When you ask your accountant or adviser how to forecast your revenue model, do they stare at you blankly, lick their finger, stick it in the air and say “well it’s just a bit of that isn’t it”?
As helpful as I’m sure that response is, I think we can do better. A well-crafted revenue forecast provides a roadmap for sustainable growth, enabling you to make informed decisions and measure yourself against your goals. Whilst almost all revenue forecasts rely on estimates and assumptions, there are absolutely ways to increase their reliability and relative accuracy. Every business is different, and there isn’t a one-size-fits-all revenue model template, but here are five key points to consider when creating a revenue forecast:
1. Budget vs forecast: know the difference
Before diving into the detail, it's essential we understand the fundamental distinction between a budget and a forecast. A budget is set at the beginning of a period (usually financial year) and remains fixed, whilst a forecast is a dynamic tool that evolves with real-time data. Whilst both might start as the same document, the forecast is constantly updated, reflecting changes in market conditions, customer behaviour, and other variables. A business needs both – the budget compares current performance against expectations set at the start of the period and outlines the variances, which in turn inform the forecast to ensure the outlook is as realistic as possible.
2. Common methods for revenue growth forecasting
a. Analysing historical data:
For businesses with a robust dataset, analysing recent months can be a powerful method to forecast future revenue growth- particularly short term. By reviewing past performance and month-on-month growth rates, businesses can project future revenues with a reasonable degree of accuracy. It's crucial to account for seasonality when doing this, and also to identify and exclude exceptional “one-offs” which skew performance.
b. Goal-oriented forecasting:
Setting specific goals, such as reaching a certain number of customers by a specific date, provides a clear target for revenue forecasting. The revenue model can then be tailored to align with these goals. This method fosters a proactive approach, driving the organisation towards defined objectives, challenging management to achieve the desired growth.
3. Consider churn in recurring revenue models
So many businesses forget to do this. For any business relying on recurring revenue, a forecast must incorporate the inevitable reality of customer churn (customers becoming inactive or moving elsewhere). By analysing historical churn rates and understanding the factors contributing to customer attrition, businesses can develop more accurate forecasts. Addressing churn head-on allows for a more realistic outlook on future revenue streams.
4. Project probabilities in project-based businesses
For businesses operating on a project-based model, it’s a good idea to introduce a probabilistic element into their revenue forecasts. Outline all active and potential future projects or contracts, detail out the associated revenue and variable costs, then assign probabilities to each of them. How likely are we to win this work? How likely is it that this existing project transitions to the second phase? Apportioning the associated revenue and costs based on this likelihood provides a more nuanced and realistic projection. This method acknowledges the uncertainty inherent in project-based work and prepares businesses for a range of potential outcomes. Finally, if built well, this model could easily be duplicated and tweaked to represent multiple scenarios. What’s our worst case, realistic case, best case? How do they compare?
5. Group customers/clients into “buckets”
Some businesses have well defined product and service lines, whilst for others this isn’t as clear-cut. An example would be a service-based business that bills its clients using rate cards (or similar) on an hourly basis. “No client is typical”, they might cry. “Forecasting our revenue just isn’t possible!” they may exclaim. Whilst it certainly is more challenging, preparing a revenue forecast for a business like this is absolutely possible.
The key is to categorise existing customers/clients into groups (or “buckets”). This could be as few as two, “small” and “large”, but is typically between three and ten. Once existing business has been profiled into buckets, a revenue forecast can be prepared utilising targets based on acquiring new work from each bucket. For example, a business might currently employ 4 account managers whom between them look after 3 large clients, 10 medium clients and 30 small clients. By creating general profiles for each of these (in terms of revenue), we can forecast how revenue would grow if 3 small clients were acquired per month, 1 medium every 2 months and 1 large every 6 months. This, in turn, can also aid the recruitment forecast, as the business generally has an idea over how much capacity a typical account manager has.
That’s all for now, I hope this was useful. Forecasting revenue can be intimidating at first, but by embracing these key principles and tailoring them to specific business models, it can serve as an invaluable tool for strategic decision-making.
The next step
If you need support with your forecast model, please contact Dan Thomas on d.thomas@uhy-manchester.com, or your usual UHY adviser who will be happy to assist you.
