What is financial forecasting, and how to conduct it?
Maintaining strong business financial health is a result of robust operating models, rigorous data analysis, real-time market insights, and meticulous planning. Businesses use financial forecasting as a strategic tool to proactively predict expected financial outcomes and undertake financial planning and risk reduction as necessary.
Below, we elaborate on what is financial forecasting, and why it is important for enterprises to conduct it.
Financial forecasting is estimating a company’s future financial position after examining its historical performance and evaluating the potential impact of current and evolving macroeconomic trends on the company’s operations.
It involves an analysis of the company’s past performances, such as sales, expenses, cash flows, and more, to deduce any possible trends and patterns. Financial forecasting also entails the consideration of any contingent events that may have a significant impact on the company’s finances.
While it is impossible for firms to predict the future, financial forecasting in financial management helps them hedge against worst-case scenarios by providing predictions for such uncertain events.
While a business can undertake several types of forecasting, including sales, income, and cash flows, the three main types of forecasting are as follows:
- Sales forecasting
Sales hold the key to a business’s future and form the basis for internal planning, particularly expense management, production cycles, and capital expenditure plans. It is the expected revenue from sales that requires maximisation, making sales forecasting a crucial exercise.
In sales forecasting, companies predict the number of products or services and the price points they expect to sell within a specified period. Enterprises rely on time series analysis to forecast sales for an existing product but may opt for qualitative techniques when estimating revenues from a new product launch.
- Cash flow forecasting
Cash flow forecastinginvolves an estimation of the cash inflows and cash outflows of a company and its net balance over a projected period on a weekly, monthly, or yearly basis. It factors in sales revenue and major expenses.
It helps put the company’s liquidity planning and working capital management into perspective by identifying any immediate funding needs. It also indicates any teething cash flow issues and the requirement for financing in the near future. However, cash flow forecasting is more precise in the short term.
- Budget forecasting
A general budget provides an overall view of the business's dynamics and financial performance. It does not involve dealing with business specifics but instead is an overall estimation of certain critical financial metrics.
Budget forecasting aids companies in formulating their business strategies. It is usually informed by historical data trends, but technological advances such as big data and machine learning have transformed the way forecasting is done.
Primarily, there are two broad categories of financial forecasting methods: qualitative and quantitative.
Qualitative forecasting uses expert judgement and subjective opinions to predict financial performance. It is useful when numerical data is limited or unreliable and when forecasting involves unprecedented situations.
- Delphi method: It involves a structured approach of consulting several experts to anonymously share their predictions about a company’s performance based on their knowledge and expertise. These responses are aggregated and revised until a consensus is reached.
- Market research: It entails gathering qualitative data about market competition, consumption patterns, and emerging trends from industry stakeholders through surveys and interviews to gain actionable insights and base forecasts on the gathered data.
Quantitative forecasts make use of historical numerical data and mathematical models to predict future outcomes. Some of the standard quantitative forecasting methods are:
- Straight line: This method forecasts financial line items by assuming a constant growth rate. For instance, if the company’s sales grew by 18% in the previous year, the same rate will apply to all future forecasts. This method does not factor in supply chain disruptions or market fluctuations.
- Percent of sales: It computes financial metrics as a percentage of sales. To illustrate, as the cost of goods sold (COGS) rises in tandem with sales, a company can divide the historical COGS by sales to deduce a steady number, which can then be used to predict future COGS figures.
- Moving average: This method averages out a company’s performance over previous periods to arrive at a forecast; higher weights may be assigned to the latest figures. It is more suitable for short-term forecasting.
- Linear regression: This method assumes the forecasted item and the factor(s) affecting its value to be the dependent and independent variables, respectively. For example, a sale is a factor of the number of items sold, price, discounts, and economic conditions.
Now, companies have started deploying predictive modelling algorithms and financial forecasting software UK to automate and improve their financial performance predictions.
The top financial forecasting models are:
Bottom-up financial forecasting: This model reviews historical company information, such as sales data, and uses it to make projections.
Top-down financial forecasting: This model starts with market assessment and then moves down to forecasting specific metrics for the company. It is useful for those looking at new product launches and market reach expansion.
Statistical forecasting: It uses statistical findings to help a business benchmark its operational performance against its peers. It involves quantitative techniques like linear regression and moving averages.
Financial forecasting is an iterative process requiring regular evaluation and adjustment that guides businesses in undertaking effective financial planning. It involves the following steps:
- Data collection: The first step is to gather and analyse historical financial data, market trends, and other information relevant to your forecast needs to truly understand the key drivers of your business.
- Make assumptions: Follow up on data gathering by formulating assumptions over a specific time frame and choosing a forecasting model most suitable to your projection goals.
- Project financial metrics: Key in the assumptions made into your chosen financial model to reflect the major relationships between critical financial dependent variables, including sales growth, expenses, and cash flows. You can also undertake a scenario analysis at this stage.
- Monitor performance: Compare the financial forecast to the actual financial performance on an ongoing basis to identify variances and the reasons behind these differences, and use this information to improve future forecasting accuracy.
Example 1: Assume a company, ABC Ltd., has an average expense-to-sales ratio of 23% and forecasts its next year’s sales to be £400,000. Using the percent of sales method, their future expense estimates will be £92,000 (£400,000 x 0.23).
Example 2: A manufacturing company, PQR Ltd., empanels 10 experts to forecast its product demand using the Delphi method, with first-round estimates in the range of 500,000-700,000 units. PQR identifies the areas of agreement and disagreement, continues to iterate the process for two additional rounds, and arrives at a final consensus of 600,000 units.
Making financial projections for new businesses can be daunting due to the lack of historical performance data but it is necessary as both banks and investors require financial estimates. In such scenarios, new firms should start by identifying key expenditures, including recurring expenses when drafting their business plan.
Then, they can proceed to create a sales forecast based on market research involving a thorough screening of peers for similar sizes and industry trends. Alternatively, firms can use qualitative methods, such as the Delphi method, to perform financial forecasting.
Performing financial forecasting in Excel is fairly easy if one has access to a complete dataset of historical time-based financial data using FORECAST.ETS formula.
To make any forecast, start by setting up a spreadsheet and pulling in and organising data series in separate columns. Then, select the time series and select “forecast sheet” from the forecast group available on the data tab.
Excel will create a new sheet of predicted values, which can be customised per your assumptions, including confidence intervals, forecast start dates, factoring in seasonality, and more. You can also use Agicap’s Excel template to undertake cash flow forecasting.
Financial forecasting holds significance as it enables businesses to make decisions about budgeting, hiring, financing, and overall strategic planning. Indeed, financial forecasting and planning go hand-in-hand, as financial forecasts form an integral part of the budget creation process.
Financial forecasting informs internal decisions, empowering teams to set realistic performance goals. It also highlights any financing requirements, such as seeking loans for a capital project, and is relied on by banks while making lending decisions.
While Excel is a useful tool for performing financial forecasting, it is prone to errors and may not be suitable when growing your business. Instead, organisations can automate their projection processes by using dedicated financial forecasting software. For instance, Agicap’s cash flow forecasting solution enables companies to dynamically forecast their cash inflows and outflows using a simplified input tool, enabling better planning for the upcoming months.