Rolling forecasts are still a fairly new concept for businesses.
In many organizations, financial planning is as follows: at the end of every year, you create a budget for the following year based on historical data. You look at how much money you spent in the past 365 days on marketing, sales, training, and technology, and then you adjust your budget accordingly. For the most part, once a business creates a budget for the next year, they don’t typically make any changes until the following year. They have their milestones and metrics in place, and they stay the course.
What technology has recently enabled, however, is the ability to know what’s happening in the business in real-time — and to make changes to your forecast based on your original budget.
Adjusting on the fly with real-time forecasting
Let’s say you had a terrible last month of sales, and you are way under where you thought the business should be at the end of the first quarter. If you want to know, from a forecasting perspective, how this one bad month impacts your budget for the year, then unless you have an integrated solution providing real-time forecasting updates, this becomes a huge project to figure out. For a lot of smaller and medium-sized companies, it’s not that they can’t make these changes or pull these insights manually. It’s just that the amount of time and energy it takes to gather all the necessary data into an Excel file, build a model, validate the model, share the model with other decision-makers, and maintain a consistent version of the model, usually takes so long most people don’t even bother with it.
As a result, once they build their static budget for the year, they don’t adapt along the way.
Real-time forecasting can be a superpower for your business. Here’s how.
Let’s just take one very simple example: measuring true ROI.
When a company puts a bonus structure together for its salespeople, or decides to fly a bunch of team members somewhere for a retreat, how do you accurately measure the ROI of those decisions? Or let’s say some months you choose to pay your vendors early, whereas other months you take advantage of the 30- or 60-day payment terms and pay your invoices right before they’re due. Are these decisions happening sporadically? Or are they informed by data, giving you more visibility into the business?
What makes real-time forecasting a superpower is the fact that it allows you to make decisions based on what’s actually happening within the business — and not based on a theoretical budget set months in advance. For example, as a startup, I know that cash on hand is extremely important for our growth trajectory right now. As a result, I wanted to come up with a bonus structure for our sales team that not only rewards them for landing new accounts, but for closing them in a certain way where the business actually captures that revenue. In order for me to come up with a bonus that was both enticing enough for the sales team, but appropriate within the context of the business’s overall financials, I needed to take into account a handful of variables:
- What is realistic for a salesperson to produce in a month?
- What will the customer be willing to pay, under what payment terms?
- What is a compelling incentive in the context of each salesperson’s yearly compensation package?
- Will this drive the desired result for the company?
To do all of this manually would have taken a significant amount of time. But using our forecasting tool, PlaceCPM, available on the AppExchange, I ran all those different numbers and came up with a model in less than 30 minutes.
The impact of real-time forecasting on hiring, administrative, benefits, fundraising, and more.
You are hiring more and more team members, but your revenues have started to slow. What should you do?
The amount you’re spending on technology is exceeding your yearly budget, but you’ve decided you need these tools in order to keep growing. How does that impact the financial plan for your business?
You still have 18+ months of runway in the bank, but now is a good time to raise more money. If you were to raise more, how much should you take in?
It’s very difficult to answer questions like these without real-time visibility. Either a significant amount of time gets wasted trying to come to these conclusions using static models built in Excel, or these decisions end up being made subjectively — neither of which is very conducive to the long-term health of the company.