Sales forecasting is one of the most powerful tools available to any business. It is said that Jeff Bezos got Amazon through the dotcom bubble due to his ability to forecast the burst and plan accordingly. It’s those that survive that are able to make it through growth inflection points. Over several posts we will walk through the pipeline forecast methodologies all the way to using AI to provide actionable insights.
This is a data driven sales forecast that relies on historical data not the ability of the sales reps to forecast. The difference between the pipeline and the business forecast is that the pipeline sales forecast isn’t actionable while the business is. We start with the basics to understand the principles of forecasting. You can’t build/scale a business without an understanding of its key components.
So, why bother with data driven sales forecasting?
Simple: Reduce risk by improving visibility
By understanding both current sales process and future demand you can identify gaps or efficiencies to help you improve the sales organization, demand generation or the product. Most businesses don’t grow linearly, there are peaks and troughs understanding where the gaps in the sales process or demand are will help smooth out the peaks and troughs. Forecasting accurately, helps you spot the troughs with enough time to make effective change and helps capitalize on the peaks.
So what is our definition of a sales forecast?
A snapshot of current pipeline combined with an understanding of how similar deals have performed historically, yielding an estimate of IF / WHEN they will close.
In short: Open Pipeline * Close Rates + Sales Cycle
Sounds simple and honestly it is, if you have all of the data you need that is.
The Pipeline Forecast can be broken down into two pieces:
- Historical data gathering
- Key Performance Indicators
Historical Data Gathering:
The foundation for an accurate forecast is a solid set of historical data. We have found that 6-24 months of data is a good baseline depending on your sales cycle.
The two pieces of information you need to be able to pull out of your historical data are:
- When a deal was created
- When a deal was won or lost
If your CRM doesn’t allow you to pull historical data or you haven’t been tracking this data then you will want to start now.
Key Performance Indicators
Let’s break down the IF and the WHEN key performance indicators that are needed to build an accurate sales forecast but let’s talk about the three most important for building your pipeline forecast.
- Close Rates – The IF
- Sales Cycle – The WHEN
- Open Pipeline – DATA
Close Rates: THE IF
Your close rate is the rate at which you win deals vs loosing deals. So if you had 20 deals in your pipeline and you won 5 and lost 15 then your close rate would be 25% or 5/25.
On average for software companies we see close rates around 33%.
By using the law of averages (with a strong enough dataset) we can determine that out of any 20 future deals (all things held constant) that 5 will close.
Sales Cycle: THE WHEN
This is the amount of time on average it takes you to close a deal. Within any organization there can be multitudes of products along with multitudes of deals types, so the sales cycles can vary.
On average for a software company we see:
SMB Market – <30 days
Mid Market – 30-60 Days
Enterprise Market – 90 Days +
Understanding your sales cycle will help you determine when the deal would close, if it were going to close.
Open Pipeline: THE DATA
All of the open deals that you currently are working on at any stage of their lifecycle. In essence these are the deals you want to close.
When you pull the open pipeline, multiply those deals by the historical close rates and then add the average historical sales cycle, you are well on your way to a solid baseline forecast.
Let’s say you have $50,000 worth of deals and your close rate is 30% that means the forecast will show you closing $15,000. Now if your sales cycle is 30 days then you can expect to close $15,000 next month. This is an extreme oversimplification of a sales forecast but illustrates the simplicity of looking at the IF and the WHEN against your current pipeline – the DATA.
Building your simple pipeline forecast, can get you to an accurate forecast but you cannot identify gaps or process that are working well within your sales blueprint. This is why we need the business forecast that doubles as your sales blueprint to understand the sales cycle stages, different product attributes or segments within business’, different regional or sales rep attributes and different customer attributes to determine where there is room for improvement.
We’ve built a FREE sales forecast module built in Google sheets here!
Subscribe to our blog as we’ll we going over the difference between your sales forecast and sales blueprint next week.
10 years of corporate finance and forecasting experience at different technology startups across the US.