If you took a history class, the teacher likely told you that to understand the present and future, you first need to understand the past.
The same can be said about accounting. The answer to where a business is and where it’s heading is likely in their historical reporting.
Financial projections are a tricky balancing act of trying to map out potential and probable outcomes. But it isn’t making wild guesses. There are safe assumptions that, when made, turn past trends into future projections.
All of it starts with taking that first look into the past.
Starting with historical information
Your first step to doing any financial projections should be looking at the last 12 months. Start with looking at income statements and cash flow statements with a monthly breakdown.
From there, you can begin some basic analysis. What were the trends in revenue? What expenses were highly variable? What were the most and least profitable months?
Level up your analysis by including operational data like headcount and inventory.
When doing this type of analysis, always be thinking about the drivers of the business. Drivers are the factors that most impact the outcome of a business. By thinking about drivers, you simplify modeling and simulating what-if scenarios by focusing on what influences an outcome or is most changed by it.
You’ll start to recognize correlations. With these trends and correlations, you can start setting assumptions.
Now that you’ve looked at 12 months of data, you start mapping out what the next 12 will look like. While it’s not going to be an exact copy-and-paste situation, there’s still a lot to learn from that can be incorporated into your forecast.
Some fixed costs are safe to assume will be unchanged. Things like rent, software costs, and some utilities.
For other costs and revenue, a good rule of thumb is assuming things will trend within 10-15% of the historical 12 months. With that in mind, you can create an upper and lower band of expected performance in a rolling forecast.
You also have an excellent source of information in your client. Ask them what their initiatives are for the next 12 months and how they expect that to influence operations. For example, maybe they’re launching a new marketing campaign with hopes of growing sales revenue by 10%.
By pairing historical information with your client’s plans for the future, you have lots of safe assumptions to make to simplify and inform your financial modeling.
Be open about the assumptions you use in your modeling. For example, if you assume that headcount needs to increase by one for every 100 units sold, it’s essential to disclose that.
The assumptions you use should be treated as conditional “ifs.” You’re framing projections as “if this trend continues, we can expect this to be the result.” The reason why this is so important is that it adds an extra element of essential information to your forecasting.
When you present a financial forecast, you’re presenting an expectation of what the business can expect and plan for. But when you include what you’ve assumed, you’re letting the business know what could be a warning sign that the predicted outcome is at risk.
Let’s go back to the assumption that headcount needs to increase by one for every 100 units sold. Together, you work with your client to find an optimal production number that maximizes profitability.
One month later, your client comes back and says the ratio is actually one more worker for every 500 units sold. It’s time to reset the assumptions and redo the forecast with this new information.
By disclosing the assumptions, your clients can approach you and let you know when information changes. That timeliness helps you incorporate the new information into the model and rework the forecast.
It’s essential to remember that not all assumptions are going to be correct, and that’s okay.
Humans get caught up in decision paralysis all the time. We like simple information that’s easy for us to process and turn into a quick decision.
The purpose of using assumptions is to take complex, dynamic information and turn it into a simple thing so we can get to the decision-making. Otherwise, it’s a lot of staring at the numbers and overanalyzing what-if situations.
When you run forecasts, you’re essentially testing your assumptions and seeing if they stand up to real-world results. Having the actuals not line up with the forecast isn’t a problem, so long as you can explain the why.
Use technology to adjust on the fly
Making a change to your model doesn’t mean you need to start from scratch. By using a financial planning and analysis tool like Jirav, you can create models where you set the parameters and run the forecasts. These models are easy to update and provide you valuable insight into the actuals versus the forecast.