments, vendors, and sources. Rather than relying on spreadsheets to consolidate and align data, you need a financial forecasting and budgeting platform where all distributed data is stored, modeled, and processed.  

With abundant data integrations, you can view financial and non-financial data from multiple sources as well as access high-level and granular data from a single source of truth. 

Sharing insights with leadership to drive results 

Leadership depends on FP&A teams for deeper insights to shape important decisions about the company’s future and drive its growth. An integrated platform lets you manage and monitor data securely and displays multi-dimensional insights for leaders to approve and base their decisions on. 

For finance teams to have a seat at the decision-making table, it is critical to take measures to ensure that the data is clean and error-free and that predictions are nuanced and accurate. 

Incorporating financial planning into scenario planning 

How do you increase the velocity of your forecasting process

By running multiple scenarios to spot risks and opportunities and assessing the key drivers affecting your business. 

To speed up the process, use existing scenarios to build new ones, change assumptions for specific situations and compare scenarios in the form of tables, bar charts, waterfall charts, and more.

The importance of financial forecasting and budgeting platforms

According to Gartner, 50% of future FP&A teams use AI-based financial forecasting and budgeting software to create short-term forecasts. The report also found that 82% of CFOs are expected to invest in advanced analytics tools. 

Using financial forecasting and budgeting software Pigment for finance, your team can build, maintain and visualize financial forecasts, plans, and reports in real-time. 

With Pigment, you can:

  • Clean and enrich data from multiple business apps in seconds
  • Model forecasts in hours instead of days
  • Run what-if scenarios on the fly to help in decision-making

As a result, your team spends less time preparing data and more time analyzing it. 

For CFOs, Pigment serves as a single source of truth to drive better business strategy. View and track all key metrics in real-time, eliminate modeling constraints of spreadsheets, and get a 360-degree view of the business to make better decisions. 

Boost your financial forecasting capabilities with the best financial planning and budgeting platform 

FP&A teams are increasingly important as strategic business partners. The archaic methods of Excel forecasting are unscalable, time-consuming, and error-prone. 

On the other hand, powerful financial forecasting and budgeting software like Pigment builds a robust set of financial forecasting models and saves time on data wrangling to focus on the true value the finance teams create.

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