Small BusinessOperationsAccounting

How to forecast revenue

Revenue forecasting can help businesses predict future income and growth with the data it already has. This can enable small business leaders to make educated guesses about the year ahead and inform their decision-making.

What is revenue forecasting?

Revenue forecasting is a strategic financial planning process that businesses use to estimate and project their future income or revenue. It involves anticipating the amount of money a business expects to generate from its core operations, products, or services over a specific period of time. Accurate revenue forecasting is essential for effective business planning, budgeting, resource allocation, and – ultimately – better decision-making.

Businesses can input a variety of data to a forecast, including historical financial data, sales figures, advertising spend, and much more.

Why is revenue forecasting important for small businesses?

With the help of accurate data, small businesses can make more informed decisions about where and when to use cash flow and tighten budgets. Businesses may also be able to optimize credit management, choose the most profitable marketing strategies, and increase or decrease recruitment when appropriate.

Revenue forecasting methods

Revenue forecasting methods can be quantitative or qualitative, using either numerical or written information. Finance teams and business owners can analyze revenue, cash flow, and income statements to produce various future scenarios.

Below are some of the methods that can be used to forecast revenue. It is advisable to discuss these different methods with the finance team before choosing.

Time series/straight-line analysis

This quantitative method uses past revenue data to extrapolate past trends into the future. Businesses can compare revenue month-by-month, year-by-year, or seasonally. A time series analysis can reveal customer behavior fluctuations and seasonal variations where there are predictable patterns, for example peaks in demand over the holiday season.

This method is one of the simplest to perform and analyze because many businesses already have easy access to this information going back over long periods and can easily derive insights from it.

Once revenue data is accumulated over a given period, it can be interrogated to provide averages that yield insights into revenue trends. There are several different models for this, including:

  • Moving averages: Moving averages are constantly updated average figures. Tracking these can smooth out fluctuations in revenue
  • Exponential smoothing: Exponential smoothing is a form of moving average that measures trend direction over a fixed period
  • Autoregressive integrated moving average (ARIMA): ARIMA prediction models are used to predict future revenues based on past revenue trends.

Regression analysis

Businesses can also analyze the effects of a specific variable on revenue, such as advertising spend, pricing, exchange rates, and overhead costs. This will project the factors that could positively and negatively affect future profits.

This technique used to model the relationship between one or more independent variables and the dependent variable, in this case the company’s revenue. Multiple regression analyses can be used when there are several independent variables influencing the dependent variable, allowing for a more comprehensive understanding of the factors affecting revenue. The goal of regression analysis is to understand the nature of the relationship between these variables, make predictions, and identify the strength and significance of the associations.

For instance, Company A made $420k in revenue in Q1 of this year. An increase of $180,000 on Q1 last year. During this period, it spent $50,000 on advertising, $25,000 on new hires, $20,000 on new equipment and $75,000 on employee training. Regression analysis would help the company’s directors to better understand the impact of each of these capital investments on the uptick in revenue.

Top-down forecasting

Top-down forecasting is an approach to revenue forecasting that begins at the highest level of the organization and then allocates or disaggregates the overall revenue target to individual business units, product lines, or other relevant components. This method involves starting with an overarching, company-wide revenue target, and then breaking it down into more detailed forecasts for specific segments or departments.

Some smaller businesses may find this method harder to measure. However, it could be particularly useful for fast-growing organizations in new sectors and businesses that already enjoy substantial market share.

Bottom-up forecasting

Micro-revenue forecasting considers drivers within the business’ operations and converts this into projected revenue. This technique starts at the individual business unit or department level and aggregates these unit-level forecasts to derive an overall revenue projection for the entire organization. This method relies on input from various operational units, such as sales teams, product lines, or geographical regions, to create a comprehensive and detailed forecast.

These drivers can include marketing and advertising spend, conversion data, average order values, customer lifetime value, and much more.

For some businesses, particularly smaller operations, this may be a more accurate and personalized method of analysis than top-down forecasting. It considers a business’s specific circumstances, rather than its relationship to competitors.

What are forecasting tools?

Businesses can forecast using an Excel spreadsheet, but many choose to use reporting software because it can be easier to use, as well as more intuitive and intelligent. This can save significant time and energy.

Many of the most popular forecasting tools will automatically import data from multiple sources, provide real-time notifications, and – most importantly – do the math.

How do you create a revenue forecast?

Once a business has chosen its forecasting tool, the next steps are the input data and set timescales.

  • Identify revenue streams. This includes physical products and services, sales, subscriptions, and any other sources of income.
  • Choose the right forecasting method. Identify business needs, review the different calculation methods, and choose the most appropriate one.
  • Set metrics. Decide how far into the future the forecast needs to project. Businesses can project a single service, product, or revenue stream. Alternatively, the forecast could consider all revenue streams simultaneously.
  • Calculate low, medium, and high revenue totals. Businesses can calculate conversative and generous figures. For example, what would the totals look like if a potential client doesn’t come on board?
  • Keep monitoring and updating. Forecasts are living documents. Keep updating the data for a detailed view of projected future revenue.

Understanding revenue forecasting

There are various forecasting methods available, each offering different benefits. It’s important to choose a method that produces appropriate insights into future revenue and can scale as the months and years go by.

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